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MONTHLY LABOR REVIEW Volume 131, Number 8 September 2008 The effect of business ownership change on occupational employment and wages 3 After a business changes ownership, employment falls but wages rise in some occupations, whereas in other occupations, employment levels are maintained and wages fall Dina Itkin Extended mass layoffs after 2001: a comparison of New York and the Nation 24 BLS data reveal that layoff activity in New York was somewhat elevated in the years that followed the 2001 recession Bruce J. Bergman Conference report Knowing younger workers better: information from the NLSY97 42 Papers from the 10th anniversary conference of the National Longitudinal Survey of Youth, 1997 cohort addressed schooling, employment, adolescent behaviors, and many other issues Dan Black, Robert Michael, and Charles Pierret Regional trends Multiple jobholding in States, 2007 James Campbell 52 53 Departments Labor month in review 2 Précis 54 Book reviews 55 Current labor statistics 57 Editor-in-Chief: Michael D. Levi Executive Editor: William Parks II Managing Editor: Leslie Brown Joyner Editors: Brian I. Baker, Casey P. Homan Book Review Editor: James Titkemeyer Design and Layout: Catherine D. Bowman, Edith W. Peters Contributing editor: Lawrence H. Leith Contributor: Stephen E. Baldwin Labor Month In Review The September Review Our first article this month examines the effect of changes in business ownership on workers related to the types of jobs they hold. Analyzing microdata from the Occupational Employment Statistics (OES) survey, Dina Itkin demonstrates that there are differential outcomes by occupation on employment and wage levels resulting from new ownership. Among a number of areas of inquiry, she identifies the industry sectors most affected by ownership change. Further, she investigates the relationship between changes in occupational composition resulting from new ownership and the employment size of the affected business. The author identifies some limitations of the study, noting, for instance, that some staffing changes might be in transition and only partially captured using her methodology. Bruce J. Bergman compares mass layoff activity in the New York City area with that of the Nation as a whole in the years prior to and after the 2001 recession. With the largest metropolitan workforce in the country, trends in the Big Apple regarding the separation of workers from their employers are always going to be of interest. Bergman finds a “qualitatively different” pattern in the industry distribution of layoffs prior to, and after, 2001, in New York, in contrast to the national experience. A trio of authors with a demonstrated interest in longitudinal studies provides a Conference Report in this month’s MLR focusing on information from the 1997 cohort of Monthly Labor Review • September 2008 the National Longitudinal Survey of Youth. In May of this past summer, BLS hosted a conference highlighting the latest research from this survey, and Dan Black, Robert Michael, and Charles Pierret provide a “brief and informal characterization” of some of the more than a dozen studies presented. They summarize the research on topics ranging from social behaviors (such as marriage and offspring and the influence of siblings) to education (including the effects of parental resources on educational attainment) to the changing characteristics of youth employment. Finally this month, James Campbell provides his annual update to patterns of multiple jobholding among the various States. A profile of the working poor The majority of the 36.5 million persons in poverty in the United States are children or adults outside of the labor force. However, there are many people who are active participants in the labor force for at least half a year, but whose incomes still fall below the official poverty level. Each year the Bureau publishes data on these socalled “working poor.” In 2006, it is estimated that 7.4 million individuals were in these circumstances, meaning they spent 27 weeks or more working or looking for work, but lived at or below the official poverty threshold relevant to their family structure. They made up 5.1 percent of all persons in the labor force for 27 weeks or more, down a bit from 2005. Some of the socioeconomic factors that often are cited as contributing to labor market outcomes are found to influence who falls into the workingpoor status. Persons with the least amount of education, for instance, make up a far higher percentage of the working poor – almost 14 percent – than those with a college degree (less than 2 percent). Persons in occupations that tend to be lower paying have a higher probability of being among the working poor, as do parttime, as compared to full-time, workers. Married couple families facing the extra expenses of childrearing are much more likely to be among the working poor than married couple families without children. A Profile of the Working Poor, 2006 can be found online at http:// www.bls.gov/cps/cpswp2006.pdf Happy Birthday, TED! Who is TED, you ask? As noted in this column before, “he” is The Editor’s Desk, a daily feature published by BLS on its Web site. TED is a reliable source of fresh content posted every business day. It was the first online-only publication available from the Bureau. Since the first issue was published in September 1998, TED hasn’t missed a day of work, as over 2,400 entries have been issued so far. Congratulations to TED, and to all who help produce this feature so reliably. For additional information about the 10th anniversary of The Editor’s Desk, please go to http://www.bls.gov/opub/ ted/tenyears.htm Business Ownership Change The effect of business ownership change on occupational employment and wages An analysis of business establishment microdata reveals that, after a business changes ownership, employment falls, but wages rise, in occupations that performed analytical, clerical, and production work; by contrast, employment levels are maintained, but wages fall, in service occupations Dina Itkin Dina Itkin is an economist in the Office of Employment and Unemployment Statistics, Bureau of Labor Statistics. E-mail: itkin.dina@bls.gov E very year, thousands of U.S. businesses are bought, sold, or merged to raise profits, reduce costs, increase market share, or otherwise interact in the dynamic economy. The national level of business ownership change peaked in the late 1990s, when the Nation was experiencing rapid economic growth, and declined gradually through 2002.1 After 2003, the number and asset trade value of ownership changes rose steadily again. Volume in 2006 exceeded that in 2005 by 38 percent and surpassed a 2000 record. The year-over-year asset trade volume of ownership change as of July 2007 was up 60 percent globally and 41 percent in the United States.2 Existing literature and anecdotal evidence have found varying effects of ownership changes on company profits, labor productivity, wages, and staffing in specific industries. For example, research using Census Bureau data on manufacturing companies found that ownership changes led to reductions in employment and wages at auxiliary (support) offices, but had little effect on employment at production plants.3 Two other studies—one of manufacturing firms4 and the other of food-manufacturing firms5—found that ownership changes resulted in employment and wage increases overall, but led to job losses in large firms. Trends in personnel changes in all sectors of the economy are of interest to economists, business owners, and workers, but there is little, if any, recent empirical research on the effects of ownership changes on detailed occupational employment. Such information provides insight into the specific jobs and skill sets that are in demand when firms reorganize or redirect their business strategies. This study uses a recent large sample of business establishment microdata to examine how overall employment and occupational composition are affected when establishments undergo a change in ownership. The study resulted in a number of interesting findings: after ownership changes, (1) employment levels of occupations that performed analytical, clerical, and production work were least likely to be maintained, and most of these groups’ wages shifted toward higher ranges; (2) employment levels of service occupations such as health care, education, and protection services were more likely to be maintained, but most of these groups’ wages shifted toward lower ranges, on average; (3) overall, employment declines were seen in establishments that changed ownership; and (4) among the industries that contracted the most, declines were concentrated in occupations that serve a support function in the industry, rather Monthly Labor Review • September 2008 Business Ownership Change than in occupations that are core to the industry’s output. These findings tended to be supported across establishments of different sizes, with decreases in the share of support occupations such as office and administrative support, management, and sales occupations in all size classes. Methodology This study was conducted with the use of microdata from the Occupational Employment Statistics (OES) survey. The OES program surveys approximately 200,000 establishments every 6 months, taking 3 years to collect its full sample of 1.2 million establishments. Establishments are eligible for selection again after 3 years. The data set consisted of all business establishments that reported to the OES survey twice over a period of 6 years. Those establishments were put into two subsamples on the basis of whether or not they changed ownership, as defined by a change in the Unemployment Insurance (UI) account number. Included in the study were microdata from all 50 States and the District of Columbia, from establishments that reported occupational employment for all of their employees and wage data for most of their employees.6 All establishments covered by State Unemployment Insurance have an assigned UI account number. When a firm changes ownership, it normally refiles with the Unemployment Insurance program and receives a new UI number. By contrast, the Quarterly Census of Employment and Wages (QCEW) program’s Longitudinal Database (LDB) assigns each establishment a unique LDB number that does not change, even if the ownership changes. A total of 277,027 establishments reported to the OES survey exactly twice during a 6-year period from 2000 to 2006.7 Of the establishments that reported twice with the same LDB number, 254,829 had the same UI number the second time they reported. These establishments serve as this study’s subsample of establishments that did not change ownership (the control subsample). The remaining 22,198 establishments had different UI numbers the second time they reported and serve as the study’s subsample of establishments that changed ownership (the ownership change subsample). Each establishment in either subsample has longitudinal occupational staffing data for two points in time. The first reports are included in the predecessor group, whose establishments reported data between 2000 and 2003. The second reports are included in the successor group, whose establishments reported data between 2003 and 2006. Monthly Labor Review • September 2008 Limitations of the study Elements of the OES sampling strategy may create a bias toward larger establishments in the study’s subsamples. The reason is that sample selection within geographic area and industry group strata is approximately proportional to size, in order to provide the most occupational coverage. Although there are more small units in the subsamples, larger units are more likely to be selected at two points in time and included in the subsamples. This bias is enhanced by the fact that the study uses unweighted employment. Although a change in UI account number in establishments with the same LDB number represents an ownership change most of the time, limitations to this definition exist. A change in UI number does not necessarily indicate a change in ownership (it could be the result of a change in the type of business entity, as, for example, when a business incorporates), and perhaps not all ownership changes were marked by a UI number change. To facilitate the identification of establishments that changed ownership, factors such as employment, trade names, physical addresses, and telephone numbers were used in determining whether to maintain the LDB number. The microdata do not differentiate among types of ownership changes, such as mergers, takeovers, divestitures, or buyouts. If the ownership change represents a merger or an acquisition, then changes in the acquiring establishment are not measured; only employment data from the acquired establishment are captured in this study. For example, if an establishment was bought by another company, the study would capture predecessor and successor data only for the establishment with the same LDB number before and after the purchase. A related limitation of the study is that the data do not indicate whether labor was voluntarily or involuntarily removed, or whether it was contracted out or outsourced, after the ownership change. Also, because the time between the first and second reporting is at least 3 years for all establishments, the study might not capture staffing changes that occurred immediately before or after the ownership change. In some cases, the transition might be only partially complete at the second reporting; in other cases, the transition may already have begun at the first reporting, in anticipation of a future takeover. Overall employment trends Certain industries were more likely to change ownership relative to other industries in the study subsample and to the economy as a whole. Table 1 shows, in order by column, the industry distributions of establishments that reported twice, Table 1. Concentration of establishments, by industry sector, in the ownership change subsample and across all establishments, 2000–06 Industry sector Number of units that reported twice Number of units that changed ownership Total..................................................................... 1 277,027 22,198 Information................................................................. 6,858 793 Accommodation and food services................... 15,283 1,760 Administrative and support and waste management and remediation services..... 13,436 1,351 Retail trade.................................................................. 41,261 3,875 Manufacturing........................................................... 40,480 3,469 Finance and insurance............................................ 10,713 915 Health care and social assistance....................... 26,317 2,226 Wholesale trade........................................................ 18,742 1,516 Transportation and warehousing....................... 10,221 814 Real estate and rental and leasing..................... 7,632 576 Mining.......................................................................... 1,618 122 Management of companies and enterprises 2,176 162 Professional and technical services................... 16,163 1,126 Utilities......................................................................... 1,754 121 Arts, entertainment, and recreation.................. 6,465 418 Other services, except public administration..... 18,805 1,204 Construction.............................................................. 21,357 1,316 Educational services................................................ 11,396 273 1 Details do not sum to total because some industries are not listed separately and some establishments lack an industry classification. The industry sector of agriculture, forestry, fishing, and hunting is excluded the industry distributions of establishments that changed ownership, and the percentage of establishments that changed ownership in each industry. The industries listed are sorted by the percent that changed ownership. Industries in which at least 10 percent of establishments changed ownership were information, accommodation and food services, and administrative and support and waste management and remediation services. The two columns headed “Percent distribution...” serve as an indication of industry distribution in the ownership change subsample relative to the industry’s representation in the economy. Industries that represented a large proportion of the ownership change subsample relative to the economy as a whole included manufacturing, retail trade, information, health care and social assistance, transportation and warehousing, and accommodation and food services. At the more detailed industry level, the OES data are consistent with other findings8 which show that, in 2003, most ownership changes were in business services, prepackaged software, commercial banks and bank holding companies, real estate, mortgage bankers and brokers, and oil and gas and petroleum refining. Overall, there was a decline in total employment from the predecessor group to the successor group after owner- Percent that changed ownership Percent distribution of ownership change subsample Average number of privatesector establishments in 2005, QCEW 1 1 8.01 100 8,294,662 11.56 3.57 141,871 11.52 7.93 572,791 Percent distribution of private sector establishments in 2005, QCEW 100 1.71 6.91 1 10.06 6.09 426,681 5.14 9.39 17.46 1,038,585 12.52 8.57 15.63 365,351 4.40 8.54 4.12 462,381 5.57 8.46 10.03 689,010 8.31 8.09 6.83 601,625 7.25 7.96 3.67 212,309 2.56 7.55 2.59 351,329 4.24 7.54 .55 26,313 .32 7.44 .73 43,239 .52 6.97 5.07 902,710 10.88 6.90 .55 16,260 .20 6.47 1.88 118,614 1.43 6.40 5.42 1,102,054 13.29 6.16 5.93 845,843 10.20 2.40 1.23 78,410 .95 because the OES and QCEW have incomplete coverage of that sector. OESdesignated government industries also are excluded. ship changes. Total employment in the predecessor group was 2,018,250, and total employment in the successor group was 1,890,986, a decrease of more than 6.31 percent.9 This employment decrease occurred despite overall private-sector employment growth of 2.82 percent between 2002 and 2005.10 Almost half (10,677) of the 22,198 establishments that changed ownership experienced a decrease in employment, 9,517 saw an increase in employment, and the remaining 2,004 had no change in employment. Although employment decreased overall in the ownership change subsample, employment change varied by industry, establishment size, and occupation. The distribution of the ownership change subsample and the control subsample is shown by establishment size in table 2. In the control subsample, there was an aggregate shift toward medium and large sizes, while in establishments that changed ownership, there was an aggregate shift toward smaller sizes. After establishments changed ownership, the concentration of establishments increased in the 1-to-9-employee and 10-to-49-employee size classes and decreased in the three larger size classes. The concentration in the 1-to-9-employee size class grew by nearly 5 percent in the ownership change subsample, while it grew by Monthly Labor Review • September 2008 Business Ownership Change Table 2. Concentration of establishments in the OES sample, by size, in the ownership change subsample and the control subsample, 2000–06 Ownership change subsample Size of establishment Number of Number of predecessor successor units units Difference between number of predecessor and successor units Control subsample Percent change Total.................................................. 22,198 22,198 … … 1–9 employees...................................... 5,277 5,530 253 4.79 10–49 employees................................. 9,094 9,151 57 .63 50–249 employees.............................. 6,199 5,973 –226 –3.65 250–999 employees............................ 1,412 1,335 –77 –5.45 1,000 or more employees................. 216 209 –7 –3.24 substantially less in the control subsample. Likewise, the number of 10-to-49-employee establishments increased in the ownership change subsample, while it decreased in the control subsample. These shifts suggest that, after ownership changes, the size distribution of establishments moved toward smaller establishments; that is, more establishments shrank than grew. Because these numbers capture only overall total concentrations at two different times, the last section of this article examines employment changes by establishment size. Changes by occupational group Changes in employment levels. After ownership changes, changes in employment were spread across several occupations, with more than half of the occupational groups seeing declines in employment and other occupational groups seeing employment increases. Table 3 presents the changes in employment in each occupational group after ownership changed. As shown in the column headed “Employment difference,” the occupations that decreased in employment level were production; office and administrative support; sales and related; management; computer and mathematical science; business and financial operations; architecture and engineering; transportation and material moving; building and grounds cleaning and maintenance; personal care and service; installation, maintenance, and repair; arts, design, entertainment, sports, and media; construction and extraction; and legal occupations. At the other end of the spectrum, the occupational groups that grew after ownership changes were health care practitioner and technical; protective service; health care support; education, training, and library; food prepara Monthly Labor Review • September 2008 Number of Number of predecessor successor units units 254,829 69,585 108,834 60,024 14,057 2,329 254,829 70,721 107,500 60,101 14,170 2,337 Difference between number of predecessor and successor units Percent change … 1,136 –1,334 77 113 8 … 1.63 –1.23 .13 .80 .34 tion and serving; community and social services; and life, physical, and social science occupations. Because changes in level do not convey growth or decline relative to other occupational groups, an analysis of the employment shares of total predecessor and successor employment follows. Relative changes in employment shares. Table 3 also shows the percentage-point difference between the predecessor and successor employment shares in both subsamples. Occupational groups are labeled “less likely” or “more likely” to be retained, on the basis of their change in employment share in the ownership change subsample relative to the control subsample. Employees who were less likely to be retained are in occupations whose employment shares (1) shrank in the ownership change subsample while they grew in the control subsample, (2) grew in the ownership change subsample by less than they grew in the control subsample, or (3) shrank in the ownership change subsample by more than they shrank in the control subsample. This set of occupations (those which are less likely to be retained) is plotted to the right of the diagonal in chart 1. For each occupational group shown in the chart, the further the point that is associated with it lies from the origin and the diagonal, the greater is the difference between the employment shares in establishments that changed ownership and in establishments that did not change ownership. Employees who performed analytical, clerical, and production work were less likely to be retained after ownership changes. The occupational groups that shrank in the ownership change subsample while they grew in the control subsample (occupational groups located in quadrant IV) were computer and mathematical science; busi- Table 3. Occupational employment level and difference in share in the ownership change subsample and the control subsample, 2000–06 Percentage-point difference between predecessor and successor employment share Ownership change subsample Control subsample Occupational Group Ownership change subsample1 Occupational groups less likely to be retained Computer and mathematical science.... Business and financial operations.......................... Arts, design, entertain ment, sports, and media... Legal ...................................... Production............................. Management........................ Sales and related................. Office and administrative support................................ Architecture and engineering........................ Life, physical, and social science................................. Occupational groups more likely to be retained Food preparation and serving related.................. Transportation and material moving............... Installation, maintenance, and repair........................... Building and grounds cleaning and maintenance...................... Protective service................ Health care support........... Health care practitioner and technical..................... Education, training, and library................................... Community and social services................................ Construction and extraction............................ Groups with a change of less than 0.01 in either subsample Personal care and service.................................. Farming, fishing, and forestry................................. 1 2 PredSucPredSucPredSuccessor ecessor cessor SucPredControl Employ- ecessor ecessor cessor employ- employ- ecessor cessor Employ- employ- employsubment ment ment employ- employment ment sample employ- employ- difference ment ment ment share share share ment difference share ment (percent) (percent) (percent) (percent) –0.72 0.14 –.28 .39 –.03 –.01 –1.05 –.86 –.58 67,063 49,262 74,172 64,278 –17,801 3.32 2.61 432,022 472,447 40,425 –9,894 3.68 3.40 635,571 733,116 2.04 2.19 97,545 3.00 3.39 .07 19,136 17,435 –1,701 .95 .92 216,138 235,383 19,245 1.02 1.09 .01 4,818 4,293 -525 .24 .23 86,609 91,014 4,405 .41 .42 –.54 320,946 280,789 –40,157 15.90 14.85 2,217,795 2,149,982 –67,813 10.49 9.95 –.52 94,876 72,694 –22,182 4.70 3.84 980,344 888,859 –91,485 4.63 4.11 –.29 199,818 176,232 –23,586 9.90 9.32 1,794,334 1,771,712 –22,622 8.48 8.20 –.48 –.28 321,625 292,198 –29,427 15.94 15.45 3,336,426 3,348,698 12,272 15.77 15.49 –.21 –.06 48,962 41,897 –7,065 2.43 2.22 404,330 400,902 –3,428 1.91 1.85 11,263 324 .54 .60 176,926 198,318 21,392 .84 .92 2,865 5.64 6.18 1,069,685 1,086,022 16,337 5.06 5.02 8.83 1,670,394 1,684,016 13,622 .05 .08 10,939 .53 –.03 113,913 116,778 .23 –.11 173,556 166,968 .09 –.06 82,013 78,499 –3,514 4.06 4.15 .01 .87 .77 –.04 .11 .17 65,291 68,638 66,298 61,425 80,719 76,718 –3,866 3.24 3.25 772,076 780,072 7,996 3.65 3.61 12,081 3.40 4.27 551,749 587,624 35,875 2.61 2.72 10,420 3.28 4.06 577,304 626,014 48,710 2.73 2.90 1.02 .45 106,778 119,360 –6,588 8.60 12,582 5.29 7.79 798,334 802,064 3,730 3.77 3.71 6.31 1,306,749 1,432,698 125,949 6.18 6.63 2.50 2,262,029 2,375,172 113,143 10.69 10.99 .97 307,033 321,000 13,967 1.45 1.48 .40 .29 42,235 47,190 4,955 .10 .03 18,266 837 .11 .09 58,491 56,922 –1,569 2.90 3.01 858,143 896,039 37,896 4.06 4.14 (2) .11 55,579 52,035 –3,544 2.75 2.75 607,194 643,456 36,262 .02 (3) 5,674 5,765 91 .28 .30 Numbers are affected by rounding. Slight negative differences. 17,429 2.09 7.90 .86 3 90,503 93,366 2,863 2.87 2.98 .43 .43 Slight positive difference. Monthly Labor Review • September 2008 Business Ownership Change Chart 1. Ownership change subsample 1.5 The effect of business ownership change on different types of occupations, 2000–06: percentagepoint difference between predecessor and successor employment shares Ownership change subsample Health care practitioner and technical d ine 1 M 0.5 ly like e r o to eta be r 1 Protective service Health care support Food preparation and serving related Education, training, and library Community and social services Construction and extraction Life, physical, and social science Transportation and material moving Installation, maintenance, and repair 0 0.5 Personal care and service 0 Building and grounds cleaning and maintenance Farming, fishing, and forestry Arts, design, entertainment, sports, and media Legal Architecture Business and financial operations and engineering Office and administrative support Sales and related Computer and mathematical science ned Management etai r e b Production ly to –0.5 –1 Less –1.5 1.5 Quadrant I Quadrant II –1 like –1.5 Quadrant IV Quadrant III 1.5 –0.5 –1 –0.5 0 0.5 1 1.5 Control subsample ness and financial operations; arts, design, entertainment, sports, and media; and legal occupations. The following occupational groups shrank by more in the ownership change subsample than they shrank in the control subsample (occupational groups located to the right of the diagonal in quadrant III): production, management, sales and related, office and administrative support, and architecture and engineering occupations. Life, physical, and social science occupations grew in the ownership change subsample, but by less than they grew in the control subsample (the occupational group located to the right of the diagonal in quadrant I). By contrast, employees who were more likely to be retained were in occupations that (1) grew in the ownership change subsample while they shrank in the control subsample or (2) grew in the ownership change subsample by more than they grew in the control subsample. (None shrank in the ownership change subsample by less than they shrank in the control subsample.) The set of occupations in which employees were more likely to be retained is plotted to the left of the diagonal in the chart. Service-related jobs, such as health care, education, and Monthly Labor Review • September 2008 protection, were the most likely to be retained after ownership changes. The occupational groups that grew in the ownership change subsample while they shrank in the control subsample (those occupations located in quadrant II) were food preparation and serving related; transportation and material moving; installation, maintenance, and repair; and building and grounds cleaning and maintenance occupations. Occupational groups that grew by more in the ownership change subsample than in the control subsample (those located to the left of the diagonal in quadrant I) included protective service; health care support; health care practitioner and technical; education, training, and library; community and social services; and construction and extraction occupations. The types of jobs that were less likely or more likely to be retained after ownership changes varied by industry, as the next section details. Changes within occupational groups Examining detailed changes within occupational groups helps uncover trends among different business functions, such as human resources, marketing, and sales. The occupations discussed in this section and listed in table 4 Table 4. Difference between predecessor and successor occupational employment level and share in the ownership change subsample, by detailed occupation, 2000–06 Occupation Predecessor employment level Management occupations Chief executives............................................................................... 4,000 Marketing managers...................................................................... 3,802 Compensation and benefits managers................................... 534 Successor employment level 2,514 2,286 783 Business and financial operations occupations Claims adjusters, examiners, and investigators.................... 1,973 1,249 Compliance officers, except agriculture, construction, health and safety, and transportation................................ 1,172 1,660 Logisticians........................................................................................ 698 1,536 Management analysts................................................................... 10,323 6,430 Financial analysts............................................................................ 5,110 3,170 Computer and mathematical science occupations Computer programmers............................................................... Computer systems analysts......................................................... Network systems and data communications analysts...... Operations research analysts...................................................... 9,777 4,261 14,673 9,258 2,149 4,562 2,603 1,418 Predecessor Successor employment employment share share Difference in share1 Percent change in share1 0.2 .19 .03 0.13 .12 .04 –0.07 –32.95 –.07 –35.83 .01 56.23 .10 .07 –.03 .06 .03 .51 .25 .09 .08 .34 .17 .03 51.12 .05 134.68 –.17 –33.53 –.09 –33.81 .48 .73 .11 .13 .23 .49 .24 .08 –.26 –.24 .13 –0.05 –32.41 –53.49 –32.65 126.48 –41.86 Architecture and engineering occupations Aerospace engineers..................................................................... Electrical and electronics drafters............................................. Mechanical engineering technicians....................................... 1,518 864 1,441 932 1,143 873 .08 .04 .07 .05 .06 .05 –.03 –34.44 .02 41.12 –.03 –35.29 Community and social services occupations Child, family, and school social workers.................................. 1,574 2,309 .08 .12 .04 56.54 Education, training, and library occupations Middle school teachers, except special and vocational education...................................................................................... 2,456 3,440 Special education teachers, middle school........................... 575 732 Special education teachers, secondary school..................... 688 1,076 Teacher assistants............................................................................ 5,092 8,839 .12 .03 .03 .25 .18 .04 .06 .47 .06 49.47 .01 35.79 .02 66.86 .22 85.26 Arts, design, entertainment, sports, and media occupations Graphic designers........................................................................... 1,609 Merchandise displayers and window trimmers................... 867 Coaches and scouts........................................................................ 530 Radio and television announcers.............................................. 522 Reporters and correspondents.................................................. 593 Technical writers.............................................................................. 972 1,968 1,081 719 1,019 1,113 633 .08 .04 .03 .03 .03 .05 .10 .06 .04 .05 .06 .03 .02 30.61 .01 33.02 .01 44.49 .03 108.11 .03 100.34 –.01 –30.50 1,716 669 1,676 2,391 663 852 2,943 3,901 646 1,377 1,557 2,016 2,568 3,259 .09 .08 .03 .15 .03 .08 .13 .04 .13 .05 .21 .07 .11 .17 –.05 –58.35 .04 52.29 .01 37.08 .06 41.50 .04 127.50 .03 38.26 .05 35.46 Health care support occupations Home health aides.......................................................................... 15,642 21,588 Medical assistants........................................................................... 3,033 3,916 Medical equipment preparers.................................................... 641 1,190 .78 .15 .03 1.14 .21 .06 .37 47.30 .06 37.79 .03 97.80 Protective service occupations Private detectives and investigators........................................ Health care practitioner and technical occupations Physician assistants........................................................................ Respiratory therapists.................................................................... Diagnostic medical sonographers............................................ Radiologic technologists and technicians............................. Psychiatric technicians.................................................................. Surgical technologists................................................................... Medical records and health information technicians........ 742 1,306 .04 .07 .03 87.77 Personal care and service occupations Nonfarm animal caretakers......................................................... 516 Residential advisors........................................................................ 565 1,231 828 .03 .03 .07 .04 .04 154.30 .02 56.43 Sales and related occupations Securities, commodities, and financial services sales agents............................................................................................. 3,039 Travel agents..................................................................................... 663 1,943 826 .15 .03 0.1 .04 –.05 –31.74 .01 32.83 See footnote at end of table. Monthly Labor Review • September 2008 Business Ownership Change Table 4. Continued—Difference between predecessor and successor occupational employment level and share in the ownership change subsample, by detailed occupation, 2000–06 Occupation Predecessor employment level Demonstrators and product promoters................................. 2,493 Real estate sales agents................................................................ 560 Successor employment level Predecessor Successor employment employment share share Difference in share1 Percent change in share1 939 758 .12 .03 .05 .04 –.07 –59.76 .01 44.77 Office and administrative support occupations Payroll and timekeeping clerks.................................................. 3,241 4,104 Credit authorizers, checkers, and clerks.................................. 1,855 979 Interviewers, except eligibility and loan................................. 2,987 3,761 Meter readers, utilities................................................................... 639 839 Legal secretaries.............................................................................. 1,758 1,117 Medical secretaries......................................................................... 3,331 5,994 Insurance claims and policy processing clerks..................... 1,631 2,621 Office machine operators, except computer........................ 1,825 1,135 .16 .09 .15 .03 .09 .17 .08 .09 .22 .05 .20 .04 .06 .32 .14 .06 .06 35.12 –.04 –43.63 .05 34.39 .01 40.06 –.03 –32.15 .15 92.12 .06 71.53 –.03 –33.63 Farming, fishing, and forestry occupations Farmworkers, farm and ranch animals.................................... 550 1,025 .03 .05 .03 98.53 788 .06 .04 –.02 –34.95 729 903 2,791 3,477 .04 .14 .05 .18 .01 32.41 .05 32.97 .03 .05 .02 56.00 .09 .51 .11 .52 .03 .32 .06 .26 –.06 –.19 –.05 –.25 –68.76 –38.18 –42.77 –48.62 .09 .04 –.05 –59.43 .56 .36 –.20 –35.66 .24 .08 .14 .04 –.10 –.05 –41.23 –57.97 .09 .05 –.04 –42.59 .08 .65 .05 .89 –.02 –30.13 .23 35.66 .24 .04 .03 .13 .05 .05 –.11 –46.64 .01 31.3 .01 36.25 Construction and extraction occupations Helpers—pipelayers, plumbers, pipefitters, and steamfitters................................................................................... Installation, maintenance, and repair occupations Control and valve installers and repairers, except mechanical door......................................................................... Telecommunications line installers and repairers............... Coin, vending, and amusement machine servicers and repairers................................................................................ 1,294 605 885 Production occupations Aircraft structure, surfaces, rigging, and systems assemblers.................................................................................... 1,737 508 Electrical and electronic equipment assemblers................. 10,291 5,960 Engine and other machine assemblers................................... 2,275 1,219 Slaughterers and meatpackers................................................... 10,402 5,007 Forging machine setters, operators, and tenders, metal and plastic........................................................................ 1,831 696 Cutting, punching, and press machine setters, operators, and tenders, metal and plastic........................ 11,262 6,789 Multiple machine tool setters, operators, and tenders, metal and plastic........................................................................ 4,935 2,717 Bindery workers............................................................................... 1,710 674 Extruding and forming machine setters, operators, and tenders, synthetic and glass fibers.............................. 1,729 931 Separating, filtering, clarifying, precipitating, and still machine setters, operators, and tenders........................... 1,554 1,018 Helpers—production workers.................................................... 13,215 16,798 Transportation and material moving occupations Bus drivers, transit and intercity................................................. 4,929 Service station attendants........................................................... 794 Crane and tower operators.......................................................... 669 1 Numbers are affected by rounding. are the 70 occupations with substantial growth or decline11 after the ownership changes and with employment of at least 500 in the predecessor and successor groups. The table shows each occupation’s employment level and employment share in the ownership change subsample’s predecessor group and successor group, and the difference between them. The occupations are categorized by occupational group. Residual (“all other”) occupations are not shown. 10 2,464 975 853 Monthly Labor Review • September 2008 Changes in employment levels. Occupations with the greatest decline in employment level (by more than 1,500 employees) across all occupational groups in the ownership change subsample were computer programmers, computer systems analysts, four “assembly” production occupations, management analysts, transit and intercity bus drivers, financial analysts, demonstrators and product promoters, and marketing managers. Occupations that exhibited the greatest growth in employment level (by more than 1,500 employees) were home health aides, teacher assistants, production worker helpers, medical secretaries, and network systems and data communications analysts. Relative changes in employment shares. It is useful to examine in detail the occupational groups that fared poorly after ownership changes. Table 4 also shows (see columns titled “Predecessor employment share” and “Successor employment share”) that, in the computer and mathematical science group, which shrank the most in the ownership change subsample and grew in the control subsample, there were decreases in the employment shares of computer programmers, operations research analysts, and computer systems analysts. Network systems and data communications analysts, by contrast, were in higher demand. Among business and financial operations occupations, which had the second-largest difference in employment in the ownership change subsample relative to occupations in the control subsample, financial analysts and management analysts were most likely to be cut. Meanwhile, logisticians and compliance officers (except agriculture, construction, health and safety, and transportation) were most likely to grow. In the management group, compensation and benefits managers saw the greatest employment increase after ownership changes, while marketing managers saw decreases in employment share. One possible interpretation of these observations is that if the establishment is acquired by an establishment with similar staff, the employees who are more likely to be let go are those who appear to have redundant occupations. For example, an establishment that is acquired may no longer need a separate information technology or marketing department. Instead, it may have an increased need for occupations such as network systems and data communications analysts or human resources personnel to facilitate the organizational transition.Other occupations that deal more directly with customers or output, such as home health aides, medical secretaries, teacher assistants, and production assembly workers, might need to be retained in order to maintain good customer service or productivity. These occupations tend to be closely related to the core output of the establishment, while the others tend to serve as operational support. The decline in certain technical jobs also might be explained by outsourcing, although this interpretation is not examined here.12 Occupational composition by wage range A brief analysis of occupational employment share by wage range reveals that, after ownership changed, the wages of the employees performing analytical and administrative work shifted upwards, while the wages of the employees performing low-skilled service work or physical labor shifted downwards. Until November 2005, the OES microdata included data on detailed occupational employment in the wage ranges defined in table 5.13 Different occupational groups generally have their employment distributions concentrated in different wage ranges. For instance, management and computer and mathematical occupations were employed mostly in wage ranges starting at $21.50 to $27.24 and running through $55.50 to $69.99. Production and personal care and service occupations, however, were employed mostly in ranges beginning at $6.75 to $8.49 and going through $17.00 to $21.49. (The actual employment distributions are not shown in the table.) A shift in employment concentration from relatively lower paid employees to relatively higher paid employees occurred in several occupational groups. In these groups, either high-paid workers were retained or hired more often than low-paid workers, or low-paid workers were more likely to lose their jobs after ownership changes. A shift from low to high wage ranges occurred in analytical and administrative occupational groups such as management; architecture and engineering; computer and mathematical science; business and financial operations; health care practitioner and technical; community and social services; office and administrative support; and arts, design, entertainment, sports, and media, among other occupations. If high pay is correlated with tenure and knowledge, then high-earning workers may be the most costly to replace. This shift from low to high wage ranges also may be a result of businesses laying off workers with less tenure: although workers in analytical and administrative occupations were less likely to be retained after ownership changes, the employees who remained had higher wages. Conversely, employees who performed low-skilled service, physical labor, or personal service work exhibited a shift toward lower wage ranges, possibly because the lowpaid workers were retained or hired at higher rates than their higher paid counterparts or because higher paid workers received pay cuts. Among these workers were food preparation and serving related, sales and related, protective service, personal care and service, construction and extraction, production, transportation and material moving, and health care support occupations. Although many of these lower skilled service, physical-labor-intensive, or personal service occupations were most likely to be retained after ownership changes, they experienced Monthly Labor Review • September 2008 11 Business Ownership Change Table 5. Difference between predecessor and successor employment shares, by hourly wage range, ownership change subsample, 2000–061 Difference between predecessor and successor percent employment, by wage range, excluding 2006 and November 2005 successors and corresponding predecessors Occupational major group Under $6.75 $6.75 to $8.49 Wages shifted higher Management............................. –0.33 –0.25 Architecture and engineering............................. – –.08 Computer and mathematical science......... .08 –.16 Business and financial operations............................... .45 .23 Health care practitioner and technical . ..................... –.64 –1.31 Office and administrative support..................................... –.17 .36 Community and social services..................................... –2.82 –3.02 Building and grounds cleaning and maintenance ........................ –2.23 –8.69 Farming, fishing, and forestry...................................... –27.17 2.11 Arts, design, entertainment, sports, and media................ –1.34 .83 Life, physical, and social science...................................... – .17 Legal............................................. – –.08 Wages shifted lower Food preparation and serving related....................... 6.49 .30 Protective service..................... –2.17 –1.10 Education, training, and library........................................ –.88 .99 Personal care and service ........ –2.42 8.77 Construction and extraction................................. 2.26 1.90 Installation, maintenance, and repair................................. .51 –.45 Production.................................. .51 6.02 Transportation and material moving.................... 2.63 4.24 Health care support................ –2.37 2.14 Sales and related...................... 4.37 –.37 $8.50 to $10.74 $10.75 to $13.49 –0.70 –0.99 .12 $17.00 to $21.49 $21.50 to $27.24 $27.25 to $34.49 –1.80 –1.73 –2.74 –1.24 –.29 –.49 –2.66 –3.75 –1.27 .22 –2.31 –2.18 –.63 1.15 –2.48 –3.65 –1.29 –3.16 –3.18 –1.42 –3.97 .55 –3.77 1.67 2.36 –.55 .22 .01 2.27 3.46 1.14 –3.90 3.90 11.12 11.51 .52 $13.50 to $16.99 $55.50 to $69.99 $70.00 and over 0.61 3.51 2.50 3.15 .91 2.66 2.03 1.12 .46 –.26 4.37 2.59 –.27 –.51 –.29 2.51 1.63 .92 .29 7.04 4.69 .47 .36 .57 –.09 –.03 (2) (3) .53 –1.74 – – – .87 –.78 –.29 –.05 –.11 –.01 – – 6.23 3.31 1.22 1.75 – – – – – 1.13 1.06 .14 –.50 1.70 1.66 –1.09 –2.97 –3.89 3.27 –.18 –.49 2.22 –5.10 –2.22 2.28 –4.56 1.20 –5.46 –3.55 .92 –1.29 .63 –2.90 2.05 –.52 2.75 2.00 2.36 8.17 –4.73 –.96 10.00 5.79 –.91 –.68 –.20 –2.26 .02 –4.30 .01 –3.80 .00 –1.15 –.02 –.30 – –.03 – – 14.65 –2.25 –5.56 –5.62 –7.21 –6.25 2.35 –3.10 –2.96 –.99 –4.47 –.42 1.66 –.03 .93 – .35 – .45 4.30 .62 –1.66 –3.88 –2.86 –.99 –.10 –.03 – .14 12.32 –.96 –3.47 1.96 –3.55 –2.37 –3.03 2.22 2.61 –2.98 –.34 2.18 1.29 –.04 .03 –.02 –.03 –.01 –.01 – – –3.76 6.11 –1.14 –.11 –4.13 1.04 –.92 -1.77 –1.29 1.30 –.19 –1.35 –.74 .23 –1.22 .01 .03 .17 –.33 –.05 .04 –.34 – .03 –.66 – –.07 –1.34 – –.20 Excludes 2006 and November 2005 successors and corresponding predecessors. 2 Slight negative difference. downward shifts in their wages. This phenomenon could have occurred either because management was more likely to spare cheaper labor and employees in these occupations were willing to work at lower wages or because higher wage workers were replaced with lower wage workers. Table 5 shows the difference between the predecessor and successor employment shares for each occupational group Monthly Labor Review • September 2008 $43.75 to $55.49 .54 1 12 $34.50 to $43.74 Slight positve difference. NOTE: Dash indicates fewer than 10 establishments reporting occupations. 3 in each wage range.14 This study does not examine wage range shifts in detailed occupations within occupational groups; therefore, it does not explain whether an occupational group’s wages shifted to lower ranges because more low-paid occupations were hired within the group or because more high-paid occupations within the group were laid off or accepted pay cuts. Table 6. Employment by industry sector, in the ownership change subsample and across all establishments, 2000–06 Industry Total employment in predecessor units Total employment in successor units Information.................................................................. 112,318 80,285 Professional and technical services1. ................. 80,795 61,069 1 Management of companies and enterprises ..... 26,810 21,305 Finance and insurance............................................. 75,040 60,222 Manufacturing............................................................ 490,076 425,913 Transportation and warehousing1...................... 88,433 78,448 Retail trade................................................................... 247,052 229,464 Utilities.......................................................................... 14,661 13,766 Construction1. ............................................................ 62,733 61,213 Difference between predecessor and successor employment –32,033 –19,726 –5,505 –14,818 –64,163 –9,985 –17,588 –895 –1,520 Percent change from predecessor to successor employment Percent change betweeen 2002 and 2005 average annual employment, QCEW –28.52 –9.16 –24.41 6.02 –20.53 2.81 –19.75 4.13 –13.09 –6.70 –11.29 2.74 –7.12 1.58 –6.10 –7.02 –2.42 8.76 Real estate and rental and leasing1. ................... 12,794 12,524 –270 –2.11 4.79 Wholesale trade1....................................................... 74,235 72,673 –1,562 –2.10 2.41 Other services, except public administration1...... 28,956 28,785 –171 –.59 1.84 Accommodation and food services.................... 119,095 119,452 357 .30 6.61 Arts, entertainment, and recreation................... 21,136 21,495 359 1.70 3.86 Educational services................................................. 80,642 84,732 4,090 5.07 9.91 Administrative and support and waste management and remediation services...... 175,422 185,003 9,581 5.46 6.35 Health care and social assistance........................ 286,663 309,902 23,239 8.11 7.01 Mining1. ........................................................................ 5,672 9,630 3,958 69.78 10.76 1 Ownership change subsample employment difference and overall employment difference had opposite signs. NOTE: Table excludes agriculture, forestry, fishing, and hunting Sectors most affected by ownership changes Table 6 shows total employment by industry sector in the ownership change subsample predecessor and successor groups, as well as the employment change and the percent change in employment from the predecessor to the successor groups.15 To provide a basis for comparison with all establishments in the economy, the last column contains the percent change between 2002 and 2005 QCEW average annual private-sector employment. (See also chart 2.) About half of the sectors contracted in the ownership change subsample while they grew overall in the economy: professional and technical services; management of companies and enterprises; finance and insurance; transportation and warehousing; retail trade; construction; real estate and rental and leasing; wholesale trade; and other services, except public administration. Moreover, all sectors except mining and except health care and social assistance either shrank in the ownership change subsample while they grew overall, or grew in the subsample by a smaller percentage than they grew overall. The information and manufacturing sectors contracted substantially more in the because the OES and QCEW have incomplete coverage of this sector. Table also excludes OES-designated government industries. ownership change subsample than they contracted across all establishments. In the information sector, employment in establishments that changed ownership fell by 29 percent, while employment in all establishments in this sector fell by 9 percent over the same period. Sectors that grew in the ownership change subsample, but by less than the industry grew as whole, were accommodation and food services; arts, entertainment, and recreation; administrative and support and waste management and remediation services; and educational services. Mining grew the most in the ownership change subsample relative to the economy. Much of this growth was due to oil and gas extraction and will be discussed in the next section. That some industries experienced particularly large employment declines in the ownership change subsample relative to the economy as a whole might explain some large declines in occupational groups that are central to those industries. For instance, in May 2006, sales and related occupations made up 54 percent of the retail trade industry. The large employment drop in retail trade establishments that changed ownership (despite overall expansion) between 2000 and 2006 might explain the cross-industry observation that sales and related occuMonthly Labor Review • September 2008 13 Business Ownership Change Chart 2. The effect of business ownership change on industry employment in the ownership change subsample and across all establishments, 2000–06: percent change in employment Ownership Ownership change subsample 70 Quadrant II change subsample 70 Quadrant I Mining 50 50 Administrative and support and waste management and remediation services 30 10 –10 –30 30 Arts, entertainment, and recreation Health care and social assistance Educational services Other services, except public administration Accommodation and food services Construction Wholesale trade Real estate and rental and leasing Real trade Utilities Transportation and warehousing Manufacturing Finance and insurance Management of companies Professional and technical services and enterprises Information –10 –30 –50 –50 –70 Quadrant III –7.0 –50 10 Quadrant IV –30 –10 10 30 50 QCEW, 2002–05 pations shrank by more in the ownership change subsample than they shrank across establishments in the control subsample. Similarly, one might speculate that the contraction in professional and technical services establishments and in information establishments contributed to the large decline in computer and mathematical science occupations. Likewise, the contraction in manufacturing establishments might have contributed to the large decline in production occupations, which made up 53 percent of the manufacturing sector in May 2006. Without a closer look at the data, however, the relationship between the decline in the industry sector and the overall employment decline of core occupations is not entirely clear. To see whether industries are more likely to reduce or retain employment in core occupations or in operational support occupations, the next section examines changes in the occupational composition of detailed industries. Occupational change by detailed industry In every establishment, workers in certain occupations are central to its industry’s core business function, and these 14 Monthly Labor Review • September 2008 –70 –70 workers tend to be employed in relatively high concentrations. Establishments also employ operational support, or auxiliary, workers in occupations that support the core business function. Occupations that serve as support in some industries can be the core of other industries. For example, in the accounting services industry, billing clerks might be a core occupation while janitors are an operational support occupation. By contrast, in the building services industry, janitors might be considered the core occupation while billing clerks are an operational support occupation. Core occupations can be thought of as those most directly related to the establishment’s output. Earlier studies of OES data show that when establishments shrink, they tend to shed support jobs at higher rates than they shed core occupations.16 In what follows, 10 industries are examined in further detail to see whether, when the declines in employment accompany ownership changes, the declines also are concentrated in support occupations. The results show that 5 of the highlighted industries experienced a shift in their employment concentration from support to core occupations after an ownership change, 3 others experienced a shift in employment concentration from core occupations to support oc- cupations, and 2 had little difference in the overall mix of core and support occupations after the change. The 10 industries that contracted the most after ownership changes were computer systems design and related services, wired telecommunication carriers, motor vehicle parts manufacturing, department stores, grocery stores, securities and commodity contracts intermediation and brokerage, management of companies and enterprises, scheduled air transportation, depository credit intermediation, and plastics product manufacturing. These industries either expanded in the overall economy or shrank by a lesser magnitude in the overall economy than they did in the ownership change subsample. At the other end of the spectrum, oil and gas extraction experienced the highest growth in the ownership change subsample (767 percent) and the third-highest increase in employment level after ownership changes, and the industry grew by a substantially greater magnitude in the subsample than it did in the economy. Tables 7–10 show how the employment of core and support occupations changed after an ownership change in these selected industries. The percentage of industry employment in the predecessor establishments represents each occupational group’s employment share in the industry, out of total industry employment of the predecessor establishments. Likewise, the percentage of industry employment in the successor establishments represents each occupational group’s employment share in the industry, out of total industry employment in the successor establishments. Industries with increased concentrations of core occupations. In most industries with large employment declines, a change in ownership resulted in an increased employment share of core occupations and a decreased share of operational support occupations. For example, as shown in table 7, in scheduled air transportation there was an increase in the share of core occupations—personal care and service occupations, which include flight attendants; and transportation and material moving occupations, which include pilots. At the same time, there was a decrease in the share of support occupations—office and administrative support; and installation, maintenance, and repair occupations. It is possible that the decrease was due to increased outsourcing in the industry, although this article does not examine that possibility. Similarly, wired telecommunications carriers that changed ownership had increased shares of installation, maintenance, and repair; computer and mathematical science; and architecture and engineering occupations, and decreased shares of office and administrative support, management, and business and financial operations occupations. Finally, in securities and commodity contracts intermediation and brokerage, there likewise was an increase in the shares of core occupations such as business and financial operations occupations and sales and related occupations (the latter of which includes securities, commodities, and financial services sales agents) and a decline in support occupations, with computer and mathematical science occupations falling from 28 percent before the ownership changes to 14 percent afterwards and office and administrative support occupations dropping from 19 percent to 15 percent of total employment. In depository credit intermediation (which shrank in the ownership change subsample, but grew overall in the economy), which consists of credit unions and commercial banks, the share of core business and financial operations occupations rose from 14 percent to 18 percent of total employment. The share of core office and administrative support occupations, which include tellers and similar core occupations employed in banks, was relatively stable at 61 percent, and sales and related occupations increased from 4 percent to 6 percent of total employment in the industry. The share of support occupations, such as management, computer and mathematical science, and legal occupations, fell. Like the aforementioned industries, management of companies and enterprises (which shrank in the ownership change subsample, but grew overall in the economy), in which operational support is the core business function, had increases in all core occupations and decreases in nonessential functions. This observation confirms previous behavioral research which found that when company headquarters and auxiliary offices undergo mergers or acquisitions, their chief executives tend to protect their immediate subordinates, managers, and administrators.17 Industries with decreased concentrations of core occupations. Sometimes a change in ownership resulted in a decreased employment share of core occupations and an increased share of operational support occupations. Industries that followed this trend included service industries such as grocery stores and department stores. In department stores and grocery stores, sales and related occupations represent the core of the business function. After an ownership change, the share of sales and related occupations in department stores fell from 73 percent to 67 percent, as shown in table 8. Similarly, in grocery stores, the share of sales and related occupations fell from 38 percent to 36 percent. In both of these industries, the share of management occupations and office and administrative support occupations rose after a change in ownership. In plastics product manufacturing establishments, the Monthly Labor Review • September 2008 15 Business Ownership Change Table 7. Industries with increased concentrations of core occupations, 2000–06 Occupational major group Predecessor employment Successor employment Predecessor employment share Successor employment share Percentagepoint difference NAICS 4811, Scheduled air transportation Total, all occupations........................................ 25,159 20,549 … … … Management .............................................................. 376 188 1.49 .91 –.58 Business and financial operations . ..................... 767 684 3.05 3.33 .28 Computer and mathematical science ................ 115 139 .46 .68 .22 Architecture and engineering .............................. 640 170 2.54 .83 –1.72 Legal .............................................................................. 11 11 .04 .05 .01 Arts, design, entertainment, sports, and media.... 133 89 .53 .43 –.10 Health care practitioner and technical . ............ 12 15 .05 .07 .03 Protective service ...................................................... 11 7 .04 .03 –.01 Food preparation and serving related . ............. 91 65 .36 .32 –.05 Personal care and service . ..................................... 6,892 6,234 27.39 30.34 2.94 Sales and related ....................................................... 178 153 .71 .74 .04 Office and administrative support . .................... 7,356 5,902 29.24 28.72 –.52 Installation, maintenance, and repair ................ 3,531 1,761 14.03 8.57 –5.46 Transportation and material moving . ............... 4,968 5,074 19.75 24.69 4.95 NAICS 5171, Wireless telecommunication carriers Total, all occupations.......................................... 42,629 30,277 … … … Management .............................................................. 3,351 834 7.86 2.75 –5.11 Business and financial operations . ..................... 4,807 3,293 11.28 10.88 –.40 Computer and mathematical science ................ 5,915 5,990 13.88 19.78 5.91 Architecture and engineering .............................. 3,116 2,570 7.31 8.49 1.18 Life, physical, and social science .......................... 416 152 .98 .50 –.47 Legal .............................................................................. 161 33 .38 .11 –.27 Arts, design, entertainment, sports, and media.... 575 78 1.35 .26 –1.09 Health care practitioner and technical . ............ 4 7 .01 .02 .01 Protective service ...................................................... 12 6 .03 .02 –.01 Building and grounds cleaning and maintenance .......................................................... 26 13 .06 .04 –.02 Sales and related ....................................................... 4,114 2,543 9.65 8.40 –1.25 Office and administrative support . .................... 13,138 7,404 30.82 24.45 –6.37 Construction and extraction ................................. 8 5 .02 .02 –.002 Installation, maintenance, and repair ................ 6,937 7,277 16.27 24.03 7.76 Production ................................................................... 3 33 .01 .11 .10 Transportation and material moving . ............... 21 39 .05 .13 .08 NAICS 5231, Securities and commodity contracts intermediation and brokerage Total, all occupations.......................................... 9,093 3,482 … … … Management .............................................................. 1,711 687 18.82 19.73 .91 Business and financial operations . ..................... 1,370 1,214 15.07 34.87 19.80 Computer and mathematical science ................ 2,533 489 27.86 14.04 –13.81 Legal .............................................................................. 119 26 1.31 .75 –.56 Sales and related ....................................................... 992 540 10.91 15.51 4.60 Office and administrative support . .................... 1,735 509 19.08 14.62 –4.46 NAICS 5221, Depository credit intermediation Total, all occupations........................................ 28,275 21,465 … … … Management .............................................................. 2,881 1,774 10.19 8.26 –1.93 Business and financial operations . ..................... 3,860 3,762 13.65 17.52 3.87 Computer and mathematical science ................ 2,718 1,378 9.61 6.42 –3.20 Architecture and engineering .............................. 88 59 .31 .27 –.04 Life, physical, and social science .......................... 45 49 .16 .23 .07 Legal .............................................................................. 80 19 .28 .09 –.19 Arts, design, entertainment, sports, and media.... 116 59 .41 .27 –.14 Protective service ...................................................... 51 29 .18 .14 –.05 Building and grounds cleaning and maintenance .......................................................... 43 25 .15 .12 –.04 16 Monthly Labor Review • September 2008 Table 7. Continued—Industries with increased concentrations of core occupations, 2000–06 Occupational major group Predecessor employment Successor employment Predecessor employment share Successor employment share Percentagepoint difference Sales and related........................................................ 1,081 1,249 3.82 5.82 1.99 Office and administrative support........................ 17,255 13,010 61.03 60.59 –.44 Installation, maintenance, and repair.................. 40 47 .14 .22 .08 Transportation and material moving................... 9 4 .03 .02 –.01 NAICS 5511, Management of companies and enterprises Total, all occupations.......................................... 26,541 20,953 … … … Management................................................................ 3,829 3,691 14.43 17.62 3.19 Business and financial operations......................... 3,480 3,581 13.11 17.09 3.98 Computer and mathematical science.................. 1,930 1,748 7.27 8.34 1.07 Architecture and engineering................................ 788 778 2.97 3.71 .74 Life, physical, and social science............................ 441 324 1.66 1.55 –.12 Community and social services.............................. 82 64 .31 .31 .00 Legal................................................................................. 218 211 .82 1.01 .19 Education, training, and library.............................. 8 30 .03 .14 .11 Arts, design, entertainment, sports, and media..... 257 324 .97 1.55 .58 Health care practitioner and technical................ 736 59 2.77 .28 –2.49 Protective service........................................................ 148 91 .56 .43 –.12 Food preparation and serving related................. 410 101 1.54 .48 –1.06 Building and grounds cleaning and maintenance............................................................ 370 132 1.39 .63 –.76 Sales and related......................................................... 1,369 1,066 5.16 5.09 –.07 Office and administrative support........................ 7,478 6,122 28.18 29.22 1.04 Construction and extraction................................... 259 139 .98 .66 –.31 Installation, maintenance, and repair.................. 886 530 3.34 2.53 –.81 Production..................................................................... 1,892 670 7.13 3.20 –3.93 Transportation and material moving................... 1,400 1,283 5.27 6.12 .85 NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed. share of production occupations fell from 59 percent to 57 percent and the share of transportation and material moving occupations also fell. By contrast, the share of office and administrative support occupations and management occupations rose. This conjunction of events supports Donald Siegel and Frank Lichtenberg’s finding that in manufacturing firms, only production personnel, as opposed to nonproduction employees, experienced relative employment declines.18 Industries without a clear shift in either core or support occupations. Two of the 10 industries examined in this section show little difference in the overall mix of core and support occupations. However, there was a shift in employment among the core occupations in these industries. As table 9 shows, in motor vehicle parts manufacturing the share of labor-intensive production occupations rose from 65 percent to 67 percent while architecture and engineering occupations; installation, maintenance, and repair occupations; and transportation and material moving occupations each decreased slightly. There was little change in support occupations, such as management occupations and office and administrative support occupations. In computer systems design and related services (which shrank in the ownership change subsample, but grew overall in the economy), there were shifts within the core and support occupational groups, but there was no clear shift toward core occupations. Among core occupations, computer and mathematical science occupations and architecture and engineering occupations saw their employment shares remain relatively stable while the share of installation, maintenance, and repair occupations, which include computer repairers, increased from 2 percent to 5 percent. Among support occupations, office and administrative support occupations shrank while sales and related occupations grew. Core detailed occupations that increased the most included sales engineers; logisticians; network systems and data communications Monthly Labor Review • September 2008 17 Business Ownership Change Table 8. Industries with decreased concentrations of core occupations, 2000–06 Occupational major group Predecessor employment Successor employment Predecessor employment share Successor employment share Percentagepoint difference NAICS 4521, Department stores Total, all occupations........................................ 72,158 63,752 … … … Management .............................................................. 1,072 1,026 1.49 1.61 .12 Business and financial operations . ..................... 475 232 .66 .36 –.29 Computer and mathematical science ................ 13 8 .02 .01 –.01 Arts, design, entertainment, sports, and media . ...................................................................... 540 571 .75 .90 .15 Health care practitioner and technical . ............ 637 622 .88 .98 .09 Health care support ................................................. 35 29 .05 .05 (1) Protective service ...................................................... 1,350 1,295 1.87 2.03 .16 Food preparation and serving related . ............. 759 576 1.05 .90 –.15 Building and grounds cleaning and maintenance .......................................................... 230 342 .32 .54 .22 Personal care and service . ..................................... 715 823 .99 1.29 .30 Sales and related ....................................................... 52,902 42,904 73.31 67.30 –6.02 Office and administrative support . .................... 11,556 13,805 16.01 21.65 5.64 Construction and extraction ................................. 38 24 .05 .04 –.02 Installation, maintenance, and repair ................ 216 310 .30 .49 .19 Production ................................................................... 387 369 .54 .58 .04 Transportation and material moving . ............... 1,218 816 1.69 1.28 –.41 NAICS 4451, Grocery stores Total, all occupations........................................ 83,107 75,679 … … … Management .............................................................. 1,186 1,107 1.43 1.46 .04 Business and financial operations . ..................... 172 167 .21 .22 .01 Computer and mathematical science ................ 9 16 .01 .02 .01 Arts, design, entertainment, sports, and media..... 241 295 .29 .39 .10 Health care practitioner and technical . ............ 1,554 1,830 1.87 2.42 .55 Health care support ................................................. 368 372 .44 .49 .05 Protective service ...................................................... 451 239 .54 .32 –.23 Food preparation and serving related . ............. 8,731 8,915 10.51 11.78 1.27 Building and grounds cleaning and maintenance .......................................................... 883 610 1.06 .81 –26 Personal care and service . ..................................... 807 37 .97 .05 –.92 Sales and related ....................................................... 31,705 27,393 38.15 36.19 –1.96 Office and administrative support . .................... 24,598 22,598 29.60 29.86 .26 Farming, fishing, and forestry ............................... 108 53 .13 .07 –.06 Installation, maintenance, and repair ................ 386 218 .46 .29 –.18 Production ................................................................... 5,066 4,959 6.10 6.55 .46 Transportation and material moving . ............... 6,842 6,870 8.23 9.08 .84 NAICS 3261, Plastics product manufacturing Total, all occupations.......................................... 19,991 17,835 … … … Management .............................................................. 758 708 3.79 3.97 .18 Business and financial operations . ..................... 265 348 1.33 1.95 .63 Computer and mathematical science ................ 59 56 .30 .31 .02 Architecture and engineering .............................. 595 815 2.98 4.57 1.59 Life, physical, and social science .......................... 77 9 .39 .05 –.33 Arts, design, entertainment, sports, and media . ........................................................................... 29 38 .15 .21 .07 Health care practitioner and technical . ............ 3 12 .02 .07 .05 Building and grounds cleaning and maintenance .......................................................... 98 89 .49 .50 .01 Sales and related ....................................................... 202 282 1.01 1.58 .57 Office and administrative support . .................... 1,509 1,435 7.55 8.05 .50 Construction and extraction ................................. 346 116 1.73 .65 –1.08 Installation, maintenance, and repair ................ 1,384 1,115 6.92 6.25 –.67 Production ................................................................... 11,708 10,191 58.57 57.14 –1.43 Transportation and material moving . ............... 2,954 2,616 14.78 14.67 –.11 Slight negative percentage-point difference. NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed. 1 18 Monthly Labor Review • September 2008 Table 9. Industries without a clear shift in either core or support occupations, 2000–06 Occupational major group Predecessor employment Successor employment Predecessor employment share Successor employment share Percentagepoint difference NAICS 3363, Motor vehicle parts manufacturing Total, all occupations....................................... 35,706 26,443 … … … Management ............................................................. 1,045 716 2.93 2.71 –.22 Business and financial operations . .................... 717 618 2.01 2.34 .33 Computer and mathematical science .............. 132 122 .37 .46 .09 Architecture and engineering ............................. 2,834 1,811 7.94 6.85 –1.09 Life, physical, and social science ......................... 49 58 .14 .22 .08 Arts, design, entertainment, sports, and media . ..................................................................... 61 75 .17 .28 .11 Health care practitioner and technical . ........... 37 38 .10 .14 .04 Protective service ..................................................... 36 33 .10 .12 .02 Building and grounds cleaning and maintenance ......................................................... 154 103 .43 .39 –.04 Sales and related ...................................................... 474 312 1.33 1.18 –.15 Office and administrative support . ................... 1,610 1,287 4.51 4.87 .36 Construction and extraction ................................ 537 378 1.50 1.43 –.07 Installation, maintenance, and repair ............... 2,075 1,186 5.81 4.49 –1.33 Production .................................................................. 23,033 17,730 64.51 67.05 2.54 Transportation and material moving . .............. 2,910 1,976 8.15 7.47 –.68 NAICS 5415, Computer systems design and related services Total, all occupations....................................... 33,688 15,081 … … … Management ............................................................. 2,937 1,196 8.72 7.93 –.79 Business and financial operations . .................... 3,520 1,507 10.45 9.99 –.46 Computer and mathematical science................. 15,005 6,792 44.54 45.04 .50 Architecture and engineering ............................. 2,519 936 7.48 6.21 –1.27 Life, physical, and social science ......................... 113 93 .34 .62 .28 Legal ............................................................................. 36 16 .11 .11 (1) Arts, design, entertainment, sports, and media . ..................................................................... 595 269 1.77 1.78 .02 Protective service ..................................................... 54 24 .16 .16 (1) Sales and related ...................................................... 1,025 801 3.04 5.31 2.27 Office and administrative support . ................... 6,767 2,535 20.09 16.81 –3.28 Installation, maintenance, and repair ............... 533 717 1.58 4.75 3.17 Production .................................................................. 471 66 1.40 .44 –.96 Transportation and material moving . .............. 65 78 .19 .52 .32 1 Slight negative percentage-point difference. NOTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed. analysts; computer software engineers, systems software; computer software engineers, applications; and computer support specialists. Meanwhile, the core detailed occupations that decreased the most after a change in ownership included industrial engineers; computer specialists, all other; computer programmers; and computer hardware engineers. An example of an industry that grew after ownership changes. The same study which found that shrinking establishments shed support occupations first also found that growing establishments add support occupations first.19 In order to contrast employment changes among industries that grew after ownership changes with those which declined, one growing industry is examined in detail. The oil and gas extraction industry (which grew by a greater magnitude in the subsample than it did overall) exhibited a drastic shift from essential labor-intensive occupational groups to operational support occupations, despite the fact that each occupational group increased in Monthly Labor Review • September 2008 19 Business Ownership Change Table 10. Example of an industry that grew after ownership change, 2000–06 Occupational major group Predecessor employment Successor employment NAICS 2111, Oil and gas extraction Total, all occupations....................................... 441 3,824 Management ............................................................. 36 534 Business and financial operations . .................... 30 997 Computer and mathematical science ............... 8 224 Architecture and engineering ............................. 33 329 Life, physical, and social science ......................... 10 400 Legal ............................................................................. 2 139 Sales and related ...................................................... 2 200 Office and administrative support . ................... 68 486 Construction and extraction ................................ 126 210 Installation, maintenance, and repair ............... 31 64 Production .................................................................. 28 76 Transportation and material moving . .............. 63 117 Predecessor employment share Successor employment share Percentagepoint difference … … … 8.16 13.96 5.80 6.80 26.07 19.27 1.81 5.86 4.04 7.48 8.60 1.12 2.27 10.46 8.19 .45 3.63 3.18 .45 5.23 4.78 15.42 12.71 –2.71 28.57 5.49 –23.08 7.03 1.67 –5.36 6.35 1.99 –4.36 14.29 3.06 –11.23 N.OTE: Detailed data on employment may not sum to total employment because not all occupational groups are listed. employment level in the successor establishments. Core construction and extraction occupations in the industry held a dominant 29-percent share before ownership changes, but only a 6-percent share afterwards, while the share of support business and financial operations occupations increased from almost 7 percent to a dominant 26 percent after ownership changes. In addition to construction and extraction occupations, the following laborintensive occupational groups decreased in employment share after ownership changes: installation, maintenance, and repair; production; and transportation and material moving occupations. In addition to business and financial operations occupations, the following operational support occupations increased in employment share after ownership changes: management; computer and mathematical science; architecture and engineering; life, physical, and social science; and legal occupations. These findings in the establishments that changed ownership in the oil and gas extraction industry are consistent with those of a separate study of recent trends in occupational employment across all establishments in the industry.20 This research found that, during the recent spate of oil and gas price increases, the overall staffing of the industry was shifting away from extraction activities and toward exploration. Occupational employment by establishment size This final section shows that changes in occupational com20 Monthly Labor Review • September 2008 position that followed ownership changes varied by the size of the establishment. Establishments were grouped into five size classes before and after the ownership change: 1 to 9 employees; 10 to 49 employees; 50 to 249 employees; 250 to 999 employees; and 1,000 or more employees. In order to focus on changes in occupational composition within size classes, the subsample was then divided into five size groups based on deviations of fewer than two size classes: very small, small, medium, large, and very large.21 Establishments chosen for the study were limited to the 21,923 out of the 22,198 establishments that changed by fewer than two size classes: 17,166 establishments that did not change size class, 2,598 establishments that decreased by one size class, and 2,159 establishments that increased by one size class.22 As was done in the industry analysis, the percent employment of each occupational group in predecessor and successor establishments was calculated for every size group. The predecessor employment share represents the percentage of occupational employment out of total predecessor employment in the size group, and the successor employment share represents the percentage of occupational employment out of total successor employment in the size group. As before, growth indicates growth in the employment share, or relative importance of the occupation, not necessarily growth in the employment level. The changes in occupational share are shown in table 11. Five occupational groups grew in establishments of all sizes: life, physical, and social science; health care practi- Table 11. Percentage-point difference between predecessor and successor employment share in the ownership change subsample, by establishment size, 2000–06 Establishment size Occupational major group Very small Management..................................................................................... Business and financial operations............................................. Computer and mathematical science...................................... Architecture and engineering..................................................... Life, physical, and social science................................................. Community and social services.................................................. Legal..................................................................................................... Education, training, and library.................................................. Arts, design, entertainment, sports, and media....................................................................................... Health care practitioner and technical ................................... Health care support........................................................................ Protective service............................................................................. Food preparation and serving related..................................... Building and grounds cleaning and maintenance.................................................................................. Personal care and service.............................................................. Sales and related.............................................................................. Office and administrative support............................................. Farming, fishing, and forestry . .................................................. Construction and extraction........................................................ Installation, maintenance, and repair....................................... Production.......................................................................................... Transportation and material moving ..................................... 1 Small Medium Large Very large –1.03 .64 –.04 –.04 .02 .08 (1) .30 –1.33 .52 .15 .05 .13 .04 –.04 .10 –0.86 .13 .09 .06 .03 –.08 .03 .34 –0.33 (1) .10 –.11 .06 .18 –.06 .31 –1.14 –1.48 –2.62 –.26 .02 .28 –.04 1.54 –.15 .14 .42 .02 .26 .23 .17 .36 .27 –.46 .02 .29 .22 1.04 –.02 (1) 1.06 .97 .83 .21 –.30 2.86 1.58 .63 .79 .19 –.40 –.78 –1.10 .07 .60 –.33 .50 .64 .04 –.07 –.78 –.22 .08 .09 –.11 .45 .33 (1) .07 –1.04 –.60 (1) –.01 .02 –.03 .30 –.48 –.36 –1.19 –.11 .01 .11 .47 –1.21 –.47 .56 .50 –.73 –.36 .03 .04 –.45 –2.24 .81 Less than 0.05 percentage-point difference. tioner and technical; health care support; education, training, and library; and protective service occupations. In contrast, three occupational groups shrank in establishments of all sizes: management occupations (with its decrease the most in small, very small, and very large establishments), sales and related occupations (with its decrease the most in medium and large establishments), and office and administrative support occupations (with its decrease the most in very small establishments). The direction and magnitude of changes in all other occupational groups, however, varied. Analytical and production occupations—business and financial operations; architecture and engineering; legal; arts, design, entertainment, sports, and media; and production occupations—did not grow in large and very large establishments. Service occupations—personal care and service; food preparation and serving related; community and social services; health care support; health care practitioner and technical; education, training, and library; building and grounds cleaning and maintenance; and transportation and material moving occupations—tended to grow the most in very large establishments. One interesting observation is that production occupations grew only in very small or small establishments and shrank in larger establishments. In fact, there was an inverse correlation between the establishment size and the effect of ownership change on production occupations. This correlation may be the result of larger companies being able to capture economies of scale. Another observation is that computer and mathematical occupations were fairly stable in all but the very large establishments. After ownership changes, the share of computer and mathematical occupations fell by 2.6 percent, the largest change of all occupational groups in any establishment size. An overview by size group also reveals some trends. Very small predecessor establishments, on the whole, were dominated by sales and related occupations and office and administrative support occupations. After ownership changes, the greatest decreases were in management, office and administrative support, and sales and related occupations, and the greatest increases were in business and financial operations and transportation and material moving occupations. In the small size group, the greatest changes were, again, decreases in management occupations and sales and related occupations and an increase in business and financial operations occupations. In the medium size group, the greatest changes were an increase in protective service occupations and decreases in sales Monthly Labor Review • September 2008 21 Business Ownership Change and related occupations and management occupations. In the large size group, the greatest changes were an increase in health care practitioner and technical occupations and decreases in production occupations and sales and related occupations. Finally, in the very large size group, the greatest changes were an increase in health care practitioner and technical occupations and health care support occupations and decreases in computer and mathematical science, production, business and financial operations, and management occupations. tions did not grow in large establishments. In contrast, many of the jobs that were more likely to be retained after ownership changes were those which performed service work, such as health care and education, and most of these groups’ wages shifted toward lower ranges. Very large establishments were most likely to retain their service occupations after changing ownership. This article leaves room for future research on the effect of ownership changes on occupational employment and wages. The methodology for identifying specific types OCCUPATIONS THAT WERE LEAST LIKELY to be retained of ownership changes and capturing more predecessor after ownership changes were those which performed ana- and successor establishment staffing data can be refined. lytical, clerical, and production work, and most of these groups’ Further regression analysis can be conducted on the effect wages shifted toward higher ranges. These occupations tended of ownership changes on core and support business functo be support occupations in the industries in which their em- tions, on wages by detailed occupation, and on staffing ployment shares declined. Some of them declined in establish- by industry or geographic location. OES data are an imments of all sizes, although many shrank the most in large and portant input in understanding and predicting the labor very large establishments. Analytical and production occupa- market outcomes of business dynamics. Notes 1 Counts include mergers, full- or partial-interest acquisitions, divestitures, and leveraged buyouts valued at $5 million. See Statistical Abstract of the United States, 2006 (U.S. Census Bureau, 2007), Table 751, “Mergers and Acquisitions—Summary, 1990 to 2003.” “What Goes Up, Must Come Down?” Mergers & Acquisitions: The Dealermaker’s Journal, July 2007, pp. 10-11; on the Internet at search.ebscohost. com.proxy2.library.jhu.edu/login.aspx?direct=true&db=buh&AN=25593842 &site=ehost-live (visited Sept. 8, 2007). 2 3 Donald Siegel and Frank Lichtenberg, “The Effect of Ownership Changes on the Employment and Wages of Central-Office and Other Personnel,” Journal of Law and Economics, October 1990, pp. 383–408. 4 Robert McGuckin and Sang Nguyen, The impact of ownership changes: a view from labor markets (U.S. Census Bureau, Center for Economic Studies, 2001). 5 Robert McGuckin, Sang Nguyen, and Arnold Reznek, “On Measuring the Impact of Ownership Change on Labor: Evidence from U.S. FoodManufacturing Plant-Level Data,” in John Haltiwanger, Marilyn Manser, and Robert Topel (eds.), Labor Statistics Measurement Issues, NBER Studies in Income and Wealth, vol. 60 (Chicago, University of Chicago Press, 1998). Approximately 2 percent of the wage data were imputed. 6 In addition, 1,233 establishments reported 3 times, and 5 firms reported 4 times; these 1,238 firms were excluded from the ownership change subsample. The exclusion of establishments that reported more than twice should not introduce significant bias into the subsample. 7 8 See, for example, the Thomson Financial Merger and Corporate Transactions database, on the Internet at www.census.gov/compendia/statab/2006/ tables/06s0752.xls. Mergers, full- or partial-interest acquisitions, divestitures, and leveraged buyouts valued at $5 million or more are listed in the database. 9 The method for obtaining published OES estimates applies weights for each sample establishment in each panel of the survey in order to represent all establishments that were part of the in-scope frame from which the panel was selected. In the study presented in this article, employment was not adjusted by the unit sampling weights. According to QCEW annual private-sector employment figures, total employment was 107,577,281 in 2002 and 110,611,016 in 2005. 10 22 Monthly Labor Review • September 2008 11 Occupations listed are those whose employment shares grew or declined by at least 0.01 percentage point and 30 percent from the predecessor to the successor group. 12 For a discussion of the outsourcing of technical jobs, see Ashkok Bardhan and Cynthia Kroll, “The New Wave of Outsourcing,” Fisher Center Research Report No. 1103 (Berkeley, CA, Fisher Center for Real Estate & Urban Economics, November 2003), on the Internet at repositories.cdlib.org/iber/ fcreue/reports/1103 (visited Sept. 26, 2008); Alan Blinder, “How Many U.S. Jobs Might Be Offshorable?” CEPS Working Paper No. 142 (Princeton, NJ, Center for Economic Policy Studies, March 2007), on the Internet at www. princeton.edu/~ceps/workingpapers/142blinder.pdf (visited Sept. 26, 2008); and J. Bradford Jensen and Lori G. Kletzer, “Measuring Tradable Services and the Task Content of Offshorable Services Jobs,” paper presented at the National Bureau of Economic Research Conference on Research in Income and Wealth, titled “Labor in the New Economy,” November 16–17, 2007, Washington, DC, on the Internet at people.ucsc.edu/~lkletzer/TradableServices&Job_task_ content_110907.pdf (visited Sept. 26, 2008). 13 Because the wage range definitions were revised in November 2005, the successor data collected with November 2005 and May 2006 reference dates, as well as their corresponding predecessor records, were removed from the subsample solely for this wage analysis. The wage analysis used 14,828 unique establishments (29,656 predecessor and successor records). 14 The employment share of an occupational group in, for example, the wage range headed “Under $6.75” is the percentage of employment in that occupational group out of total employment in the occupational group. 15 A few establishments changed their industry classification when they reported the second time, but most that did so did not change industry sector. For consistency, the successors’ industries were assigned to the predecessors’. 16 Zachary Warren, “Occupational Shares in Growing and Shrinking Establishments,” Occupational Employment and Wages (Bureau of Labor Statistics, May 2005), pp. 1–14; see especially p. 5. 17 Andre Shleifer and Robert Vishny, “Value Maximization and the Acquisition Process,” Journal of Economic Perspectives, winter 1988, pp. 7–20. 18 Siegel and Lichtenberg, “The Effect of Ownership Changes.” 19 Warren, “Occupational Shares.” 20 Jeffrey Holt, “Recent Changes in Occupational Employment and Wages in Oil and Gas Extraction,” internal BLS document, 2008. 21 The very small group consisted of establishments with 1–9 employees before the ownership change and either 1–9 employees or 10–49 employees after the ownership change. The small group comprised establishments whose predecessors were in the 10–49-employee size class and whose successors stayed in the same size class or changed by one size class. The medium group encompassed establishments whose predecessors were in the 50–249-employee size class and whose successors were in the same size class or one size class below or above it. The large group consisted of establishments whose predecessors were in the 250–999-employee size class and whose successors were in the same size class or one size class below or above it. Finally, the very large group comprised establishments whose predecessors started in the employee size class of 1,000 or more and whose successors either remained in this size class or contracted to the 250–999-employee size class. 22 Excluded from the study were the 246 establishments that changed by two size classes, the 25 establishments that changed by three size classes, and the 4 establishments that changed by four size classes. Small units might have been acquired by larger corporations with the intent to expand them, so their occupational employment changes are relative extremes. Monthly Labor Review • September 2008 23 New York Mass Layoffs Extended mass layoffs after 2001: a comparison of New York and the Nation BLS data reveal that layoff activity in New York was somewhat elevated in the years that followed the 2001 recession; a rising level of job cuts due to contractual turnover among growth industries helped transform the mass layoff experience in the metropolitan area Bruce J. Bergman W ith the largest metropolitan workforce in the Nation, the New York area1 is at or near the top of many lists. Separations due to layoffs, or, simply, layoff separations, are no exception: between 2001 and 2006, New York consistently ranked among the top 10 metropolitan areas in this category. Viewed over the longer period of 11 years for which comparable data are available, extended mass layoff actions2 caused hundreds of thousands of New York area employees to be involuntarily separated from their workplaces. A question that arises, then, is, Was the New York area a standout in terms of layoffs, or did it not differ qualitatively from the Nation in that regard? To answer that question, this article examines data made available for the first time from the Bureau of Labor Statistics (BLS). worker dislocation caused by the recession and the September 11 terrorist attacks that year, what differed between the New York area and the Nation that led to divergent trends in layoff activity after 2001? The analysis that follows examines both the type of layoff and the reasons for its occurrence in the context of varying employment trends among industry sectors. First, data from the BLS Mass Layoff Statistics program that summarize extended mass layoff activity are used to measure both the primary reasons for layoff events and the magnitude of layoffs resulting from permanent closures of the worksites.3 Then the distribution of layoff separations by sector is examined, with the New York experience evaluated within the framework of employment growth and the local industry mix. Was New York different? New York and national layoff events data reveal that the New York area mass layoff experience not only deviated from national trends, but also underwent a significant change after 2001. While the total number of layoffs in the United States declined to the lowest levels recorded since they were first tracked in 1996, New York layoff activity remained at a relatively high level after 2001. Following widespread Eleven-year layoff totals. From 1996 through 2006, the New York area had 2,629 extended mass layoff events, roughly 4.5 percent of the national total. Although that figure amounted to a relatively high total for New York compared with other metropolitan areas, slightly more than 6 percent of all business establishments with at least 50 employees (the scope of the study4) were located in the New York area. BLS Bruce J. Bergman is an economist in the Office of Field Operations, Economic Analysis and Information Branch, Bureau of Labor Statistics, New York office. 24 Monthly Labor Review • September 2008 Layoff events in the New York area resulted in separations of 439,198 employees, with approximately 1 out of every 5 events (about the same as the national proportion) resulting from a permanent worksite closure. With respect to the leading causes of layoffs, a similar pattern existed between the New York area and the Nation, but with notable differences in magnitude.5 (See chart 1.) Seasonal layoffs accounted for 39 percent of the extended layoff actions in the New York metropolitan area during the 11-year period. Twenty-five percent of the layoff events had to do with internal company restructuring, a category that includes all events involving financial difficulty, bankruptcy, ownership change, and reorganization. Nationally, seasonal factors and internal company restructuring accounted for a respective 30 percent and 20 percent of all layoff actions. The other two leading justifications for job cutbacks involved slack work, indicating nonseasonal insufficient demand for the company’s products or services, and the completion of a contract. In the New York area, about 12 percent of layoff events resulted from each of these factors, while nationally, slack work accounted for a greater share (16 percent) of major cutbacks. Chart 1. Annual levels and the convergence of rates. On an annual basis, major layoff events in the New York area ranged from 147 in 1996 to 305 in 2005. (See table 1.) Although these layoffs more than doubled in 10 years, when they are compared with the number of establishments the change is seen to be less dramatic. Approximating a rate of such events per 100 establishments reveals relatively little change over the period examined:6 the New York area layoff event rate remained close to 1.0, below the comparable national rate. Nationally, a spike in the layoff event rate from 1.2 to 1.9 occurred in 2001. Within 3 years, the national rate returned to its prerecession range, whereupon it continued to decline further. Less pronounced, but more protracted, was the impact in New York: the rate of layoff events rose from 0.8 to 1.2, but it stayed close to that level for the next 3 years. These differing trends eventually led to the rate in the New York area (1.3) slightly exceeding that of the Nation (1.2) in 2005. (See chart 2.) Much has been written about the “jobless” recovery from the recession, and BLS data indicate that, in the wake of job destruction during the last recession, job creation slowed. Nevertheless, during the years after the 2001 recession, in both New York and the Nation, the unemployment rate Percent distribution of extended mass layoff events, by reason, New York-Northern New Jersey-Long Island and United States, 1996–2006 Percent of all events 45.0 Percent of all events 45.0 40.0 40.0 35.0 New York-Northern New Jersey-Long Island United States 30.0 35.0 30.0 25.0 25.0 20.0 20.0 15.0 15.0 10.0 10.0 5.0 5.0 0.0 Seasonal Internal restructuring Slack work Contract completed Other 0.0 Reason for layoff Monthly Labor Review • September 2008 25 New York Mass Layoffs Table 1. Reasons for extended mass layoff events in New York-Northern New Jersey-Long Island and in the United States, 1996–2006 Measure 1997 147 72 75 8 42 13 12 200 111 89 15 44 15 15 1998 1999 2000 2001 2002 2003 2004 2005 2006 158 68 90 5 48 9 28 200 89 111 14 54 17 26 290 53 208 22 139 25 22 288 100 188 33 77 40 38 253 89 163 42 45 47 29 296 101 195 55 67 31 42 305 117 188 62 52 39 35 259 103 156 63 47 33 13 New York-Northern New Jersey-Long Island Total, private nonfarm..................................... Seasonal............................................................... Total, nonseasonal, nonvacation.............. Contract completed................................ Internal company restructuring.......... Slack work................................................... Other reasons............................................ 1996 233 108 125 8 53 21 43 United States1 Total, private nonfarm..................................... Seasonal............................................................... Total, nonseasonal, nonvacation.............. Contract completed................................ Internal company restructuring.......... Slack work................................................... Other reasons............................................ 1 Data on layoffs were reported by District of Columbia. 4,760 4,671 4,859 4,556 4,591 7,375 6,337 6,181 5,010 4,881 4,885 1,487 1,637 1,430 1,427 1,548 1,439 1,558 1,630 1,678 1,808 1,613 3,222 2,955 3,348 3,025 2,968 5,817 4,699 4,447 3,222 2,976 3,160 512 700 670 642 575 630 754 874 772 692 1,056 1,012 798 829 926 958 1,894 1,609 1,272 989 773 818 816 655 740 563 599 1,925 1,282 949 579 566 597 882 802 1,109 894 836 1,368 1,054 1,352 882 945 689 employers in all States and the fell to relatively low levels. But in terms of the frequency of mass layoffs, the New York area remained close to (within 14 percent of ) the elevated level of layoffs that occurred in 2001, while national levels declined by more than 14 percent in 2002 and continued to decline to prerecession levels after that. Five-year comparisons: pre- and post-2001. Another way to view the 2001 turning point is to compare layoffs during the 5 years prior to the recession with those occurring during the 5 years after. Prior to the recession, the New York area averaged fewer than 100 nonseasonal, nonvacation mass layoff events; by contrast, the post-2001 average was 178. Nationally, a comparison of 5-year averages also shows an increase, but much less pronounced—at 19 percent, from 3,104 to 3,701. (See table 2.) Besides identifying the magnitude of the total increase, a comparison of the two time segments reveals another difference between New York and the Nation. Nationally, internal restructuring accounted for about 20 percent of the layoff events in both periods, while contract completion remained close to 14 percent. In the New York area, the share of layoff actions due to internal restructuring fell to 21 percent over the 2002–06 period, from 26 percent during 1996–2000. Job cutbacks due to contract completion increased dramatically between the two periods: from 2000 to 2006, this reason was associated with 18 percent 26 Monthly Labor Review • September 2008 SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. of layoff events, whereas in the earlier period, only 5 percent of layoffs in the New York area were due to contract completion. More significantly, in both 2005 and 2006, contract completion caused more layoff events than did internal restructuring. Layoffs related to contract completion in the New York area were less common prior to 2001 not only relative to the period that followed, but also compared with the Nation: during the more recent 5-year period, a greater percentage of layoffs was due to completed contracts in the New York area than in the United States as a whole. With the increased importance of contract completion and the diminished frequency of major job cuts due to internal restructuring came a reduced likelihood of layoffs due to worksite closure.7 Of the layoffs involving companies that underwent internal restructuring due to financial difficulty, reorganization, bankruptcy, or a change in ownership between 1996 and 2006, permanent worksite closings factored into about 45 percent of the events in both the New York area and the Nation. In contrast, permanent worksite closures accounted for about 3 percent of layoff events related to contract completion in the Nation. A result of an increasing share of layoffs due to contract completion was that, although the New York area tended to have a higher percentage of layoffs due to permanent worksite closures, those events became less frequent in Chart 2. Rate of extended mass layoff events, New York-Northern New Jersey-Long Island and United States, 1996–2006 Layoff events per 100 establishments 2.0 Layoff events per 100 establishments 2.0 United States 1.8 1.8 1.6 1.6 1.4 1.4 1.2 1.2 1.0 1.0 New York-Northern New Jersey-Long Island 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 1996 SOURCE: 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 0.0 BLS Mass Layoff Statistics program; and U.S. Census Bureau, County Business Patterns. the post-2001 period. During the 5 years prior to the recession, permanent closures accounted for 36 percent of the nonseasonal, nonvacation layoff events. In the 5 years that followed 2001, that number dropped to 25 percent. Nationally, the percentage was about 22 percent in both periods. (See tables 2 and 3.) What distinguished the New York area? Historically, economic downturns were typically accompanied by an increase in the rate of layoffs. In better times, with increased production, rates tended to decrease. National data confirm this pattern, but variation may exist among areas. Locality differences in business startup activity and in labor turnover and attrition, along with resulting labor market flows, influence the extent of both unemployment and layoffs in the face of industry-level shocks.8 New York’s experience testifies that even with an improving economy, layoffs might increase. An examination of both employment growth and business activity, as measured by establishment entry and exit, offers some explanation. Business startup and migration. BLS employment data show that overall job growth during most of the 1996– 2001 period remained close to or above that of the Nation. An analysis of major metropolitan areas prepared for the Appalachian Regional Commission shows that, during that period, the New York area had relatively high business outmigration rates: about 1 percent of new and existing firms had relocated elsewhere by the end of the period.9 Nevertheless, aggregate business startup rates in the New York area were even with national levels, indicating some level of strength, despite the relocations. Employment growth and a slow recovery. Total nonfarm employment in the New York area grew at a rate of more than 2 percent annually between 1997 and 2000. Slowing started in early 2001, but after the terrorist attack of September 11 and through the first half of 2002, job loss in the metropolitan area acclerated to a rate of 2 percent during the first half of 2002. Job loss persisted, albeit to a lesser degree, until continuous over-the-year job growth resumed in the second quarter of 2004. In most industry sectors, employment followed a similar pattern of a deMonthly Labor Review • September 2008 27 New York Mass Layoffs Table 2. Comparisons of extended mass layoff events in New York-Northern New Jersey-Long Island and the United States, 5- and 11-year averages, 1996–2006 Measure 11-year 1996–2000 2002–2006 average average average New York-Northern New Jersey-Long Island All events, number.................................. Percentage involving internal restructuring..................................... Percentage involving contract completion........................................ Percentage with recall expected... Nonseasonal, nonvacation events, number............................................... Percentage involving permanent worksite closure........................... 239 188 280 25.4 25.7 20.6 12.4 49.3 5.3 56.1 18.2 46.6 144 98 178 28.8 36.1 24.9 All events, number.................................. 5,282 Percentage involving internal restructuring..................................... 20.4 Percentage involving contract completion............................................ 13.6 Percentage with recall expected............................................ 50.7 Nonseasonal, nonvacation events, number............................................... 3,622 Percentage involving permanent worksite closure........................... 21.8 4,687 5,459 19.3 20.6 13.2 15.2 55.9 48.8 3,104 3,701 22.1 21.5 United States1 1 Data on layoffs were reported by employers in all States and the District of Columbia. SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. layed return to prerecession (1996–2000) growth levels. (See table 4.) BLS Business Employment Dynamics data provide additional information about the nature of the slow recovery. In New York State, a sustained period of expansion occurred from the first quarter of 1996 through the fourth quarter of 2000. During that time span, job creation outpaced job destruction.10 The situation changed in 2001, and not until the fourth quarter of 2003 would the pace of job creation again be greater than that of job destruction. At the national level, data also show both an increase in job losses and a decline in job gains that characterize the 2001 recession. Employment in created jobs amounted to 8 percent of the total workforce in the mid-1990s; 10 years later, the job creation rate was below 7 percent. Despite a slow rate of job creation, total nonfarm employment returned to its prerecession peak sooner in the United States as a whole than it did in the New York area. A slow local recovery is echoed in the layoff separa28 Monthly Labor Review • September 2008 tion data. Nonseasonal, nonvacation layoffs reached their peak in 2001. (See table 5.) That year, almost 38,000 such separations were reported. Prior to 2001, the New York area had had fewer than 16,000 in 4 out of 5 years, but not until 2006 did the area total again fall below 25,000. Although the U.S. layoff peak also was in 2001, the number of separations nationally in both 2005 and 2006 was the lowest recorded between 1996 and 2006. Initial claims for unemployment insurance related to extended mass layoffs largely followed the pattern of separations:11 elevated levels during the years following 2001, not returning to prerecession levels. But between 2003 and 2005, when claims related to extended layoffs were declining throughout the Nation, claims in the New York area increased. (See table 6.) How much impact did these factors have on regional layoffs? A graph of initial claims indexed to 1996 levels shows clearly that initial claims in the New York area seemed to ratchet up, even following the 2001 slowdown. (See chart 3.) At the national level, both the initial claims total and the number of initial claims due to major layoffs returned to earlier levels. So, too, did a similar return occur in 2 of the 3 States in which the New York area is located: New Jersey and Pennsylvania. These two States, as well as the Mid-Atlantic Census Division as a whole, did not experience as sharp a spike in claims due to the recession as did the Nation, and the number of claims returned closer to pre-2001 levels. That the relative growth in initial claims from the MidAtlantic Census Division was more similar to U.S. growth, as opposed to that of the New York area, is somewhat surprising, given that about 45 percent of the division’s unemployed resided in the New York area, and about the same percentage of the division’s employed worked there. In terms of layoff separations, however, New York contributed only between one-quarter and one-third of the division’s total. In light of these numbers, some might interpret the indexes of initial claims to imply that New York area layoffs did not have a significant impact on the regional economy. BLS data on displaced workers, however, suggest that the impact of the layoffs might go beyond the number of initial claims.12 Between 2003 and 2005, 431,000 New York, New Jersey, and Pennsylvania workers permanently lost jobs they had held for 3 or more years due to closures, termination of their positions or shifts, or insufficient work. Nineteen percent of all displaced workers in the Mid-Atlantic division were collecting unemployment benefits in 2006, compared with 13 percent throughout the Nation. Table 3. Permanent worksite closures: extended mass layoff events and separations in New York-Northern New Jersey-Long Island and in the United States, 1996–2006 Measure 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 New York-Northern New Jersey Long Island Events: Total, private nonfarm................................. Internal company restructuring............ Separations: Total, private nonfarm................................. Internal company restructuring............ 28 22 26 17 51 31 38 29 34 24 63 45 48 31 39 16 42 28 57 31 45 27 6,620 6,034 9,545 6,565 3,655 13,011 10,326 7,395 8,079 10,202 7,423 5,762 4,278 5,763 5,532 2,842 8,606 6,792 2,742 5,883 6,657 5,359 United States1 Events: Total, private nonfarm................................. Internal company restructuring............ Separations: Total, private nonfarm................................. Internal company restructuring.............. 757 435 595 326 662 356 671 405 755 1,240 1,155 492 760 677 919 536 746 500 560 371 621 417 181,589 151,966 151,526 181,970 183,335 377,360 298,634 210,903 159,867 107,399 153,718 109,331 86,550 87,131 121,915 134,584 266,042 192,982 132,615 110,732 76,408 112,341 1 Data on layoffs were reported by employers in all States and the District of Columbia. More research is needed to determine whether metropolitan area mass layoffs were responsible for the higher economic cost of job displacement in the Mid-Atlantic region. Key patterns in reasons for layoff separations. Up to now, this article has focused on the overall levels and types of extended mass layoff events and the related initial claims for unemployment insurance. Data show a clear difference between the 5-year periods before and after 2001 in the New York metropolitan area. An examination of local employment growth rates yields a similar dichotomy between the two periods. Data on separations by reason for layoff and by industry help validate these findings and also may help answer the question, “Was a slow local recovery solely to blame for increased job cuts?” Separations data confirm that two significant factors contributed to the shift in layoff activity in the New York area: (1) increased slack work, reflecting a period of reduced demand after 2001; and (2) an increase in completed contracts, suggesting an increased number of shorter term employment contracts. Layoffs resulting from slack work peaked in New York in 2002–03, contrasting with the national total, which peaked in 2001. Beyond this factor, New York layoffs related to contract completion reached their highest levels in 11 years during 2004–05. Nationally, separations due to completed contracts were at relatively average levels during those years. Chart 4 illustrates these differences between the New York area and the Nation in the distribution of layoff separations by reason. Slack work and contract completion piggybacked SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. on the primary reason for major cutbacks—internal restructuring—resulting in a sustained elevated level of separations. The number of separations due to internal company restructuring peaked both nationally and in New York in 2001. Layoffs separations by industry. To complete the evaluation of what distinguished the New York area, a closer look at layoff data by industry is necessary. Although data that quantify reasons associated with layoffs are not available for local industries, comparisons with national figures reveal some interesting findings. Between 1996 and 2006, manufacturing accounted for 97,256 (or 22 percent of all) extended mass layoff separations in the New York area, followed by transportation and warehousing with 62,449 (or 14 percent) of the separations. More than 40,000 separations occurred in both the construction and the arts, entertainment, and recreation sectors. Finance and insurance, as well as accommodation and food services, recorded over 30,000 mass layoff separations, and both the information and administrative and waste services sectors experienced more than 20,000 layoffs. Economic circumstances of sectors differ, especially with regard to competition, the use of contingent workers, and business demand. Accordingly, the 2001 slowdown did not affect all sectors in the same way. In fact, the recession was not responsible for the largest number of layoffs in every sector either. For example, manufacturing had almost 34,000 separations due to major layoffs between 1996 and 1998, the worst 3-year period the industry had Monthly Labor Review • September 2008 29 New York Mass Layoffs Table 4. Percent distribution of employment among industries, and over-the-year employment change, private sector, New York-Northern New Jersey-Long Island and United States, 1996–2006 Industry Share of total employment 1996 Over-the-year employment change as a percentage of base-year employment 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 New York-Northern New Jersey-Long Island Total private nonfarm............. Construction and mining............... Manufacturing................................... Trade, transportation, and utilities............................................... Wholesale trade.............................. Retail trade....................................... Transportation and warehousing.............................. Information......................................... Financial activities............................ Finance and insurance................. Professional and business services.............................................. Professional and technical services......................................... Administrative and waste services......................................... Education and health services..... Health care and social assistance ................................... Leisure and hospitality.................... Accommodation and food services......................................... Other services, except public administration ............................... 100.0 4.5 8.4 1.6 2.5 –2.0 2.4 4.6 .1 2.7 7.1 –.9 2.7 9.3 –2.3 2.5 5.9 –2.3 0.0 3.1 –6.8 –2.0 .1 –8.3 –0.5 –1.1 –5.5 0.5 1.4 –3.5 0.7 .8 –3.8 1.3 3.9 –2.7 22.7 6.3 11.8 .5 .0 1.2 1.4 1.2 1.7 1.5 1.3 2.0 2.4 1.0 3.2 2.2 .5 3.2 –.8 .7 –1.4 –2.2 –3.5 –.5 –.2 –.2 .3 .3 –.4 .9 .1 –.3 .7 .6 .2 .4 4.2 4.4 11.3 8.6 –.1 2.8 –.1 –.6 2.3 3.3 1.0 .7 1.7 2.5 2.3 2.2 2.8 3.4 1.3 1.0 2.2 6.5 1.3 1.3 –1.9 4.8 –2.3 –2.6 –5.2 –9.0 –3.5 -4.2 –2.2 –6.3 –.7 –1.4 –.2 –2.6 .6 .2 –1.0 .0 1.2 1.3 1.6 1.3 1.5 1.7 17.4 4.7 5.2 5.5 4.8 4.4 .6 -4.0 –1.3 .6 1.2 2.1 8.6 3.6 5.6 7.0 5.7 5.6 –.1 -4.9 –2.2 .9 2.4 4.4 6.8 18.3 7.3 2.7 5.6 2.1 5.2 2.9 4.9 2.7 4.8 1.8 1.4 2.2 –4.1 3.1 –1.1 2.1 .4 1.4 –.5 1.6 –.1 2.1 14.9 8.2 1.8 2.0 2.1 3.2 2.6 2.9 2.8 2.8 1.9 3.4 1.7 1.9 3.1 .7 2.9 2.3 1.2 2.8 1.7 1.4 2.0 2.0 6.5 1.6 2.8 2.7 2.3 2.9 1.5 –.1 3.3 2.5 1.9 2.0 4.8 2.7 2.6 3.0 4.7 2.8 1.4 1.4 1.1 2.1 2.9 .3 100.0 2.4 .3 2.8 2.5 2.1 –.3 –1.7 –.4 1.3 1.9 2.0 6.7 14.7 4.4 .0 4.8 1.1 5.1 .8 5.1 –1.4 3.4 –.3 .6 –4.8 –1.8 –7.2 .1 –4.9 3.6 –1.3 5.2 –.6 5.1 –.2 23.5 5.3 13.8 1.7 1.6 1.8 1.9 2.6 1.7 2.0 2.3 1.5 2.3 1.7 2.5 1.8 .7 2.1 –.9 –2.7 –.3 –1.9 –2.1 –1.4 –.8 –.8 –.7 1.0 1.0 .9 1.7 1.8 1.5 1.0 2.3 .3 3.9 3.0 7.1 5.3 2.5 3.4 2.1 1.6 2.3 4.9 3.0 2.9 3.5 .4 4.0 4.3 3.2 6.2 2.5 2.5 2.6 6.2 .5 .2 –.9 –.1 1.6 1.6 –3.4 –6.4 .5 .8 –.9 –6.1 1.7 1.8 1.5 –2.2 .7 .4 2.6 –2.8 1.5 1.2 2.4 –.2 2.6 2.7 14.7 4.8 6.5 5.7 5.3 4.4 –1.1 –3.0 .1 2.6 3.4 3.5 8.6 4.6 6.0 6.5 5.9 5.6 2.5 –3.3 –.7 2.2 4.1 4.5 7.1 14.5 6.0 3.0 8.2 3.0 6.0 2.5 5.9 2.4 4.2 2.1 –4.2 3.5 –2.6 3.5 1.0 2.4 2.9 2.2 3.1 2.5 2.8 2.7 12.2 11.0 2.9 2.6 2.8 2.2 2.4 1.9 2.2 2.8 1.9 2.8 3.3 1.5 3.2 –.4 2.5 1.6 2.1 2.6 2.4 2.6 2.6 2.6 9.4 2.4 1.8 1.8 2.6 2.4 1.4 –.1 1.5 2.7 2.6 2.7 4.8 2.6 2.9 3.1 2.2 1.6 1.7 2.2 .5 .1 –.3 .7 United States1 Total private nonfarm............. Construction and mining............... Manufacturing................................... Trade, transportation, and utilities............................................... Wholesale trade.............................. Retail trade....................................... Transportation and warehousing ............................. Information ........................................ Financial activities............................ Finance and insurance ................ Professional and business services.............................................. Professional and technical services......................................... Administrative and waste services......................................... Education and health services..... Health care and social assistance ................................... Leisure and hospitality.................... Accommodation and food services......................................... Other services, except public administration................................. 1 Data on layoffs were reported by employers in all States and the District of Columbia. 30 Monthly Labor Review • September 2008 SOURCE: Bureau of Labor Statistics, Current Employment Statistics program. Table 5. Extended mass layoff separations by industry and reason for layoff, private nonfarm sector, New York-Northern New Jersey-Long Island, 1996–2006 Measure Total, private nonfarm.............................. Industry Construction......................................................... Manufacturing..................................................... Wholesale trade................................................... Retail trade............................................................ Transportation and warehousing................. Information........................................................... Finance and insurance...................................... Real estate and rental and leasing................ Professional and technical services . ........... Administrative and waste services............... Health care and social assistance.................. Arts, entertainment, and recreation............. Accommodation and food services ............ Other services, except public administration................................................... Reason Seasonal................................................................. Total, nonseasonal, nonvacation................... Contract completion...................................... Internal company restructuring................. Slack work........................................................... 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 34,828 36,942 37,823 22,153 27,430 54,928 52,335 39,527 51,118 47,597 33,517 4,006 5,599 1,305 7,594 10,754 15,643 430 1,296 758 1,387 1,693 1,124 5,296 4,801 6,867 – ( 1 ) 1,886 2,554 771 2,881 ( 1 ) ( 1 ) ( 1 ) ( 1 ) ( 1 ) ( 1 ) 2,019 1,044 1,512 1,774 2,196 1,033 5,267 4,260 1,561 2,012 747 1,486 330 946 915 ( 1 ) 6,628 1,160 1,087 5,812 246 1,283 ( 1 ) 475 944 1,015 1,209 1,445 459 19,123 21,473 17,106 10,245 15,705 15,469 20,717 11,908 1,801 2,757 885 604 9,571 8,309 8,152 7,578 2,304 2,080 2,773 858 Data do not meet BLS or State agency disclosure standards. NOTE: Dash represents zero. 1 during the 11 years studied. By contrast, the worst 3-year period for construction was from 2003 through 2005, when the industry recorded 19,000 separations. The extent of layoffs related to permanent worksite closure, accounting for about 20 percent of New York area layoff separations, also is instructive regarding the variation among industries that exists with business turnover. About one-third of the annual average of 2,866 manufacturing separations per year involved closures. Of all industries, manufacturing had the highest number of separations due to workplace closings every year, with the exception of 1996 and 2001. (See table 7.) Nevertheless, in 6 of the 11 years studied, another industry in decline—wholesale trade—had a higher percentage of layoffs due to permanent closures. In retail trade, a large industry characterized by high turnover, closures caused about half of the layoff separations, on average, and this percentage also exceeded that of manufacturing in 6 of the 11 years examined. Construction separations Looking at extended mass layoff activity in relatively high layoff sectors in the context of overall employment growth highlights additional differences between New York and the Nation. A healthy real estate market, along with in- 1,009 1,159 8,689 9,948 727 1,003 609 1,967 7,062 11,193 718 2,211 1,095 6,424 554 1,775 446 3,096 512 2,646 1,594 948 2,381 4,147 515 6,681 996 926 13,511 17,094 13,919 37,834 1,339 3,014 6,038 25,013 3,177 5,296 SOURCE: 5,007 10,236 510 1,204 4,595 4,925 7,382 1,350 1,810 3,911 704 5,117 3,443 5,468 8,960 2,129 635 3,806 3,386 1,724 ( 1 ) 1,712 2,075 1,607 4,925 893 6,041 6,578 1,053 2,022 5,581 6,394 4,596 1,784 2,466 2,248 3,095 4,048 4,249 7,982 7,220 945 1,372 2,622 3,090 2,045 310 4,109 2,204 2,603 4,307 7,469 695 628 465 376 4,353 5,006 715 1,113 4,814 2,040 570 – 1,721 3,497 1,503 3,810 3,708 (1) 17,307 11,581 14,200 16,145 13,756 35,028 27,946 36,918 31,452 19,761 7,704 8,104 10,522 8,935 6,235 13,920 7,979 12,187 10,453 7,934 6,421 5,989 5,947 3,627 3,247 Bureau of Labor Statistics, Mass Layoff Statistics program. tensive efforts to rebuild lower Manhattan, fueled growth among the building trades. Between 1999 and 2004, New York area construction employment grew by about 13 percent, while the number of establishments grew by 14 percent. Nationally, the employee and establishment counts both grew by less than 10 percent. (See table 8.) As regards layoffs, construction accounted for at least 10 percent of the separations in the United States every year except 2001 and 2002. In New York, a similar situation existed: during the 5 years after 2001, the construction sector averaged more than 5,500 separations per year due to extended mass layoffs, amounting to 12 percent of the total separations in the New York area. (See table 9.) In both the New York area and the United States, the quantity of construction layoffs was disproportionate to the sector’s employment. Nationally, construction accounted for about 6 percent of total private nonfarm employment. Among establishments with at least 50 employees, from which the layoff statistics were derived, construction employees amounted to yet a smaller percentage of all employees. The disparity between relative shares of total layoffs and total employment was even more evident in the New York area, where construction had a location quotient of 0.72, indicating less industry concentration compared with that of the Nation.13 Monthly Labor Review • September 2008 31 New York Mass Layoffs Table 6. Initial claimants for unemployment insurance resulting from extended mass layoffs, private nonfarm sector, selected areas in the Mid-Atlantic Census Division and the United States, 1996–2006 Area 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 United States........................................................ 805,810 879,831 1,056,462 796,917 846,267 1,457,512 1,218,143 1,200,811 903,079 834,533 950,157 Mid-Atlantic Division...................................... 156,959 134,635 152,283 122,073 116,224 201,435 210,161 189,699 181,403 158,413 178,957 New Jersey.................................................... 30,489 35,347 31,910 22,353 25,945 39,114 41,868 38,747 33,841 28,075 30,517 New York........................................................ 38,416 26,113 37,478 27,260 28,481 54,877 79,493 73,111 75,146 75,311 79,472 Pennsylvania................................................ 88,054 73,175 82,895 72,460 61,798 107,444 88,800 77,841 72,416 55,027 68,968 New York-Northern New Jersey Long Island................................................... 21,302 27,262 32,346 21,242 27,368 46,964 47,988 36,467 51,846 50,222 40,867 SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. This pattern of relatively high layoff activity also was reflected in national layoff and discharge rates, as captured by the BLS Job Openings and Labor Turnover Survey (JOLTS):14 between 2001 and 2006, construction recorded the highest layoff and discharge rates among all sectors. With the use of extended mass layoff separations data, a rate similar to the turnover rate can be computed in the context of relative employment levels to help gauge extended mass layoff activity over time among establishments with at least 50 employees. This measure, too, confirms that construction tended to have the highest rate of separations among national sectors. With the exception of 2001, construction led the other sectors, with a separation rate that ranged from 4.5 percent to 7.8 percent. From 2003 through 2006, the national rate declined each year, from 5.8 percent to 4.5 percent. (See table 10.) Rather than reflecting an industry in decline, construction layoff activity was more indicative of the short-term employment relationship that has become more characteristic of the industry. National data indicate that more than 85 percent of all construction layoffs were due to the ending of seasonal work and the completion of contracts, with specialty trade contractors having a high percentage of separations due to contract completion. Furthermore, construction employers expected a recall in 59 percent of the layoff events in the United States, above the 52percent average for private industry as a whole. Laid-off construction workers were reemployed relatively quickly: construction had one of the shortest average jobless durations among all sectors. Manufacturing layoffs In the late 1990s, manufacturing employment declined in New York, as it did throughout the Nation, but the rate of job loss worsened with the 2001 recession. Over-the32 Monthly Labor Review • September 2008 year job loss accelerated in the New York area, while it moderated nationally. The deterioration in manufacturing was particularly pronounced in the New York area, as a comparison of 2004 with 1999 figures indicates. Seventeen percent fewer manufacturing establishments were in New York, while the decline in the Nation was 6 percent. Among establishments employing at least 50 employees, the decline was more significant: by 2004, the number of manufacturers of that size contracted by 23 percent in the New York area, while the number of like-sized manufacturing establishments in the United States dropped by 14 percent. Manufacturing accounted for a dwindling, but significant, share of national employment, declining steadily from about 25 percent in 1996 to about 18 percent in 2006. Meanwhile, at least 25 percent (ranging up to 47 percent in 1998) of all extended mass layoff separations occurred in the sector each year. In New York, the story was different: the only years that manufacturing accounted for at least one-quarter of the separations were between 1997 and 2000, when the area economy was adding jobs at its fastest pace during the 11 years studied. Since 2004, when manufacturing amounted to 7 percent of total New York area employment, the sector has accounted for 15 percent or less of the layoff separations in New York. Nationwide, manufacturing separations due to extended mass layoffs reached their height in 2001, with 627,930, a rate of 4.7 percent. Since then, both levels and rates have declined, and between 2004 and 2006, the rate of manufacturing separations in the United States was not more than 2.5 percent. Above the private-industry average, the manufacturing separations rate was still well behind that of construction. In the New York area, however, a relatively high number of major manufacturing job cuts failed to color the total extended mass layoff picture as it did nationally. The primary reason was that manufacturing was less Chart 3. Indexes of initial unemployment insurance claims, New York-Northern New Jersey-Long Island, United States, and Mid-Atlantic Division, 1996–2006 Index (1996 = 100) 250.0 Index (1996 = 100) 250.0 200.0 200.0 150.0 150.0 100.0 100.0 50.0 U.S., all claims U.S., extended mass layoff claims New York-Northern New Jersey Long Island, extended mass layoff claims 0.0 Mid-Atlantic, all claims Mid-Atlantic, extended mass layoff claims 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 SOURCES: BLS Mass Layoff Statistics program, Employment and Training Administration, Office of Workforce Security. concentrated in New York than throughout the Nation: a location quotient of 0.54 indicates less of a presence for the sector in the New York area than throughout the Nation. What accounted for the sharper decline in New York area manufacturing employment if not mass layoffs? Production jobs may have moved out of high-priced Manhattan to lower cost areas either within New York City or beyond the metropolitan area. If such moves were partial and gradual, and did not result in at least 50 people being laid off over a 5-week period, the job cuts would not be captured in the mass layoff numbers, but the net result would be reflected in the BLS employment data.15 Beyond less industry concentration, a different factor tempered the impact of mass layoffs in manufacturing in the New York area. Four industries accounted for half of the 97,256 extended mass layoff separations in manufacturing: apparel recorded 14,906 (15.3 percent) of the separations, followed by chemical products with 12,226 (12.6 percent), food products with 11,202 (11.5 percent), and machinery with 10,795 (11.1 percent). (See table 11.) 50.0 0.0 Although the apparel industry had the highest number of extended mass layoff separations, only 15 percent of those separations in the New York area involved permanent worksite closures. (See chart 5.) The low number of separations due to the permanent closure of New York apparel manufacturers stood in stark contrast to the situation in the Nation as a whole, where 56 percent of this industry’s separations involved shutdowns. Apparel manufacturing continued to be one of the metropolitan area’s primary industries, while maintaining international prominence, even with declining employment. Between 1996 and 2001, despite low business startup activity in almost every manufacturing industry, apparel startups were high. Many of the large apparel manufacturers that had remained in the New York area adapted to changing business conditions by trimming staff, as opposed to closing down permanently.16 In 1996, 23 percent of all apparel establishments in the United States were located in metropolitan New York. The percentage decreased to 19 percent in 2006, while the area’s employment share for the industry grew from 12 percent to 14 percent of the U.S. total during the same period. Meanwhile, the average Monthly Labor Review • September 2008 33 New York Mass Layoffs Chart 4. Extended mass layoff separations, by reason for layoff, New York-Northern New Jersey-Long Island and United States, 1996–2006 Separations Separations 28,000 28,000 New York-Northern New Jersey-Long Island 24,000 24,000 Internal restructuring 20,000 20,000 Seasonal 16,000 16,000 12,000 12,000 Contract completed 8,000 8,000 4,000 0 4,000 Slack work 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 0 Separations Separations 600,000 600,000 United States 500,000 500,000 Internal restructuring 400,000 400,000 Seasonal 300,000 300,000 200,000 200,000 Contract completed 100,000 100,000 Slack work 0 1996 1997 1998 1999 2000 SOURCE: BLS Mass Layoff Statistics program. 34 Monthly Labor Review • September 2008 2001 2002 2003 2004 2005 2006 0 Table 7. Permanent worksite closures: extended mass layoff separations, by selected industry, New YorkNorthern New Jersey-Long Island, 1996–2006 Industry Construction......................................................... Manufacturing..................................................... Wholesale trade ................................................. Retail trade............................................................ Transportation and warehousing ................ Information........................................................... Finance and insurance...................................... Administrative and waste services .............. 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 – ( 1 ) – – – ( 1 ) – – – 603 624 2,157 2,311 3,889 3,611 1,531 2,380 3,215 4,852 2,775 2,228 2,819 – 636 494 930 ( 1 ) 608 ( 1 ) ( 1 ) ( 1 ) 495 410 871 – 357 927 289 1,506 644 295 835 923 436 1 1 1 1 ( ) ( ) 494 ( ) – 2,423 1,500 ( ) 951 423 – – ( 1 ) 975 – ( 1 ) 442 1,400 ( 1 ) ( 1 ) ( 1 ) 495 2,256 ( 1 ) 1,882 355 ( 1 ) ( 1 ) 931 ( 1 ) 737 655 (1) 850 ( 1 ) ( 1 ) – ( 1 ) 355 999 267 – ( 1 ) 1,399 Data do not meet BLS or State agency disclosure standards. NOTE: Dash represents zero. 1 establishment size in apparel declined in both New York and the Nation.17 The New York experience contrasted with that of the United States, in which manufacturing weighed heavily on the layoff picture. In the Nation, the sector accounted for close to 30 percent of all extended separations from 2002 to 2006. In New York, manufacturing accounted for 17 percent of the layoff separations, and between 2004 and 2006 the share fell to 14 percent. Transportation and warehousing layoffs Compared with its share of national employment among establishments with at least 50 employees, transportation and warehousing consistently had a higher percentage of total separations. Since 2002, the national rate of extended mass layoffs in transportation and warehousing has been relatively close to manufacturing’s national rate. Separations in this sector usually have amounted to between 5 percent and 8 percent of the U.S. total since 1996. In the New York area, however, extended mass layoff separations in the transportation and warehousing sector accounted for 10 percent of total extended mass layoff separations, or about 4,300 separations per year, on average, between 2002 and 2006. As with manufacturing, the layoff share during this period, though relatively high, was down from earlier years: from 1996 to 2001, transportation and warehousing accounted for between 13 percent and 26 percent of New York area layoffs, averaging about 6,000 separations annually. This reduced level of layoff activity contrasts with the national experience: during the 5 years before 2001, between 49,000 and 58,000 separations occurred in the sector, while the average for the 5 years ending in 2006 was 73,000. SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. Leisure and hospitality turnover In the years that followed 2001, New York area separations due to layoffs in the arts, entertainment, and recreation sector ranged from 3,810 to 5,117, averaging 8 percent of the private-industry total, compared with 3.5 percent nationally. In New York, as well as in the United States, the sector accounted for about 2 percent of total employment. A higher incidence of layoffs also was evident in accommodation and food services. Employment in this sector in the New York area was characterized by growth over most of the 11-year period studied, similar to the rest of the United States. After 2001, the sector accounted for about 7.5 percent of New York area layoff separations, compared with 6 percent nationally. The difference in layoff proportions between the New York accommodation and food services sector and its national counterpart may have been influenced by higher establishment growth in the metropolitan area. Employment data show that establishment growth in New York became more concentrated among smaller sizes (outside the scope of the BLS Mass Layoff Statistics program), while nationally, the sector became increasingly more consolidated among larger establishments. Between 1999 and 2004, employment growth in the sector in New York outpaced growth in both construction and retail trade. The number of establishments grew by 16 percent, but among establishments with 50 or more employees, the increase measured just 10 percent. On a national basis, the number of accommodation and food service establishments increased by 10 percent, but those with more than 49 employees increased by 17 percent. Accommodation and food services had a relatively high Monthly Labor Review • September 2008 35 New York Mass Layoffs Table 8. Change in the number of establishments, and employment by industry and establishment size, New YorkNorthern NewJersey-Long Island and United States, 1999–2004 All establishments Industry Employment change, 1999–2004 Establishments employing at least 50 workers Establishment change, 1999–2004 Employment change, 1999–2004 Establishment change as a percentage of all establishments, 2004 New York -Northern New Jersey-Long Island Total private............................................................. Construction..................................................................... Manufacturing . .............................................................. Wholesale trade.............................................................. Retail trade ....................................................................... Transportation and warehousing ............................ Information....................................................................... Finance and insurance . ............................................... Real estate and rental and leasing........................... Professional and technical services ........................ Administrative and waste services........................... Health care and social assistance ............................. Accommodation and food services ........................ Other services, except public administration ..... 3.7 12.7 –19.4 –4.2 12.7 .3 10.4 –.6 12.1 6.9 –1.5 11.4 13.6 8.8 5.0 13.7 –16.6 –3.1 5.0 8.5 6.7 2.0 11.2 9.0 –.3 12.3 15.7 6.5 3.2 11.1 –22.7 –5.6 24.0 13.3 4.8 –3.1 8.7 3.3 –1.1 14.2 9.6 4.2 4.5 2.2 10.3 4.2 4.3 7.9 10.6 5.7 1.3 2.8 7.2 5.1 4.8 1.7 3.9 7.2 17.0 –1.1 6.0 13.0 7.4 8.7 11.3 17.7 4.1 14.1 11.5 5.1 5.4 8.9 –5.9 –4.6 .8 10.4 10.4 12.5 17.0 14.2 2.4 12.6 9.5 2.3 4.0 9.4 –14.0 –3.1 7.9 21.0 2.1 3.8 7.5 11.6 –.9 14.3 17.0 5.4 5.3 2.8 16.0 4.8 5.4 7.1 9.1 3.7 1.4 2.6 8.5 6.3 7.7 1.7 United States Total private............................................................. Construction..................................................................... Manufacturing . .............................................................. Wholesale trade.............................................................. Retail trade . ..................................................................... Transportation and warehousing............................. Information . .................................................................... Finance and insurance . ............................................... Real estate and rental and leasing........................... Professional and technical services ........................ Administrative and waste services . ........................ Health care and social assistance ............................ Accommodation and food services ........................ Other services, except public administration....... SOURCE: U.S. Census Bureau, County Business Patterns. number of layoffs, despite a low industry concentration. At 0.72, the area location quotient for accommodation and food services was the same as that for construction, indicating a smaller share of local, compared with national, employment. The 2002–06 period was worse than the 5 years prior to 2001 in terms of layoff separations in the industry, and that was true at both the local and national level, despite continued growth. Information layoffs Increased layoff activity despite sector growth also was evident in the information sector. Annual job gains in New York were strong between 1996 and 2001, averaging from 36 Monthly Labor Review • September 2008 2.5 percent to 6.5 percent. Communications industry startup activity was 20 percent above national averages during this period. The recession, however, hit the sector particularly hard: in 2002, job losses for the year amounted to 9 percent. Although nationally the sector continued to lose jobs, in the New York metropolitan area the information industry rebounded in 2006, finally adding employment, at a rate of 1.3 percent. JOLTS data indicate that, between 2001 and 2006, the information sector ranked among the sectors with the lowest national layoff and discharge rates. However, in terms of extended mass layoffs, the sector experienced an above-average rate exceeding 2 percent of the U.S. employed between 2002 and 2003, as it did earlier, in 1996 Table 9. Percent distribution of extended mass layoff separations by industry, New York-Northern New Jersey-Long Island and United States, 1996–2006 Industry 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 100.0 11.5 21.8 1.2 4.0 15.2 – 7.3 ( 1 ) ( 1 ) 5.8 5.1 15.1 5.8 100.0 15.2 29.1 3.5 4.6 13.0 ( 1 ) 2.1 ( 1 ) ( 1 ) 2.8 5.9 11.5 2.0 100.0 3.5 41.4 2.0 3.0 18.2 5.0 7.6 ( 1 ) ( 1 ) 4.0 2.7 4.1 3.9 100.0 ( 1 ) 29.9 5.2 4.9 26.2 1.1 5.8 ( 1 ) 2.1 4.3 4.6 5.5 6.5 100.0 3.7 31.7 2.7 2.2 25.7 2.6 4.0 2.0 1.6 1.9 5.8 8.7 1.9 100.0 2.1 18.1 1.8 3.6 20.4 4.0 11.7 3.2 5.6 4.8 1.7 7.5 12.2 100.0 9.6 19.6 1.0 2.3 8.8 9.4 14.1 2.6 3.5 7.5 1.3 9.8 6.6 100.0 13.8 22.7 5.4 1.6 9.6 8.6 4.4 ( 1 ) 4.3 5.2 4.1 12.5 2.3 100.0 11.8 12.9 2.1 4.0 10.9 12.5 9.0 3.5 4.8 4.4 6.1 7.9 8.3 100.0 16.8 15.2 2.0 2.9 5.5 6.5 4.3 .7 8.6 4.6 5.5 9.0 15.7 100.0 13.0 14.9 2.1 3.3 14.4 6.1 1.7 – 5.1 10.4 4.5 11.4 11.1 New York-New JerseyLong Island Total, private nonfarm............................ Construction....................................................... Manufacturing................................................... Wholesale trade................................................. Retail trade.......................................................... Transportation and warehousing............... Information......................................................... Finance and insurance ................................... Real estate and rental and leasing.............. Professional and technical services............ Administrative and waste services............. Health care and social assistance................ Arts, entertainment, and recreation........... Accommodation and food services........... Other services, except public administration................................................. .9 2.6 2.4 2.1 3.6 1.7 1.3 1.6 .9 .8 (1) 100.0 11.2 37.0 2.1 12.3 4.6 5.2 3.0 .4 2.7 6.4 3.8 3.3 4.8 100.0 14.0 34.1 1.6 10.1 6.1 6.1 2.2 .4 3.5 5.3 3.6 5.0 5.2 100.0 10.8 47.3 1.4 5.9 5.7 4.4 2.3 .2 2.2 5.4 3.1 3.1 4.8 100.0 13.0 39.5 1.9 10.2 5.5 2.6 2.4 .2 2.7 6.8 3.9 2.9 4.3 100.0 12.1 40.0 1.9 9.6 5.5 1.6 3.4 .2 2.4 8.5 4.2 2.8 4.5 100.0 7.3 41.2 1.9 8.7 7.7 4.0 2.2 .5 3.4 11.0 1.6 2.6 5.2 100.0 9.3 35.7 1.9 10.7 6.4 4.6 3.0 .2 4.6 10.6 2.4 3.6 4.0 100.0 10.9 31.6 2.5 10.5 7.2 5.4 3.3 .3 3.3 12.2 2.7 3.1 4.4 100.0 12.0 25.6 1.6 14.5 5.9 3.7 3.4 .4 3.3 11.4 4.4 3.8 6.9 100.0 13.8 25.2 1.5 9.0 7.6 2.6 2.1 .3 4.7 10.6 4.9 5.9 8.5 100.0 13.5 29.4 1.5 10.7 7.5 2.0 3.3 .2 4.7 9.8 3.2 4.6 7.2 .8 1.2 1.2 1.3 1.2 .7 1.1 1.0 1.5 1.5 1.1 United States2 Total, private nonfarm............................ Construction....................................................... Manufacturing................................................... Wholesale trade................................................. Retail trade.......................................................... Transportation and warehousing............... Information......................................................... Finance and insurance ................................... Real estate and rental and leasing.............. Professional and technical services . ......... Administrative and waste services............. Health care and social assistance................ Arts, entertainment, and recreation........... Accommodation and food services .......... Other services, except public administration ............................................... Data do not meet BLS or State agency disclosure standards. Data on layoffs were reported by employers in all States and the District of Columbia. 1 2 and 1997 (while the sector was expanding). In the New York area, extended mass layoffs in the information sector resulted in about 4,000 separations, on average, between 2002 and 2006, or 6.7 percent of all metropolitan area separations. The largest number of separations during these years occurred in 2004, when the overall employment picture was starting to improve. Nationally, this sector accounted for 3.6 percent of all private-industry layoff separations. The disparity between local and national proportions, however, was consistent with the difference in employment shares: as indicated by a 1.47 location quotient, information sector employment was more highly concentrated in the New York area. NOTE: Dash represents zero. SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. Finance and insurance separations After a slow period in 1996 and 1997, finance and insurance employment grew between 1 percent and 2 percent annually in the New York area prior to the 2001 recession. Employment declined between 2001 and 2003, but by 2005 growth had returned to prerecession rates, unlike growth rates in most of the other sectors in the area. Finance and insurance layoff separations varied quite a bit from year to year, with the peak occurring in 2002, when there were more than 7,000 extended separations. In 2006, the sector saw 570 separations, the lowest numMonthly Labor Review • September 2008 37 New York Mass Layoffs Table 10. Rates of extended mass layoff separations, by industry, United States,1 1996–2006 Average percent employment in Industry establishments with 1996 50 or more employees Total, private nonfarm........................ Construction . ................................................ Manufacturing............................................... Wholesale trade............................................. Retail trade...................................................... Transportation and warehousing .......... Information..................................................... Finance and insurance................................ Real estate and rental and leasing.......... Professional and technical services . ..... Administrative and waste services ........ Health care and social assistance............ Accommodation and food services ...... Other services, except public administration............................................. 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 57.4 36.0 79.2 42.0 50.1 67.0 72.4 57.9 29.3 46.1 71.2 66.7 42.8 1.7 6.8 2.6 1.0 1.7 1.8 2.4 1.0 .8 1.0 1.5 .5 1.2 1.7 7.8 2.4 .7 1.4 2.3 2.6 .7 .7 1.3 1.1 .4 1.3 1.7 5.7 3.3 .6 .8 2.2 1.9 .7 .3 .8 1.1 .4 1.2 1.5 5.6 2.6 .7 1.3 1.9 1.0 .7 .3 .8 1.2 .4 .9 1.5 4.8 2.6 .7 1.2 1.8 .6 1.0 .4 .7 1.4 .5 1.0 2.4 4.6 4.7 1.2 1.7 4.1 2.2 1.0 1.2 1.5 3.1 .3 1.8 2.1 5.1 3.8 1.0 1.8 3.1 2.3 1.2 .5 1.9 2.6 .3 1.2 2.0 5.8 3.4 1.3 1.7 3.3 2.9 1.2 .6 1.4 2.9 .4 1.3 1.7 5.1 2.3 .7 1.9 2.2 1.6 1.0 .7 1.1 2.2 .5 1.6 1.5 4.9 2.0 .6 1.1 2.5 1.1 .6 .5 1.3 1.7 .5 1.7 1.5 4.5 2.5 0.6 1.3 2.5 .9 .9 .3 1.3 1.6 .3 1.5 23.3 .9 1.4 1.3 1.3 1.2 1.1 1.5 1.2 1.5 1.4 1.1 1 Data on layoffs were reported by employers in all States and the District of Columbia. ber recorded for finance and insurance during the 11 years studied. In the 5 years after 2001, this sector accounted for 6.7 percent of all separations in the New York area, compared with just 3.0 percent nationally over the same period. However, the metropolitan area’s share of separations was not disproportionate to its portion of total employment: in the New York area, about 8 percent of all private-industry workers were employed in finance and insurance. Nationally, the share was between 5 percent and 6 percent. Furthermore, a slightly greater percentage of finance establishments staff at least 50 employees in the New York area compared with the Nation: about 6 percent of all finance establishments in New York employed at least 50 employees, while nationally the figure was approximately 4 percent. Thus, even though major job cuts in finance were a significant part of the layoff activity in the New York area, they were neither extraordinary (on the basis of industry concentration and size) nor permanently damaging to the sector’s local strength. Nevertheless, BLS layoff data show that finance separations were costly: in 2005 and 2006, the longest average jobless duration, based on the average number of continued claims in the United States, was experienced by claimants laid off from finance and insurance companies. Employees from that sector also exhausted their benefits at high rates. 38 Monthly Labor Review • September 2008 SOURCES: Bureau of Labor Statistics, Mass Layoff Statistics program and Quarterly Census of Employment and Wages. Table 11. Total extended mass layoff separations, by selected industries, New York-Northern New Jersey-Long Island, 1996–2006 Industry Manufacturing.............................................. Apparel ....................................................... Chemicals .................................................. Food.............................................................. Machinery ................................................. Miscellaneous manufacturing.......... Transportation equipment................. Computer and electronic products................................................. Paper . .......................................................... Printing and related support activities................................................. Leather and allied products.............. Fabricated metal products................. Plastics and rubber products............ Electrical equipment and appliances . .......................................... Nonmetallic mineral products......... Primary metals ....................................... Furniture and related products....... Textile mills................................................ Textile product mills.............................. Petroleum and coal products........... Beverage and tobacco products..... Wood products........................................ All layoff separations Permanent worksite closure separations 97,256 14,906 12,226 11,202 10,795 9,254 8,760 31,768 2,224 4,760 4,666 3,492 3,509 2,681 5,766 3,744 1,757 1,210 3,520 3,318 3,140 3,086 909 539 865 1,450 2,024 1,365 1,261 1,012 590 387 325 (1) (1) 1,262 629 ( 1) 773 (1) (1) (1) (1) (1) Data do not meet BLS or State agency disclosure standards. SOURCE: Bureau of Labor Statistics, Mass Layoff Statistics program. 1 Chart 5. Percent of separations not involving permanent worksite closure in manufacturing, New YorkNorthern New Jersey-Long Island, 1996–2006 Industry All manufacturing Apparel Leather and allied products Printing and related support activities Fabricated metal products Computer and electronic products Transportation equipment Paper Machinery Other manufacturing Miscellaneous manufacturing Chemicals Food Nonmetallic mineral products Plastics and rubber products Electrical equipment and appliances Furniture and related products 0 SOURCE: 20 40 60 Layoff separations (percent) Bureau of Labor Statistics, Mass Layoff Statistics program. Administrative and waste services After continued strong growth in the late 1990s, amounting to increases of between 5 percent and 7 percent a year, employment in New York area administrative and support and waste management and remediation services (or, simply, administrative and waste services) slowed with the recession and then remained relatively unchanged. Layoffs in New York in this sector reached their peak of 3,911 in 2002. In the years that followed, administrative and waste services had at least 2,000 layoffs annually, compared with an average of 1,206 during the 5 years prior to 2001. From 2002 through 2006, separations in administrative and waste services amounted to 4.9 percent of the total in New York, while nationally, the sector accounted for almost 11 percent of all layoffs, slightly more than its share of employment among establishments with at least 50 employees. A large number of separations due to contract completion occurred in this sector, which includes temporary help agencies and professional employer organizations. 80 100 TWO SECTORS THAT WERE RESPONSIBLE for a substantial portion of layoffs in the greater New York area prior to 2001 were the manufacturing sector and the transportation and warehousing sector. The share of area separations in these two sectors declined after 2001, while layoff activity increased in four other sectors: construction; administrative and waste services; arts, entertainment, and recreation; and accommodation and food services. The differences between the manufacturing sector and the transportation and warehousing sector, reflected in the nature of, and reason for, the layoffs, as well as the extent of related permanent closures, contributed to a fundamental change in the character of job displacement in the New York area. Particularly noteworthy is the fact that layoff displacement increased among several local industries during periods of employment growth. The mass layoff experience in the greater New York area after 2001 was qualitatively different from what it was prior to 2001, in contrast to the national pattern. Although some of the difference might be explained by the local industry mix, other factors helped transform the character of extended mass layoffs in New York. Foremost, the New York Monthly Labor Review • September 2008 39 New York Mass Layoffs area experienced dramatic growth in layoff actions due to the completion of employment contracts. In 2005 and 2006, contract completion accounted for more nonseasonal layoff events than internal company restructuring did, reversing the pattern of the past. A possible explanation for this shift is that increased business activity, especially within construction, coupled with a drive to keep costs down throughout industry, led to both an increase in contracting and a decrease in costly restructuring.18 Furthermore, as suggested by the analysis of New York area data presented in this article, the ability of employers to adapt to both competitive pressures and slack work by trimming staffs varied by industry. For example, large employers in apparel, a key local manufacturing industry, reduced the size of their workforce more often than permanently closing down operations. The analysis presented herein has attempted to make comparisons between the New York metropolitan area and the Nation over time. Additional information is needed, however, to complete an assessment of extended mass layoffs, affording opportunities for future research. Information on business turnover and job creation and destruction, by firm or establishment size in metropolitan areas, would round out the employment picture and help explain layoff trends. Beyond this benefit, the information could aid in the distribution of funds for employment services19 and provide a more robust picture of industry health. As the Workforce Information Council concluded in a report about local data needs, “Understanding the impact of layoffs and plant closings on labor markets, workers, and communities requires information on other dynamic aspects of the labor market.”20 Indeed, local layoff data, such as those presented herein, would be greatly enhanced with local job dynamics data. Notes 1 The New York-Northern New Jersey-Long Island Metropolitan Statistical Area (MSA), as defined by the Office of Management and Budget in Bulletin 06–01, is composed of New York City and Nassau, Putnam, Rockland, Suffolk, and Westchester Counties in New York; Bergen, Essex, Hudson, Hunterdon, Middlesex, Monmouth, Morris, Ocean, Passaic, Somerset, Sussex, and Union Counties in New Jersey, and Pike County, Pennsylvania. For convenience, the New York-Northern New Jersey-Long Island MSA is referred to as the New York area, or simply New York, throughout this article. 2 Each extended layoff event causes at least 50 employees to lose work for more than 30 days. If large layoffs occur gradually, in such a way that the requirement of 50 unemployment claims filed in a 5week period is not reached, then the layoff event is not counted as an extended layoff by the Mass Layoff Statistics program. The 31-day minimum duration for qualification as a layoff limits the focus of the survey program to more permanent job dislocation. Most layoff events involving 50 or more workers last for 30 days or less. Along with the minimum required duration, in cases with no direct job loss, such as employers transferring work elsewhere without laying off workers, no information is collected, even though some displacement may result. 3 The Mass Layoff Statistics program is a Federal-State program that utilizes a standardized, automated approach to identifying, describing, and tracking the effects of major job cutbacks, using data from each State’s unemployment insurance database. Each month, States report on establishments with at least 50 initial claims filed against them during a consecutive 5-week period. The establishments are contacted by the State agency to determine whether these separations lasted 31 days or longer; if so, other information concerning the layoff is collected. The program also provides measures of laid-off workers’ spells of unemployment to the point when regular unemployment insurance benefits are exhausted. These measures include the average number of continued claims, as well as the percentage of claimants receiving final payment. (A continued claim is a claim filed after the initial claim, either by mail, by telephone, or in person, for waiting-period credit or for payment for a certified week of unemployment.) 4 An establishment is a unit at a single physical location at which predominantly one type of economic activity is conducted. 40 Monthly Labor Review • September 2008 Of the 25 categories currently used to classify justifications for a layoff, only a handful accounted for most of the separations in the New York area. Other, less frequently used reasons failed to yield publishable local-level results. Recently, the BLS concluded an in-depth review of all reasons for separation, in an effort to improve the capture and classification of economic reasons. Data published for 2007 now reflect an enhanced classification scheme. Additional and enhanced categories, as well as aggregations of related reasons, are currently available. 5 6 Not an output of the BLS Mass Layoff Statistics program, the rates produced for these analyses were used to facilitate comparisons across years and among industry sectors. The layoff event rate indicates the number of layoff events per 100 establishments (in which at least 50 workers are employed). To compute this rate, establishment counts by size of establishment were derived from the U.S. Census Bureau’s County Business Patterns. The layoff separation rate, indicating the number of extended mass layoff separations per 1,000 workers employed, was computed at the national level with employment data by size of establishment from the BLS Quarterly Census of Employment and Wages (QCEW). 7 A worksite closure involves the complete shutdown of either a multiunit or a single-unit establishment, or the partial closure of a multiunit establishment wherein entire worksites affected by layoffs are closed or planned to be closed. 8 See Steven J. Davis, R. Jason Faberman, and John Haltiwanger, “The Flow Approach to Labor Markets: New Data Sources and Micro-Macro Links,” NBER working paper 12167 (National Bureau of Economic Research, April 2006); on the Internet at papers.nber.org/ papers/w12167.pdf. 9 “Analysis of Business Formation, Survival, and Attrition Rates of New and Existing Firms and Related Job Flows in Appalachia” (Camp Hill, PA, The Brandow Company, October 2001); on the Internet at www.arc.gov/images/reports/bizform/analysis-final.pdf. 10 See non-seasonally-adjusted historical data on State gross job gains and losses, on the Internet at www.bls.gov/bdm. 11 An initial claimant is a person who files any notice of unemploy- ment to initiate a request either for a determination of entitlement to, and eligibility for, compensation or for a subsequent period of unemployment within a benefit year or other period of eligibility. 12 Important distinctions exist between extended mass layoff data and displaced worker data. In addition to tallying those who lost jobs, the displaced worker count includes workers who left jobs in anticipation of losing them. Displaced workers are persons 20 years of age and older who lost or left jobs. Displaced worker data are restricted to longtenured employees: those who had worked for their employer for at least 3 years. Extended mass layoff data cover only separated workers, without any age or tenure restrictions. (See “Worker Displacement, 2003–2005,” BLS news release (Bureau of Labor Statistics, Aug 17, 2006), on the Internet at www.bls.gov/news.release/archives/disp_08172006.pdf.) 13 The location quotient is the ratio of employment in a particular industry in a certain geographical area (in this article, the New York metropolitan area) to base-industry employment (in this article, the private-sector total), divided by the ratio of employment in the same industry in the base area (the United States) to base-industry employment in the base area. For this computation, 2006 annual averages from the QCEW were used. “Job Openings and Labor Turnover: January 2007,” BLS news release (Bureau of Labor Statistics, Mar. 13, 2007), on the Internet at www.bls.gov/news.release/archives/jolts_03132007.pdf. Layoffs and discharges are involuntary separations initiated by the employer and include layoffs with no intent to rehire; formal layoffs lasting or expected to last more than 7 days; discharges resulting from mergers, downsizing, or closings; firings or other discharges for cause; terminations of permanent or short-term employees; and terminations of seasonal employees. 14 15 Movement of work within the same company or to a different company, either domestically or outside the country, occurred in less than 10 percent of all nonseasonal layoff events in the United States. In 2004, the BLS Mass Layoff Statistics program added offshoring and outsourcing of work as reasons that identify job loss associated with the movement of work, within a company and to another company, domestically and out of the country. Nearly all the overseas relocations occurred in manufacturing. Nevertheless, because of publishability criteria, data on movement of work and overseas relocations were not available for the New York area. Criteria that safeguard confidentiality restrict what is published at the local level and result in the suppression of information that is available at the national level, such as additional information on relocations. See “New York City’s Garment Industry: A New Look?” (New York and Albany, Fiscal Policy Institute, August 2003). 16 17 In 1996, businesses with between 50 and 999 workers accounted for 16.4 percent of U.S. apparel establishments and 71.2 percent of em- ployment in the industry. By 2006, the share had declined to 9.6 percent of establishments and 60.8 percent of employment. It must be pointed out, however, that small apparel manufacturers, namely, those employing fewer than 50 workers (and not studied by the BLS Mass Layoff Statistics program), accounted for 90 percent of establishments in 2006. Without knowing the exact reasons for layoffs in each New York area industry, however, this hypothesis cannot be completely validated. Additional data limitations include employer coverage and the duration of layoffs. BLS mass layoff data cover only establishments that employ 50 or more workers. Smaller establishments were outside the scope of the survey, although layoff activity in these establishments is documented to have been significant. Between 1992 and the fourth quarter of 2006, more than half of the gross job losses were in firms with fewer than 50 employees; during that period, 87.1 percent of firms which closed were in that size class. BLS Business Employment Dynamics size class statistics are measured at the firm level rather than the establishment level. (A firm is a business organization consisting of one or more domestic establishments in the same area and industry under common ownership or control. The firm and the establishment are the same for single-establishment firms.) (See “Business Employment Dynamics: Second Quarter 2006,” BLS news release (Bureau of Labor Statistics Aug. 16, 2007), on the Internet at www.bls.gov/news.release/archives/cewbd_08162007.pdf; and “New Quarterly Data from BLS on Business Employment Dynamics by Size of Firm,” BLS news release (Bureau of Labor Statistics, Dec. 8, 2005), on the Internet at www.bls.gov/news.release/pdf/cewfs. pdf.) Although a large percentage of job flows occurs in smaller firms, BLS data indicate that larger size classes experienced more quarters of net loss, as reflected in negative net employment change, related to the 2001 recession. 18 The Workforce Reinvestment Act (Public Law 105–220—Aug. 7, 1998) mandates the development of a comprehensive workforce information system that includes “the incidence of, industrial and geographical location of, and number of workers displaced by, permanent layoffs and plant closings.” Analysis of such information, as intended by the Act, is not only for the allocation of Federal funds, but also for national, State, and local policymaking, the implementation of Federal policies, program planning and evaluation, and researching labor market dynamics. 19 The Workforce Information Council is a collaboration of Federal and State agency officials that plans, guides, and oversees the U.S. workforce information system. The report, titled Needs and Alternatives for Plant Closing and Layoff Statistics: Report to the Workforce Information Council (Plant Closing and Layoff Statistics Work Team, Mar. 22, 2000), is on the Internet at www.workforceinfocouncil.org/documents/wg_ LayoffStats.zip. 20 Monthly Labor Review • September 2008 41 Conference Report Knowing younger workers better: information from the NLSY97 Papers from the 10th anniversary conference of the National Longitudinal Survey of Youth, 1997 cohort, addressed schooling, employment, adolescent behaviors, and many other aspects of youths’ lives Dan Black, Robert Michael, and Charles Pierret Dan Black is a professor of public policy at the University of Chicago and Principal Investigator of the National Longitudinal Survey of Youth 1997 Cohort at NORC. Robert Michael is the Eliakim Hastings Moore Distinguished Service Professor Emeritus at the University of Chicago and the Project Director of the National Longitudinal Surveys Program at NORC. Charles Pierret is director of the National Longitudinal Surveys Program at the Bureau of Labor Statistics. E-mail: pierret.charles@bls.gov The statements in this article do not necessarily reflect the views of any of the aforementioned institutions. 42 F or more than 40 years, the U.S. Department of Labor has undertaken a series of major, national studies that track labor force behavior. These studies follow the same men and women, year after year, and by doing so reveal much about what affects wages and hours of work, how new skills influence success in the job market, how health and schooling interact to influence careers, and how unexpected events—from plant closings and bad weather to product innovations and the openings of new markets—affect earnings. The National Longitudinal Surveys (NLS) program has become one of the Nation’s most respected and influential sources of data about the work force since its inception in 1966, administered through the Employment and Training Administration until 1984 and through BLS thereafter. The NLS program consists of seven samples of men and women who have been surveyed periodically and have reported on many of their behaviors in and related to labor markets. These surveys have been used in thousands of research projects within the Government and in research universities and analytic think tanks. The studies constitute a major component of what researchers now know about the roles of schooling, intellectual ability, health, mi- Monthly Labor Review • September 2008 gration, community, and family in developing the “human capital” and “social capital” that influence the distribution of earnings in the United States and the level of our Nation’s gross domestic product. In May 2008, BLS hosted a conference to highlight new research using the most recent data from one of these data sources, the National Longitudinal Survey of Youth, 1997 cohort (NLSY97).1 This survey of young people born from 1980 to 1984 (age 12 to 17 in the first year of the survey) has now taken place for 10 consecutive years. The face-to-face interview of these youths asks about their schooling, employment, adolescent behaviors, and many other aspects of their lives. In the data that were available for study at the time of the conference, these nearly 9,000 men and women from across the Nation were only in their early- to mid20s, but already their reported experiences and behaviors revealed important facts that will have an impact on the labor force for decades to come. This article offers a brief and informal characterization of a few of the studies on which presenters reported at the conference. The conference presentations were based on preliminary research findings of these studies that are now undergoing peer scrutiny prior to official publication in scholarly journals and books. (See the box.) Employment Changing characteristics of youth. Employment of the NLSY97 youths is perhaps the central behavior of interest. One important paper concerning employment presented at the conference was written by Joseph Altonji, Prashant Bharadwaj, and Fabian Lange from Yale University and entitled “Changes in the Characteristics of American Youth: Implications for Adult Outcomes.” The paper asks what one can predict today about the labor force 20 years from now when the NLSY97 cohort will be in its peak earning years. The analysis is based on the experiences of the National Longitudinal Survey of Youth 1979 Cohort (NLSY79)—an earlier NLS cohort, fielded in 1979—with respondents born between 1957 and 1964. The authors use the relationship between early labor-market-relevant characteristics of youths in the NLSY79 and their subsequent mid-career labor market outcomes to predict midcareer labor market outcomes of the NLSY97 cohort on the basis of their current characteristics. The paper comprises two parts. In the first, the authors “create a set of youth characteristics that correlate with adult outcomes and are comparable across the NLSY97 and the NLSY79.” Even though the authors attempt to make the two data sets directly comparable, differences in sampling, attrition, and questions make this a complicated exercise. For example, the NLSY97 was sampled at younger ages (12–17) than the NLSY79 (14–22). Although a greater percent of youths eligible for the sample were actually interviewed in the first round of the NLSY97, Tenth Anniversary Conference Papers, NLSY97, May 29–30, 2008 Joseph G. Altonji, Prashant Bharadwaj, and Fabian Lange, “Changes in the Characteristics of American Youth: Implications for Adult Outcomes.” Joseph G. Altonji, Sarah Cattan, and Iain Ware, “Sibling Influences on Teenage Risky Behaviors.” Alison Aughinbaugh and Rosella M. Gardecki, “Attrition in the National Longitudinal Survey of Youth 1997.” Philippe Belley, Marc Frenette, and Lance Lochner, “PostSecondary Attendance by Parental Income: A Canada-U.S. Comparison.” Dan A. Black, Kerwin Charles, and Seth Sanders, “The Problem with Men.” Dan A. Black, Robert T. Michael, and Kanru Xia, “The Propensity to be an NLSY97 Respondent: Evidence from the Screener Data.” A. Rupa Datta Parvati Krishnamurty, “High School Experience: Comparing Self-Report and Transcript Data from the NLSY97.” Keith Finlay, “Effect of Employer Access to Criminal History Data on the Labor Market Outcomes of Ex-Offenders and Non-Offenders.” Tricia Gladden and Charles Pierret, “Employment Before Age 16: Does it Make a Difference?” Jeffrey Grogger, “Speech Patterns and Black-White Wage Inequality.” Carolyn J. Hill, Harry J. Holzer and Henry Chen, “Against the Tide: Household Structure, Opportunities, and Outcomes among White and Minority Youth,” chapters 3 and 4. Robert Kaestner and Michael Grossman, “Effects of Weight on Adolescent Educational Attainment.” Jennifer Manlove, Mindy E. Scott, Erum Ikramullah, Kate Perper, and Emily Lilja, “Relationship Context and the Transition to a Nonmarital Birth.” Kristin Moore, and Kassim Mbwana, “Preventing Risky Sex and Adolescent Parenthood: Does the Effectiveness of Parenting Practices Differ For Children with Varied Risks?” Randall J.Olsen, “The Desirability of Partner Traits and Two Decades of Change in the Marriage Market: A Oneand-a-Half Sex Model of Marriage.” Michael R. Pergamit, “Who Runs Away from Home? An Exploratory Analysis.” James R. Walker, “Choice, Enrollment and Educational Attainment within the NLSY79 and NLSY97.” Kenneth I. Wolpin, and Antonio Merlo, “Youth Crime and High School Completion.” Lawrence Wu and Pamela Kaufman, “Two Decades of Change in Premarital First Births: Cohort Comparisons from the NLSY79 and NLSY97.” NOTE: Many of those papers which are available can be found online at: http://harrisschool.uchicago.edu/research/conferences/NLSYConf/ Monthly Labor Review • September 2008 43 Conference Report subsequent attrition has been higher. Because they were younger when they were first interviewed, NLSY97 sample members had more years to drop out of the survey before age 22, when many of the characteristics that the authors study are measured. The authors devote a great deal of effort to ensuring that any differences in measured characteristics are real and not an artifact of survey differences. The authors’ most substantive finding is important: they find that the NLSY97 had more skills at the age of 22 than the NLSY79 did. The greatest advantage of the NLSY97 was in education; along all measured dimensions of educational attainment, the younger cohort was clearly superior to the older cohort. By age 22, the 1997 cohort had completed more than one-third of a year more of school, was more likely to have a high school diploma—or, failing that, to have a GED—and was much more likely to still be attending school or to have finished 14 years of school than the 1979 cohort. This skills advantage manifested itself in significant gains on the Armed Forces Qualifying Test (AFQT), the test the military uses to determine skill levels when making admission and job assignments. These gains were especially remarkable for minority youth, with African Americans’ (or Blacks’) scores improving by 36 percent and Hispanics’ scores improving by 24 percent between the two cohorts (compared with a 5 percent improvement for Whites). Gains in parents’ education were also significant, with the average NLSY97 youth having a mother with 1 year more of education and a father with three-quarters of a year more education than the mother and father of the youth’s counterpart in the NLSY79. Where the 1997 cohort falls short in comparison with the 1979 cohort is in the area of family structure. A much larger percentage (47 percent versus 25 percent) of the 1997 cohort was living in families in which one of the parents was not present. So although parents of the younger cohort had more skills to impart to their children, they had less contact with their children. The second part of the Altonji, Bharadwaj, and Lange paper uses the reported childhood experiences from the 1979 and 1997 cohorts, along with the experiences from adulthood from the 1979 cohort, to predict outcomes for the 1997 cohort as adults. Using the characteristics derived in the first part of the paper, the authors estimate the impact that changes in skill level will have on the wage distribution when the cohort has reached middle age. Overall, they expect wages to increase by 6 percent to 7 percent, though the increase will be greater at the upper end of the distribution and lesser at the lower end. This means an increase in inequality over the next decades. The authors suggest that increases in skills for groups 44 Monthly Labor Review • September 2008 that were relatively disadvantaged in the 1979 cohort, however, will result in diminishing gaps between the sexes and among races. Black and Hispanic males will gain significantly on white males except at the very top of the wage distribution. From the bottom of the wage distribution to the 90th percentile, the wage gap should close by about 4 percentage points for both black and Hispanic males relative to white males. Similarly, wage gains for females should exceed those of males, causing the wage gap between the sexes to decrease by around 2 percentage points. Within-group inequality will grow as skills become more unequal within groups, but average skills across sex and race groups will become less unequal, resulting in less wage inequality across groups. So while the increase in inequality that has plagued the economy for the last 30 years is likely to continue, it will be based less on race and sex than it has been in the past. The authors remind readers that their conclusions rest, necessarily, on the assumptions that the labor market premium or discount for a racial or ethnic group or for one sex or the other remains the same over time. Similarly, their expectations of the future labor market do not take into account broader questions pertaining to how the financial returns of schooling will change as markets and products develop or how the continued competitiveness of global markets might affect labor market trends. In this sense, the analysis undertaken by Altonji, Bharadwaj, and Lange offers only a partial answer to the question of how the workforce will fare in the years ahead, but their answer, cautiously constructed and conditioned as it is, uses these NLSY longitudinal data sets in the best way possible and offers a decidedly optimistic assessment of future developments in the labor force. Employment before age 16. Another paper from the conference that focuses on employment is one that exploits the NLSY97’s data on work history and its links across several domains to examine the consequences of employment at a very young age among the youths in the cohort. Tricia Gladden and Charles Pierret from the Bureau of Labor Statistics use the extensive data on very early employment in the NLSY97 in their paper “Employment Before Age 16: Does it Make a Difference?” They point out that collecting information on teen employment was a key reason that the survey was started. Standard labor market surveys such as the Current Population Survey only report about employment starting at age 16. However, a majority of youths in the NLSY97 reported doing some work for pay before this age. Gladden and Pierret posit that it is unclear whether early employment is ultimately beneficial to these youths. On the one hand, early employment may teach important lessons such as responsibility, perseverance, and self-reliance and allow youths to accumulate experience that will prove useful later in their careers. On the other hand, early employment may be distracting, taking youths away from educational and developmental activities that will prove more beneficial than the menial jobs that are available to young workers. It may also introduce them to older youths who are engaged in behaviors that are not age-appropriate for the young workers. Gladden and Pierret’s paper explores the correlation between youth employment and a number of outcomes in the late teen years as a first attempt to measure the effects of early employment. The NLSY97 interviewed youths as young as 12 and asked them to report on jobs they held at any time after their 12th birthday. Because these children were not legally able to hold a job with an employer, the NLSY97 concentrated on “freelance jobs” among this group. These are informal jobs such as babysitting or yard work where the employee works directly for the ultimate consumer of the service, usually on an as-needed basis. Respondents older than 14 were also asked about traditional “employee jobs”—that is, those in which the youth worked for an employer who provided goods or services to many consumers. Restaurants and retail establishments provided typical employee jobs for teens in the sample. Gladden and Pierret identify respondents who worked in freelance jobs between the ages of 11 and 15 and those who worked in employee jobs at 14 or 15. They then follow these youths until the age of 20, examining various outcomes along the way. Two findings are notable from this research. First, once youths enter the labor force, they tend to continue to work throughout their teen years. Between 80 percent and 90 percent of youths who worked at a given age worked again at the next age. Thus, those who start young will likely continue to work at least part of the year until age 20. Second, after controlling for standard background variables (race, sex, income, family structure, parents’ education, and AFQT score) working at freelance jobs at young ages is correlated with a number of negative outcomes. Those who worked at freelance jobs before age 15 achieved less schooling by age 20; smoked, drank alcohol, and used marijuana more often before age 16; and were more likely to carry a handgun, assault someone, or be arrested by age 18 than youths who waited until age 16 for their first job. Gladden and Pierret are quick to point out that this may be largely an effect of selection—those who are likely to work at a young age may also be the type to want less schooling and to engage in substance abuse and delinquent behavior, in which case the correlation does not imply that working per se causes these behaviors. But the link between early employment and these outcomes certainly warrants further investigation. Access to criminal records. One of the attractive features of the NLSY97 data set is that it captures a lot of information that is tangentially related to employment. One of these pieces of information is the youth’s criminal record—the data include information on many illegal actions that resulted in arrests, convictions, periods of incarceration, and other run-ins with the law. Incarcerations, naturally, influence labor market behavior, especially when youths are incarcerated long enough to prevent them from participating in the regular labor market. The NLSY97, being a longitudinal data set, can be used to assess the impact of the incarceration on subsequent employment. Keith Finlay from Tulane University, in his paper “Effect of Employer Access to Criminal History Data on the Labor Market Outcomes of Ex-Offenders and NonOffenders,” uses the information about incarceration and subsequent employment along with one other piece of information—the State in which the young man or woman resides post incarceration. He points out that over the interval of interest for these cohorts of youths—1997 to 2003—some 16 States, starting with Florida in 1997, adopted the practice of releasing on the Internet information from the criminal records of all convicted felons. Finlay studies the employment experience of people who have and have not been incarcerated, in States with and without Internet reporting. An employer may have a notion that a job applicant of a particular type—age, sex, race, or ethnic group, for example—is more likely to have a criminal record. If this notion causes the employer not to hire someone of that type, this is a phenomenon called “statistical discrimination.” However, argues Finlay, in a State that puts information concerning people’s criminal records on the Internet—making it easy for employers to determine whether a particular job candidate is a convicted felon—employers have far less reason to “statistically discriminate” against non-felons. In short, this State policy is expected to be detrimental to the employment prospects of people who have been incarcerated but to be helpful to those from high-incarcerated groups who have not themselves been jailed. Finlay explains that there are 369 NLSY97 respondents who have been incarcerated as adults (4.4 percent of his whole sample). For men age 19, the cumulative rates of adult incarceration were: 3 percent of white males, 8 percent of African-American males, 4 percent of Hispanic Monthly Labor Review • September 2008 45 Conference Report males, and less than 1 percent of each of the three groups of females. For men age 24, however, the cumulative rates of those same six groups were dramatically higher: 8 percent of white males, 19 percent of African-American males, 12 percent of Hispanic males, and 2 percent to 3 percent of the respective groups of females. Finlay studies the relationship between incarceration and employment, wages, and earnings; his findings confirm his expectations: “ex-offenders are less likely to be employed, have lower wages, and have lower earnings in [S]tates with Internet sites providing information about ex-offenders.” And the magnitude of this effect is considerable: in the open-records States, ex-offenders have a 5-percentage-point lower likelihood of employment, 9 percent lower hourly wages and 19 percent lower annual earnings. The evidence is less striking, but again affirming, for the effects of open records for non-offenders from groups with high rates of incarceration; however, the association is not statistically significant. Education Educational attainment. Education is certainly a key factor in the attainment of a successful career. The NLS data sets, with their depth of information on the educational experiences of cohorts 20 years apart, provide excellent data on the change in educational attainment over the last 2 decades. James Walker of the University of Wisconsin at Madison, in his paper titled “College Choice, Enrollment and Educational Attainment in the NLSY79 and NLSY97,” provides a detailed comparison of the two cohorts and emphasizes some fascinating developments in the educational attainment of individuals in the two data sets at ages 24 or 25. He reports an increase in mean years of schooling of 0.4 year from the 1979 cohort to the 1997 cohort; median years of schooling increased from 12 years for the 1979 cohort to 13 years for the cohort of 1997. Somewhat surprisingly, the interquartile range of schooling increased dramatically, from 1.5 years in the NLSY79 to 3.5 years in the NLSY97. Walker documents a substantial decline in the percentage of people who did not obtain a high school diploma or pass the General Educational Development (GED) tests. Among males, for example, this fraction dropped from 14.8 percent in the 1979 cohort to just 7.6 percent in the 1997 cohort. For women, the drop was a bit less dramatic, from 11.8 percent in the 1979 cohort to 7.8 percent in the 1997 cohort. One can see the same pattern of improvement in education when considering those without a high school degree—either dropouts or those with GEDs. The 46 Monthly Labor Review • September 2008 percentage of men without a high school degree declined from 23.8 percent in the 1979 cohort to just 16.7 percent in the 1997 cohort. For women, the gain is again somewhat muted; in the 1979 cohort, 19.7 percent of women did not have a high school degree, but by the 1997 cohort the figure had shrunk to 15.1 percent. This decline represents a substantial improvement in human capital across these two cohorts. Results at other levels of education are equally encouraging. About 20.9 percent of men in the 1979 cohort had a bachelor’s degree, a figure that increased to 24.2 percent in the 1997 cohort. For women, the increase was astonishing; in the 1979 cohort, 18.6 percent had a bachelor’s degree, but by the 1997 cohort, 30.4 percent of women had a bachelor’s degree. Thus, in the 1979 cohort, there were 1.12 men for each woman with a bachelor’s degree, but by the 1997 cohort, this had fallen to just 0.80 man per woman. This striking change reflects a difference between the sexes in college enrollment rates—while men’s attendance at 4-year universities increased from 34.3 percent to 42.3 percent, women’s attendance at 4-year universities increased from 30.9 percent to 47.8 percent. The graduation rate conditional on attending 4-year universities declined for men from 60.9 percent in the 1979 cohort to 57.2 percent in the 1997 cohort. Despite the large increase in college attendance among women, their graduation rate increased from 60.2 percent to 63.6 percent. Thus, in the 1997 cohort, women were more likely than men to attend university, and those who did were more likely than men to graduate. African Americans, too, made considerable progress, although the gains are much more concentrated in the upper end of the distribution for Blacks than for Whites. For instance, the percentage of black respondents who did not obtain either a GED or a high school diploma declined from 16.5 to 13.5 from the 1979 cohort to the 1997 cohort, whereas the corresponding percentage of white respondents declined from 11.3 to 5.8. Thus, despite starting from a smaller percentage of nongraduates, Whites experienced a greater decline in the percentage who did not obtain either a GED or high school diploma than did Blacks. Similarly, the percentage of black respondents without a high school degree was essentially unchanged, increasing from 25.2 in the 1979 cohort to 25.3 in the 1997 cohort. For Whites, however, that percentage dropped from 19.0 in the 1979 cohort to 13.2 in the 1997 cohort. Progress was even more dramatic for Hispanics. In the 1979 cohort, 36.5 percent of respondents did not have a high school degree, but this dropped to 19.6 percent in the 1997 cohort. Thus, in one generation, African Americans replaced Hispanic Americans as the group having the highest fraction of youth without a high school degree. At the other end of the distribution, however, African Americans showed a much more substantial improvement than did Hispanics. In the 1979 cohort, 8.5 percent of the African American population had a bachelor’s degree by age 25, but this percentage grew to 15.0 by the 1997 cohort. In contrast, in the 1979 cohort, 9.4 percent of Hispanics had a bachelor’s degree by age 25, but this grew much less rapidly, to 11.7 percent in the 1997 cohort. By comparison, the percentage of whites with a bachelor’s degree grew from 23.9 in the 1979 cohort to 32.6 in the later cohort. Thus, there is a very distinctive pattern among the three major race/ethnic groups. For Whites, education levels have increased across the distribution, with fewer who fail to obtain a high school degree and an ever-greater proportion obtaining a bachelor’s degree. The 1980s and 1990s were a period of spectacular increase in the returns to investment of schooling, and the change in the behavior of the white Americans in the cohort is generally and properly viewed as a response to that increase in returns. In contrast, the Hispanic Americans in the cohort exhibited a modest growth in the proportion obtaining a bachelor’s degree but a substantial decline in the proportion without a high school degree. Thus, the distribution of education levels among Hispanics became much more concentrated in younger cohorts. African Americans had a substantial expansion in the proportion with a bachelor’s degree but virtually no change in the proportion without a high school degree. Thus, the distribution of educational levels among African Americans became more diffuse in the younger cohorts. Understanding the reasons for these three distinct changes in the distribution of educational levels will be an important goal for future research. Walker also reports differences in educational attainment by the respondents’ scores on the Armed Forces Qualification Test (AFQT). He divides the respondents into thirds (“terciles”), and reports the educational attainment of each. Here, again, the news is good: in each ability tercile the fraction without a high school degree declined and the fraction with a bachelor’s degree increased. Not surprisingly, the largest drop in the proportion of people without a high school degree was in the lowest tercile of AFQT scores. In the 1979 cohort, 39.5 percent of the lowest ability third did not receive a high school degree, but this fell to 35.3 percent in the 1997 cohort. Walker also documents a large increase in the proportion of people getting a GED in this bottom tercile: 11.3 percent did so in the 1979 cohort, whereas 14.3 percent did so in the 1997 cohort. The largest growth in the proportion with a bachelor’s degree occurred in the middle tercile of AFQT scores, a rise from 18.2 percent in the 1979 cohort to 22.1 percent in the 1997 cohort. The effects of parental resources. A similar pattern emerges when Walker partitions the sample into terciles by parents’ income, measured in the first round for both cohorts. From the 1979 cohort to the 1997 cohort, in each tercile the proportion without a high school degree declined, and the proportion with a bachelor’s degree increased. There is one important difference in the results for parental income compared with the results for the AFQT. The greatest gain in the proportion obtaining a bachelor’s degree occurred in the lowest tercile of the AFQT score distribution but in the highest tercile of parental income. Indeed, there is a strong monotonic relationship between income and the percentage point gain in the proportion with a bachelor’s degree: the highest tercile had an 11.4-percentage-point increase, the middle tercile had a 7.8-percentage-point increase, and the lowest tercile only had a 1.7 percentagepoint increase. Thus, the correlation between the possession of a bachelor’s degree and parental income became even stronger in the younger cohort. This increased correlation of educational attainment and parental income suggests a growing importance of parental resources in determining who can afford college. In a paper they presented at the recent NLSY97 conference, Philippe Belley and Lance Lochner of the University of Western Ontario and Marc Frenette of Statistics Canada reported on a preliminary investigation that is further exploring this correlation using the NLSY97 and a Canadian longitudinal data set.2 They expand upon a paper that Belley and Lochner recently published in the first issue of the Journal of Human Capital;3 in it, Belley and Lochner use a structural model and the NLSY79 and NLSY97 to estimate the impact of parental resources on educational attainment. Consistent with several other studies, Belley and Lochner find that parental income and resources played virtually no role in the determination of enrollment rates for the 1979 cohort. For the 1997 cohort, however, parental resources were much more important in determining who attended college. The paper explains that parental income is important because students are constrained from borrowing against their future earnings. Thus, though it makes economic sense to attend college, many members of the younger cohort were able to do so only if their parents could help them financially. Both the paper published in the Journal of Human CapMonthly Labor Review • September 2008 47 Conference Report ital and the paper presented at the conference highlight a potentially serious problem in American higher education. In the years between the two cohorts, the cost of highquality university education has skyrocketed. For instance, the Chicago Tribune has reported that the cost of sending an in-State student to the University of Illinois at Champaign-Urbana—an elite public institution—now exceeds $20,000 a year. Because the growth of college tuition and fees has far outstripped the growth in federally funded student loans, one might expect that the increased costs would limit access to costly, elite schools. Nevertheless, Americans face a staggering quantity of choice in higher education with wide variation in prices. Community colleges, for example, often represent an attractive option at a price that is an order of magnitude lower than the cost at an elite school. These drastically lower prices, coupled with the possibility of living at home and avoiding additional costs, could lead one to believe that capital market constraints would not prevent aspiring college students from attending higher education. However, there exists evidence to the contrary. In a series of papers, Todd R. Stinebrickner of the University of Western Ontario and Ralph Stinebrickner of Berea College examine the behavior of Berea College students. Berea is an especially useful college to study because it charges no tuition and provides students with a modest stipend as payment for a campus job. The policy is intended to assure that no students are excluded from Berea because they cannot afford the tuition bill. Yet, Stinebrickner and Stinebrickner find that despite the free tuition and limited direct cost of attending Berea, family income is still critically important for graduation.4 The reason seems to be that there are many events and circumstances—a parent’s illness or unemployment, for example—that may make it difficult for students to complete their college studies. Students from wealthier families have a larger number of options available to address these difficulties. Understanding the roles of capital markets and family resources in accessing and completing college is an important research agenda for the future. Obesity. A topic that has been a focus of much research in health economics is the direction of causality in the strong link between health and schooling. Some researchers suggest that schooling affects health, others suggest that health affects schooling, and still others suggest that there are other factors— third forces—that influence both in the same direction, causing the observed positive association. One of the authors of a paper at the recent NLSY97 conference, Michael Grossman of the City University of 48 Monthly Labor Review • September 2008 New York Graduate Center, has been the primary scholar in this debate over the past several decades; the paper he and his colleague, Robert Kaestner of the University of Illinois at Chicago, presented at the conference addresses one small piece of this puzzle.5 Kaestner and Grossman note that adolescent obesity has risen dramatically in recent years, and they ask whether obesity has an effect on educational attainment among adolescents. If it does, that would be one avenue through which health status influences the level of education. Kaestner and Grossman point out that a relationship between obesity and educational attainment could work in several ways logically, and economic theory alone does not shed much light on which of several potential routes of influence might dominate. Obese adolescents might suffer from discrimination from teachers and/or peers that could adversely affect their schooling, and they might also have related health troubles such as sleeping disorders and depression that could adversely affect their cognitive functioning or cause them to miss days of school. Conversely, overweight youths might engage less in sports and physical activities and even in social activities, and as a result they may spend more, not less, time studying and thus perform better academically. Kaestner and Grossman turn to the NLSY97 data for evidence. This is a case in which a negative finding is noteworthy. After undertaking a quite thorough study, with sophisticated formal theoretical modeling and statistical analyses, the researchers conclude that there is very little evidence in the NLSY97 data that obesity has any discernible effect on the educational attainment of these young adults, either positive or negative. They study boys and girls separately, looking at the extreme tails of the distribution of weight and noting the highest grade of school attended, the highest grade completed, and whether or not the student dropped out of school. In neither estimates from very simple models nor in Kaestner and Grossman’s estimates from quite complex and highly controlled models is there evidence of an effect of weight on schooling. Obesity, they conclude, does not play a direct role in the strong, positive association between health and schooling. Social Behaviors Although a primary motivation for the NLS program is a better understanding of the labor market experiences of the workforce, BLS has understood the importance of investigating a wide range of other behaviors, both within the family and in the community, as forces that affect employment, marketable skills, occupation choices and opportunities, and career trajectories, as well as hours of work, wages, and earnings. The NLS data sets have long been used for studying many types of youth and adult behaviors, and the recent conference suggests that the most recent NLSY97 data have much to contribute to our understanding of family and youth behaviors. Marriage and offspring. Robert Michael of the University of Chicago, in remarks that opened the conference, pointed to both the continuity and change in demographic trends between the 1979 and 1997 cohorts. The most dramatic trend, he claimed, is found in terms of formal marriage: 8.7 percent of 18-year-old females in the 1979 cohort had married, whereas only 1.6 percent of their counterparts in the 1997 cohort had done so. By age 21 the trend was even more striking, with 33.4 percent of the females from the 1979 cohort married but only 12.1 percent from the 1997 cohort married. Similarly, 15.1 percent of 21-year-old men from the 1979 cohort were married, compared with 5.2 percent from the 1997 cohort. Although these figures reflect the well-documented decline in formal marriage in the United States, if instead one considers the percentage of the 1997 cohort who have formed a dyadic partnership, the numbers look much like the 1979 numbers for formal marriages: 33.1 percent of the females reported having formed a cohabitational partnership, and 19.1 percent of the males reported having done so. The big decline is in formal marriage, not in forming a dyadic partnership. Concerning the percentage of young mothers, there was essentially no difference between the 1979 and 1997 cohorts—7.8 percent of women in the 1979 cohort had a child by age 18, compared with 7.6 percent of the 1997 cohort. The difference between cohorts in the percentage of those who were mothers by age 21 is also small; 23.2 percent of the NLSY79 met the criteria, compared with 23.8 percent of the NLSY97. For the males, there was a slight increase in reported parentage at age 18, with 1.3 percent of the 1979 cohort having at least one child at age 18, compared with 2.3 percent of the 1997 cohort. By age 21, 8.6 percent of the males from the 1979 cohort reported being a father, compared with 11.2 percent of the males in the 1997 cohort. Adolescent sexual activity. Researchers from Child Trends, a Washington, DC, think tank that focuses on issues of child development and policy, investigated the risky behavior of adolescent sexual activity and the role that parents play in affecting this behavior.6 Kristin Moore and Kassim Mbwana examined whether the youths who were 12–14 at the beginning of the survey began having sex before age 17 (53 percent did so), whether they used contraceptives or engaged in “unsafe sex” when they did have sex (16 percent were judged to have had unsafe sex in the 12 months before age 17), whether those who were sexually active had multiple partners by the time they turned 17 (some 44 percent had two or more partners), and whether or not they had become teenage parents before turning 18 (6 percent did so). This study examined three aspects of how the teenagers’ parents’ styles of supervision, guidance, and support affected these elements of the youths’ sexual behavior. First, the authors investigated the influences of different parenting styles on sexual risktaking by adolescents. Second, the researchers examined whether the influence of parenting style varied depending upon the risks that the adolescent faced. Finally, Moore and Mbwana examined whether parental awareness of children’s activities prevented the children from engaging in sexual activity. The NLSY97 data have considerable detail regarding how parents guide and monitor their children’s social and private lives. One set of measures used in this study—measures that are well-explored by developmental psychologists and believed to be influential in the development of preschool and elementary school children—characterizes parental styles into a four-category typology: some parents are “authoritative” (which means they are rather strict, yet highly supportive, of their adolescent children), others are “permissive” (which means they are not strict, but are quite supportive), others are “uninvolved” (meaning they are neither strict with their children nor supportive), while still others are “authoritarian” (meaning they are strict, but not supportive). Moore and Mbwana’s study borrows this typology and uses it to analyze the influence of parenting styles on the sexual behaviors of adolescents. In particular, the study focuses on the influence of an “authoritative” (strict but supportive) style of parenting. The findings at this stage in the investigation are robust ones: holding constant many of the known factors that affect adolescent behaviors, authoritative parenting was clearly associated with less sexual risk taking by girls, specifically through later initiation of sex, less unsafe sex, fewer sex partners, and lower rates of teenage parenting. For boys, the effects were not as strong, but where the effects were in evidence—in the age of onset of sexual activity—more authoritative parenting was associated with a delay in the age at first sex. Greater levels of risky sexual activity occurring among adolescents’ peers, in their schools, and in their neighborhoods were also associated with a higher probability of early sex, unsafe sex, more partners, and teen parenthood; Monthly Labor Review • September 2008 49 Conference Report however, little evidence was found that the importance of parenting varies by risk level. These studies concerning parenting styles control for several important factors that also influence this behavior. For example, adolescents who live with both their biological parents engage in less sexual risk taking, those whose mothers were themselves teenage parents exhibit more risky sexual behaviors, and those who grew up in an impoverished family take more sexual risks. The last issue that the Moore and Mbwana paper explores is the influence of parental awareness of adolescents’ activities, as measured by how well the parents know their child’s close friends, how well they know those close friends’ parents, whether they know with whom their child spends time when he or she is not at home, and how well they know their child’s teachers. The findings suggest that parental awareness results in both boys and girls delaying sexual activity, engaging in less unsafe sex, and being less likely to have multiple sexual partners. The study concludes that “[p]arents matter for all adolescents” in this important arena of sexual risk taking. The influence of siblings. Another paper presented at the conference also looks within the family at factors that appear to be associated with risky behaviors, but this one focuses on the influence of siblings instead of parenting styles.7 Joseph Altonji of Yale, Sarah Cattan of the University of Chicago, and Iain Ware of 3iGroup point out that several studies have found substantial correlations in risky behavior between siblings, raising the possibility that adolescents may directly influence the actions of their brothers or sisters. The researchers note that there is an insightful body of literature in psychology that suggests that such sibling effects may exist, particularly for younger children who look to their older siblings for cues about appropriate teenage behaviors. The authors note, however, that much of the published empirical analyses of sibling effects are compromised by the difficulty of distinguishing direct influences from the impact of shared unobserved factors. Multivariate regressions relating the behavior of siblings undoubtedly reflect the fact that a variety of common influences affect the actions of all siblings in a household, so the fact that siblings behave similarly does not necessarily imply that one child affects his or her brother or sister. Altonji, Cattan, and Ware look at a wide range of risky activities from the NLSY97 data set and find strong positive sibling correlations. The primary contribution of the paper is their assessment of the extent to which these correlations are due to causal effects from one sibling to another. 50 Monthly Labor Review • September 2008 The researchers articulate a sibling model of consumer choice that serves as a basis for their econometric identification strategy. It is based on the fact that the behavior of a child at a given point in time cannot directly influence a sibling’s actions in a prior year. The authors also assume that the direction of any influence is from an older sibling to a younger sibling. They estimate a joint dynamic model of the behavior of older and younger siblings that allows for family effects, individual specific heterogeneity, and past choices. Their results suggest that smoking, drinking, and marijuana use are influenced by the example of older siblings, although much of the link between siblings reflects association rather than causation. Running away from home. One of the more unusual topics explored at the recent conference addressed the issue of adolescents running away from home.8 In his paper, Michael Pergamit of the Urban Institute explains what the published literature reveals about runaways. He states that nearly all the available information regarding this phenomenon comes from samples of youths in homeless shelters, in crisis centers, or living on the street; these data sources, unfortunately, do not permit analysts to compare youths who have run away with those who have not. For example, one cannot investigate the prevalence of running away using data of that nature, nor can one track how runaways and youths who have never run away differ in their developmental pathways prior to or after running away. Moreover, the information about the family and schooling experiences prior to running away are, in the shelter samples, necessarily collected after the running away episode and may thereby be tainted or shaded by the experience itself. The NLSY97 annually asked the youths if they had ever run away from home. The survey used the definition supplied by the Department of Justice, that running away is “staying away at least one night without parents’ prior knowledge or permission.” Each year, as long as the youth was residing with parents and was under age 18, he or she was asked about incidents of running away occurring since the previous interview; consequently, this study captures a sample of runaways that reflects the whole set of children who ran away, not just those who ended up in shelters or crisis centers. In some cases, the data also include key information about the youth from years prior to episodes of running away. The paper exploits these features of the NLSY97 data, focusing primarily on children who were age 12 or 13 in the first year of the study. The prevalence of running away is itself one of the most interesting findings in this paper, which estimates that of the roughly 20 million U.S. youths born between 1980 and 1984, some 17.8 percent had run away by the age of 18. The rate is higher for females—19.8 percent—than for males—15.8 percent. It is also slightly higher for Hispanic youths than for Whites or African Americans: 19.4 percent of Hispanics and 17.4 percent of both Whites and African Americans had run away by age 18. Of all children who had run away, about half had done so only once, but approximately 10 percent had done so seven or more times; of the youths who reported incidents of running away, the average number of these incidents was 3.3. About one-third of children who ran away had done so before age 14. In a statistical model that identified which adolescents had run away from home while controlling for several attributes, it is interesting that the sex of the adolescents was not a factor. As if to illustrate the challenge of summarizing findings from complex studies, however, the paper notes that boys who did run away did so less often than girls but that boys did so at a younger age than girls. African Americans and Hispanics were both less likely to run away than were Whites after statistical controls were introduced. Similarly, having siblings had no apparent effect on running away. Children with higher scores on the AFQT were less likely to run away, while, as one might expect, youths who had a poor relationship with parents, who scored high on measures of behavioral problems, or who had mental health problems were significantly more likely to run away. Urban youths were much more likely to run away than youths in rural settings. The study also finds that “the more things the family does together the lower is the probability of running away.” The author notes that it will be important to track the effects of running away on the life trajectories of these young men and women as they age through their 20s and beyond. This is surely one of the key benefits of a data set like the NLSY97 that identifies behaviors and events early in life and can then reveal whether that behavior is associated with later life events, and, if so, to what extent. THE FINDINGS BRIEFLY SUMMARIZED IN THIS ARTICLE represent about half the research papers delivered at the Tenth Anniversary Conference in May 2008. In turn, the papers presented at the conference reflect only a small portion of the new facts and relationships discovered so far by researchers working with the NLSY97 data sets. Assuming the survey respondents continue to be willing to accept the request for an hour-long interview each year, as their lives unfold over the next decade or so, researchers’ understanding of the U.S. labor market and the behavior of the cohort born between 1980 and 1984 will continue to grow. The ever-improving understanding of the forces shaping labor market experiences should help policymakers, and the deeper understanding of the consequences of private decisions should be of value to families everywhere. Notes ACKNOWLEDGMENT: The authors thank Rupa Datta and Donna Rothstein for contributions to this summary paper. dence from a Liberal Arts College with a Full Tuition Subsidy Program,” Journal of Human Resources, Summer 2003, pp. 591–617. The NLSY97 Tenth Anniversary Conference, held in 2008 at the Bureau of Labor Statistics in Washington, DC, May 29–30, was supported by grants from the Spencer Foundation, the NORC Population Research Center, and the Harris School’s Center for Human Potential and Public Policy. Robert Kaestner and Michael Grossman, “Effects of Weight on Adolescent Educational Attainment.” Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008. 1 Philippe Belley, Marc Frenette, and Lance Lochner, “Post-Secondary Attendance by Parental Income: A Canada-U.S. Comparison.” Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008. 2 Phillipe Belley and Lance Lochner, “The Changing Role of Family Income and Ability in Determining Educational Achievement,” Journal of Human Capital, Winter 2007, pp. 37–90. 3 Ralph Stinebrickner and Todd R. Stinebrickner, “Understanding Educational Outcomes of Students from Low-Income Families: Evi4 5 Kristin Moore and Kassim Mbwana, “Preventing Risky Sex and Adolescent Parenthood: Does the Effectiveness of Parenting Practices Differ For Children with Varied Risks?” Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008. 6 7 Joseph G. Altonji, Sarah Cattan and Iain Ware, “Sibling Influences on Teenage Risky Behaviors.” Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008. Michael R. Pergamit, “Who Runs Away from Home? An Exploratory Analysis.” Paper presented at the NLSY97 Tenth Anniversary Conference, Washington, DC, May 2008. 8 Monthly Labor Review • September 2008 51 Regional Trends Multiple Jobholding in States in 2007 Jim Campbell I n 2007, 26 States and the District of Columbia experienced decreases in their multiple jobholding rates from 2006, 20 States recorded increases, and 4 States had no change.1 The national multiple jobholding rate was unchanged in 2007, at 5.2 percent. The largest over-the-year rate decreases among the States were Jim Campbell is an economist in the Division of Local Area Unemployment Statistics, Bureau of Labor Statistics. E-mail: Campbell.Jim@bls.gov posted in Idaho (–1.8 percentage points), Alaska (–1.6 points), and Wyoming (–1.3 points). Kansas experienced the largest increase among the States (+1.4 percentage points), followed by Kentucky (+0.8 point) and West Virginia (+0.7 point). Although the U.S. multiple jobholding rate was the same as in 2006, it was 1.0 percentage point lower than in 1996, when it peaked at 6.2 percent.2 Compared with 1996, 44 States and the District of Columbia had lower multiple jobholding rates in 2007, and only 6 States had higher rates. The largest declines over this period occurred in Idaho (–3.0 per- centage points), Indiana and Missouri (–2.8 points each), and Arkansas (–2.6 points). Over the 1996–2007 period, only one State had an increase in its multiple jobholding rate that was greater than 0.4 percentage point: Vermont (+0.8 point). The multiple jobholding rates for individual States varied considerably from the U.S. average. (See chart 1.) Overall, 28 States had higher multiple jobholding rates than the national average, 20 States and the District of Columbia had lower rates, and 2 States had the same rate. Northern States generally had higher rates than southern States. Table 1. Multiple jobholders as a percentage of total employment by State, 2006 and 2007 annual averages State/area 2006 United States.............................................. 5.2 Alabama....................................................... 4.5 Alaska............................................................ 2007 State/area 2006 2007 5.2 Missouri.............................................. 6.7 6.2 4.7 Montana............................................. 8.1 8.0 9.0 7.4 Nebraska............................................ 9.9 9.7 Arizona.......................................................... 4.7 4.5 Nevada................................................ 4.0 3.8 Arkansas....................................................... 5.4 4.5 New Hampshire............................... 7.3 6.9 California...................................................... 4.2 4.4 New Jersey......................................... 4.9 4.6 Colorado....................................................... 5.8 6.0 New Mexico....................................... 5.3 5.0 Connecticut................................................. 5.9 6.3 New York............................................ 4.5 4.2 Delaware...................................................... 4.4 4.4 North Carolina.................................. 5.3 5.3 District of Columbia................................. 5.4 4.6 North Dakota.................................... 8.4 8.7 Florida........................................................... 3.9 3.9 Ohio..................................................... 6.4 6.3 Georgia......................................................... 3.5 4.1 Oklahoma.......................................... 4.7 4.4 Hawaii............................................................ 8.0 8.2 Oregon................................................ 6.3 5.7 52 Idaho.............................................................. 8.3 6.5 Pennsylvania..................................... 5.5 5.3 Illinois............................................................ 4.9 5.2 Rhode Island..................................... 6.9 6.6 Indiana.......................................................... 4.3 4.7 South Carolina.................................. 4.5 4.9 Iowa................................................................ 8.9 8.8 South Dakota.................................... 9.9 10.2 Kansas........................................................... 7.5 8.9 Tennessee.......................................... 5.1 4.5 Kentucky....................................................... 5.6 6.4 Texas.................................................... 4.3 4.5 Louisiana...................................................... 4.5 4.4 Utah..................................................... 7.5 6.9 Maine............................................................. 8.2 8.1 Vermont.............................................. 9.3 9.4 Maryland...................................................... 5.5 5.9 Virginia................................................ 4.9 4.8 Massachusetts............................................ 5.6 5.2 Washington....................................... 5.7 5.9 Michigan...................................................... 5.6 5.7 West Virginia..................................... 3.5 4.2 Minnesota.................................................... 8.7 8.7 Wisconsin........................................... 7.7 7.5 Mississippi.................................................... 4.1 4.7 Wyoming............................................ 9.3 8.0 Monthly Labor Review • September 2008 Chart 1. Multiple jobholding rates by State, 2007 annual averages (U.S. rate = 5.2 percent) Mountain West North Central East North Central New England Middle Atlantic # # # # # D.C. Pacific South Atlantic East South Central West South Central 7.6 percent or more 5.6 to 7.5 percent 4.6 to 5.5 percent 4.5 percent or below SOURCE: Current Population Survey. All seven States in the West North Central division continued to register multiple jobholding rates above that of the Nation. The northern States in the Mountain and New England divisions also continued to have relatively high rates. South Dakota recorded the highest rate, 10.2 percent, followed by Nebraska and Vermont, at 9.7 and 9.4 percent, respectively. Many of the upper Plains States with high multiple jobholding rates also have high shares of agricultural and part-time employment. In addition, multiple jobholding seems generally to be highest in States that have low average commuting times.3 Most of the States with high multiple jobholding rates in 2007 have had consistently high rates over the 1996–2007 period. Thirteen of the 16 States in the South region, as well as the District of Columbia, had multiple jobholding rates below the U.S. figure.4 Among the 9 States with rates below 4.5 percent, 6 were in the South. Nevada recorded the lowest multiple jobholding rate in 2007, 3.8 percent, followed by Florida, at 3.9 percent, and Georgia, at 4.1 percent. Notes 1 Data on multiple jobholders are from the Current Population Survey (CPS), a survey of about 60,000 households selected to represent the U.S. civilian noninstitutional population aged 16 years and older. The CPS is conducted monthly by the U.S. Census Bureau for the Bureau of Labor Statistics. Multiple jobholders are those who report in the reference week that they are wage or salary workers who hold two or more jobs, self-employed workers who also hold a wage or salary job, or unpaid family workers who also hold a wage or salary job. 2 Annual multiple jobholding data for States became available following the redesign of the Current Population Survey in 1994. 3 Average commute times are from the 2000 Census of Population and Housing. 4 The South region is composed of the East South Central, South Atlantic, and West South Central divisions. Monthly Labor Review • September 2008 53 Précis Procrastination: an economic analysis Most people are quite familiar with procrastination—a tendency that affects the way they complete (or do not complete) projects in the workplace, in school, at home, and elsewhere. A conventional explanation for procrastination is that people act rationally, choosing to postpone tasks because they find it difficult to muster the self-discipline to begin them earlier. In “An Economic Model of the Planning Fallacy” (NBER Working Paper Series, National Bureau of Economic Research, August 2008), Markus K. Brunnermeier, Filippos Papakonstantinou, and Jonathan A. Parker use advanced mathematics, along with data from experiments, to argue in favor of an alternative theory. They contend that the only cause of procrastination is people’s tendency to underestimate the amount of time needed to complete a project. Various studies—in both laboratory and nonlaboratory settings—have demonstrated that when given an unpleasant task, the average person takes much longer to complete it than he or she predicted before beginning the task. The paper’s authors call the faulty reasoning behind this behavior “the planning fallacy.” Because of the planning fallacy, people often spend a disproportionately large amount of time working on projects close to the deadline. The authors explain that people do this because the utility derived from the felicitous belief that a project will be easy to complete outweighs the cost of not properly “smoothing” work over time. The researchers believe that, subconsciously, people actually do realize about how long most projects take; yet, when faced with a new project, they still consciously believe that the project will take less time. 54 Monthly Labor Review • September 2008 When people are asked to complete a simple, non-onerous task in an experiment, they actually tend to complete the task slightly more quickly than they predicted beforehand. However, when people are paid on the basis of how quickly they complete either a non-onerous or a burdensome task, they tend to underestimate the amount of time necessary to finish it. By contrast, financial incentives for accurate prediction can eliminate the planning fallacy. Brunnermeier, Papakonstantinou, and Parker argue that the results of the aforementioned experiments bolster their view that procrastination is based on the planning fallacy. The greater the anticipatory benefit to believing that the project will take little time, the stronger is the tendency to underestimate the amount of time necessary to complete it. Nevertheless, most people are aware of their penchant for postponing work; consequently, they often set intermediate deadlines in an effort to mitigate their procrastination. U.S. economy as a very large business. This fictional business employs all of the workers in the U.S. economy, owns all of the capital, and returns all of its profits to its “shareholders,” the U.S. public. Campbell presents tools for evaluating the contributions of particular product lines to U.S. economic growth and the effect they have on the business cycle. He extends his analysis by using the same tools to measure a large firm’s exposure to macroeconomic risks. Campbell employs two macroeconomic concepts to assess the contributions to overall economic growth made by particular sectors, as well as the sustainability of that growth: the fundamental national product accounting identity, which divides the total value of goods and services produced by the economy into discrete expenditure components, and the contributions to growth formula, which equates the rate of GDP growth with the sum of the individual component growth rates multiplied by their share of expenditures in the previous quarter. When he applies these concepts to the U.S. economy, Campbell finds Business cycle analysis that macroeconomic risks are largely Policymakers and business managers the result of periodic fluctuations alike must regularly face the chal- in nonresidential fixed investment, lenge presented by the recurrent cy- which accounts for a substantial clical fluctuations in the U.S. econo- portion of overall economic activmy. Understanding the business cycle ity. (Nonresidential fixed investis crucial to both: policymakers must ment consists of purchases by firms make decisions about monetary and of nonresidential structures, equipfiscal policy in an effort to smooth ment, and software.) Expenditures out the cycles, while profit-maximiz- on nondurable goods and services, ing managers must make informed which represent a very large portion decisions about their individual firms of national income, fluctuate little during the various stages of the busi- from quarter to quarter and thus ness cycle. In “How the U.S. economy contribute only marginally to macresembles a (very) big business” (Eco- roeconomic risks. nomic Perspectives, Federal Reserve Campbell suggests that his methBank of Chicago, third quarter 2008), odology might be used by others to senior Bank economist Jeffrey R. set macroeconomic benchmarks and Campbell analyzes the fluctuations in “start a conversation about a business’s U.S. economic growth by treating the place in the larger economy.” Book Reviews Employment and America’s future A Future of Good Jobs? America’s Challenge in the Global Economy. By Timothy J. Bartik and Susan N. Houseman, Kalamazoo, MI, Upjohn Institute for Employment Research, 2008, 327 pp., $20.00/paperback; $40.00/cloth. The papers in this volume were prepared by editors Timothy J. Bartik and Susan N. Houseman for a conference held in June 2007, in honor of the 75th anniversary of the W.E. Upjohn Unemployment Trustee Corporation. In the 15 months between the conference and the writing of this review, the state of the U.S. economy has worsened. Although the need to address the labor market and related problems identified in this excellent collection of papers is even greater now than when they were written, macroeconomic conditions make it more difficult to do so. It is as if able diagnosticians supplied the prognosis for a patient with several interacting chronic conditions, only to have the patient come down with the flu. The suggested treatment plan may have to be postponed or modified until the temporary ailment is over. Chapter 1 provides a clear synthesis of the topics discussed by the authors of the remaining six chapters: Robert J. Lerman on education and training; Katherine Swartz on health care financing; Lori G. Kletzer on trade and immigration; Katharine G. Abraham and Susan N. Houseman on labor market issues for older workers; Paul Osterman on demand-side policies aiding lowerskill workers; and Steven Raphael on problems and policies relating to disadvantaged workers in general and former convicts in particular. The analysis and policy proposals focus on problems facing workers in the lower 4/5 of the income distribution. The net impact of economic change in recent decades is manifested in growing income inequality, but the way in which inequality has grown has intensified the problem. Over the quarter century from 1980 to the mid-2000s, real wages have declined for the bottom 10th percentile of the wage distribution, and increased by less than 20 percent for the group between the 10th and 80th percentiles. Presumably coincidentally, the chapters divide into two groups by authors’ gender. The three by the male authors concentrate on problems faced by workers with lower levels of skill and education, whereas those written by the female authors are about issues that affect most of the population and workforce. This is not to imply that the former group is dealing with less important problems; rather, that those issues with broader impact may receive greater policy attention and political support than those affecting a smaller segment of the population. Nearly 20 years ago, Gary Burtless edited a collection of papers on the plight of the unskilled, especially unskilled men, titled A Future of Lousy Jobs? (See Burtless, Gary, ed. A Future of Lousy Jobs? The Changing Structure of U.S. Wages, The Brookings Institution, Washington, DC 1990.) According to Burtless: “If the demand for unskilled labor has dropped, the obvious policy response is to improve the qualifications of less skilled workers to match the developing requirements of the job market. If the [N]ation has too many unskilled workers, rather than too many bad jobs, both efficiency and equity will be served by improving the skills of workers now lodged at the bottom.” In addition to the play on that title, the current book’s most direct link with the earlier work is in the chapters by Lerman, Osterman and Raphael. The “Lousy Jobs” analysis attributed the declining economic fortunes of less skilled men to their excess supply, combined with greater demand for more skilled workers, when firms and industries changed the skill mix of their labor inputs to meet the needs of the new technologies. There are simply not enough jobs for the less skilled, and, according to Burtless, the remedy is to upgrade the education and training of those at the bottom of the economic ladder. The three authors just mentioned are generally in accord with this diagnosis for the less skilled worker in the contemporary labor market. Rapid technological change and increased globalization, plus the declining impact of institutional protections such as unions, make the outlook for less-skilled workers even bleaker today than it was in the early 1990s. Lerman’s prescription includes developing educational approaches that raise and better reward noncognitive and occupational skills that are in short supply. This will require changes in emphasis within the educational sector, favoring work-based learning, which means a need for further investment by employers in the skills of workers. Osterman also calls for enhanced programs to encourage job upgrading in skills and pay; he sees the need as well for workers to have restored institutional safeguards, Monthly Labor Review • September 2008 55 Book Reviews such as increased minimum wages and acceptance of unions, which will complement the incentives provided to employers to promote upgrading. Raphael recommends helping lowwage workers directly by expanding the Earned Income Tax Credit (EITC) to bring in childless adults, especially low-income married couples. He also points to the often neglected subsector of the low-wage, low-skill population and the growing number of individuals with prison records, and advocates specific policies to reduce the barriers they face to obtaining productive, legal jobs. Katherine Swartz is concerned with reforming how the United States finances health insurance in the face of declining percentages of workers (and retirees) presently covered by employer-based plans. The three principles of her proposed strategy are: 1. Everyone should be enrolled in a health insurance plan for which they pay some minimum amount; 2. Additional premiums paid by individuals and families should be in proportion to their income; and 3. Contributions (taxes) should be collected from employers. Swartz argues that such a comprehensive cost-sharing plan should not be more expensive than the present system of spotty coverage that emphasizes cost-shifting and contains 56 Monthly Labor Review • September 2008 perverse incentives for both workers and employers. The remaining two chapters focus on the problems facing workers who are dislocated or need to find new jobs for other reasons. Two of the initiating factors analyzed by Lori Kletzer are increasing trade and immigration. Jobs may disappear due to import competition or outsourcing, while increased inflows of foreign-born workers augment the labor supply at both the low skill and high skill ends of the labor market. The consensus among economists is that, although there is a net social gain from trade and immigration, those who experience losses are concentrated among the less skilled native-born population, worsening their income and employment prospects. Kletzer notes, however, that the largest and most comprehensive adjustment assistance program (Unemployment Insurance or UI), needs to be changed to reflect the new economic realities. Other programs are neither large enough nor appropriately targeted to offset the gaps in the present UI system. Katharine G. Abraham and Susan N. Houseman address a problem that is caused by a major social success; more of us are living longer, healthier lives. The challenge is how to maintain living standards during these “golden years.” One response to this need to make savings and income last longer is for older workers to stay in, or return to, the labor market for more years than they perhaps had hoped. Less certain pension and health care coverage from employers, and changes to Social Security and Medicare, both favor a trend by Americans to work more hours and retire later. However, this pressure runs up against the existence of impediments to older worker employment, on both the supply and demand sides. Funding for employment and training programs targeted on older workers is substantially below levels of a decade ago in real terms, without taking into account the increased universe of eligibility. Program implementation can be sharpened to better meet the needs of older workers but issues such as health insurance, which may act as a disincentive to employers for hiring older workers, also have to be addressed in a broader context. As these authors individually and collectively realize, there is no onesize-fits-all solution to lowering the barriers to good jobs faced by people in various situations. The policy proposals they suggest range from incremental changes in program performance standards to a comprehensive reworking of our health care financing system. But they do all have the common goal of working toward a more equitable society, for which the authors should be applauded. —Stephen E. Baldwin Economist Bethesda, MD Current Labor Statistics Monthly Labor Review September 2008 NOTE: Many of the statistics in the following pages were subsequently revised. These pages have not been updated to reflect the revisions. To obtain BLS data that reflect all revisions, see http://www.bls.gov/data/home.htm For the latest set of "Current Labor Statistics," see http://www.bls.gov/opub/mlr/curlabst.htm Current Labor Statistics Notes on current labor statistics . .............. 58 Comparative indicators 1. Labor market indicators..................................................... 70 2. Annual and quarterly percent changes in compensation, prices, and productivity........................... 71 3. Alternative measures of wages and compensation changes.................................................... 71 Labor force data 4. Employment status of the population, seasonally adjusted......................................................... 5. Selected employment indicators, seasonally adjusted......... 6. Selected unemployment indicators, seasonally adjusted..... 7. Duration of unemployment, seasonally adjusted................ 8. Unemployed persons by reason for unemployment, seasonally adjusted......................................................... 9. Unemployment rates by sex and age, seasonally adjusted ......................................................... 10. Unemployment rates by State, seasonally adjusted............. 11. Employment of workers by State, seasonally adjusted.......................................................... 12. Employment of workers by industry, seasonally adjusted.......................................................... 13. Average weekly hours by industry, seasonally adjusted....... 14. Average hourly earnings by industry, seasonally adjusted.......................................................... 15. Average hourly earnings by industry.................................. 16. Average weekly earnings by industry................................. 17. Diffusion indexes of employment change, seasonally adjusted ...................................................... 18. Job openings levels and rates, by industry and regions, seasonally adjusted........................................................ 19. Hires levels and rates by industry and region, seasonally adjusted........................................................ 20. Separations levels and rates by industry and region, seasonally adjusted......................................................... 21. Quits levels and rates by industry and region, seasonally adjusted........................................................ 72 73 74 74 Labor compensation and collective bargaining data 30. 31. 32. 33. Employment Cost Index, compensation .......................... 99 Employment Cost Index, wages and salaries .................... 101 Employment Cost Index, benefits, private industry .......... 103 Employment Cost Index, private industry workers, by bargaining status, and region..................................... 104 34. National Compensation Survey, retirement benefits, private industry ............................................................. 105 35. National Compensation Survey, health insurance, private industry............................................................... 108 36. National Compensation Survey, selected benefits, private industry.............................................................. 110 37. Work stoppages involving 1,000 workers or more............. 110 Price data 81 82 83 38. Consumer Price Index: U.S. city average, by expenditure category and commodity and service groups.................. 111 39. Consumer Price Index: U.S. city average and local data, all items ........................................................ 114 40. Annual data: Consumer Price Index, all items and major groups........................................................... 115 41. Producer Price Indexes by stage of processing................... 116 42. Producer Price Indexes for the net output of major industry groups.............................................................. 117 43. Annual data: Producer Price Indexes by stage of processing..................................................... 118 44. U.S. export price indexes by end-use category................... 118 45. U.S. import price indexes by end-use category................... 119 46. U.S. international price indexes for selected categories of services...................................................... 119 84 Productivity data 85 47. Indexes of productivity, hourly compensation, and unit costs, data seasonally adjusted.......................... 120 48. Annual indexes of multifactor productivity........................ 121 49. Annual indexes of productivity, hourly compensation, unit costs, and prices...................................................... 122 50. Annual indexes of output per hour for select industries..... 123 75 75 76 76 77 80 85 86 86 22. Quarterly Census of Employment and Wages, 10 largest counties . ....................................................... 87 23. Quarterly Census of Employment and Wages, by State... 89 24. Annual data: Quarterly Census of Employment and Wages, by ownership............................................... 90 25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, by supersector....... 91 26. Annual data: Quarterly Census of Employment and Wages, by metropolitan area ......................................... 92 27. Annual data: Employment status of the population.......... 97 28. Annual data: Employment levels by industry ................. 97 29. Annual data: Average hours and earnings level, by industry..................................................................... 98 International comparisons data 51. Unemployment rates in 10 countries, seasonally adjusted......................................................... 127 52. Annual data: Employment status of the civilian working-age population, 10 countries........................... 128 53. Annual indexes of productivity and related measures, 16 economies................................................................ 129 Injury and Illness data 54. Annual data: Occupational injury and illness..................... 131 55. Fatal occupational injuries by event or exposure ................ 133 Monthly Labor Review • September 2008 57 Notes on Current Labor Statistics Current Labor Statistics This section of the Review presents the principal statistical series collected and calculated by the Bureau of Labor Statistics: series on labor force; employment; unemployment; labor compensation; consumer, producer, and international prices; productivity; international comparisons; and injury and illness statistics. In the notes that follow, the data in each group of tables are briefly described; key definitions are given; notes on the data are set forth; and sources of additional information are cited. General notes The following notes apply to several tables in this section: Seasonal adjustment. Certain monthly and quarterly data are adjusted to eliminate the effect on the data of such factors as climatic conditions, industry production schedules, opening and closing of schools, holiday buying periods, and vacation practices, which might prevent short-term evaluation of the statistical series. Tables containing data that have been adjusted are identified as “seasonally adjusted.” (All other data are not seasonally adjusted.) Seasonal effects are estimated on the basis of current and past experiences. When new seasonal factors are computed each year, revisions may affect seasonally adjusted data for several preceding years. Seasonally adjusted data appear in tables 1–14, 17–21, 48, and 52. Seasonally adjusted labor force data in tables 1 and 4–9 and seasonally adjusted establishment survey data shown in tables 1, 12–14, and 17 are revised in the March 2007 Review. A brief explanation of the seasonal adjustment methodology appears in “Notes on the data.” Revisions in the productivity data in table 54 are usually introduced in the September issue. Seasonally adjusted indexes and percent changes from month-to-month and quarter-to-quarter are published for numerous Consumer and Producer Price Index series. However, seasonally adjusted indexes are not published for the U.S. average AllItems CPI. Only seasonally adjusted percent changes are available for this series. Adjustments for price changes. Some data—such as the “real” earnings shown in table 14—are adjusted to eliminate the effect of changes in price. These adjustments are made by dividing current-dollar values by the Consumer Price Index or the appropriate component of the index, then multiplying by 100. For example, given a current hourly wage rate of $3 and a current price index number of 150, where 1982 = 100, the hourly rate expressed in 1982 dollars is $2 ($3/150 x 100 = $2). The $2 (or any other resulting 58 Monthly Labor Review • September 2008 values) are described as “real,” “constant,” or “1982” dollars. Sources of information Data that supplement the tables in this section are published by the Bureau in a variety of sources. Definitions of each series and notes on the data are contained in later sections of these Notes describing each set of data. For detailed descriptions of each data series, see BLS Handbook of Methods, Bulletin 2490. Users also may wish to consult Major Programs of the Bureau of Labor Statistics, Report 919. News releases provide the latest statistical information published by the Bureau; the major recurring releases are published according to the schedule appearing on the back cover of this issue. More information about labor force, employment, and unemployment data and the household and establishment surveys underlying the data are available in the Bureau’s monthly publication, Employment and Earnings. Historical unadjusted and seasonally adjusted data from the household survey are available on the Internet: www.bls.gov/cps/ Historically comparable unadjusted and seasonally adjusted data from the establishment survey also are available on the Internet: www.bls.gov/ces/ Additional information on labor force data for areas below the national level are provided in the BLS annual report, Geographic Profile of Employment and Unemployment. For a comprehensive discussion of the Employment Cost Index, see Employment Cost Indexes and Levels, 1975–95, BLS Bulletin 2466. The most recent data from the Employee Benefits Survey appear in the following Bureau of Labor Statistics bulletins: Employee Benefits in Medium and Large Firms; Employee Benefits in Small Private Establishments; and Employee Benefits in State and Local Governments. More detailed data on consumer and producer prices are published in the monthly periodicals, The CPI Detailed Report and Producer Price Indexes. For an overview of the 1998 revision of the CPI, see the December 1996 issue of the Monthly Labor Review. Additional data on international prices appear in monthly news releases. Listings of industries for which productivity indexes are available may be found on the Internet: www.bls.gov/lpc/ For additional information on international comparisons data, see Interna- tional Comparisons of Unemployment, Bulletin 1979. Detailed data on the occupational injury and illness series are published in Occupational Injuries and Illnesses in the United States, by Industry, a BLS annual bulletin. Finally, the Monthly Labor Review carries analytical articles on annual and longer term developments in labor force, employment, and unemployment; employee compensation and collective bargaining; prices; productivity; international comparisons; and injury and illness data. Symbols n.e.c. = n.e.s. = p = r = not elsewhere classified. not elsewhere specified. preliminary. To increase the timeliness of some series, preliminary figures are issued based on representative but incomplete returns. revised. Generally, this revision reflects the availability of later data, but also may reflect other adjustments. Comparative Indicators (Tables 1–3) Comparative indicators tables provide an overview and comparison of major bls statistical series. Consequently, although many of the included series are available monthly, all measures in these comparative tables are presented quarterly and annually. Labor market indicators include employment measures from two major surveys and information on rates of change in compensation provided by the Employment Cost Index (ECI) program. The labor force participation rate, the employment-population ratio, and unemployment rates for major demographic groups based on the Current Population (“household”) Survey are presented, while measures of employment and average weekly hours by major industry sector are given using nonfarm payroll data. The Employment Cost Index (compensation), by major sector and by bargaining status, is chosen from a variety of BLS compensation and wage measures because it provides a comprehensive measure of employer costs for hiring labor, not just outlays for wages, and it is not affected by employment shifts among occupations and industries. Data on changes in compensation, prices, and productivity are presented in table 2. Measures of rates of change of compensation and wages from the Employment Cost Index program are provided for all civilian nonfarm workers (excluding Federal and household workers) and for all private nonfarm workers. Measures of changes in consumer prices for all urban consumers; producer prices by stage of processing; overall prices by stage of processing; and overall export and import price indexes are given. Measures of productivity (output per hour of all persons) are provided for major sectors. Alternative measures of wage and compensation rates of change, which reflect the overall trend in labor costs, are summarized in table 3. Differences in concepts and scope, related to the specific purposes of the series, contribute to the variation in changes among the individual measures. Employment and Unemployment Data 4 weeks. Persons who did not look for work because they were on layoff are also counted among the unemployed. The unemployment rate represents the number unemployed as a percent of the civilian labor force. The civilian labor force consists of all employed or unemployed persons in the civilian noninstitutional population. Persons not in the labor force are those not classified as employed or unemployed. This group includes discouraged workers, defined as persons who want and are available for a job and who have looked for work sometime in the past 12 months (or since the end of their last job if they held one within the past 12 months), but are not currently looking, because they believe there are no jobs available or there are none for which they would qualify. The civilian noninstitutional population comprises all persons 16 years of age and older who are not inmates of penal or mental institutions, sanitariums, or homes for the aged, infirm, or needy. The civilian labor force participation rate is the proportion of the civilian noninstitutional population that is in the labor force. The employment-population ratio is employment as a percent of the civilian noninstitutional population. (Tables 1; 4–29) Notes on the data Household survey data From time to time, and especially after a decennial census, adjustments are made in the Current Population Survey figures to correct for estimating errors during the intercensal years. These adjustments affect the comparability of historical data. A description of these adjustments and their effect on the various data series appears in the Explanatory Notes of Employment and Earnings. For a discussion of changes introduced in January 2003, see “Revisions to the Current Population Survey Effective in January 2003” in the February 2003 issue of Employment and Earnings (available on the BLS Web site at www.bls.gov/cps/rvcps03.pdf). Effective in January 2003, BLS began using the X-12 ARIMA seasonal adjustment program to seasonally adjust national labor force data. This program replaced the X-11 ARIMA program which had been used since January 1980. See “Revision of Seasonally Adjusted Labor Force Series in 2003,” in the February 2003 issue of Employment and Earnings (available on the BLS Web site at www.bls.gov/cps/cpsrs.pdf) for a discussion of the introduction of the use of X-12 ARIMA for seasonal adjustment of the labor force data and the effects that it had on the data. At the beginning of each calendar year, historical seasonally adjusted data usually are revised, and projected seasonal adjustment factors are calculated for use during the Notes on the data Definitions of each series and notes on the data are contained in later sections of these notes describing each set of data. Description of the series Employment data in this section are obtained from the Current Population Survey, a program of personal interviews conducted monthly by the Bureau of the Census for the Bureau of Labor Statistics. The sample consists of about 60,000 households selected to represent the U.S. population 16 years of age and older. Households are interviewed on a rotating basis, so that three-fourths of the sample is the same for any 2 consecutive months. Definitions Employed persons include (1) all those who worked for pay any time during the week which includes the 12th day of the month or who worked unpaid for 15 hours or more in a family-operated enterprise and (2) those who were temporarily absent from their regular jobs because of illness, vacation, industrial dispute, or similar reasons. A person working at more than one job is counted only in the job at which he or she worked the greatest number of hours. Unemployed persons are those who did not work during the survey week, but were available for work except for temporary illness and had looked for jobs within the preceding January–June period. The historical seasonally adjusted data usually are revised for only the most recent 5 years. In July, new seasonal adjustment factors, which incorporate the experience through June, are produced for the July–December period, but no revisions are made in the historical data. F OR ADDITIONAL INFORMATION on national household survey data, contact the Division of Labor Force Statistics: (202) 691–6378. Establishment survey data Description of the series Employment, hours, and earnings data in this section are compiled from payroll records reported monthly on a voluntary basis to the Bureau of Labor Statistics and its cooperating State agencies by about 160,000 businesses and government agencies, which represent approximately 400,000 individual worksites and represent all industries except agriculture. The active CES sample covers approximately one-third of all nonfarm payroll workers. Industries are classified in accordance with the 2002 North American Industry Classification System. In most industries, the sampling probabilities are based on the size of the establishment; most large establishments are therefore in the sample. (An establishment is not necessarily a firm; it may be a branch plant, for example, or warehouse.) Self-employed persons and others not on a regular civilian payroll are outside the scope of the survey because they are excluded from establishment records. This largely accounts for the difference in employment figures between the household and establishment surveys. Definitions An establishment is an economic unit which produces goods or services (such as a factory or store) at a single location and is engaged in one type of economic activity. Employed persons are all persons who received pay (including holiday and sick pay) for any part of the payroll period including the 12th day of the month. Persons holding more than one job (about 5 percent of all persons in the labor force) are counted in each establishment which reports them. Production workers in the goods-producing industries cover employees, up through the level of working supervisors, who engage directly in the manufacture or construction of the establishment’s product. In private service-providing industries, data are collected for nonsupervisory workers, which include most employees except those in executive, Monthly Labor Review • September 2008 59 Current Labor Statistics managerial, and supervisory positions. Those workers mentioned in tables 11–16 include production workers in manufacturing and natural resources and mining; construction workers in construction; and nonsupervisory workers in all private service-providing industries. Production and nonsupervisory workers account for about four-fifths of the total employment on private nonagricultural payrolls. Earnings are the payments production or nonsupervisory workers receive during the survey period, including premium pay for overtime or late-shift work but excluding irregular bonuses and other special payments. Real earnings are earnings adjusted to reflect the effects of changes in consumer prices. The deflator for this series is derived from the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Hours represent the average weekly hours of production or nonsupervisory workers for which pay was received, and are different from standard or scheduled hours. Overtime hours represent the portion of average weekly hours which was in excess of regular hours and for which overtime premiums were paid. The Diffusion Index represents the percent of industries in which employment was rising over the indicated period, plus one-half of the industries with unchanged employment; 50 percent indicates an equal balance between industries with increasing and decreasing employment. In line with Bureau practice, data for the 1-, 3-, and 6month spans are seasonally adjusted, while those for the 12-month span are unadjusted. Table 17 provides an index on private nonfarm employment based on 278 industries, and a manufacturing index based on 84 industries. These indexes are useful for measuring the dispersion of economic gains or losses and are also economic indicators. Notes on the data Establishment survey data are annually adjusted to comprehensive counts of employment (called “benchmarks”). The March 2003 benchmark was introduced in February 2004 with the release of data for January 2004, published in the March 2004 issue of the Review. With the release in June 2003, CES completed a conversion from the Standard Industrial Classification (SIC) system to the North American Industry Classification System (naics) and completed the transition from its original quota sample design to a probability-based sample design. The industry-coding update included reconstruction of historical estimates in order to preserve 60 Monthly Labor Review • September 2008 time series for data users. Normally 5 years of seasonally adjusted data are revised with each benchmark revision. However, with this release, the entire new time series history for all CES data series were re-seasonally adjusted due to the NAICS conversion, which resulted in the revision of all CES time series. Also in June 2003, the CES program introduced concurrent seasonal adjustment for the national establishment data. Under this methodology, the first preliminary estimates for the current reference month and the revised estimates for the 2 prior months will be updated with concurrent factors with each new release of data. Concurrent seasonal adjustment incorporates all available data, including first preliminary estimates for the most current month, in the adjustment process. For additional information on all of the changes introduced in June 2003, see the June 2003 issue of Employment and Earnings and “Recent changes in the national Current Employment Statistics survey,” Monthly Labor Review, June 2003, pp. 3–13. Revisions in State data (table 11) occurred with the publication of January 2003 data. For information on the revisions for the State data, see the March and May 2003 issues of Employment and Earnings, and “Recent changes in the State and Metropolitan Area CES survey,” Monthly Labor Review, June 2003, pp. 14–19. Beginning in June 1996, the BLS uses the X-12-ARIMA methodology to seasonally adjust establishment survey data. This procedure, developed by the Bureau of the Census, controls for the effect of varying survey intervals (also known as the 4- versus 5-week effect), thereby providing improved measurement of over-the-month changes and underlying economic trends. Revisions of data, usually for the most recent 5-year period, are made once a year coincident with the benchmark revisions. In the establishment survey, estimates for the most recent 2 months are based on incomplete returns and are published as preliminary in the tables (12–17 in the Review). When all returns have been received, the estimates are revised and published as “final” (prior to any benchmark revisions) in the third month of their appearance. Thus, December data are published as preliminary in January and February and as final in March. For the same reasons, quarterly establishment data (table 1) are preliminary for the first 2 months of publication and final in the third month. Fourth-quarter data are published as preliminary in January and February and as final in March. F OR ADDITIONAL INFORMATION on establishment survey data, contact the Division of Current Employment Statistics: (202) 691–6555. Unemployment data by State Description of the series Data presented in this section are obtained from the Local Area Unemployment Statistics (LAUS) program, which is conducted in cooperation with State employment security agencies. Monthly estimates of the labor force, employment, and unemployment for States and sub-State areas are a key indicator of local economic conditions, and form the basis for determining the eligibility of an area for benefits under Federal economic assistance programs such as the Job Training Partnership Act. Seasonally adjusted unemployment rates are presented in table 10. Insofar as possible, the concepts and definitions underlying these data are those used in the national estimates obtained from the CPS. Notes on the data Data refer to State of residence. Monthly data for all States and the District of Columbia are derived using standardized procedures established by BLS. Once a year, estimates are revised to new population controls, usually with publication of January estimates, and benchmarked to annual average CPS levels. FOR ADDITIONAL INFORMATION on data in this series, call (202) 691–6392 (table 10) or (202) 691–6559 (table 11). Quarterly Census of Employment and Wages Description of the series Employment, wage, and establishment data in this section are derived from the quarterly tax reports submitted to State employment security agencies by private and State and local government employers subject to State unemployment insurance (ui) laws and from Federal, agencies subject to the Unemployment Compensation for Federal Employees (ucfe) program. Each quarter, State agencies edit and process the data and send the information to the Bureau of Labor Statistics. The Quarterly Census of Employment and Wages (QCEW) data, also referred as ES202 data, are the most complete enumeration of employment and wage information by industry at the national, State, metropolitan area, and county levels. They have broad economic significance in evaluating labor market trends and major industry developments. Definitions In general, the Quarterly Census of Employment and Wages monthly employment data represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered private industry employment includes most corporate officials, executives, supervisory personnel, professionals, clerical workers, wage earners, piece workers, and part-time workers. It excludes proprietors, the unincorporated self-employed, unpaid family members, and certain farm and domestic workers. Certain types of nonprofit employers, such as religious organizations, are given a choice of coverage or exclusion in a number of States. Workers in these organizations are, therefore, reported to a limited degree. Persons on paid sick leave, paid holiday, paid vacation, and the like, are included. Persons on the payroll of more than one firm during the period are counted by each ui-subject employer if they meet the employment definition noted earlier. The employment count excludes workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness, or unpaid vacations. Federal employment data are based on reports of monthly employment and quarterly wages submitted each quarter to State agencies for all Federal installations with employees covered by the Unemployment Compensation for Federal Employees (ucfe) program, except for certain national security agencies, which are omitted for security reasons. Employment for all Federal agencies for any given month is based on the number of persons who worked during or received pay for the pay period that included the 12th of the month. An establishment is an economic unit, such as a farm, mine, factory, or store, that produces goods or provides services. It is typically at a single physical location and engaged in one, or predominantly one, type of economic activity for which a single industrial classification may be applied. Occasionally, a single physical location encompasses two or more distinct and significant activities. Each activity should be reported as a separate establishment if separate records are kept and the various activities are classified under different NAICS industries. Most employers have only one establishment; thus, the establishment is the predominant reporting unit or statistical entity for reporting employment and wages data. Most employers, including State and local governments who operate more than one establishment in a State, file a Multiple Worksite Report each quarter, in addition to their quarterly ui report. The Multiple Worksite Report is used to collect separate employment and wage data for each of the employer’s establishments, which are not detailed on the ui report. Some very small multi-establishment employers do not file a Multiple Worksite Report. When the total employment in an employer’s secondary establishments (all establishments other than the largest) is 10 or fewer, the employer generally will file a consolidated report for all establishments. Also, some employers either cannot or will not report at the establishment level and thus aggregate establishments into one consolidated unit, or possibly several units, though not at the establishment level. For the Federal Government, the reporting unit is the installation: a single location at which a department, agency, or other government body has civilian employees. Federal agencies follow slightly different criteria than do private employers when breaking down their reports by installation. They are permitted to combine as a single statewide unit: 1) all installations with 10 or fewer workers, and 2) all installations that have a combined total in the State of fewer than 50 workers. Also, when there are fewer than 25 workers in all secondary installations in a State, the secondary installations may be combined and reported with the major installation. Last, if a Federal agency has fewer than five employees in a State, the agency headquarters office (regional office, district office) serving each State may consolidate the employment and wages data for that State with the data reported to the State in which the headquarters is located. As a result of these reporting rules, the number of reporting units is always larger than the number of employers (or government agencies) but smaller than the number of actual establishments (or installations). Data reported for the first quarter are tabulated into size categories ranging from worksites of very small size to those with 1,000 employees or more. The size category is determined by the establishment’s March employment level. It is important to note that each establishment of a multi-establishment firm is tabulated separately into the appropriate size category. The total employment level of the reporting multi-establishment firm is not used in the size tabulation. Covered employers in most States report total wages paid during the calendar quarter, regardless of when the services were performed. A few State laws, however, specify that wages be reported for, or based on the period during which services are performed rather than the period during which compensation is paid. Under most State laws or regulations, wages include bonuses, stock options, the cash value of meals and lodging, tips and other gratuities, and, in some States, employer contributions to certain deferred compensation plans such as 401(k) plans. Covered employer contributions for old-age, survivors, and disability insurance (oasdi), health insurance, unemployment insurance, workers’ compensation, and private pension and welfare funds are not reported as wages. Employee contributions for the same purposes, however, as well as money withheld for income taxes, union dues, and so forth, are reported even though they are deducted from the worker’s gross pay. Wages of covered Federal workers represent the gross amount of all payrolls for all pay periods ending within the quarter. This includes cash allowances, the cash equivalent of any type of remuneration, severance pay, withholding taxes, and retirement deductions. Federal employee remuneration generally covers the same types of services as for workers in private industry. Average annual wage per employee for any given industry are computed by dividing total annual wages by annual average employment. A further division by 52 yields average weekly wages per employee. Annual pay data only approximate annual earnings because an individual may not be employed by the same employer all year or may work for more than one employer at a time. Average weekly or annual wage is affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations. When average pay levels between States and industries are compared, these factors should be taken into consideration. For example, industries characterized by high proportions of part-time workers will show average wage levels appreciably less than the weekly pay levels of regular full-time employees in these industries. The opposite effect characterizes industries with low proportions of part-time workers, or industries that typically schedule heavy weekend and overtime work. Average wage data also may be influenced by work stoppages, labor turnover rates, retroactive payments, seasonal factors, bonus payments, and so on. Notes on the data Beginning with the release of data for 2001, publications presenting data from the Covered Employment and Wages program have switched to the 2002 version of the North Monthly Labor Review • September 2008 61 Current Labor Statistics American Industry Classification System (NAICS) as the basis for the assignment and tabulation of economic data by industry. NAICS is the product of a cooperative effort on the part of the statistical agencies of the United States, Canada, and Mexico. Due to difference in NAICS and Standard Industrial Classification ( SIC) structures, industry data for 2001 is not comparable to the SIC-based data for earlier years. Effective January 2001, the program began assigning Indian Tribal Councils and related establishments to local government ownership. This BLS action was in response to a change in Federal law dealing with the way Indian Tribes are treated under the Federal Unemployment Tax Act. This law requires federally recognized Indian Tribes to be treated similarly to State and local governments. In the past, the Covered Employment and Wage (CEW) program coded Indian Tribal Councils and related establishments in the private sector. As a result of the new law, CEW data reflects significant shifts in employment and wages between the private sector and local government from 2000 to 2001. Data also reflect industry changes. Those accounts previously assigned to civic and social organizations were assigned to tribal governments. There were no required industry changes for related establishments owned by these Tribal Councils. These tribal business establishments continued to be coded according to the economic activity of that entity. To insure the highest possible quality of data, State employment security agencies verify with employers and update, if necessary, the industry, location, and ownership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from the verification process are introduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. For these reasons, some data, especially at more detailed geographic levels, may not be strictly comparable with earlier years. County definitions are assigned according to Federal Information Processing Standards Publications as issued by the National Institute of Standards and Technology. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those areas designated by the Census Bureau where counties have not been created. County data also are presented for the New England States for comparative purposes, even though townships are the more common designation used in New England (and New Jersey). The Office of Management and Budget 62 Monthly Labor Review • September 2008 (OMB) defines metropolitan areas for use in Federal statistical activities and updates these definitions as needed. Data in this table use metropolitan area criteria established by OMB in definitions issued June 30, 1999 (OMB Bulletin No. 99-04). These definitions reflect information obtained from the 1990 Decennial Census and the 1998 U.S. Census Bureau population estimate. A complete list of metropolitan area definitions is available from the National Technical Information Service (NTIS), Document Sales, 5205 Port Royal Road, Springfield, Va. 22161, telephone 1-800-553-6847. OMB defines metropolitan areas in terms of entire counties, except in the six New England States where they are defined in terms of cities and towns. New England data in this table, however, are based on a county concept defined by OMB as New England County Metropolitan Areas (NECMA) because county-level data are the most detailed available from the Quarterly Census of Employment and Wages. The NECMA is a county-based alternative to the city- and town-based metropolitan areas in New England. The NECMA for a Metropolitan Statistical Area (MSA) include: (1) the county containing the first-named city in that MSA title (this county may include the first-named cities of other MSA, and (2) each additional county having at least half its population in the MSA in which first-named cities are in the county identified in step 1. The NECMA is officially defined areas that are meant to be used by statistical programs that cannot use the regular metropolitan area definitions in New England. For additional information on the covered employment and wage data, contact the Division of Administrative Statistics and Labor Turnover at (202) 691–6567. Job Openings and Labor Turnover Survey Description of the series Data for the Job Openings and Labor Turnover Survey (JOLTS) are collected and compiled from a sample of 16,000 business establishments. Each month, data are collected for total employment, job openings, hires, quits, layoffs and discharges, and other separations. The JOLTS program covers all private nonfarm establishments such as factories, offices, and stores, as well as Federal, State, and local government entities in the 50 States and the District of Columbia. The JOLTS sample design is a random sample drawn from a universe of more than eight million establishments compiled as part of the operations of the Quarterly Census of Employment and Wages, or QCEW, program. This program includes all employers subject to State unemployment insurance (UI) laws and Federal agencies subject to Unemployment Compensation for Federal Employees (UCFE). The sampling frame is stratified by ownership, region, industry sector, and size class. Large firms fall into the sample with virtual certainty. JOLTS total employment estimates are controlled to the employment estimates of the Current Employment Statistics (CES) survey. A ratio of CES to JOLTS employment is used to adjust the levels for all other JOLTS data elements. Rates then are computed from the adjusted levels. The monthly JOLTS data series begin with December 2000. Not seasonally adjusted data on job openings, hires, total separations, quits, layoffs and discharges, and other separations levels and rates are available for the total nonfarm sector, 16 private industry divisions and 2 government divisions based on the North American Industry Classification System (NAICS), and four geographic regions. Seasonally adjusted data on job openings, hires, total separations, and quits levels and rates are available for the total nonfarm sector, selected industry sectors, and four geographic regions. Definitions Establishments submit job openings infor-mation for the last business day of the reference month. A job opening requires that (1) a specific position exists and there is work available for that position; and (2) work could start within 30 days regardless of whether a suitable candidate is found; and (3) the employer is actively recruiting from outside the establishment to fill the position. Included are full-time, part-time, permanent, short-term, and seasonal openings. Active recruiting means that the establishment is taking steps to fill a position by advertising in newspapers or on the Internet, posting help-wanted signs, accepting applications, or using other similar methods. Jobs to be filled only by internal transfers, promotions, demotions, or recall from layoffs are excluded. Also excluded are jobs with start dates more than 30 days in the future, jobs for which employees have been hired but have not yet reported for work, and jobs to be filled by employees of temporary help agencies, employee leasing companies, outside contractors, or consultants. The job openings rate is computed by dividing the number of job openings by the sum of employment and job openings, and multiplying that quotient by 100. Hires are the total number of additions to the payroll occurring at any time during the reference month, including both new and rehired employees and full-time and parttime, permanent, short-term and seasonal employees, employees recalled to the location after a layoff lasting more than 7 days, on-call or intermittent employees who returned to work after having been formally separated, and transfers from other locations. The hires count does not include transfers or promotions within the reporting site, employees returning from strike, employees of temporary help agencies or employee leasing companies, outside contractors, or consultants. The hires rate is computed by dividing the number of hires by employment, and multiplying that quotient by 100. Separations are the total number of terminations of employment occurring at any time during the reference month, and are reported by type of separation—quits, layoffs and discharges, and other separations. Quits are voluntary separations by employees (except for retirements, which are reported as other separations). Layoffs and discharges are involuntary separations initiated by the employer and include layoffs with no intent to rehire, formal layoffs lasting or expected to last more than 7 days, discharges resulting from mergers, downsizing, or closings, firings or other discharges for cause, terminations of permanent or short-term employees, and terminations of seasonal employees. Other separations include retirements, transfers to other locations, deaths, and separations due to disability. Separations do not include transfers within the same location or employees on strike. The separations rate is computed by dividing the number of separations by employment, and multiplying that quotient by 100. The quits, layoffs and discharges, and other separations rates are computed similarly, dividing the number by employment and multiplying by 100. Notes on the data The JOLTS data series on job openings, hires, and separations are relatively new. The full sample is divided into panels, with one panel enrolled each month. A full complement of panels for the original data series based on the 1987 Standard Industrial Classification (SIC) system was not completely enrolled in the survey until January 2002. The supple-mental panels of establishments needed to create NAICS estimates were not completely enrolled until May 2003. The data collected up until those points are from less than a full sample. Therefore, estimates from earlier months should be used with caution, as fewer sampled units were reporting data at that time. In March 2002, BLS procedures for collecting hires and separations data were revised to address possible underreporting. As a result, JOLTS hires and separations estimates for months prior to March 2002 may not be comparable with estimates for March 2002 and later. The Federal Government reorganization that involved transferring approximately 180,000 employees to the new Department of Homeland Security is not reflected in the JOLTS hires and separations estimates for the Federal Government. The Office of Personnel Management’s record shows these transfers were completed in March 2003. The inclusion of transfers in the JOLTS definitions of hires and separations is intended to cover ongoing movements of workers between establishments. The Department of Homeland Security reorganization was a massive one-time event, and the inclusion of these intergovernmental transfers would distort the Federal Government time series. Data users should note that seasonal adjustment of the JOLTS series is conducted with fewer data observations than is customary. The historical data, therefore, may be subject to larger than normal revisions. Because the seasonal patterns in economic data series typically emerge over time, the standard use of moving averages as seasonal filters to capture these effects requires longer series than are currently available. As a result, the stable seasonal filter option is used in the seasonal adjustment of the JOLTS data. When calculating seasonal factors, this filter takes an average for each calendar month after detrending the series. The stable seasonal filter assumes that the seasonal factors are fixed; a necessary assumption until sufficient data are available. When the stable seasonal filter is no longer needed, other program features also may be introduced, such as outlier adjustment and extended diagnostic testing. Additionally, it is expected that more series, such as layoffs and discharges and additional industries, may be seasonally adjusted when more data are available. JOLTS hires and separations estimates cannot be used to exactly explain net changes in payroll employment. Some reasons why it is problematic to compare changes in payroll employment with JOLTS hires and separations, especially on a monthly basis, are: (1) the reference period for payroll employment is the pay period including the 12th of the month, while the reference period for hires and separations is the calendar month; and (2) payroll employment can vary from month to month simply because part-time and oncall workers may not always work during the pay period that includes the 12th of the month. Additionally, research has found that some reporters systematically underreport separations relative to hires due to a number of factors, including the nature of their payroll systems and practices. The shortfall appears to be about 2 percent or less over a 12-month period. F OR ADDITIONAL INFORMATION on the Job Openings and Labor Turnover Survey, contact the Division of Administrative Statistics and Labor Turnover at (202) 961–5870. Compensation and Wage Data (Tables 1–3; 30–37) The National Compensation Survey (NCS) produces a variety of compensation data. These include: The Employment Cost Index (ECI) and NCS benefit measures of the incidence and provisions of selected employee benefit plans. Selected samples of these measures appear in the following tables. NCS also compiles data on occupational wages and the Employer Costs for Employee Compensation (ECEC). Employment Cost Index Description of the series The Employment Cost Index (ECI) is a quarterly measure of the rate of change in compensation per hour worked and includes wages, salaries, and employer costs of employee benefits. It is a Laspeyres Index that uses fixed employment weights to measure change in labor costs free from the influence of employment shifts among occupations and industries. The ECI provides data for the civilian economy, which includes the total private nonfarm economy excluding private households, and the public sector excluding the Federal government. Data are collected each quarter for the pay period including the 12th day of March, June, September, and December. Sample establishments are classified by industry categories based on the 2002 North American Classification System (NAICS). Within a sample establishment, specific job categories are selected and classified into about 800 occupations according to the 2000 Standard Occupational Classification (SOC) System. Individual occupations are comMonthly Labor Review • September 2008 63 Current Labor Statistics bined to represent one of ten intermediate aggregations, such as professional and related occupations, or one of five higher level aggregations, such as management, professional, and related occupations. Fixed employment weights are used each quarter to calculate the most aggregate series—civilian, private, and State and local government. These fixed weights are also used to derive all of the industry and occupational series indexes. Beginning with the March 2006 estimates, 2002 fixed employment weights from the Bureau’s Occupational Employment Statistics survey were introduced. From March 1995 to December 2005, 1990 employment counts were used. These fixed weights ensure that changes in these indexes reflect only changes in compensation, not employment shifts among industries or occupations with different levels of wages and compensation. For the series based on bargaining status, census region and division, and metropolitan area status, fixed employment data are not available. The employment weights are reallocated within these series each quarter based on the current eci sample. The indexes for these series, consequently, are not strictly comparable with those for aggregate, occupational, and industry series. Definitions Total compensation costs include wages, salaries, and the employer’s costs for employee benefits. Wages and salaries consist of earnings before payroll deductions, including production bonuses, incentive earnings, commissions, and cost-of-living adjustments. Benefits include the cost to employers for paid leave, supplemental pay (including nonproduction bonuses), insurance, retirement and savings plans, and legally required benefits (such as Social Security, workers’ compensation, and unemployment insurance). Excluded from wages and salaries and employee benefits are such items as paymentin-kind, free room and board, and tips. Notes on the data The ECI data in these tables reflect the con-version to the 2002 North American Industry Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. ECI series based on NAICS and SOC became the official BLS estimates starting in March 2006. The ECI for changes in wages and salaries 64 Monthly Labor Review • September 2008 in the private nonfarm economy was published beginning in 1975. Changes in total compensation cost—wages and salaries and benefits combined—were published beginning in 1980. The series of changes in wages and salaries and for total compensation in the State and local government sector and in the civilian nonfarm economy (excluding Federal employees) were published beginning in 1981. Historical indexes (December 2005=100) are available on the Internet: www.bls.gov/ect/ A DDITIONAL INFORMATION on the Employment Cost Index is available at www. bls.gov/ncs/ect/home.htm or by telephone at (202) 691–6199. National Compensation Survey Benefit Measures Description of the series benefit measures of employee benefits are published in two separate reports. The annual summary provides data on the incidence of (access to and participation in) selected benefits and provisions of paid holidays and vacations, life insurance plans, and other selected benefit programs. Data on percentages of establishments offering major employee benefits, and on the employer and employee shares of contributions to medical care premiums also are presented. Selected benefit data appear in the following tables. A second publication, published later, contains more detailed information about health and retirement plans. NCS Definitions Employer-provided benefits are benefits that are financed either wholly or partly by the employer. They may be sponsored by a union or other third party, as long as there is some employer financing. However, some benefits that are fully paid for by the employee also are included. For example, long-term care insurance paid entirely by the employee are included because the guarantee of insurability and availability at group premium rates are considered a benefit. Employees are considered as having access to a benefit plan if it is available for their use. For example, if an employee is permitted to participate in a medical care plan offered by the employer, but the employee declines to do so, he or she is placed in the category with those having access to medical care. Employees in contributory plans are considered as participating in an insurance or retirement plan if they have paid required contributions and fulfilled any applicable service requirement. Employees in noncontributory plans are counted as participating regardless of whether they have fulfilled the service requirements. Defined benefit pension plans use predetermined formulas to calculate a retirement benefit (if any), and obligate the employer to provide those benefits. Benefits are generally based on salary, years of service, or both. Defined contribution plans generally specify the level of employer and employee contributions to a plan, but not the formula for determining eventual benefits. Instead, individual accounts are set up for participants, and benefits are based on amounts credited to these accounts. Tax-deferred savings plans are a type of defined contribution plan that allow participants to contribute a portion of their salary to an employer-sponsored plan and defer income taxes until withdrawal. Flexible benefit plans allow employees to choose among several benefits, such as life insurance, medical care, and vacation days, and among several levels of coverage within a given benefit. Notes on the data ADDITIONAL INFORMATION ON THE NCS benefit measures is available at www.bls. gov/ncs/ebs/home.htm or by telephone at (202) 691–6199. Work stoppages Description of the series Data on work stoppages measure the number and duration of major strikes or lockouts (involving 1,000 workers or more) occurring during the month (or year), the number of workers involved, and the amount of work time lost because of stoppage. These data are presented in table 37. Data are largely from a variety of published sources and cover only establishments directly involved in a stoppage. They do not measure the indirect or secondary effect of stoppages on other establishments whose employees are idle owing to material shortages or lack of service. Definitions Number of stoppages: The number of strikes and lockouts involving 1,000 workers or more and lasting a full shift or longer. Workers involved: The number of workers directly involved in the stoppage. Number of days idle: The aggregate number of workdays lost by workers involved in the stoppages. Days of idleness as a percent of estimated working time: Aggregate workdays lost as a percent of the aggregate number of standard workdays in the period multiplied by total employment in the period. Notes on the data This series is not comparable with the one terminated in 1981 that covered strikes involving six workers or more. A DDITIONAL INFORMATION on work stop-pages data is available at www. bls. gov/cba/home.htm or by telephone at (202) 691–6199. Price Data (Tables 2; 38–46) Price data are gathered by the Bureau of Labor Statistics from retail and primary markets in the United States. Price indexes are given in relation to a base period—December 2003 = 100 for many Producer Price Indexes (unless otherwise noted), 1982–84 = 100 for many Consumer Price Indexes (unless otherwise noted), and 1990 = 100 for International Price Indexes. Consumer Price Indexes Description of the series The Consumer Price Index (CPI) is a measure of the average change in the prices paid by urban consumers for a fixed market basket of goods and services. The CPI is calculated monthly for two population groups, one consisting only of urban households whose primary source of income is derived from the employment of wage earners and clerical workers, and the other consisting of all urban households. The wage earner index (CPI-W) is a continuation of the historic index that was introduced well over a half-century ago for use in wage negotiations. As new uses were developed for the CPI in recent years, the need for a broader and more representative index became apparent. The all-urban consumer index (CPI-U), introduced in 1978, is representative of the 1993–95 buying habits of about 87 percent of the noninstitutional population of the United States at that time, compared with 32 percent represented in the CPI-W. In addition to wage earners and clerical workers, the CPI-U covers professional, managerial, and technical workers, the self-employed, shortterm workers, the unemployed, retirees, and others not in the labor force. The CPI is based on prices of food, clothing, shelter, fuel, drugs, transportation fares, doctors’ and dentists’ fees, and other goods and services that people buy for day-to-day living. The quantity and quality of these items are kept essentially unchanged between major revisions so that only price changes will be measured. All taxes directly associated with the purchase and use of items are included in the index. Data collected from more than 23,000 retail establishments and 5,800 housing units in 87 urban areas across the country are used to develop the “U.S. city average.” Separate estimates for 14 major urban centers are presented in table 39.The areas listed are as indicated in footnote 1 to the table. The area indexes measure only the average change in prices for each area since the base period, and do not indicate differences in the level of prices among cities. Notes on the data In January 1983, the Bureau changed the way in which homeownership costs are meaured for the CPI-U. A rental equivalence method replaced the asset-price approach to homeownership costs for that series. In January 1985, the same change was made in the CPI-W. The central purpose of the change was to separate shelter costs from the investment component of homeownership so that the index would reflect only the cost of shelter services provided by owner-occupied homes. An updated CPI-U and CPI-W were introduced with release of the January 1987 and January 1998 data. FOR ADDITIONAL INFORMATION, contact the Division of Prices and Price Indexes: (202) 691–7000. Producer Price Indexes Description of the series Producer Price Indexes (PPI) measure average changes in prices received by domestic producers of commodities in all stages of processing. The sample used for calculating these indexes currently contains about 3,200 commodities and about 80,000 quotations per month, selected to represent the movement of prices of all commodities produced in the manufacturing; agriculture, forestry, and fishing; mining; and gas and electricity and public utilities sectors. The stage-of-processing structure of PPI organizes products by class of buyer and degree of fabrication (that is, finished goods, intermediate goods, and crude materials). The traditional commodity structure of PPI organizes products by similarity of end use or material composition. The industry and product structure of PPI organizes data in accordance with the 2002 North American Industry Classification System and product codes developed by the U.S. Census Bureau. To the extent possible, prices used in calculating Producer Price Indexes apply to the first significant commercial transaction in the United States from the production or central marketing point. Price data are generally collected monthly, primarily by mail questionnaire. Most prices are obtained directly from producing companies on a voluntary and confidential basis. Prices generally are reported for the Tuesday of the week containing the 13th day of the month. Since January 1992, price changes for the various commodities have been averaged together with implicit quantity weights representing their importance in the total net selling value of all commodities as of 1987. The detailed data are aggregated to obtain indexes for stage-of-processing groupings, commodity groupings, durability-of-product groupings, and a number of special composite groups. All Producer Price Index data are subject to revision 4 months after original publication. FOR ADDITIONAL INFORMATION, contact the Division of Industrial Prices and Price Indexes: (202) 691–7705. International Price Indexes Description of the series The International Price Program produces monthly and quarterly export and import price indexes for nonmilitary goods and services traded between the United States and the rest of the world. The export price index provides a measure of price change for all products sold by U.S. residents to foreign buyers. (“Residents” is defined as in the national income accounts; it includes corporations, businesses, and individuals, but does not require the organizations to be U.S. owned nor the individuals to have U.S. citizenship.) The import price index provides a measure of price change for goods purchased from other countries by U.S. residents. The product universe for both the import and export indexes includes raw materials, agricultural products, semifinished manufactures, and finished manufactures, including both capital and consumer goods. Price data for these items are collected primarily by mail questionnaire. In nearly all cases, the data are collected directly from the exporter or importer, although in a few cases, prices are obtained from other sources. To the extent possible, the data gathered refer to prices at the U.S. border for exports and at either the foreign border or the U.S. Monthly Labor Review • September 2008 65 Current Labor Statistics border for imports. For nearly all products, the prices refer to transactions completed during the first week of the month. Survey respondents are asked to indicate all discounts, allowances, and rebates applicable to the reported prices, so that the price used in the calculation of the indexes is the actual price for which the product was bought or sold. In addition to general indexes of prices for U.S. exports and imports, indexes are also published for detailed product categories of exports and imports. These categories are defined according to the five-digit level of detail for the Bureau of Economic Analysis End-use Classification, the three-digit level for the Standard International Trade Classification (SITC), and the four-digit level of detail for the Harmonized System. Aggregate import indexes by country or region of origin are also available. BLS publishes indexes for selected categories of internationally traded services, calculated on an international basis and on a balance-of-payments basis. Notes on the data The export and import price indexes are weighted indexes of the Laspeyres type. The trade weights currently used to compute both indexes relate to 2000. Because a price index depends on the same items being priced from period to period, it is necessary to recognize when a product’s specifications or terms of transaction have been modified. For this reason, the Bureau’s questionnaire requests detailed descriptions of the physical and functional characteristics of the products being priced, as well as information on the number of units bought or sold, discounts, credit terms, packaging, class of buyer or seller, and so forth. When there are changes in either the specifications or terms of transaction of a product, the dollar value of each change is deleted from the total price change to obtain the “pure” change. Once this value is determined, a linking procedure is employed which allows for the continued repricing of the item. FOR ADDITIONAL INFORMATION, contact the Division of International Prices: (202) 691–7155. Productivity Data (Tables 2; 47–50) Business and major sectors Description of the series The productivity measures relate real output to real input. As such, they encompass a fam66 Monthly Labor Review • September 2008 ily of measures which include single-factor input measures, such as output per hour, output per unit of labor input, or output per unit of capital input, as well as measures of multifactor productivity (output per unit of combined labor and capital inputs). The Bureau indexes show the change in output relative to changes in the various inputs. The measures cover the business, nonfarm business, manufacturing, and nonfinancial corporate sectors. Corresponding indexes of hourly compensation, unit labor costs, unit nonlabor payments, and prices are also provided. Definitions Output per hour of all persons (labor productivity) is the quantity of goods and services produced per hour of labor input. Output per unit of capital services (capital productivity) is the quantity of goods and services produced per unit of capital services input. Multifactor productivity is the quantity of goods and services produced per combined inputs. For private business and private nonfarm business, inputs include labor and capital units. For manufacturing, inputs include labor, capital, energy, nonenergy materials, and purchased business services. Compensation per hour is total compensation divided by hours at work. Total compensation equals the wages and salaries of employees plus employers’ contributions for social insurance and private benefit plans, plus an estimate of these payments for the self-employed (except for nonfinancial corporations in which there are no self-employed). Real compensation per hour is compensation per hour deflated by the change in the Consumer Price Index for All Urban Consumers. Unit labor costs are the labor compensation costs expended in the production of a unit of output and are derived by dividing compensation by output. Unit nonlabor payments include profits, depreciation, interest, and indirect taxes per unit of output. They are computed by subtracting compensation of all persons from current-dollar value of output and dividing by output. Unit nonlabor costs contain all the components of unit nonlabor payments except unit profits. Unit profits include corporate profits with inventory valuation and capital consumption adjustments per unit of output. Hours of all persons are the total hours at work of payroll workers, self-employed persons, and unpaid family workers. Labor inputs are hours of all persons adjusted for the effects of changes in the education and experience of the labor force. Capital services are the flow of services from the capital stock used in production. It is developed from measures of the net stock of physical assets—equipment, structures, land, and inventories—weighted by rental prices for each type of asset. Combined units of labor and capital inputs are derived by combining changes in labor and capital input with weights which represent each component’s share of total cost. Combined units of labor, capital, energy, materials, and purchased business services are similarly derived by combining changes in each input with weights that represent each input’s share of total costs. The indexes for each input and for combined units are based on changing weights which are averages of the shares in the current and preceding year (the Tornquist index-number formula). Notes on the data Business sector output is an annually-weighted index constructed by excluding from real gross domestic product (GDP) the following outputs: general government, nonprofit institutions, paid employees of private households, and the rental value of owner-occupied dwellings. Nonfarm business also excludes farming. Private business and private nonfarm business further exclude government enterprises. The measures are supplied by the U.S. Department of Commerce’s Bureau of Economic Analysis. Annual estimates of manufacturing sectoral output are produced by the Bureau of Labor Statistics. Quarterly manufacturing output indexes from the Federal Reserve Board are adjusted to these annual output measures by the BLS. Compensation data are developed from data of the Bureau of Economic Analysis and the Bureau of Labor Statistics. Hours data are developed from data of the Bureau of Labor Statistics. The productivity and associated cost measures in tables 47–50 describe the relationship between output in real terms and the labor and capital inputs involved in its production. They show the changes from period to period in the amount of goods and services produced per unit of input. Although these measures relate output to hours and capital services, they do not measure the contributions of labor, capital, or any other specific factor of production. Rather, they reflect the joint effect of many influences, including changes in technology; shifts in the composition of the labor force; capital investment; level of output; changes in the utilization of capacity, energy, material, and research and development; the organi- zation of production; managerial skill; and characteristics and efforts of the work force. FOR ADDITIONAL INFORMATION on this productivity series, contact the Division of Productivity Research: (202) 691–5606. Industry productivity measures Description of the series The BLS industry productivity indexes measure the relationship between output and inputs for selected industries and industry groups, and thus reflect trends in industry efficiency over time. Industry measures include labor productivity, multifactor productivity, compensation, and unit labor costs. The industry measures differ in methodology and data sources from the productivity measures for the major sectors because the industry measures are developed independently of the National Income and Product Accounts framework used for the major sector measures. Definitions Output per hour is derived by dividing an index of industry output by an index of labor input. For most industries, output indexes are derived from data on the value of industry output adjusted for price change. For the remaining industries, output indexes are derived from data on the physical quantity of production. The labor input series is based on the hours of all workers or, in the case of some transportation industries, on the number of employees. For most industries, the series consists of the hours of all employees. For some trade and services industries, the series also includes the hours of partners, proprietors, and unpaid family workers. Unit labor costs represent the labor compensation costs per unit of output produced, and are derived by dividing an index of labor compensation by an index of output. Labor compensation includes payroll as well as supplemental payments, including both legally required expenditures and payments for voluntary programs. Multifactor productivity is derived by dividing an index of industry output by an index of combined inputs consumed in producing that output. Combined inputs include capital, labor, and intermediate purchases. The measure of capital input represents the flow of services from the capital stock used in production. It is developed from measures of the net stock of physical assets—equipment, structures, land, and inventories. The measure of intermediate purchases is a combination of purchased materials, services, fuels, and electricity. Notes on the data The industry measures are compiled from data produced by the Bureau of Labor Statistics and the Census Bureau, with additional data supplied by other government agencies, trade associations, and other sources. FOR ADDITIONAL INFORMATION on this series, contact the Division of Industry Productivity Studies: (202) 691–5618, or visit the Web site at: www.bls.gov/lpc/home.htm International Comparisons (Tables 51–53) Labor force and unemployment Description of the series Tables 51 and 52 present comparative measures of the labor force, employment, and unemployment approximating U.S. concepts for the United States, Canada, Australia, Japan, and six European countries. The Bureau adjusts the figures for these selected countries, for all known major definitional differences, to the extent that data to prepare adjustments are available. Although precise comparability may not be achieved, these adjusted figures provide a better basis for international comparisons than the figures regularly published by each country. For further information on adjustments and comparability issues, see Constance Sorrentino, “International unemployment rates: how comparable are they?” Monthly Labor Review, June 2000, pp. 3–20, available on the Internet at www. bls.gov/opub/mlr/2000/06/art1full.pdf. Definitions For the principal U.S. definitions of the labor force, employment, and unemployment, see the Notes section on Employment and Unemployment Data: Household survey data. Notes on the data Foreign country data are adjusted as closely as possible to the U.S. definitions. Primary areas of adjustment address conceptual differences in upper age limits and defini- tions of employment and unemployment, provided that reliable data are available to make these adjustments. Adjustments are made where applicable to include employed and unemployed persons above upper age limits; some European countries do not include persons older than age 64 in their labor force measures, because a large portion of this population has retired. Adjustments are made to exclude active duty military from employment figures, although a small number of career military may be included in some European countries. Adjustments are made to exclude unpaid family workers who worked fewer than 15 hours per week from employment figures; U.S. concepts do not include them in employment, whereas most foreign countries include all unpaid family workers regardless of the number of hours worked. Adjustments are made to include full-time students seeking work and available for work as unemployed when they are classified as not in the labor force. Where possible, lower age limits are based on the age at which compulsory schooling ends in each country, rather than based on the U.S. standard of 16. Lower age limits have ranged between 13 and 16 over the years covered; currently, the lower age limits are either 15 or 16 in all 10 countries. Some adjustments for comparability are not made because data are unavailable for adjustment purposes. For example, no adjustments to unemployment are usually made for deviations from U.S. concepts in the treatment of persons waiting to start a new job or passive jobseekers. These conceptual differences have little impact on the measures. Furthermore, BLS studies have concluded that no adjustments should be made for persons on layoff who are counted as employed in some countries because of their strong job attachment as evidenced by, for example, payment of salary or the existence of a recall date. In the United States, persons on layoff have weaker job attachment and are classified as unemployed. The annual labor force measures are obtained from monthly, quarterly, or continuous household surveys and may be calculated as averages of monthly or quarterly data. Quarterly and monthly unemployment rates are based on household surveys. For some countries, they are calculated by applying annual adjustment factors to current published data and, therefore, are less precise indicators of unemployment under U.S. concepts than the annual figures. The labor force measures may have breaks in series over time due to changes in surveys, sources, or estimation methods. Breaks are noted in data tables. For up-to-date information on adjustments and breaks in series, see the Technical Monthly Labor Review • September 2008 67 Current Labor Statistics Notes of Comparative Civilian Labor Force Statistics, 10 Countries, on the Internet at www.bls.gov/fls/flscomparelf.htm, and the Notes of Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted, on the Internet at www.bls.gov/fls/flsjec.pdf. F OR ADDITIONAL INFORMATION on this series, contact the Division of Foreign Labor Statistics: (202) 691-5654 or flshelp@ bls.gov. Manufacturing productivity and labor costs Description of the series Table 53 presents comparative indexes of manufacturing output per hour (labor productivity), output, total hours, compensation per hour, and unit labor costs for the United States, Australia, Canada, Japan, the Republic of Korea, Taiwan, and 10 European countries. These measures are trend comparisons—that is, series that measure changes over time— rather than level comparisons. BLS does not recommend using these series for level comparisons because of technical problems. BLS constructs the comparative indexes from three basic aggregate measures—output, total labor hours, and total compensation. The hours and compensation measures refer to employees (wage and salary earners) in Belgium and Taiwan. For all other economies, the measures refer to all employed persons, including employees, self-employed persons, and unpaid family workers. The data for recent years are based on the United Nations System of National Accounts 1993 (SNA 93). Manufacturing is generally defined according to the International Standard Industrial Classification (ISIC). However, the measures for France include parts of mining as well. For the United States and Canada, it is defined according to the North American Industry Classification System (NAICS 97). Definitions Output. For most economies, the output measures are real value added in manufacturing from national accounts. However, output for Japan prior to 1970 and for the Netherlands prior to 1960 are indexes of industrial production. The manufacturing value added measures for the United Kingdom are essentially identical to their indexes of industrial production. For United States, the output measure for the manufacturing sector is a chain-weighted 68 Monthly Labor Review • September 2008 index of real gross product originating (deflated value added) produced by the Bureau of Economic Analysis of the U.S. Department of Commerce. Most of the other economies now also use chain-weighted as opposed to a fixed-year weights that are periodically updated. To preserve the comparability of the U.S. measures with those of other economies, BLS uses gross product originating in manufacturing for the United States. The gross product originating series differs from the manufacturing output series that BLS publishes in its quarterly news releases on U.S. productivity and costs (and that underlies the measures that appear in tables 48 and 50 in this section). The quarterly measures are on a “sectoral output” basis, rather than a valueadded basis. Sectoral output is gross output less intrasector transactions. Total hours refer to hours worked in all economies. The measures are developed from statistics of manufacturing employment and average hours. For most other economies, recent years’ aggregate hours series are obtained from national statistical offices, usually from national accounts. However, for some economies and for earlier years, BLS calculates the aggregate hours series using employment figures published with the national accounts, or other comprehensive employment series, and data on average hours worked. Hourly compensation is total compensation divided by total hours. Total compensation includes all payments in cash or in-kind made directly to employees plus employer expenditures for legally required insurance programs and contractual and private benefit plans. For Australia, Canada, France, and Sweden, compensation is increased to account for important taxes on payroll or employment. For the United Kingdom, compensation is reduced between 1967 and 1991 to account for subsidies. Labor productivity is defined as real output per hour worked. Although the labor productivity measure presented in this release relates output to the hours worked of persons employed in manufacturing, it does not measure the specific contributions of labor as a single factor of production. Rather, it reflects the joint effects of many influences, including new technology, capital investment, capacity utilization, energy use, and managerial skills, as well as the skills and efforts of the workforce. Unit labor costs are defined as the cost of labor input required to produce one unit of output. They are computed as compensation in nominal terms divided by real output. Unit labor costs can also be computed by dividing hourly compensation by output per hour, that is, by labor productivity. Notes on the data The measures for recent years may be based on current indicators of manufacturing output (such as industrial production indexes), employment, average hours, and hourly compensation until national accounts and other statistics used for the long-term measures become available. F OR ADDITIONAL INFORMATION on this series, go to http://www.bls.gov/news. release/prod4.toc.htm or contact the Division of Foreign Labor Statistics at (202) 691–5654. Occupational Injury and Illness Data (Tables 54–55) Survey of Occupational Injuries and Illnesses Description of the series The Survey of Occupational Injuries and Illnesses collects data from employers about their workers’ job-related nonfatal injuries and illnesses. The information that employers provide is based on records that they maintain under the Occupational Safety and Health Act of 1970. Self-employed individuals, farms with fewer than 11 employees, employers regulated by other Federal safety and health laws, and Federal, State, and local government agencies are excluded from the survey. The survey is a Federal-State cooperative program with an independent sample selected for each participating State. A stratified random sample with a Neyman allocation is selected to represent all private industries in the State. The survey is stratified by Standard Industrial Classification and size of employment. Definitions Under the Occupational Safety and Health Act, employers maintain records of nonfatal work-related injuries and illnesses that involve one or more of the following: loss of consciousness, restriction of work or motion, transfer to another job, or medical treatment other than first aid. Occupational injury is any injury such as a cut, fracture, sprain, or amputation that results from a work-related event or a single, instantaneous exposure in the work environment. Occupational illness is an abnormal condition or disorder, other than one resulting from an occupational injury, caused by exposure to factors associated with employment. It includes acute and chronic illnesses or disease which may be caused by inhalation, absorption, ingestion, or direct contact. Lost workday injuries and illnesses are cases that involve days away from work, or days of restricted work activity, or both. Lost workdays include the number of workdays (consecutive or not) on which the employee was either away from work or at work in some restricted capacity, or both, because of an occupational injury or illness. BLS measures of the number and incidence rate of lost workdays were discontinued beginning with the 1993 survey. The number of days away from work or days of restricted work activity does not include the day of injury or onset of illness or any days on which the employee would not have worked, such as a Federal holiday, even though able to work. Incidence rates are computed as the number of injuries and/or illnesses or lost work days per 100 full-time workers. Notes on the data The definitions of occupational injuries and illnesses are from Recordkeeping Guidelines for Occupational Injuries and Illnesses (U.S. Department of Labor, Bureau of Labor Statistics, September 1986). Estimates are made for industries and employment size classes for total recordable cases, lost workday cases, days away from work cases, and nonfatal cases without lost workdays. These data also are shown separately for injuries. Illness data are available for seven categories: occupational skin diseases or disorders, dust diseases of the lungs, respiratory conditions due to toxic agents, poisoning (systemic effects of toxic agents), disorders due to physical agents (other than toxic materials), disorders associated with repeated trauma, and all other occupational illnesses. The survey continues to measure the number of new work-related illness cases which are recognized, diagnosed, and reported during the year. Some conditions, for example, long-term latent illnesses caused by exposure to carcinogens, often are difficult to relate to the workplace and are not adequately recognized and reported. These long-term latent illnesses are believed to be understated in the survey’s illness measure. In contrast, the overwhelming majority of the reported new illnesses are those which are easier to directly relate to workplace activity (for example, contact dermatitis and carpal tunnel syndrome). Most of the estimates are in the form of incidence rates, defined as the number of injuries and illnesses per 100 equivalent full-time workers. For this purpose, 200,000 employee hours represent 100 employee years (2,000 hours per employee). Full detail on the available measures is presented in the annual bulletin, Occupational Injuries and Illnesses: Counts, Rates, and Characteristics. Comparable data for more than 40 States and territories are available from the bls Office of Safety, Health and Working Conditions. Many of these States publish data on State and local government employees in addition to private industry data. Mining and railroad data are furnished to BLS by the Mine Safety and Health Administration and the Federal Railroad Administration. Data from these organizations are included in both the national and State data published annually. With the 1992 survey, BLS began publishing details on serious, nonfatal incidents resulting in days away from work. Included are some major characteristics of the injured and ill workers, such as occupation, age, gender, race, and length of service, as well as the circumstances of their injuries and illnesses (nature of the disabling condition, part of body affected, event and exposure, and the source directly producing the condition). In general, these data are available nationwide for detailed industries and for individual States at more aggregated industry levels. FOR ADDITIONAL INFORMATION on occupational injuries and illnesses, contact the Office of Occupational Safety, Health and Working Conditions at (202) 691–6180, or access the Internet at: www.bls. gov/iif/ Census of Fatal Occupational Injuries The Census of Fatal Occupational Injuries compiles a complete roster of fatal job-related injuries, including detailed data about the fatally injured workers and the fatal events. The program collects and cross checks fatality information from multiple sources, including death certificates, State and Federal workers’ compensation reports, Occupational Safety and Health Administration and Mine Safety and Health Administration records, medical examiner and autopsy reports, media accounts, State motor vehicle fatality records, and follow-up questionnaires to employers. In addition to private wage and salary workers, the self-employed, family members, and Federal, State, and local government workers are covered by the program. To be included in the fatality census, the decedent must have been employed (that is working for pay, compensation, or profit) at the time of the event, engaged in a legal work activity, or present at the site of the incident as a requirement of his or her job. Definition A fatal work injury is any intentional or unintentional wound or damage to the body resulting in death from acute exposure to energy, such as heat or electricity, or kinetic energy from a crash, or from the absence of such essentials as heat or oxygen caused by a specific event or incident or series of events within a single workday or shift. Fatalities that occur during a person’s commute to or from work are excluded from the census, as well as work-related illnesses,which can be difficult to identify due to long latency periods. Notes on the data Twenty-eight data elements are collected, coded, and tabulated in the fatality program, including information about the fatally injured worker, the fatal incident, and the machinery or equipment involved. Summary worker demographic data and event characteristics are included in a national news release that is available about 8 months after the end of the reference year. The Census of Fatal Occupational Injuries was initiated in 1992 as a joint Federal-State effort. Most States issue summary information at the time of the national news release. F OR ADDITIONAL INFORMATION on the Census of Fatal Occupational Injuries contact the BLS Office of Safety, Health, and Working Conditions at (202) 691– 6175, or the Internet at: www.bls.gov/iif/ Monthly Labor Review • September 2008 69 Current Labor Statistics: Comparative Indicators 1. Labor market indicators Selected indicators 2006 2006 2007 II III 2007 IV I II 2008 III IV I II Employment data Employment status of the civilian noninstitutional population (household survey): 1 Labor force participation rate........................................................ Employment-population ratio........................................................ Unemployment rate………………………………………………….… Men………………………………………………..…….….………… 16 to 24 years........................................................................... 25 years and older.................................................................... Women……………………………………………….….…………… 16 to 24 years........................................................................... 25 years and older.................................................................... Employment, nonfarm (payroll data), in thousands: 66.2 63.1 4.6 4.6 11.2 3.5 4.6 9.7 3.7 66.0 63.0 4.6 4.7 11.6 3.6 4.5 9.4 3.6 66.2 63.1 4.7 4.7 11.2 3.6 4.6 9.3 3.8 66.2 63.1 4.7 4.6 11.4 3.5 4.7 10.1 3.8 66.3 63.4 4.4 4.5 11.0 3.3 4.4 9.7 3.5 66.2 63.2 4.5 4.6 10.8 3.6 4.4 9.0 3.5 66.0 63.0 4.5 4.6 11.5 3.5 4.4 9.0 3.6 66.0 62.9 4.7 4.8 11.8 3.6 4.6 9.8 3.7 66.0 62.8 4.8 4.9 12.2 3.7 4.7 9.9 3.8 66.0 62.7 4.9 5.0 12.7 3.8 4.8 10.0 3.9 66.1 62.6 5.3 5.5 13.3 4.2 5.1 11.0 4.1 1 Total nonfarm…………………….................................................... 136,086 Total private....................................................................... 114,113 137,626 115,423 135,910 113,996 136,528 114,472 136,982 114,899 137,310 115,167 137,625 115,423 137,837 115,610 138,078 115,759 137,831 115,454 137,640 115,181 22,531 Manufacturing………….………………..………………………… 14,155 22,221 13,883 22,570 14,200 22,564 14,138 22,436 14,033 22,362 13,953 22,267 13,890 22,138 13,822 21,976 13,772 21,737 13,644 21,505 13,537 Service-providing……………………………………………….…………..…113,556 115,405 113,340 113,964 114,546 114,948 115,358 115,699 116,102 116,094 116,135 Goods-producing ……………………………………………….………….. Average hours: Total private........................................………….......................... Manufacturing………...…………………………………………… Overtime……..………….………………...……………………… 33.9 41.1 4.4 33.8 41.2 4.2 33.9 41.2 4.5 33.8 41.3 4.4 33.9 41.1 4.2 33.9 41.2 4.1 33.9 41.4 4.1 33.8 41.4 4.2 33.8 41.1 4.0 33.8 41.2 4.0 33.7 40.8 3.9 Civilian nonfarm ……………………………….…………………………….…… 3.3 3.3 .9 1.1 .6 .9 .8 1.0 .6 .8 .7 Private nonfarm……………...............………............................... 3.2 3.0 .9 .8 .7 .8 .9 .8 .6 .9 .7 2.5 2.4 1.0 .7 .5 .4 1.0 .5 .6 1.0 .7 1, 2, 3 Employment Cost Index Total compensation: 4 5 Goods-producing ……………………………………………….………… 5 Service-providing ……………………………………………….………… State and local government ……………….……………………… Workers by bargaining status (private nonfarm): Union…………………………………………………………………… Nonunion………………………………………………………………… 1 3.4 3.2 .8 .9 .7 .9 .9 .9 .6 .9 .7 4.1 4.1 .4 2.3 .9 1.0 .6 1.8 .7 .5 .5 3.0 3.2 2.0 3.2 1.3 .8 .6 .9 .6 .6 -.3 1.0 1.2 .9 .5 .8 .7 .6 .8 .9 .8 .7 Quarterly data seasonally adjusted. Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter. 3 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 2 70 Monthly Labor Review • September 2008 4 Excludes Federal and private household workers. Goods-producing industries include mining, construction, and manufacturing. Serviceproviding industries include all other private sector industries. 5 NOTE: Beginning in January 2003, household survey data reflect revised population controls. Nonfarm data reflect the conversion to the 2002 version of the North American Industry Classification System (NAICS), replacing the Standard Industrial Classification (SIC) system. NAICS-based data by industry are not comparable with SIC based data. 2. Annual and quarterly percent changes in compensation, prices, and productivity Selected measures 2006 2006 2007 II 2007 III IV I II 2008 III IV I II 1, 2, 3 Compensation data Employment Cost Index—compensation: Civilian nonfarm................................................................... Private nonfarm............................................................... Employment Cost Index—wages and salaries: Civilian nonfarm………………………………………………. Private nonfarm............................................................... Price data 3.3 3.2 3.3 3.0 0.9 .9 1.1 .8 0.6 .7 0.9 .8 0.8 .9 1.0 .8 0.6 .6 0.8 .9 0.7 .7 3.2 3.2 3.4 3.3 .8 1.0 1.1 .8 .6 .7 1.1 1.1 .7 .8 1.0 .9 .7 .6 .8 .9 .7 .7 3.2 2.8 1.6 .0 -.5 1.8 1.5 .1 .7 1.7 2.5 3.0 3.5 1.6 6.5 1.4 3.9 4.5 1.8 4.0 12.2 1.7 2.1 .2 3.0 1.8 -.9 -1.3 .0 -.4 1.2 .1 -.2 1.3 -.8 4.0 2.2 2.8 .3 1.5 5.7 1.9 2.5 -.1 3.2 3.8 .1 .2 -.1 .1 -2.4 1.8 1.9 1.2 2.0 11.9 2.9 3.5 .9 4.8 16.0 4.0 5.2 .4 7.0 14.9 1.0 1.0 1.6 1.6 .8 .8 -1.5 -1.6 1.2 1.8 .2 .7 3.6 2.2 6.4 6.0 .9 1.8 2.2 2.6 2.3 2.2 1.3 - -1.8 3.1 1.3 .7 2.1 2.9 .9 1.0 - 1 Consumer Price Index (All Urban Consumers): All Items...... Producer Price Index: Finished goods..................................................................... Finished consumer goods................................................. Capital equipment…………………………………………… Intermediate materials, supplies, and components………… Crude materials..................................................................... 4 Productivity data Output per hour of all persons: Business sector..................................................................... Nonfarm business sector....................................................... 5 Nonfinancial corporations ……………….…………...……………… 1 Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter. Compensation and price data are not seasonally adjusted, and the price data are not compounded. 2 only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 4 Annual rates of change are computed by comparing annual averages. Quarterly percent changes reflect annual rates of change in quarterly indexes. The data are seasonally adjusted. Excludes Federal and private household workers. 3 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes 5 Output per hour of all employees. 3. Alternative measures of wage and compensation changes Quarterly change Components 2007 II Four quarters ending— 2008 III IV I 2007 II II III 2008 IV I II 1 Average hourly compensation: All persons, business sector.......................................................... All persons, nonfarm business sector........................................... Employment Cost Index—compensation: 3.6 3.3 4.4 5.4 5.0 5.2 3.8 3.6 4.4 4.2 4.8 4.6 3.7 3.6 3.7 3.6 4.2 4.3 .8 .9 1.2 .9 .6 1.0 .8 .5 .8 1.8 .6 .6 .7 .6 .7 .8 .9 .8 .9 .5 .7 .7 .8 .7 .5 3.3 3.1 2.1 3.3 4.8 3.3 3.1 2.0 3.2 4.3 3.3 3.0 2.0 3.2 4.1 3.3 3.2 3.1 3.2 3.6 3.1 3.0 2.7 3.0 3.5 .7 .8 .9 .8 .5 1.0 .9 .7 .9 1.7 .7 .6 .3 .7 .7 .8 .9 .8 .9 .6 .7 .7 1.1 .7 .5 3.4 3.3 2.5 3.4 3.8 3.3 3.4 2.7 3.4 3.5 3.4 3.3 2.3 3.5 3.5 3.2 3.2 2.6 3.3 3.5 3.2 3.1 2.9 3.2 3.4 2 3 Civilian nonfarm ……….………………………………………….…………..… Private nonfarm…....................................................................... Union………….......................................................................... Nonunion………….................................................................... State and local government…..................................................... Employment Cost Index—wages and salaries: 3 1.9 .8 2 Civilian nonfarm ……….………………………………………….…………..… Private nonfarm…....................................................................... Union………….......................................................................... Nonunion………….................................................................... State and local government…..................................................... 1 Seasonally adjusted. "Quarterly average" is percent change from a quarter ago, at an annual rate. 2 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 3 Excludes Federal and private household workers. Monthly Labor Review • September 2008 71 Current Labor Statistics: Labor Force Data 4. Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] Employment status 2007 Annual average 2006 2007 July Aug. Sept. Oct. 2008 Nov. Dec. Jan. Feb. Mar. Apr. May June July TOTAL Civilian noninstitutional 1 population ……………………. 228,815 Civilian labor force.............. 151,428 66.2 Participation rate........... Employed........................ 144,427 Employment-pop63.1 ulation ratio 2…………… 7,001 Unemployed................... 4.6 Unemployment rate..... Not in the labor force........ 77,387 231,867 231,958 232,211 232,461 232,715 232,939 233,156 232,616 232,809 232,995 233,198 233,405 233,627 233,864 153,124 153,182 152,886 153,506 153,306 153,828 153,866 153,824 153,374 153,784 153,957 154,534 154,390 154,603 66.0 66.0 65.8 66.0 65.9 66.0 66.0 66.1 65.9 66.0 66.0 66.2 66.1 66.1 146,047 146,045 145,753 146,260 146,016 146,647 146,211 146,248 145,993 145,969 146,331 146,046 145,891 145,819 63.0 7,078 4.6 78,743 63.0 7,137 4.7 78,776 62.8 7,133 4.7 79,325 62.9 7,246 4.7 78,955 62.7 7,291 4.8 79,409 63.0 7,181 4.7 79,111 62.7 7,655 5.0 79,290 62.9 7,576 4.9 78,792 62.7 7,381 4.8 79,436 62.6 7,815 5.1 79,211 62.7 7,626 5.0 79,241 62.6 8,487 5.5 78,871 62.4 8,499 5.5 79,237 62.4 8,784 5.7 79,261 Men, 20 years and over Civilian noninstitutional 1 population ……………………. 102,145 Civilian labor force.............. 77,562 75.9 Participation rate........... Employed........................ 74,431 Employment-pop72.9 ulation ratio 2…………… 3,131 Unemployed................... 4.0 Unemployment rate..... Not in the labor force……… 24,584 103,555 103,598 103,723 103,847 103,973 104,087 104,197 103,866 103,961 104,052 104,152 104,258 104,371 104,490 78,596 78,619 78,526 78,689 78,664 79,075 79,004 78,864 78,748 78,838 78,776 78,878 79,037 79,327 75.9 75.9 75.7 75.8 75.7 76.0 75.8 75.9 75.7 75.8 75.6 75.7 75.7 75.9 75,337 75,324 75,274 75,332 75,274 75,834 75,499 75,427 75,362 75,197 75,148 75,001 74,998 75,094 72.8 3,259 4.1 24,959 72.7 3,295 4.2 24,979 72.6 3,252 4.1 25,197 72.5 3,357 4.3 25,158 72.4 3,389 4.3 25,309 72.9 3,240 4.1 25,012 72.5 3,505 4.4 25,193 72.6 3,437 4.4 25,002 72.5 3,386 4.3 25,213 72.3 3,641 4.6 25,214 72.2 3,628 4.6 25,376 71.9 3,877 4.9 25,380 71.9 4,038 5.1 25,334 71.9 4,234 5.3 25,163 Women, 20 years and over Civilian noninstitutional 1 population ……………………. 109,992 Civilian labor force.............. 66,585 60.5 Participation rate........... Employed........................ 63,834 Employment-pop58.0 ulation ratio 2…………… 2,751 Unemployed................... 4.1 Unemployment rate..... Not in the labor force……… 43,407 111,330 111,367 111,479 111,590 111,703 111,805 111,903 111,739 111,822 111,902 111,990 112,083 112,183 112,290 67,516 67,566 67,616 67,795 67,623 67,776 67,866 67,982 67,816 68,159 68,176 68,390 68,446 68,303 60.6 60.7 60.7 60.8 60.5 60.6 60.6 60.8 60.6 60.9 60.9 61.0 61.0 60.8 64,799 64,792 64,826 65,033 64,827 64,980 64,912 65,098 64,950 65,055 65,260 65,138 65,238 65,167 58.2 2,718 4.0 43,814 58.2 2,774 4.1 43,801 58.2 2,790 4.1 43,863 58.3 2,762 4.1 43,795 58.0 2,796 4.1 44,080 58.1 2,796 4.1 44,029 58.0 2,954 4.4 44,037 58.3 2,885 4.2 43,756 58.1 2,865 4.2 44,006 58.1 3,104 4.6 43,743 58.3 2,916 4.3 43,814 58.1 3,252 4.8 43,693 58.2 3,208 4.7 43,737 58.0 3,135 4.6 43,988 16,982 7,012 41.3 5,911 16,993 6,997 41.2 5,930 17,009 6,744 39.7 5,653 17,024 7,021 41.2 5,895 17,040 7,020 41.2 5,914 17,048 6,977 40.9 5,832 17,056 6,996 41.0 5,801 17,012 6,978 41.0 5,724 17,027 6,810 40.0 5,681 17,041 6,787 39.8 5,717 17,056 7,005 41.1 5,923 17,064 7,266 42.6 5,907 17,073 6,907 40.5 5,655 17,084 6,973 40.8 5,558 34.8 1,101 15.7 9,970 34.9 1,067 15.3 9,996 33.2 1,092 16.2 10,264 34.6 1,126 16.0 10,003 34.7 1,105 15.7 10,020 34.2 1,145 16.4 10,071 34.0 1,196 17.1 10,059 33.6 1,254 18.0 10,034 33.4 1,130 16.6 10,216 33.5 1,070 15.8 10,254 34.7 1,082 15.4 10,051 34.6 1,358 18.7 9,798 33.1 1,253 18.1 10,166 32.5 1,415 20.3 10,110 Both sexes, 16 to 19 years Civilian noninstitutional 1 population ……………………. 16,678 7,281 Civilian labor force.............. 43.7 Participation rate........... 6,162 Employed........................ Employment-pop36.9 ulation ratio 2…………… 1,119 Unemployed................... 15.4 Unemployment rate..... Not in the labor force……… 9,397 White3 Civilian noninstitutional 1 population ……………………. 186,264 Civilian labor force.............. 123,834 66.5 Participation rate........... Employed........................ 118,833 Employment-pop63.8 ulation ratio 2…………… 5,002 Unemployed................... 4.0 Unemployment rate..... Not in the labor force……… 62,429 188,253 188,312 188,479 188,644 188,813 188,956 189,093 188,787 188,906 189,019 189,147 189,281 189,428 189,587 124,935 124,945 124,596 125,316 125,151 125,430 125,460 125,340 124,940 125,190 125,171 125,762 125,704 125,971 66.4 66.3 66.1 66.4 66.3 66.4 66.3 66.4 66.1 66.2 66.2 66.4 66.4 66.4 119,792 119,713 119,340 119,992 119,883 120,194 119,889 119,858 119,534 119,574 119,667 119,661 119,518 119,542 63.6 5,143 4.1 63,319 63.6 5,232 4.2 63,368 63.3 5,256 4.2 63,883 63.6 5,324 4.2 63,329 63.5 5,268 4.2 63,662 63.6 5,235 4.2 63,526 63.4 5,571 4.4 63,633 63.5 5,482 4.4 63,447 63.3 5,406 4.3 63,966 63.3 5,616 4.5 63,829 63.3 5,504 4.4 63,975 63.2 6,101 4.9 63,519 63.1 6,186 4.9 63,724 63.1 6,428 5.1 63,616 27,485 17,496 63.7 16,051 27,498 17,593 64.0 16,172 27,541 17,524 63.6 16,176 27,584 17,483 63.4 16,046 27,627 17,430 63.1 15,946 27,666 17,453 63.1 15,980 27,704 17,538 63.3 15,961 27,640 17,713 64.1 16,090 27,675 17,632 63.7 16,169 27,709 17,702 63.9 16,116 27,746 17,753 64.0 16,234 27,780 17,742 63.9 16,029 27,816 17,716 63.7 16,085 27,854 17,767 63.8 16,040 58.4 1,445 8.3 9,989 58.8 1,421 8.1 9,905 58.7 1,347 7.7 10,017 58.2 1,437 8.2 10,101 57.7 1,483 8.5 10,197 57.8 1,473 8.4 10,212 57.6 1,577 9.0 10,165 58.2 1,623 9.2 9,927 58.4 1,463 8.3 10,043 58.2 1,586 9.0 10,007 58.5 1,520 8.6 9,992 57.7 1,713 9.7 10,038 57.8 1,632 9.2 10,100 57.6 1,726 9.7 10,088 Black or African American3 Civilian noninstitutional 1 population ……………………. 27,007 Civilian labor force.............. 17,314 64.1 Participation rate........... Employed........................ 15,765 Employment-pop58.4 ulation ratio 2…………… 1,549 Unemployed................... 8.9 Unemployment rate..... Not in the labor force……… 9,693 See footnotes at end of table. 72 Monthly Labor Review • September 2008 4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] Employment status 2007 Annual average 2006 2007 July Aug. 31,383 21,602 68.8 20,382 31,423 21,613 68.8 20,345 31,520 21,781 69.1 20,578 64.9 1,220 5.6 9,781 64.7 1,269 5.9 9,809 65.3 1,204 5.5 9,738 Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July 31,617 21,872 69.2 20,619 31,714 21,778 68.7 20,554 31,809 21,872 68.8 20,623 31,903 21,888 68.6 20,517 31,643 21,698 68.6 20,320 31,732 21,755 68.6 20,401 31,820 21,775 68.4 20,269 31,911 21,917 68.7 20,404 31,998 22,102 69.1 20,573 32,087 22,131 69.0 20,420 32,179 22,071 68.6 20,435 65.2 1,253 5.7 9,745 64.8 1,224 5.6 9,936 64.8 1,249 5.7 9,938 64.3 1,371 6.3 10,016 64.2 1,378 6.3 9,946 64.3 1,354 6.2 9,977 63.7 1,507 6.9 10,045 63.9 1,512 6.9 9,994 64.3 1,529 6.9 9,896 63.6 1,711 7.7 9,956 63.5 1,636 7.4 10,108 Hispanic or Latino ethnicity Civilian noninstitutional 1 population ……………………. 30,103 Civilian labor force.............. 20,694 68.7 Participation rate........... Employed........................ 19,613 Employment-pop65.2 ulation ratio 2…………… 1,081 Unemployed................... 5.2 Unemployment rate..... Not in the labor force ………… 9,409 1 The population figures are not seasonally adjusted. Civilian employment as a percent of the civilian noninstitutional population. 3 Beginning in 2003, persons who selected this race group only; persons who selected more than one race group are not included. Prior to 2003, persons who reported more than one race were included in the group they identified as the main race. NOTE: Estimates for the above race groups (white and black or African American) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2003, data reflect revised population controls used in the household survey. 2 5. Selected employment indicators, monthly data seasonally adjusted [In thousands] Selected categories Annual average 2006 2007 2007 July Aug. Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Characteristic Employed, 16 years and older.. 144,427 146,047 146,045 145,753 146,260 146,016 146,647 146,211 146,248 145,993 145,969 146,331 146,046 145,891 145,819 Men....................................... 77,502 78,254 78,237 78,066 78,229 78,177 78,604 78,260 78,157 78,113 77,948 78,038 77,954 77,794 77,823 Women............................…… 66,925 67,792 67,808 67,687 68,030 67,838 68,043 67,951 68,091 67,880 68,021 68,293 68,092 68,097 67,996 Married men, spouse 45,700 46,314 46,307 46,193 46,235 46,189 46,339 46,213 46,063 46,136 45,961 45,964 45,862 45,911 46,120 35,272 35,832 35,938 35,794 35,712 35,449 35,689 35,565 35,536 35,648 35,749 36,177 36,171 36,270 36,185 4,162 4,401 4,332 4,517 4,499 4,401 4,513 4,665 4,769 4,884 4,914 5,220 5,233 5,416 5,724 2,658 2,877 2,751 2,955 2,991 2,788 3,008 3,174 3,247 3,291 3,323 3,558 3,595 3,816 4,194 1,189 1,210 1,210 1,175 1,166 1,215 1,223 1,236 1,163 1,222 1,362 1,323 1,281 1,336 1,286 reasons……………………… 19,591 19,756 19,957 19,779 19,812 19,337 19,539 19,526 19,613 19,348 19,409 19,809 19,428 19,496 19,406 4,071 4,317 4,259 4,466 4,397 4,302 4,453 4,577 4,677 4,790 4,797 5,125 5,164 5,308 5,599 2,596 2,827 2,711 2,916 2,922 2,745 2,981 3,120 3,174 3,231 3,238 3,513 3,531 3,744 4,156 1,178 1,199 1,205 1,152 1,153 1,207 1,205 1,219 1,149 1,216 1,354 1,331 1,288 1,328 1,277 reasons.................………… 19,237 19,419 19,569 19,469 19,451 19,157 19,224 19,225 19,296 19,019 19,072 19,456 19,047 19,106 19,051 present................................ Married women, spouse present................................ Persons at work part time1 All industries: Part time for economic reasons…………………….… Slack work or business conditions…………......... Could only find part-time work……………………… Part time for noneconomic Nonagricultural industries: Part time for economic reasons…………………….… Slack work or business conditions....................... Could only find part-time work……………………… Part time for noneconomic 1 Excludes persons "with a job but not at work" during the survey period for such reasons as vacation, illness, or industrial disputes. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. Monthly Labor Review • September 2008 73 Current Labor Statistics: Labor Force Data 6. Selected unemployment indicators, monthly data seasonally adjusted [Unemployment rates] Annual average Selected categories 2006 2007 2007 2008 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Characteristic Total, 16 years and older............................ Both sexes, 16 to 19 years..................... Men, 20 years and older......................... Women, 20 years and older................... 4.6 15.4 4.0 4.1 4.6 15.7 4.1 4.0 4.7 15.3 4.2 4.1 4.7 16.2 4.1 4.1 4.7 16.0 4.3 4.1 4.8 15.7 4.3 4.1 4.7 16.4 4.1 4.1 5.0 17.1 4.4 4.4 4.9 18.0 4.4 4.2 4.8 16.6 4.3 4.2 5.1 15.8 4.6 4.6 5.0 15.4 4.6 4.3 5.5 18.7 4.9 4.8 5.5 18.1 5.1 4.7 5.7 20.3 5.3 4.6 White, total 1……………………………… 4.0 13.2 14.6 11.7 3.5 3.6 4.1 13.9 15.7 12.1 3.7 3.6 4.2 13.8 15.5 12.0 3.8 3.6 4.2 14.4 16.5 12.2 3.8 3.7 4.2 14.3 16.4 12.2 3.9 3.5 4.2 14.0 15.9 12.0 3.8 3.6 4.2 14.7 17.8 11.8 3.7 3.7 4.4 14.4 16.8 12.1 3.9 4.0 4.4 15.6 19.0 12.3 3.9 3.8 4.3 14.4 17.1 11.8 3.9 3.8 4.5 13.2 14.7 11.7 4.1 4.1 4.4 13.8 15.2 12.4 4.1 3.7 4.9 16.4 17.7 14.9 4.4 4.1 4.9 16.6 17.8 15.3 4.5 4.2 5.1 19.0 22.2 15.6 4.7 4.1 8.9 29.1 32.7 25.9 8.3 7.5 8.3 29.4 33.8 25.3 7.9 6.7 8.1 27.0 31.1 23.5 7.6 6.9 7.7 31.2 33.2 29.4 6.8 6.5 8.2 28.9 33.9 24.2 7.5 7.1 8.5 27.9 36.0 20.1 8.2 7.1 8.4 29.7 34.6 24.9 7.9 7.0 9.0 34.7 39.5 30.1 8.4 7.0 9.2 35.7 41.3 28.5 8.3 7.3 8.3 31.7 32.6 30.9 7.9 6.5 9.0 31.3 38.9 25.4 8.4 7.5 8.6 24.5 27.9 21.9 8.4 7.4 9.7 32.3 40.1 25.2 8.9 8.2 9.2 29.6 35.5 23.9 9.3 7.4 9.7 32.0 38.0 26.5 10.0 7.5 5.2 2.4 2.9 4.5 5.1 5.6 2.5 2.8 4.6 4.9 5.9 2.7 2.9 4.6 5.1 5.5 2.5 3.1 4.6 4.9 5.7 2.5 2.9 4.7 4.7 5.6 2.6 2.9 4.7 5.0 5.7 2.6 3.0 4.6 5.0 6.3 2.7 3.1 4.9 5.6 6.3 2.7 3.1 4.8 5.4 6.2 2.7 3.1 4.8 5.0 6.9 2.8 3.3 5.0 5.3 6.9 2.8 3.0 5.0 4.9 6.9 2.9 3.1 5.5 5.5 7.7 3.0 3.3 5.5 5.4 7.4 3.2 3.3 5.7 5.5 Both sexes, 16 to 19 years................ Men, 16 to 19 years........................ Women, 16 to 19 years.................. Men, 20 years and older.................... Women, 20 years and older.............. Black or African American, total 1……… Both sexes, 16 to 19 years................ Men, 16 to 19 years........................ Women, 16 to 19 years.................. Men, 20 years and older.................... Women, 20 years and older.............. Hispanic or Latino ethnicity……………… Married men, spouse present................ Married women, spouse present........... Full-time workers................................... Part-time workers.................................. Educational attainment2 Less than a high school diploma................ 6.8 7.1 7.2 6.7 7.5 7.4 7.6 7.6 7.7 7.3 8.2 7.8 8.3 8.7 8.5 Some college or associate degree……….. 4.3 3.6 4.4 3.6 4.5 3.6 4.4 3.7 4.6 3.4 4.6 3.5 4.5 3.3 4.7 3.7 4.6 3.6 4.7 3.7 5.1 3.8 5.0 3.9 5.2 4.3 5.1 4.2 5.2 4.5 Bachelor's degree and higher 4……………. 2.0 2.0 2.1 2.1 2.0 2.1 2.2 2.2 2.1 2.1 2.1 2.1 2.2 2.3 2.4 Feb. Mar. May June High school graduates, no college 3……… 1 Beginning in 2003, persons who selected this race group only; persons who selected more than one race group are not included. Prior to 2003, persons who reported more than one race were included in the group they identified as the main race. 2 Data refer to persons 25 years and older. 7. Duration of unemployment, monthly data seasonally adjusted [Numbers in thousands] Weeks of unemployment Less than 5 weeks........................... 5 to 14 weeks.................................. 15 weeks and over.......................... 15 to 26 weeks............................. 27 weeks and over....................... Mean duration, in weeks................... Median duration, in weeks............... Annual average 2006 2,614 2,121 2,266 1,031 1,235 16.8 8.3 2007 2,542 2,232 2,303 1,061 1,243 16.8 8.5 2007 July 2,496 2,220 2,402 1,091 1,311 17.3 8.9 Aug. 2,610 2,201 2,375 1,124 1,252 16.9 8.6 Sept. 2,537 2,330 2,392 1,112 1,280 16.6 8.9 2008 Oct. 2,508 2,454 2,367 1,052 1,315 17.0 8.7 Nov. 2,633 2,157 2,398 1,014 1,384 17.2 8.7 NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. 74 Monthly Labor Review • September 2008 Dec. 2,793 2,330 2,520 1,182 1,338 16.6 8.4 Jan. 2,634 2,396 2,503 1,124 1,380 17.5 8.8 2,639 2,396 2,377 1,079 1,299 16.8 8.4 2,767 2,525 2,400 1,118 1,282 16.2 8.1 Apr. 2,484 2,495 2,626 1,272 1,353 16.9 9.3 3,244 2,469 2,773 1,223 1,550 16.6 8.3 2,712 2,999 2,916 1,328 1,587 17.5 10.0 July 2,835 2,823 3,118 1,440 1,678 17.1 9.7 8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted [Numbers in thousands] Reason for unemployment Job losers 1…………………….… On temporary layoff.............. Not on temporary layoff........ Job leavers.............................. Reentrants............................... New entrants........................... Annual average 2006 2007 2007 July Aug. Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July 3,321 921 2,400 827 2,237 616 3,515 976 2,539 793 2,142 627 3,629 983 2,646 823 2,082 602 3,632 981 2,652 794 2,076 603 3,622 963 2,660 839 2,154 685 3,731 1,064 2,668 790 2,103 709 3,609 979 2,630 783 2,160 669 3,857 975 2,882 798 2,343 697 3,796 1,040 2,756 830 2,201 667 3,854 971 2,883 769 2,112 648 4,154 1,056 3,098 781 2,117 681 4,014 1,099 2,915 850 2,134 624 4,282 1,113 3,169 870 2,460 828 4,370 1,077 3,292 833 2,498 748 4,407 1,037 3,370 861 2,705 811 47.4 13.2 34.3 11.8 32.0 8.8 49.7 13.8 35.9 11.2 30.3 8.9 50.8 13.8 37.1 11.5 29.2 8.4 51.1 13.8 37.3 11.2 29.2 8.5 49.6 13.2 36.4 11.5 29.5 9.4 50.9 14.5 36.4 10.8 28.7 9.7 50.0 13.6 36.4 10.8 29.9 9.3 50.1 12.7 37.5 10.4 30.4 9.1 50.7 13.9 36.8 11.1 29.4 8.9 52.2 13.2 39.0 10.4 28.6 8.8 53.7 13.7 40.1 10.1 27.4 8.8 52.7 14.4 38.2 11.2 28.0 8.2 50.7 13.2 37.5 10.3 29.1 9.8 51.7 12.7 39.0 9.9 29.6 8.9 50.2 11.8 38.4 9.8 30.8 9.2 2.4 .5 1.4 .4 2.4 .5 1.4 .4 2.4 .5 1.4 .4 2.4 .5 1.4 .5 2.3 .5 1.4 .4 2.5 .5 1.5 .5 2.5 .5 1.4 .4 2.5 .5 1.4 .4 2.7 .5 1.4 .4 2.6 .6 1.4 .4 2.8 .6 1.6 .5 2.8 .5 1.6 .5 2.9 .6 1.7 .5 Jan. Feb. Mar. Apr. Percent of unemployed Job losers 1…………………….… On temporary layoff............... Not on temporary layoff......... Job leavers............................... Reentrants................................ New entrants............................ Percent of civilian labor force 2.2 2.3 Job losers 1…………………….… .5 .5 Job leavers............................... 1.5 1.4 Reentrants................................ .4 .4 New entrants............................ 1 Includes persons who completed temporary jobs. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. 9. Unemployment rates by sex and age, monthly data seasonally adjusted [Civilian workers] Sex and age Annual average 2006 2007 Total, 16 years and older.................. 16 to 24 years............................... 16 to 19 years............................ 16 to 17 years......................... 18 to 19 years......................... 20 to 24 years............................ 25 years and older........................ 25 to 54 years......................... 55 years and older.................. 4.6 10.5 15.4 17.2 14.1 8.2 3.6 3.8 3.0 4.6 10.5 15.7 17.5 14.5 8.2 3.6 3.7 3.1 Men, 16 years and older................. 16 to 24 years............................. 16 to 19 years.......................... 16 to 17 years....................... 18 to 19 years....................... 20 to 24 years.......................... 25 years and older...................... 25 to 54 years....................... 55 years and older................ 4.6 11.2 16.9 18.6 15.7 8.7 3.5 3.6 3.0 Women, 16 years and older........... 16 to 24 years............................. 16 to 19 years.......................... 16 to 17 years………………… 18 t0 19 years………………… 20 to 24 years.......................... 25 years and older...................... 25 to 54 years....................... 55 years and older 1………… 1 2007 July Aug. Sept. 4.7 10.6 15.3 17.0 14.0 8.5 3.7 3.8 3.2 4.7 10.8 16.2 18.6 14.6 8.4 3.6 3.8 3.2 4.7 11.0 16.0 18.6 14.3 8.8 3.7 3.8 3.1 4.7 11.6 17.6 19.4 16.5 8.9 3.6 3.7 3.2 4.7 11.5 16.9 19.3 15.4 9.2 3.6 3.7 3.4 4.7 11.6 18.0 21.7 15.2 8.9 3.6 3.7 3.4 4.6 9.7 13.8 15.9 12.4 7.6 3.7 3.9 4.5 9.4 13.8 15.7 12.5 7.3 3.6 3.8 4.6 9.6 13.6 14.8 12.6 7.7 3.8 3.9 2.9 3.0 3.5 2008 Oct. Nov. Dec. 4.8 10.8 15.7 17.5 14.3 8.6 3.7 3.8 3.1 4.7 10.7 16.4 19.0 14.4 8.0 3.7 3.8 3.0 5.0 11.8 17.1 19.6 15.4 9.4 3.9 4.1 3.2 4.9 11.7 18.0 20.4 15.9 8.7 3.8 3.9 3.2 4.8 11.3 16.6 18.3 15.5 8.9 3.8 3.9 3.2 5.1 11.3 15.8 18.6 14.0 9.3 4.0 4.2 3.4 5.0 11.0 15.4 19.7 13.2 8.9 3.9 4.2 3.0 May 5.5 13.0 18.7 21.2 17.5 10.4 4.1 4.4 3.3 June 5.5 12.6 18.1 23.3 15.6 10.1 4.3 4.5 3.3 July 5.7 13.4 20.3 24.9 17.3 10.2 4.4 4.6 3.6 4.9 12.2 18.3 21.9 16.2 9.5 3.7 3.8 3.3 4.9 12.0 18.1 19.0 16.8 9.3 3.7 3.8 3.1 4.7 11.8 19.5 21.4 17.8 8.6 3.6 3.7 3.1 5.1 12.8 19.8 22.1 18.4 9.8 3.8 4.0 3.2 5.1 13.1 21.8 24.0 19.5 9.4 3.8 4.0 3.2 4.9 12.5 18.7 20.5 18.0 9.9 3.7 3.8 3.2 5.2 12.5 17.8 22.0 15.2 10.3 4.0 4.1 3.3 5.1 12.0 16.9 22.2 14.5 9.9 4.0 4.3 3.0 5.6 14.1 20.7 23.3 19.6 11.0 4.2 4.4 3.4 5.7 13.8 19.9 26.2 17.1 11.2 4.3 4.6 3.4 6.1 15.2 23.4 29.4 19.9 11.6 4.6 4.9 3.7 4.6 10.0 14.4 15.5 13.9 7.9 3.7 3.9 4.5 9.8 13.7 15.6 12.3 7.9 3.7 3.8 4.6 9.6 13.3 16.1 11.6 7.7 3.7 3.9 4.6 9.4 13.4 17.1 10.7 7.4 3.8 4.0 4.9 10.7 14.4 17.3 12.3 8.8 3.9 4.1 4.7 10.1 14.2 17.2 12.1 8.0 3.8 3.9 4.7 9.9 14.5 16.2 12.8 7.7 3.8 4.0 5.0 10.0 13.8 15.5 12.8 8.1 4.1 4.2 4.8 9.8 14.0 17.5 11.8 7.7 3.9 4.0 5.3 11.9 16.6 19.0 15.2 9.6 4.1 4.4 5.2 11.2 16.3 20.3 13.9 8.8 4.2 4.4 5.2 11.4 17.1 20.4 14.6 8.7 4.2 4.3 3.4 3.0 3.0 2.8 2.9 3.4 3.3 3.4 2.8 2.8 3.4 4.3 Data are not seasonally adjusted. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. Monthly Labor Review • September 2008 75 Current Labor Statistics: Labor Force Data 10. Unemployment rates by State, seasonally adjusted June 2007 State May June 2007p 2008p June 2007 State June 2008p Alabama............................………………… Alaska........................................................ Arizona............................…………………… Arkansas.................................................... California............................………………… 3.5 6.1 3.6 5.4 5.3 4.7 6.9 4.4 5.1 6.8 4.7 6.7 4.8 5.0 7.0 Missouri……………………………………… Montana..................................................... Nebraska............................………………… Nevada...................................................... New Hampshire............................………… 5.0 3.1 3.1 4.8 3.6 6.0 4.2 3.2 6.2 4.0 5.7 4.1 3.3 6.4 4.0 Colorado.................................................... Connecticut............................……………… Delaware................................................... District of Columbia............................…… Florida........................................................ 3.7 4.4 3.3 5.7 4.0 4.9 5.4 4.1 6.6 5.6 5.1 5.5 4.2 6.3 5.5 New Jersey................................................ New Mexico............................……………… New York................................................... North Carolina............................…………… North Dakota............................................. 4.2 3.5 4.6 4.7 3.2 5.4 3.8 5.2 5.9 3.3 5.3 3.9 5.3 5.9 3.2 Georgia............................………………… Hawaii........................................................ Idaho............................……………………… Illinois......................................................... Indiana............................…………………… 4.4 2.6 2.7 5.0 4.5 5.7 3.6 3.6 6.4 5.3 5.6 3.8 3.8 6.8 5.9 Ohio............................……………………… Oklahoma.................................................. Oregon............................…………………… Pennsylvania............................................. Rhode Island............................…………… 5.7 4.4 5.2 4.3 5.0 6.3 3.5 5.6 5.2 7.2 6.6 3.9 5.5 5.2 7.5 Iowa............................……………………… Kansas....................................................... Kentucky............................………………… Louisiana................................................... Maine............................…………………… 3.8 4.1 5.5 3.7 4.7 3.9 4.6 6.2 4.0 5.4 4.0 4.3 6.3 3.8 5.3 South Carolina............................………… South Dakota............................................. Tennessee............................……………… Texas......................................................... Utah............................……………………… 5.7 2.9 4.6 4.3 2.7 6.5 2.9 6.4 4.5 3.2 6.1 2.8 6.5 4.4 3.3 Maryland............................………………… Massachusetts........................................... Michigan............................………………… Minnesota.................................................. Mississippi............................……………… 3.6 4.5 7.1 4.5 6.3 4.0 4.9 8.5 5.4 6.9 4.0 5.2 8.5 5.3 7.0 Vermont............................………………… Virginia....................................................... Washington............................……………… West Virginia............................................. Wisconsin............................……………… Wyoming.................................................... 3.8 3.0 4.5 4.5 4.8 3.1 4.9 3.9 5.3 5.3 4.4 2.9 4.7 4.0 5.4 5.3 4.6 3.2 p = preliminary 11. Employment of workers on nonfarm payrolls by State, seasonally adjusted State June 2007 May June 2007p 2008p State June 2007 May June 2007p 2008p Alabama............................………… 2,182,845 2,206,959 2,193,795 Alaska............................................. 352,104 360,020 359,753 Arizona............................…………… 3,021,368 3,068,807 3,071,144 Arkansas........................................ 1,366,002 1,383,946 1,374,363 California............................………… 18,182,148 18,446,229 18,431,325 Missouri……………………………… 3,030,362 Montana......................................... 501,499 Nebraska............................………… 985,015 Nevada........................................... 1,334,388 New Hampshire............................… 738,169 3,031,728 503,998 996,099 1,394,653 745,382 3,013,754 504,237 994,983 1,394,472 746,147 Colorado......................................... 2,701,057 Connecticut............................……… 1,861,099 Delaware........................................ 442,229 District of Columbia........................ 323,288 Florida............................................ 9,135,410 2,765,873 1,886,487 446,064 331,839 9,263,932 2,759,853 1,886,827 446,101 328,482 9,250,317 New Jersey..................................... New Mexico............................…… New York........................................ North Carolina............................… North Dakota.................................. 4,467,625 942,437 9,528,910 4,526,537 365,424 4,516,789 949,666 9,590,326 4,561,644 373,012 4,505,006 951,334 9,620,555 4,559,713 372,443 Georgia............................………… 4,811,005 Hawaii............................................. 649,855 Idaho............................…………… 755,181 Illinois............................................. 6,705,295 Indiana............................…………… 3,208,264 4,901,799 663,369 755,212 6,824,185 3,229,677 4,889,808 663,245 752,324 6,775,620 3,219,283 Ohio............................……………… Oklahoma....................................... Oregon............................…………… Pennsylvania.................................. Rhode Island............................…… 5,980,866 1,734,455 1,927,115 6,297,400 577,971 6,005,619 1,735,085 1,945,592 6,405,503 571,560 5,988,368 1,733,393 1,938,370 6,394,738 572,128 Iowa............................……………… Kansas........................................... Kentucky............................………… Louisiana........................................ Maine............................…………… 1,659,989 1,479,438 2,045,058 1,989,101 703,976 1,679,525 1,494,578 2,047,456 2,008,102 708,936 1,672,261 1,491,211 2,041,828 2,012,118 710,175 South Carolina............................… 2,133,783 2,150,865 2,142,982 South Dakota.................................. 442,728 444,744 444,627 Tennessee............................……… 3,033,878 3,062,538 3,043,947 Texas.............................................. 11,484,815 11,712,220 11,682,351 Utah............................……………… 1,360,251 1,388,270 1,380,611 Maryland............................………… Massachusetts............................... Michigan............................………… Minnesota....................................... Mississippi............................……… 2,975,302 3,409,437 5,023,547 2,931,395 1,311,772 3,017,148 3,391,913 5,007,445 2,951,882 1,341,915 3,012,875 3,409,561 4,990,167 2,935,404 1,327,847 Vermont............................………… 353,877 Virginia........................................... 4,051,667 Washington............................……… 3,402,395 West Virginia.................................. 808,350 Wisconsin............................……… 3,087,244 Wyoming........................................ 287,901 NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database. p 76 May 2007p = preliminary Monthly Labor Review • September 2008 352,292 4,125,326 3,451,292 816,375 3,089,857 290,173 353,420 4,124,453 3,449,748 813,277 3,078,458 290,369 12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Industry Annual average 2006 TOTAL NONFARM................. 136,086 TOTAL PRIVATE........................ 114,113 2007 2007 July Aug. Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp 137,623 137,682 137,756 137,837 137,977 138,037 138,078 138,002 137,919 137,831 137,764 137,717 137,666 137,615 115,420 115,512 115,544 115,610 115,715 115,759 115,745 115,666 115,557 115,454 115,363 115,264 115,170 115,094 22,531 22,221 22,242 22,176 22,138 22,101 22,049 21,976 21,907 21,816 21,737 21,628 21,577 21,500 21,454 684 64.4 619.7 134.5 1 220.3 Mining, except oil and gas …… 78.0 Coal mining…………………… Support activities for mining…… 264.9 7,691 Construction................................ Construction of buildings........... 1,804.9 985.1 Heavy and civil engineering…… Speciality trade contractors....... 4,901.1 Manufacturing.............................. 14,155 Production workers................ 10,137 8,981 Durable goods........................... 6,355 Production workers................ 558.8 Wood products.......................... 509.6 Nonmetallic mineral products 464.0 Primary metals.......................... Fabricated metal products......... 1,553.1 1,183.2 Machinery………..................... Computer and electronic 723 60.8 662.1 146.0 224.5 77.6 291.6 7,614 1,761.0 1,001.2 4,851.9 13,884 9,979 8,816 6,257 519.7 503.4 456.0 1,563.3 1,188.2 726 59.9 666.3 146.3 225.4 77.4 294.6 7,632 1,765.3 1,002.3 4,863.9 13,884 9,985 8,817 6,258 523.4 504.4 456.4 1,564.2 1,192.5 727 59.5 667.2 147.0 226.4 77.6 293.8 7,605 1,751.2 999.0 4,854.7 13,844 9,956 8,792 6,239 518.5 501.2 452.7 1,562.8 1,187.5 727 59.7 667.4 147.3 226.7 78.0 293.4 7,589 1,749.4 998.8 4,840.3 13,822 9,958 8,778 6,245 513.1 501.0 451.6 1,565.0 1,186.2 727 59.1 667.8 148.9 226.9 78.1 292.0 7,577 1,736.6 999.5 4,841.3 13,797 9,934 8,761 6,232 511.8 500.9 451.5 1,568.0 1,189.0 735 59.9 675.0 152.3 226.0 78.7 296.7 7,520 1,716.4 999.0 4,804.8 13,794 9,944 8,763 6,242 509.0 499.5 452.6 1,565.6 1,189.9 739 60.6 677.9 153.1 225.2 78.3 299.6 7,465 1,702.4 993.8 4,768.4 13,772 9,933 8,739 6,220 507.2 496.4 452.2 1,562.7 1,191.0 744 60.7 683.2 154.5 227.0 78.6 301.7 7,426 1,690.2 984.6 4,750.8 13,737 9,922 8,718 6,214 503.5 494.4 452.3 1,560.9 1,193.8 744 60.2 684.0 153.8 225.7 78.7 304.5 7,382 1,673.0 977.6 4,731.8 13,690 9,879 8,685 6,182 498.6 492.2 451.4 1,557.1 1,191.7 750 60.1 689.7 155.2 226.2 79.2 308.3 7,343 1,668.2 976.9 4,697.5 13,644 9,847 8,652 6,152 492.9 487.7 451.3 1,556.9 1,195.1 752 60.8 690.9 154.2 225.8 79.3 310.9 7,284 1,648.2 967.4 4,668.0 13,592 9,799 8,607 6,112 490.9 486.3 450.1 1,544.1 1,193.1 760 59.5 700.6 158.3 229.6 80.5 312.7 7,246 1,634.9 965.3 4,645.6 13,571 9,784 8,594 6,100 482.4 482.1 448.7 1,544.2 1,195.1 767 57.4 709.6 160.5 230.4 80.8 318.7 7,197 1,623.9 959.9 4,613.3 13,536 9,749 8,575 6,078 477.6 479.6 448.1 1,539.2 1,195.6 778 57.9 719.9 162.8 231.7 80.7 325.4 7,175 1,622.8 958.6 4,593.6 13,501 9,731 8,558 6,070 473.7 477.5 447.4 1,537.4 1,201.7 products 1……………………… 1,307.5 Computer and peripheral 1,271.9 1,268.3 1,265.6 1,260.5 1,256.5 1,260.5 1,257.6 1,256.3 1,251.9 1,254.1 1,253.8 1,250.1 1,246.1 1,243.6 GOODS-PRODUCING……………… Natural resources and mining…………..……….......…… Logging.................................... Mining.......................................... Oil and gas extraction…………… equipment.............................. Communications equipment… 196.2 136.2 186.9 128.6 186.2 127.5 186.1 128.5 185.9 128.5 185.1 128.1 185.5 129.5 185.4 129.0 184.9 129.5 185.9 128.7 186.0 129.4 186.7 130.9 186.2 130.4 184.3 131.5 185.6 129.6 Semiconductors and electronic components.......... Electronic instruments………. 457.9 444.5 444.5 444.0 443.7 443.1 439.9 442.5 437.4 442.0 435.8 441.9 437.0 443.0 434.9 443.7 433.5 444.3 429.7 442.9 428.7 446.2 426.7 445.7 424.2 445.6 422.1 444.6 421.9 443.4 Electrical equipment and appliances............................... Transportation equipment......... 432.7 1,768.9 427.2 1,710.9 427.7 1,704.7 426.1 1,705.7 426.0 1,706.1 427.2 1,689.3 426.6 1,693.5 423.8 1,684.7 421.6 1,678.1 420.8 1,672.0 419.9 1,651.1 421.5 1,630.6 422.1 1,636.8 422.7 1,637.1 423.5 1,628.8 Furniture and related products.....……………………… 560.1 643.7 Miscellaneous manufacturing Nondurable goods..................... 5,174 Production workers................ 3,782 Food manufacturing.................. 1,479.4 534.5 641.0 5,068 3,723 1,481.3 536.1 639.5 5,067 3,727 1,488.8 533.0 638.8 5,052 3,717 1,480.6 530.6 637.6 5,044 3,713 1,476.0 528.3 638.2 5,036 3,702 1,478.6 527.0 638.8 5,031 3,702 1,477.9 523.8 639.9 5,033 3,713 1,486.3 520.4 636.4 5,019 3,708 1,483.2 516.0 633.3 5,005 3,697 1,482.7 511.2 632.0 4,992 3,695 1,477.0 506.4 630.2 4,985 3,687 1,473.8 503.5 629.1 4,977 3,684 1,473.5 501.6 627.0 4,961 3,671 1,471.8 499.3 624.9 4,943 3,661 1,467.6 Beverages and tobacco products………………………… Textile mills……………………… Textile product mills................... Apparel…………………………. Leather and allied products....... Paper and paper products......... 194.2 195.0 166.7 232.4 36.8 470.5 195.7 169.9 158.4 213.0 33.9 460.6 197.0 168.1 157.1 212.8 33.1 459.8 196.1 166.4 156.9 211.3 33.3 459.1 195.7 164.8 156.3 209.2 34.0 459.0 195.2 164.9 155.9 206.8 33.7 459.2 194.3 164.9 157.2 206.4 34.1 458.6 192.0 163.0 155.7 204.8 33.7 460.3 191.1 162.0 154.0 202.0 34.5 459.0 189.3 161.4 153.0 200.6 33.5 457.8 190.8 158.7 153.3 198.1 33.5 457.9 193.3 156.4 152.2 198.0 33.9 458.4 193.7 155.1 151.0 196.6 33.7 458.1 193.0 152.0 149.2 195.5 34.3 456.8 193.0 149.4 148.0 194.4 33.4 456.6 Printing and related support activities………………………… Petroleum and coal products..... Chemicals.................................. Plastics and rubber products.. 634.4 113.2 865.9 785.5 624.2 113.4 862.9 754.0 623.3 112.5 862.5 752.4 621.0 112.5 864.2 750.2 623.0 112.9 864.3 748.4 622.2 112.6 860.7 745.9 622.0 112.1 860.5 743.0 619.5 111.7 862.0 744.2 620.1 112.2 861.2 739.7 614.6 112.5 861.0 738.7 614.2 112.2 860.5 735.6 611.7 112.2 861.3 734.1 607.3 113.4 861.6 732.8 601.7 114.0 861.3 731.1 598.5 114.6 859.2 728.2 SERVICE-PROVIDING................... 113,556 115,402 115,440 115,580 115,699 115,876 115,988 116,102 116,095 116,103 116,094 116,136 116,140 116,166 116,161 PRIVATE SERVICEPROVIDING……………………… 91,582 Trade, transportation, and utilities................................ Wholesale trade......................... Durable goods………………….. Nondurable goods…………… 26,276 5,904.5 3,074.8 2,041.3 93,199 93,270 93,368 93,472 93,614 93,710 93,769 93,759 93,741 93,717 93,735 93,687 93,670 93,640 26,608 6,028.3 3,130.7 2,069.3 26,617 6,040.7 3,140.2 2,069.2 26,640 6,047.1 3,141.9 2,072.7 26,649 6,055.6 3,143.4 2,078.5 26,644 6,069.8 3,147.4 2,086.5 26,693 6,075.0 3,152.4 2,086.6 26,658 6,072.9 3,145.0 2,089.3 26,631 6,067.3 3,138.0 2,090.9 26,579 6,057.6 3,127.3 2,088.4 26,552 6,054.3 3,127.8 2,087.5 26,496 6,043.9 3,118.1 2,086.9 26,451 6,038.4 3,109.8 2,089.3 26,436 6,035.3 3,105.4 2,088.0 26,397 6,018.4 3,097.3 2,078.7 Electronic markets and agents and brokers…………… 788.5 828.4 831.3 832.5 833.7 835.9 836.0 838.6 838.4 841.9 839.0 838.9 839.3 841.9 842.4 Retail trade................................. 15,353.3 15,490.7 15,489.1 15,502.3 15,487.3 15,469.1 15,513.1 15,487.8 15,472.2 15,428.8 15,401.4 15,355.7 15,331.8 15,325.5 15,309.0 Motor vehicles and parts dealers 1……………………… Automobile dealers.................. 1,909.7 1,246.7 1,913.1 1,245.3 1,911.9 1,244.7 1,914.7 1,245.6 1,916.0 1,246.6 1,911.9 1,247.4 1,911.0 1,244.9 1,909.3 1,244.6 1,910.2 1,244.0 1,905.1 1,236.2 1,901.5 1,233.7 1,897.6 1,228.8 1,892.9 1,224.2 1,885.6 1,217.4 1,875.0 1,209.0 Furniture and home furnishings stores.................... 586.9 581.0 577.7 579.2 576.2 577.3 584.9 584.5 579.9 575.9 570.6 569.0 568.5 568.2 567.9 Electronics and appliance stores....................................... 541.1 543.7 545.0 542.7 540.1 537.1 542.6 540.4 534.3 533.6 535.0 534.7 539.3 535.8 536.9 See notes at end of table. Monthly Labor Review • September 2008 77 Current Labor Statistics: Labor Force Data 12. Continued–Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Annual average Industry 2007 2008 2007 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp 1,305.3 2,848.5 1,307.3 2,847.1 1,315.6 2,852.2 1,291.9 2,856.0 1,285.4 2,859.6 1,279.9 2,871.9 1,271.6 2,871.9 1,266.0 2,880.1 1,258.5 2,885.7 1,250.8 2,890.1 1,240.5 2,882.4 1,240.3 2,880.7 1,236.1 2,881.6 1,230.6 2,882.3 961.1 864.1 988.6 861.2 985.6 861.5 989.4 860.8 990.1 864.2 991.0 862.0 998.6 859.1 999.9 850.5 1,000.6 853.8 993.5 854.2 993.9 852.6 993.4 847.4 990.9 841.2 990.7 844.9 988.6 844.2 Clothing and clothing accessories stores …………………1,450.9 1,500.4 1,496.7 1,501.5 1,502.4 1,500.9 1,524.5 1,508.6 1,498.2 1,496.3 1,498.9 1,495.4 1,494.5 1,496.2 1,496.9 General merchandise stores 1…… 2,935.0 Department stores………………… 1,557.2 Miscellaneous store retailers……… 881.0 Nonstore retailers…………………… 432.8 658.2 2,984.6 1,576.7 868.7 437.6 660.5 2,987.0 1,580.1 871.3 437.5 661.8 2,978.9 1,573.0 869.7 435.8 665.1 2,976.5 1,570.5 873.3 435.5 664.0 2,975.8 1,568.5 869.0 435.1 664.0 2,968.2 1,560.6 868.3 440.1 661.6 2,976.7 1,568.4 866.3 446.5 667.2 2,971.1 1,564.3 869.4 441.4 661.9 2,955.7 1,543.3 865.3 443.1 658.6 2,943.9 1,534.3 862.8 442.7 651.5 2,939.0 1,528.1 863.3 441.5 653.2 2,928.5 1,514.7 860.8 441.0 651.1 2,939.3 1,514.2 858.6 437.4 648.2 2,943.2 1,512.0 859.2 436.0 Transportation and warehousing................................. 4,469.6 Air transportation…………….……… 487.0 Rail transportation……...…………… 227.5 62.7 Water transportation………...……… Truck transportation………..……… 1,435.8 4,536.0 492.6 234.4 64.3 1,441.2 4,533.0 493.4 234.4 65.0 1,437.4 4,535.4 494.6 234.4 65.1 1,438.2 4,551.2 494.5 234.6 65.0 1,440.6 4,548.7 495.2 234.0 64.9 1,433.6 4,549.0 503.0 233.8 65.0 1,428.7 4,539.9 502.1 232.5 64.4 1,423.1 4,534.5 504.7 233.8 63.8 1,422.5 4,535.5 508.2 233.7 62.5 1,417.4 4,537.7 507.5 233.7 61.6 1,420.4 4,538.3 504.5 233.5 62.3 1,415.2 4,524.1 501.3 233.0 61.3 1,409.8 4,517.7 499.4 233.0 61.8 1,399.2 4,511.9 498.5 234.4 61.1 1,394.1 2006 Building material and garden supply stores................................ 1,324.1 Food and beverage stores............. 2,821.1 Health and personal care stores……………………………… Gasoline stations…………………… Sporting goods, hobby, book, and music stores…………… 645.5 Transit and ground passenger transportation………...…………… Pipeline transportation………...…… 399.3 38.7 410.0 40.1 411.0 40.0 413.3 40.1 417.8 40.1 417.4 40.3 411.5 40.6 411.8 40.8 411.9 40.6 413.5 40.9 412.9 41.2 418.3 41.3 412.9 42.2 416.8 42.7 415.6 43.2 Scenic and sightseeing transportation…….………………… 27.5 29.4 28.9 29.3 29.8 30.3 30.9 31.3 31.0 31.5 31.7 31.3 31.1 31.0 30.6 Support activities for transportation………………..…… Couriers and messengers……...…… Warehousing and storage………… Utilities………………………….………...... Information…………………...…. 570.6 582.4 638.1 548.5 3,038 582.9 582.5 658.7 553.4 3,029 583.7 580.1 659.1 554.3 3,027 583.7 579.2 657.5 555.1 3,024 586.5 580.3 662.0 554.8 3,031 589.9 577.9 665.2 556.1 3,027 589.2 584.4 661.9 555.5 3,022 587.1 588.1 658.7 557.1 3,018 584.9 585.5 655.8 557.1 3,014 585.9 586.0 655.9 557.0 3,016 586.3 585.3 657.1 558.2 3,013 588.2 585.0 658.7 557.7 3,007 587.1 587.2 658.2 557.1 3,002 586.6 588.1 659.1 557.6 2,996 586.9 588.8 658.7 557.8 2,983 Publishing industries, except Internet…………………...………… 902.4 898.2 898.7 897.0 893.7 894.6 892.2 889.7 889.2 886.8 882.9 882.8 879.7 877.0 873.6 Motion picture and sound recording industries……...………… 375.7 328.3 Broadcasting, except Internet.. 380.0 326.4 377.9 325.1 376.3 325.2 384.3 327.0 380.5 324.8 376.3 325.0 376.3 321.9 372.9 323.0 380.1 322.1 383.0 322.5 382.5 320.8 380.9 321.2 380.2 319.8 375.5 320.2 Internet publishing and broadcasting………………...……… Telecommunications………….…… 1,047.6 1,028.3 1,026.6 1,025.1 1,024.4 1,023.6 1,026.4 1,026.8 1,025.3 1,022.0 1,020.1 1,018.0 1,017.7 1,018.1 1,012.9 270.5 125.7 8,308 6,146.6 272.8 126.3 8,331 6,165.8 272.3 127.6 8,312 6,148.4 273.1 128.8 8,294 6,136.0 273.2 130.0 8,283 6,124.5 272.6 129.5 8,260 6,115.5 273.5 129.3 8,252 6,111.2 273.0 130.5 8,244 6,106.2 274.2 131.2 8,231 6,102.2 272.3 131.9 8,231 6,103.4 272.2 130.7 8,229 6,103.8 272.1 130.1 8,226 6,098.8 271.3 130.0 8,213 6,086.7 270.5 130.2 8,213 6,084.6 21.2 21.1 20.8 21.1 20.9 20.8 20.7 20.7 20.7 20.9 20.9 21.1 21.0 20.9 20.9 related activities 1………………… 2,924.9 Depository credit 2,881.6 2,892.3 2,870.4 2,856.7 2,844.8 2,834.3 2,829.2 2,825.0 2,820.4 2,811.8 2,807.9 2,800.5 2,792.3 2,788.5 intermediation 1…………………… 1,802.0 Commercial banking..…………… 1,322.9 1,822.5 1,345.8 1,823.8 1,346.7 1,825.8 1,347.3 1,831.0 1,350.1 1,829.3 1,350.1 1,823.4 1,344.7 1,824.6 1,345.9 1,821.5 1,342.2 1,823.3 1,344.9 1,821.6 1,343.4 1,822.9 1,344.2 1,820.6 1,343.4 1,818.4 1,343.2 1,817.3 1,342.5 818.3 847.9 851.2 852.6 853.2 855.0 856.9 856.7 859.2 862.5 865.8 867.2 866.6 866.2 865.2 Insurance carriers and related activities………………...… 2,303.7 2,308.1 2,314.2 2,315.4 2,317.0 2,315.3 2,315.6 2,316.8 2,313.9 2,311.1 2,318.4 2,319.7 2,323.2 2,319.5 2,322.3 87.9 87.8 87.3 88.9 88.2 88.6 88.0 87.8 87.4 87.3 86.5 87.9 87.5 87.8 87.7 Real estate and rental and leasing………………………..… 2,172.5 Real estate……………………….… 1,499.0 Rental and leasing services……… 645.5 2,161.7 1,491.9 640.3 2,165.4 1,493.8 641.4 2,163.3 1,493.9 638.9 2,157.7 1,489.8 637.8 2,158.6 1,489.1 639.7 2,144.7 1,477.1 637.4 2,140.6 1,476.4 633.6 2,138.0 1,471.4 635.2 2,128.6 1,466.0 631.0 2,127.8 1,465.0 631.1 2,124.9 1,465.7 627.4 2,127.3 1,466.4 629.5 2,126.2 1,465.7 628.6 2,128.5 1,463.3 632.8 ISPs, search portals, and data processing………..………… Other information services………… 263.2 120.8 8,328 Financial activities………………..… Finance and insurance……………..…6,156.0 Monetary authorities— central bank…………………..…… Credit intermediation and Securities, commodity contracts, investments…………… Funds, trusts, and other financial vehicles…………….…… Lessors of nonfinancial intangible assets………………..… 28.1 29.5 30.2 30.5 30.1 29.8 30.2 30.6 31.4 31.6 31.7 31.8 31.4 31.9 32.4 Professional and business services…………………………...… 17,566 17,962 17,958 17,979 18,000 18,070 18,079 18,131 18,101 18,073 18,014 18,031 17,982 17,943 17,919 services1…………………………… 7,356.7 Legal services……………..……… 1,173.2 7,662.0 1,176.4 7,664.2 1,173.7 7,688.0 1,174.2 7,729.7 1,178.6 7,759.3 1,179.7 7,784.8 1,175.2 7,820.5 1,173.9 7,819.2 1,173.0 7,829.2 1,174.9 7,823.5 1,172.6 7,845.6 1,172.5 7,839.1 1,172.2 7,856.3 1,172.7 7,866.8 1,173.3 889.0 947.2 947.8 954.0 964.5 971.3 979.4 993.3 992.3 991.9 983.3 986.1 973.8 977.5 977.8 Architectural and engineering services…………………………… 1,385.7 1,436.0 1,436.5 1,439.0 1,443.2 1,451.1 1,453.9 1,460.4 1,460.5 1,463.0 1,461.8 1,464.9 1,464.9 1,469.3 1,471.4 Professional and technical Accounting and bookkeeping services…………………………… . See notes at end of table 78 Monthly Labor Review • September 2008 12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Industry Annual average 2007 2008 2006 2007 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp 1,284.6 1,359.8 1,366.8 1,371.2 1,375.5 1,380.0 1,387.5 1,391.4 1,391.6 1,393.5 1,391.3 1,403.9 1,408.9 1,412.2 1,419.3 886.4 952.8 946.6 956.3 967.2 974.8 985.1 994.3 989.2 992.7 997.0 1,001.3 1,006.9 1,015.2 1,019.3 1,810.9 1,846.0 1,845.0 1,849.2 1,854.7 1,860.9 1,850.0 1,847.8 1,845.5 1,844.7 1,839.7 1,841.0 1,836.4 1,836.8 1,832.8 Administrative and waste services…………………………… 8,398.3 Administrative and support 8,453.6 8,448.6 8,441.3 8,415.3 8,449.6 8,444.1 8,462.8 8,436.2 8,398.6 8,351.2 8,344.4 8,306.0 8,250.0 8,219.6 8,096.7 3,600.9 2,605.1 805.5 8,092.2 3,584.6 2,596.5 805.5 8,083.4 3,570.2 2,589.4 803.8 8,057.4 3,533.0 2,565.1 802.7 8,092.2 3,567.7 2,592.0 798.5 8,081.4 3,563.9 2,583.7 798.9 8,099.3 3,566.9 2,578.5 803.7 8,070.8 3,562.1 2,574.6 797.4 8,036.1 3,531.6 2,536.8 796.6 7,987.3 3,483.7 2,506.0 794.1 7,978.9 3,462.2 2,487.1 792.8 7,939.8 3,421.8 2,451.6 789.2 7,883.9 3,366.2 2,418.6 786.9 7,853.4 3,332.0 2,389.6 786.3 Computer systems design and related services………… Management and technical consulting services…………… Management of companies and enterprises……..………..... services 1……………………… 8,050.2 Employment services 1……… 3,680.9 Temporary help services…… 2,637.4 792.9 Business support services…… Services to buildings and dwellings………………… 1,801.4 1,851.2 1,854.9 1,858.0 1,863.2 1,866.3 1,861.1 1,872.0 1,861.3 1,859.7 1,857.3 1,864.6 1,865.9 1,869.3 1,867.9 Waste management and remediation services…………. 348.1 356.9 356.4 357.9 357.9 357.4 362.7 363.5 365.4 362.5 363.9 365.5 366.2 366.1 366.2 17,826 2,900.9 18,327 2,949.1 18,360 2,962.7 18,422 2,981.3 18,451 2,967.7 18,490 2,974.9 18,522 2,975.5 18,568 2,984.5 18,617 3,003.4 18,665 3,009.6 18,709 3,018.6 18,757 3,030.5 18,820 3,047.3 18,875 3,080.8 18,914 3,086.1 Educational and health services………………...………. Educational services…….……… Health care and social assistance……….……………… 14,925.3 15,377.6 15,396.8 15,440.8 15,483.0 15,515.1 15,546.7 15,583.2 15,613.6 15,655.0 15,690.5 15,726.1 15,772.4 15,794.0 15,828.3 Ambulatory health care services 1……………………… 5,285.8 Offices of physicians…………… 2,147.8 Outpatient care centers……… 492.6 865.6 Home health care services…… Hospitals………………………… 4,423.4 5,477.1 2,204.0 507.1 913.3 4,517.3 5,484.7 2,204.7 505.0 917.7 4,524.2 5,504.4 2,211.7 507.2 923.0 4,533.4 5,523.1 2,219.1 509.3 925.2 4,541.6 5,547.3 2,226.1 511.4 930.3 4,549.7 5,554.8 2,232.2 511.0 929.1 4,558.8 5,566.0 2,235.6 513.0 930.9 4,572.4 5,581.7 2,240.8 511.5 934.7 4,579.3 5,600.0 2,248.2 512.0 939.5 4,592.8 5,612.5 2,251.7 511.9 943.3 4,606.4 5,632.8 2,259.6 514.9 946.1 4,616.2 5,649.9 2,265.2 516.6 951.0 4,635.0 5,667.3 2,272.8 516.8 954.6 4,640.2 5,688.5 2,279.3 520.6 959.6 4,650.6 2,952.0 1,600.8 2,431.2 849.2 13,474 2,954.9 1,602.2 2,433.0 847.7 13,476 2,960.0 1,604.8 2,443.0 850.7 13,494 2,962.8 1,604.3 2,455.5 857.4 13,552 2,963.1 1,603.1 2,455.0 853.3 13,604 2,967.5 1,605.9 2,465.6 856.7 13,628 2,971.2 1,608.2 2,473.6 857.1 13,635 2,974.6 1,608.8 2,478.0 859.2 13,644 2,979.9 1,613.3 2,482.3 858.6 13,660 2,983.4 1,609.6 2,488.2 861.8 13,676 2,987.3 1,610.7 2,489.8 858.1 13,690 2,989.8 1,612.1 2,497.7 860.2 13,679 2,991.5 1,611.7 2,495.0 850.5 13,686 2,992.8 1,611.8 2,496.4 845.5 13,687 Nursing and residential care facilities 1………………… 2,892.5 Nursing care facilities………… 1,581.4 Social assistance 1……………… 2,323.5 818.3 Child day care services……… Leisure and hospitality……….. 13,110 Arts, entertainment, and recreation……….…….…… 1,928.5 1,977.5 1,968.8 1,970.5 1,985.3 1,996.4 2,001.4 2,010.3 2,016.1 2,019.1 2,025.7 2,021.1 2,013.1 2,008.2 2,005.5 Performing arts and spectator sports………………… 398.5 412.4 405.8 409.2 414.3 419.0 426.4 429.9 429.5 431.0 433.9 436.4 434.7 436.8 434.9 Museums, historical sites, zoos, and parks………………… 123.8 130.2 131.9 131.1 131.6 131.9 131.6 131.5 132.6 131.7 133.4 132.6 133.9 132.1 131.5 1,406.3 1,434.9 1,431.1 1,430.2 1,439.4 1,445.5 1,443.4 1,448.9 1,454.0 1,456.4 1,458.4 1,452.1 1,444.5 1,439.3 1,439.1 Amusements, gambling, and recreation……………………… Accommodations and food services…………………… 11,181.1 11,496.3 11,507.0 11,523.6 11,567.0 11,607.5 11,626.8 11,624.7 11,628.0 11,640.7 11,650.7 11,668.7 11,665.8 11,677.4 11,681.1 Accommodations………………. 1,832.1 1,856.4 1,853.6 1,844.1 1,856.4 1,863.6 1,870.3 1,858.1 1,854.9 1,854.4 1,849.4 1,853.0 1,849.0 1,849.2 1,849.7 Food services and drinking places…………………………… 9,349.0 Other services…………………… 5,438 Repair and maintenance……… 1,248.5 Personal and laundry services 1,288.4 9,639.9 5,491 1,257.0 1,305.2 9,653.4 5,501 1,257.8 1,307.9 9,679.5 5,497 1,259.6 1,305.7 9,710.6 5,495 1,262.5 1,304.4 9,743.9 5,496 1,260.1 1,303.4 9,756.5 5,506 1,258.0 1,309.7 9,766.6 5,507 1,255.5 1,306.9 9,773.1 5,508 1,252.9 1,306.6 9,786.3 5,517 1,255.2 1,306.4 9,801.3 5,522 1,254.8 1,308.5 9,815.7 5,525 1,254.0 1,309.9 9,816.8 5,527 1,251.7 1,310.6 9,828.2 5,521 1,246.1 1,312.2 9,831.4 5,527 1,245.2 1,313.3 Membership associations and organizations…………………… 2,901.2 Government.................................. Federal........................................ Federal, except U.S. Postal Service.................................... U.S. Postal Service……………… State........................................... Education................................ Other State government.......... Local........................................... Education................................ Other local government........... 2,928.8 2,935.4 2,931.2 2,927.6 2,932.8 2,938.0 2,944.4 2,948.9 2,955.6 2,959.0 2,961.4 2,964.3 2,963.1 2,968.1 21,974 2,732 22,203 2,727 22,170 2,726 22,212 2,724 22,227 2,721 22,262 2,722 22,278 2,728 22,333 2,735 22,336 2,717 22,362 2,725 22,377 2,726 22,401 2,734 22,453 2,740 22,496 2,742 22,521 2,739 1,962.6 769.7 5,075 2,292.5 2,782.0 14,167 7,913.0 6,253.8 1,964.6 762.3 5,125 2,318.4 2,806.6 14,351 7,976.6 6,374.5 1,964.3 761.6 5,123 2,313.8 2,808.8 14,321 7,938.2 6,382.5 1,963.4 760.6 5,123 2,313.6 2,809.5 14,365 7,972.0 6,393.4 1,961.4 759.3 5,138 2,327.7 2,810.3 14,368 7,970.6 6,397.5 1,963.5 758.3 5,138 2,325.9 2,812.4 14,402 7,994.6 6,406.9 1,966.7 761.7 5,131 2,314.3 2,816.5 14,419 7,999.6 6,419.2 1,972.3 763.1 5,153 2,332.5 2,820.9 14,445 8,016.5 6,428.2 1,977.3 739.7 5,159 2,335.1 2,824.0 14,460 8,018.0 6,441.5 1,982.9 741.6 5,158 2,332.9 2,824.9 14,479 8,031.9 6,447.5 1,986.6 739.1 5,157 2,332.9 2,823.8 14,494 8,035.7 6,457.8 1,996.0 737.9 5,170 2,340.8 2,829.1 14,497 8,032.1 6,465.0 2,006.5 733.3 5,174 2,344.4 2,829.7 14,539 8,060.0 6,479.2 2,011.2 730.8 5,186 2,352.3 2,833.8 14,568 8,075.0 6,493.0 2,010.5 728.6 5,198 2,359.0 2,838.9 14,584 8,077.2 6,506.5 1 Includes other industries not shown separately. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. Monthly Labor Review • September 2008 79 Current Labor Statistics: Labor Force Data 13. Average weekly hours of production or nonsupervisory workers1 on private nonfarm payrolls, by industry, monthly data seasonally adjusted Industry Annual average 2006 2007 2007 2008 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp TOTAL PRIVATE………………………… 33.9 33.8 33.8 33.8 33.8 33.8 33.8 33.8 33.7 33.7 33.8 33.8 33.7 33.7 GOODS-PRODUCING……………………… 40.5 40.6 40.6 40.6 40.6 40.6 40.7 40.5 40.4 40.4 40.5 40.4 40.2 40.3 40.3 Natural resources and mining…………… 45.6 45.9 45.9 45.7 46.2 46.0 46.2 45.8 45.7 45.7 46.2 44.9 44.6 45.0 44.9 Construction………………………………… 39.0 39.0 38.9 38.8 38.9 39.0 39.1 39.0 38.8 38.7 38.9 38.9 38.5 38.7 38.7 Manufacturing…………………….............. Overtime hours.................................. 41.1 4.4 41.2 4.2 41.4 4.2 41.3 4.2 41.4 4.2 41.2 4.1 41.3 4.1 41.1 4.0 41.1 4.0 41.1 4.0 41.2 4.0 41.0 4.0 41.0 3.9 41.0 3.8 41.0 3.8 Durable goods..…………………............ Overtime hours.................................. Wood products..................................... Nonmetallic mineral products............... Primary metals..................................... Fabricated metal products................... Machinery………………………………… Computer and electronic products…… Electrical equipment and appliances… Transportation equipment.................... Furniture and related products……….. Miscellaneous manufacturing.............. 41.4 4.4 39.8 43.0 43.6 41.4 42.4 40.5 41.0 42.7 38.8 38.7 41.5 4.2 39.4 42.3 42.9 41.6 42.6 40.6 41.2 42.8 39.2 38.9 41.6 4.2 39.9 42.6 43.2 41.7 42.5 40.3 41.4 43.3 39.2 39.2 41.7 4.2 39.6 42.8 43.0 41.7 42.6 40.6 41.2 43.1 39.7 39.4 41.6 4.2 39.7 42.7 42.6 41.9 42.7 40.6 41.2 42.8 39.4 39.7 41.5 4.1 39.5 42.6 42.6 41.7 42.9 40.6 40.7 42.7 39.1 39.0 41.5 4.1 39.0 42.9 42.7 41.7 42.9 40.9 41.2 42.6 38.9 38.8 41.3 4.0 39.2 41.5 42.2 41.6 42.9 40.5 41.6 42.1 39.1 38.8 41.4 4.1 39.0 42.2 42.5 41.6 43.1 40.4 41.4 42.6 38.3 39.0 41.4 4.1 39.0 42.1 42.4 41.7 43.0 40.5 41.1 42.9 38.2 38.8 41.5 4.0 38.7 43.1 42.9 41.7 42.7 41.0 41.3 42.3 38.7 39.3 41.3 4.0 38.8 42.2 42.4 41.6 42.5 41.1 41.1 42.3 38.7 39.3 41.2 3.9 39.1 42.3 42.2 41.4 42.1 41.2 41.1 42.1 38.8 39.2 41.2 3.8 39.3 42.1 42.5 41.2 42.1 41.2 41.0 42.2 39.0 39.2 41.3 3.8 39.0 42.6 42.2 41.2 42.2 41.2 40.8 42.6 38.4 39.3 Nondurable goods.................................. Overtime hours.................................. Food manufacturing............................… Beverage and tobacco products.......... Textile mills……………………………… Textile product mills…………………… Apparel................................................. Leather and allied products.................. Paper and paper products……………… 40.6 4.4 40.1 40.8 40.6 39.8 36.5 38.9 42.9 40.8 4.1 40.7 40.8 40.3 39.7 37.2 38.1 43.2 40.9 4.1 40.8 40.7 40.2 40.8 37.5 37.5 43.0 40.8 4.1 40.6 41.0 39.9 39.9 37.2 37.7 43.1 40.9 4.1 40.7 40.8 40.4 39.9 37.2 37.9 43.2 40.8 4.1 40.8 40.6 40.2 39.2 36.6 37.7 43.3 40.9 4.1 40.6 40.5 39.9 39.1 36.9 38.1 43.7 40.8 4.0 40.4 40.8 40.2 39.9 37.5 39.1 44.0 40.6 3.9 40.5 40.5 38.7 38.6 36.7 38.2 44.0 40.6 3.9 40.6 40.1 38.8 39.3 36.8 38.2 43.9 40.7 3.9 40.7 40.4 38.8 39.3 36.7 38.7 43.6 40.5 3.9 40.8 39.6 38.4 38.3 36.6 38.6 43.3 40.5 3.8 40.8 39.7 39.0 38.7 36.0 38.7 42.5 40.5 3.8 40.6 39.0 38.9 39.1 36.4 38.5 42.7 40.5 3.7 40.6 39.1 39.3 39.1 36.8 38.3 42.4 Printing and related support activities............................................. Petroleum and coal products…………… Chemicals………………………………… Plastics and rubber products…………… 39.2 45.0 42.5 40.6 39.1 44.2 41.9 41.3 38.8 44.0 42.2 41.5 39.1 43.7 42.1 41.3 38.9 43.4 42.0 41.6 38.8 42.9 41.7 41.7 39.0 43.8 42.1 42.1 38.8 44.0 41.5 41.4 38.4 43.8 41.6 41.1 38.2 43.6 41.4 41.2 38.6 43.5 41.9 41.1 38.5 43.2 41.3 41.0 38.5 44.2 41.3 41.0 38.1 44.4 41.8 41.1 38.0 45.2 41.8 41.3 PRIVATE SERVICEPROVIDING……………………………… 32.5 32.4 32.4 32.4 32.4 32.4 32.4 32.4 32.4 32.3 32.4 32.4 32.4 32.4 32.3 Trade, transportation, and utilities.......………………....................... Wholesale trade........………………....... Retail trade………………………………… Transportation and warehousing………… Utilities……………………………………… Information………………………………… Financial activities………………………… 33.4 38.0 30.5 36.9 41.4 36.6 35.7 33.3 38.2 30.2 36.9 42.4 36.5 35.9 33.2 38.1 30.1 36.8 42.6 36.6 35.9 33.3 38.2 30.1 36.9 42.4 36.4 35.8 33.3 38.2 30.2 36.9 42.5 36.5 35.7 33.2 38.1 30.1 36.7 42.2 36.2 35.7 33.3 38.1 30.2 36.8 42.5 36.2 35.8 33.3 38.3 30.1 36.8 42.8 36.3 35.8 33.4 38.4 30.2 36.6 43.1 36.3 35.8 33.3 38.2 30.1 36.7 42.8 36.2 35.8 33.4 38.4 30.2 36.7 43.3 36.6 35.8 33.4 38.3 30.2 36.7 42.6 36.5 35.9 33.3 38.3 30.1 36.5 42.4 36.6 36.0 33.3 38.3 30.1 36.5 42.8 36.6 35.9 33.2 38.4 30.0 36.4 42.3 36.7 35.7 Professional and business services…………………………………… Education and health services…………… Leisure and hospitality…………………… Other services……………........................ 34.6 32.5 25.7 30.9 34.8 32.6 25.5 30.9 34.8 32.6 25.3 30.9 34.7 32.6 25.4 30.8 34.8 32.6 25.4 30.9 34.8 32.6 25.4 30.8 34.7 32.6 25.3 30.9 34.8 32.6 25.3 30.8 34.7 32.6 25.3 30.8 34.6 32.6 25.3 30.8 34.8 32.7 25.3 30.9 34.8 32.6 25.4 30.8 34.8 32.7 25.3 30.8 34.8 32.6 25.3 30.8 34.8 32.6 25.2 30.8 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 80 Monthly Labor Review • September 2008 NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. 33.7 14. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry, monthly data seasonally adjusted Industry Annual average 2007 2008 2006 2007 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp TOTAL PRIVATE Current dollars……………………… Constant (1982) dollars…………… $16.76 8.24 $17.42 8.32 $17.47 8.33 $17.51 8.35 $17.57 8.35 $17.59 8.34 $17.64 8.27 $17.70 8.27 $17.75 8.26 $17.81 8.29 $17.87 8.28 $17.89 8.27 $17.95 8.24 $18.00 8.17 $18.07 8.12 GOODS-PRODUCING............................... 18.02 18.67 18.69 18.73 18.78 18.77 18.84 18.90 18.98 19.04 19.12 19.12 19.17 19.25 19.35 19.90 20.02 16.81 15.96 17.68 15.33 20.96 20.95 17.26 16.43 18.19 15.67 20.95 20.94 17.30 16.46 18.23 15.70 21.09 21.01 17.33 16.49 18.27 15.71 20.99 21.12 17.34 16.50 18.28 15.74 21.05 21.07 17.34 16.52 18.28 15.73 21.02 21.20 17.40 16.58 18.31 15.85 21.54 21.30 17.41 16.60 18.33 15.86 21.75 21.38 17.49 16.68 18.41 15.92 21.69 21.47 17.55 16.74 18.49 15.94 22.01 21.56 17.61 16.79 18.54 16.03 21.61 21.60 17.62 16.80 18.58 15.99 21.71 21.70 17.65 16.85 18.61 16.04 22.01 21.77 17.71 16.93 18.67 16.11 22.54 21.86 17.79 17.00 18.76 16.15 PRIVATE SERVICEPROVIDING..........……………….............. 16.42 17.10 17.15 17.19 17.26 17.28 17.33 17.39 17.44 17.50 17.55 17.58 17.64 17.69 17.75 Trade,transportation, and utilities………………………………….... Wholesale trade.................................... Retail trade........................................... Transportation and warehousing……… Utilities…………………………………… Information.............................................. Financial activities.................................. 15.39 18.91 12.57 17.28 27.40 23.23 18.80 15.79 19.59 12.76 17.73 27.87 23.94 19.64 15.82 19.58 12.79 17.78 27.82 23.92 19.67 15.85 19.66 12.80 17.79 27.99 23.97 19.75 15.90 19.72 12.83 17.86 28.14 24.01 19.76 15.94 19.77 12.86 17.86 28.32 24.10 19.78 15.93 19.86 12.81 17.93 28.18 24.11 19.87 16.00 19.93 12.81 18.07 28.52 24.18 19.91 16.02 19.97 12.80 18.10 28.61 24.33 20.00 16.07 20.00 12.84 18.21 28.58 24.41 20.05 16.11 20.03 12.86 18.25 28.77 24.53 20.11 16.11 20.05 12.85 18.33 28.56 24.50 20.16 16.16 20.06 12.90 18.38 28.81 24.67 20.23 16.19 20.12 12.90 18.39 29.14 24.74 20.26 16.19 20.16 12.90 18.38 28.61 24.87 20.31 Professional and business services................................................. 19.13 20.13 20.19 20.25 20.36 20.31 20.42 20.46 20.53 20.63 20.74 20.84 20.90 21.01 21.12 Education and health services................................................. Leisure and hospitality.......................... Other services......................................... 17.38 9.75 14.77 18.11 10.41 15.42 18.14 10.46 15.46 18.20 10.50 15.51 18.29 10.55 15.55 18.34 10.60 15.59 18.43 10.61 15.66 18.48 10.65 15.71 18.54 10.67 15.74 18.59 10.73 15.76 18.61 10.74 15.77 18.64 10.79 15.79 18.71 10.81 15.81 18.75 10.85 15.85 18.83 10.87 15.89 Natural resources and mining............... Construction........................................... Manufacturing......................................... Excluding overtime........................... Durable goods…………………………… Nondurable goods……………………… 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. Monthly Labor Review • September 2008 81 Current Labor Statistics: Labor Force Data 15. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry Industry Annual average 2006 TOTAL PRIVATE……………………………… $16.76 Seasonally adjusted……………………. – 2007 2007 July Aug. Sept. Oct. 2008 Nov. Dec. Jan. Feb. Mar. Apr. May Junep Julyp $17.42 $17.44 $17.42 $17.64 $17.60 $17.63 $17.75 $17.80 $17.85 $17.92 $17.91 $17.90 $17.96 $17.99 – 17.47 17.51 17.57 17.59 17.64 17.70 17.75 17.81 17.87 17.89 17.95 18.00 18.07 GOODS-PRODUCING...................................... 18.02 18.67 18.72 18.81 18.91 18.86 18.88 18.96 18.90 18.94 19.03 19.06 19.13 19.24 19.38 Natural resources and mining…………….. 19.90 20.96 20.87 20.97 20.93 21.02 20.99 21.68 21.96 21.87 22.26 21.77 21.51 21.74 22.44 Construction.………….................................. 20.02 20.95 21.02 21.13 21.32 21.25 21.26 21.38 21.24 21.35 21.43 21.48 21.60 21.69 21.92 Manufacturing…………………………………… 16.81 17.26 17.22 17.31 17.39 17.34 17.42 17.51 17.53 17.55 17.60 17.63 17.63 17.71 17.72 Durable goods..………………….................. Wood products ......................................... Nonmetallic mineral products ……………… Primary metals ......................................... Fabricated metal products ….................... Machinery …………..……………………… Computer and electronic products ........... Electrical equipment and appliances ........ Transportation equipment ........................ Furniture and related products ................. Miscellaneous manufacturing ................... 17.68 13.39 16.59 19.36 16.17 17.20 18.94 15.54 22.41 13.80 14.36 18.19 13.67 16.93 19.66 16.53 17.72 19.95 15.94 23.02 14.32 14.66 18.10 13.62 17.04 19.85 16.52 17.82 20.08 16.09 22.67 14.36 14.82 18.27 13.61 16.88 19.72 16.58 17.69 20.06 16.03 23.33 14.31 14.77 18.35 13.65 16.94 19.83 16.61 17.79 20.20 16.10 23.42 14.36 14.78 18.30 13.81 16.94 19.81 16.69 17.68 20.28 15.80 23.20 14.36 14.70 18.36 13.82 17.05 19.69 16.70 17.74 20.22 15.68 23.41 14.35 14.72 18.46 13.88 16.94 19.73 16.82 17.95 20.33 15.73 23.46 14.50 15.00 18.43 13.90 16.99 20.04 16.77 17.72 20.51 15.70 23.34 14.38 14.91 18.50 13.82 16.86 19.99 16.78 17.81 20.60 15.73 23.48 14.37 14.95 18.53 13.89 16.80 20.21 16.85 17.85 20.80 15.66 23.46 14.42 15.08 18.56 13.96 17.12 20.20 16.81 17.88 20.90 15.76 23.52 14.45 14.97 18.57 14.08 16.90 20.23 16.84 17.98 20.99 15.69 23.53 14.48 14.97 18.67 14.12 16.98 20.25 16.92 17.87 21.06 15.75 23.79 14.58 15.15 18.64 14.23 16.94 20.47 16.93 17.94 21.16 15.86 23.72 14.49 15.35 Nondurable goods………………………...... Food manufacturing ...........................…… Beverages and tobacco products ............. 15.33 13.13 18.18 15.67 13.54 18.49 15.74 13.57 18.61 15.69 13.61 17.78 15.77 13.65 18.40 15.71 13.61 18.69 15.83 13.63 19.54 15.90 13.70 19.69 15.99 13.87 19.55 15.93 13.74 19.64 16.01 13.83 19.59 16.03 13.86 19.26 16.04 13.89 19.05 16.08 13.95 18.57 16.20 14.01 18.80 12.55 11.86 10.65 11.44 18.01 15.80 24.11 19.60 14.97 13.00 11.78 11.05 12.04 18.43 16.15 25.26 19.56 15.38 13.13 11.89 11.15 12.18 18.68 16.19 25.12 19.70 15.31 13.21 11.74 11.12 12.10 18.30 16.28 25.43 19.47 15.45 13.16 11.73 11.17 12.24 18.54 16.37 25.95 19.52 15.45 12.93 11.75 11.16 12.10 18.50 16.48 24.92 19.35 15.41 13.06 11.67 11.20 12.50 18.47 16.33 26.95 19.52 15.49 13.13 11.75 11.28 12.12 18.71 16.65 25.52 19.57 15.65 13.29 11.68 11.43 12.78 18.78 16.51 26.55 19.46 15.56 13.35 11.62 11.46 12.68 18.61 16.49 26.51 19.40 15.58 13.45 11.78 11.35 12.81 18.66 16.65 27.22 19.35 15.69 13.45 11.78 11.51 12.63 18.58 16.64 27.12 19.39 15.77 13.50 11.86 11.43 12.88 18.74 16.66 27.01 19.37 15.71 13.58 11.80 11.36 12.88 18.89 16.78 27.17 19.33 15.69 13.76 11.80 11.35 12.85 19.18 16.79 27.69 19.43 15.86 Textile mills .............................................. Textile product mills ................................. Apparel ..................................................... Leather and allied products ……………… Paper and paper products ………………… Printing and related support activities…... Petroleum and coal products ……………… Chemicals …………………………………… Plastics and rubber products .................... PRIVATE SERVICEPROVIDING ……………………………………. 16.42 17.10 17.10 17.05 17.31 17.27 17.31 17.45 17.52 17.58 17.65 17.62 17.59 17.64 17.64 Trade, transportation, and utilities…….…….......................................... Wholesale trade ……………………………… Retail trade …………………………………… Transportation and warehousing …………… Utilities ………..…..….………..……………… 15.39 18.91 12.57 17.28 27.40 15.79 19.59 12.76 17.73 27.87 15.89 19.70 12.84 17.90 27.70 15.81 19.58 12.78 17.84 27.73 16.00 19.85 12.91 17.96 28.27 15.94 19.75 12.85 17.89 28.44 15.84 19.89 12.70 17.94 28.17 15.89 20.10 12.64 18.04 28.61 16.02 20.01 12.78 18.08 28.62 16.08 20.03 12.82 18.14 28.61 16.16 20.08 12.90 18.19 28.88 16.16 20.01 12.90 18.28 28.69 16.14 19.93 12.91 18.33 28.83 16.20 20.05 12.92 18.44 29.01 16.20 20.11 12.93 18.49 28.41 Information…………………………………..... 23.23 23.94 23.77 23.85 24.22 24.15 24.11 24.34 24.44 24.44 24.58 24.52 24.60 24.73 24.74 Financial activities……..……….................... 18.80 19.64 19.66 19.65 19.88 19.79 19.83 19.97 19.96 20.07 20.18 20.22 20.20 20.27 20.22 19.13 20.13 20.26 20.01 20.34 20.19 20.33 20.67 20.65 20.77 20.93 20.84 20.81 21.03 21.01 services………………………………………… 17.38 Professional and business services………………………………………… Education and health 18.11 18.18 18.20 18.33 18.33 18.42 18.51 18.61 18.58 18.62 18.63 18.64 18.68 18.87 Leisure and hospitality ……………………… 9.75 10.41 10.33 10.39 10.53 10.61 10.67 10.77 10.73 10.82 10.76 10.80 10.82 10.77 10.72 Other services…………………...................... 14.77 15.42 15.39 15.43 15.58 15.55 15.61 15.75 15.74 15.78 15.84 15.82 15.84 15.85 15.80 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 82 Monthly Labor Review • September 2008 16. Average weekly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry Industry Annual average 2006 2007 2008 May. Junep Julyp $599.99 604.68 $601.44 604.92 $612.44 606.60 $606.26 608.96 766.91 766.21 769.03 783.07 779.08 988.20 986.34 1,017.28 970.94 950.74 987.00 1,007.56 805.00 800.63 825.06 824.83 833.76 852.42 859.26 728.42 716.98 714.29 723.36 722.83 721.07 729.65 719.43 763.78 534.83 731.45 842.73 701.40 762.82 771.63 546.87 696.23 844.44 708.12 780.83 759.32 530.98 696.59 851.70 695.96 763.73 758.50 523.78 686.20 847.58 693.01 762.27 767.14 531.99 715.68 869.03 702.65 763.98 766.53 538.86 722.46 852.44 699.30 761.69 765.08 553.34 718.25 853.71 697.18 756.96 774.81 564.80 726.74 868.73 698.80 754.11 760.51 559.24 726.73 853.60 690.74 749.89 827.42 833.06 841.66 822.45 826.06 852.80 854.81 862.69 873.99 865.44 659.69 658.83 666.54 943.07 1,012.52 1,011.74 649.38 992.96 652.29 671.67 999.61 1,006.43 649.98 638.64 994.28 1,002.60 645.19 994.70 646.16 999.60 640.15 648.90 985.91 1,013.45 640.74 977.26 562.91 561.48 559.65 545.00 555.17 553.44 557.48 556.42 2007 July Aug. Sept. $589.72 – $596.45 590.49 $592.28 591.84 $603.29 593.87 $594.88 594.54 $594.13 596.23 $605.28 598.26 $592.74 598.18 $596.19 600.20 $605.70 604.01 730.16 757.06 758.16 769.33 777.20 771.37 770.30 771.67 756.00 751.92 907.95 961.78 957.93 962.52 979.52 981.63 969.74 992.94 781.21 816.06 828.19 836.75 842.14 841.50 829.14 825.27 691.02 711.36 704.30 718.37 725.16 717.88 722.93 732.00 532.99 Wood products ......................... 712.71 Nonmetallic mineral products.... Primary metals…………………… 843.59 668.98 Fabricated metal products......... Machinery………………………… 728.84 754.12 539.10 716.79 843.28 687.13 753.99 743.91 546.16 729.31 849.58 682.28 753.79 763.69 543.04 732.59 844.02 693.04 750.06 770.70 548.73 735.20 848.72 699.28 761.41 763.11 548.26 730.11 841.93 700.98 762.01 766.96 809.19 801.19 812.43 828.20 636.95 957.65 656.58 985.57 535.90 561.03 TOTAL PRIVATE………………… $567.87 Seasonally adjusted.......... – GOODS-PRODUCING…………… Natural resources and mining……………………….. CONSTRUCTION Manufacturing…………………… Durable goods…………………… Oct. Nov. Dec Jan. Feb. Mar. Apr. Computer and electronic products.................................. Electrical equipment and appliances............................... Transportation equipment……… Furniture and related products……………………….. 576.69 572.96 578.55 541.75 571.54 Miscellaneous manufacturing.......................... 555.90 569.98 573.53 581.94 588.24 574.77 571.14 589.50 580.00 575.58 594.15 586.82 583.83 595.40 597.12 Nondurable goods....................... 621.97 525.99 639.99 550.65 639.04 552.30 641.72 556.65 651.30 566.48 644.11 560.73 653.78 562.92 656.67 561.70 646.00 556.19 638.79 546.85 648.41 555.97 647.61 559.94 646.41 565.32 652.85 566.37 652.86 567.41 741.34 509.39 472.24 389.20 445.47 772.39 753.80 524.47 467.96 411.52 459.43 795.20 761.15 519.95 477.98 413.67 450.66 799.50 739.65 524.44 468.43 412.55 453.75 788.73 747.04 536.93 468.03 414.41 462.67 813.91 751.34 515.91 457.08 410.69 458.59 806.60 787.46 521.09 457.46 415.52 478.75 816.37 793.51 539.64 478.23 423.00 484.80 834.47 778.09 514.32 449.68 416.05 484.36 826.32 769.89 512.64 454.34 420.58 480.57 805.81 785.56 521.86 464.13 418.82 499.59 807.98 768.47 515.14 450.00 423.57 491.31 802.66 763.91 523.80 454.24 412.62 502.32 788.95 733.52 529.62 468.46 415.78 501.03 804.71 736.96 533.89 459.02 414.28 485.73 807.48 618.92 632.08 621.70 638.18 644.98 644.37 640.14 654.35 630.68 629.92 644.36 640.64 638.08 634.28 629.63 Food manufacturing................... Beverages and tobacco products.................................. Textile mills……………………… Textile product mills…………… Apparel…………………………… Leather and allied products....... Paper and paper products……. Printing and related support activities……………… Petroleum and coal products………………………… 1,085.50 1,115.24 1,117.84 1,106.21 1,144.40 1,074.05 1,204.67 1,099.91 1,157.58 1,134.63 1,165.02 1,163.45 1,188.44 1,228.08 1,270.97 819.99 823.46 819.69 821.79 801.09 823.74 818.03 809.54 801.22 810.77 800.81 794.17 811.86 810.23 Chemicals………………………… 833.67 Plastics and rubber products………………………… PRIVATE SERVICEPROVIDING………….................... Trade, transportation, and utilities……………………… Wholesale trade......…………...... Retail trade………………………… 608.41 635.15 624.65 635.00 647.36 642.60 652.13 657.30 639.52 637.22 644.86 646.57 644.11 649.57 645.50 532.78 554.78 560.88 554.13 567.77 557.82 559.11 570.62 558.89 564.32 573.63 567.36 566.40 578.59 571.54 514.34 718.63 383.02 526.38 748.90 385.20 535.49 758.45 392.90 529.64 747.96 388.51 542.40 768.20 396.34 529.21 752.48 386.79 525.89 757.81 382.27 535.49 779.88 385.52 525.46 758.38 379.57 529.03 759.14 380.75 538.13 775.09 387.00 534.90 764.38 385.71 534.23 761.33 387.30 545.94 779.95 394.06 541.08 770.21 391.78 Transportation and 654.83 664.09 663.65 668.11 656.56 661.99 678.30 650.88 654.85 667.57 663.56 665.38 680.44 673.04 warehousing……………………… 636.97 Utilities……………………………… 1,135.34 1,182.17 1,180.02 1,175.75 1,215.61 1,208.70 1,194.41 1,221.65 1,222.07 1,218.79 1,241.84 1,225.06 1,219.51 1,247.43 1,201.74 Information………………………… 850.42 873.63 884.24 870.53 896.14 874.23 872.78 893.28 877.40 879.84 902.09 887.62 890.52 917.48 910.43 Financial activities………………… 672.21 705.29 717.59 699.54 721.64 702.55 705.95 726.91 708.58 716.50 730.52 721.85 721.14 739.86 719.83 Professional and business services……………… 709.10 696.35 715.97 702.61 705.45 727.58 704.17 714.49 734.64 725.23 724.19 744.46 729.05 662.27 700.15 Education and Education and health services…………………… 564.94 590.18 598.12 593.32 603.06 595.73 600.49 607.13 604.83 603.85 608.87 603.61 605.80 610.84 615.16 Leisure and hospitality…………. 250.34 265.45 271.68 270.14 269.57 268.43 266.75 272.48 262.89 269.42 272.23 272.16 273.75 278.94 276.58 Other services……………………… 456.50 476.80 480.17 478.33 484.54 478.94 480.79 488.25 480.07 482.87 489.46 485.67 486.29 492.94 488.22 1 Data relate to production workers in natural resources and mining and manufacturing, NOTE: See "Notes on the data" for a description of the most recent benchmark revision. construction workers in construction, and nonsupervisory workers in the service- Dash indicates data not available. providing industries. p = preliminary. Monthly Labor Review • September 2008 83 Current Labor Statistics: Labor Force Data 17. Diffusion indexes of employment change, seasonally adjusted [In percent] Timespan and year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Private nonfarm payrolls, 278 industries Over 1-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 50.5 52.2 65.1 51.6 45.4 50.5 60.6 60.9 51.8 41.4 64.1 54.2 64.4 52.7 47.4 62.6 58.2 59.3 51.1 45.6 61.7 55.8 53.3 56.6 46.4 58.9 58.2 52.7 50.4 42.3 56.0 58.0 60.4 52.2 41.4 50.0 61.3 58.9 51.6 56.9 54.7 53.5 56.4 56.9 53.6 55.8 54.6 51.3 62.4 57.1 48.2 51.8 54.7 56.0 48.5 Over 3-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 54.4 52.2 67.2 58.4 46.7 52.9 55.5 66.2 54.7 42.7 57.3 57.5 66.6 55.3 42.3 63.5 60.8 65.5 54.7 44.0 68.8 58.9 60.6 56.2 43.1 66.6 61.9 58.2 53.3 44.0 61.3 60.4 56.0 53.1 38.3 56.4 63.9 58.9 54.7 57.7 61.1 55.7 58.4 59.5 54.4 56.4 56.8 61.9 54.9 57.1 54.7 54.6 61.3 58.4 52.4 Over 6-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 50.0 54.6 63.1 59.1 51.5 51.6 57.3 64.4 56.4 49.8 55.3 56.8 67.2 57.5 44.7 60.9 57.5 67.0 56.8 46.5 63.7 57.5 64.4 58.8 43.6 65.1 58.2 66.4 58.2 39.1 65.1 64.4 61.5 56.2 38.9 63.9 62.8 61.7 58.0 60.4 62.0 60.4 58.2 61.7 59.3 59.7 57.1 58.2 61.5 60.8 54.6 56.0 62.0 56.0 53.8 Over 12-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 40.5 60.6 67.2 62.6 53.8 42.3 60.8 65.1 59.1 54.6 45.1 59.7 65.5 60.4 52.6 48.9 58.9 62.6 58.9 50.4 51.3 58.0 64.8 59.5 49.3 58.2 60.0 66.4 58.4 45.8 57.5 60.9 64.4 57.5 45.8 55.7 63.3 64.4 58.8 57.3 60.4 66.2 61.7 58.8 58.9 65.1 60.4 60.6 59.5 64.4 59.9 60.8 61.7 65.5 57.7 Manufacturing payrolls, 84 industries Over 1-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 43.5 36.3 57.7 47.6 40.5 47.6 48.8 45.8 35.7 28.6 47.0 42.9 54.8 30.4 38.1 63.7 44.6 48.8 29.8 35.1 50.6 42.3 38.1 37.5 44.6 51.2 35.1 53.0 39.3 30.4 58.3 38.1 50.6 41.7 28.6 42.9 47.0 44.0 33.3 42.9 45.8 36.3 40.5 48.2 46.4 40.5 45.2 42.3 47.0 38.1 44.6 39.9 47.0 39.3 36.3 Over 3-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 41.1 38.1 54.8 33.9 35.7 40.5 39.3 52.4 28.6 27.4 43.5 42.3 47.6 32.1 26.8 56.5 44.6 48.8 27.4 29.2 58.9 36.3 44.6 29.8 29.8 61.3 37.5 50.6 32.7 35.7 57.7 33.3 42.9 31.0 23.8 47.0 39.9 47.6 34.5 46.4 45.8 36.3 32.1 41.7 41.7 37.5 39.3 44.6 38.7 32.1 44.0 38.7 49.4 34.5 41.7 Over 6-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 29.2 33.9 42.9 34.5 34.5 31.5 38.1 45.2 27.4 33.9 32.7 35.1 50.6 23.8 32.1 44.6 36.9 47.6 27.4 28.0 49.4 32.1 48.2 31.5 26.8 54.8 32.1 47.6 34.5 20.8 59.5 41.7 46.4 33.3 21.4 56.0 35.7 48.8 31.0 51.2 36.3 43.5 29.2 51.8 36.9 41.7 35.1 44.0 37.5 38.7 34.5 38.7 42.3 29.8 32.7 Over 12-month span: 2004............................................... 2005.............................................. 2006.............................................. 2007………………………………… 2008………………………………… 13.1 44.6 44.6 39.3 29.8 14.3 43.5 40.5 36.3 29.8 13.1 41.7 40.5 36.9 29.8 20.2 40.5 39.3 28.6 24.4 23.2 36.3 39.3 29.8 27.4 35.7 35.1 44.6 26.2 24.4 36.9 32.1 41.7 26.8 25.0 38.1 33.9 42.3 29.2 36.9 32.7 46.4 30.4 44.0 33.3 48.2 29.8 44.6 33.3 45.2 33.3 44.6 38.1 44.0 33.9 NOTE: Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment. 84 Monthly Labor Review • September 2008 See the "Definitions" in this section. See "Notes on the data" for a description of the most recent benchmark revision. Data for the two most recent months are preliminary. 18. Job openings levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region Jan. 2 Total ……………………………………………… Percent 2008 Feb. Mar. 2008 Apr. May p June Jan. July Feb. 2.7 Mar. 2.7 Apr. 2.6 May 2.6 June 2.6 2.5 p July 3,889 3,799 3,672 3,612 3,631 3,497 3,416 2.4 Total private 2………………………………… 3,449 3,350 3,225 3,192 3,185 3,073 2,983 2.9 2.8 2.7 2.7 2.7 2.6 2.5 Construction……………………………… 133 123 102 99 130 100 84 1.8 1.6 1.4 1.3 1.8 1.4 1.2 Manufacturing…………………………… 286 239 251 244 249 241 233 2.0 1.7 1.8 1.8 1.8 1.7 1.7 Trade, transportation, and utilities……… 643 598 562 550 572 539 591 2.4 2.2 2.1 2.0 2.1 2.0 2.2 Professional and business services…… 752 699 714 676 649 670 600 4.0 3.7 3.8 3.6 3.5 3.6 3.2 Education and health services………… 680 737 696 684 648 682 674 3.5 3.8 3.6 3.5 3.3 3.5 3.4 Leisure and hospitality…………………… 515 530 501 491 503 452 436 3.6 3.7 3.5 3.5 3.5 3.2 3.1 439 450 441 422 451 417 432 1.9 2.0 1.9 1.8 2.0 1.8 1.9 2.2 Industry Government………………………………… Region 3 Northeast………………………………… 662 576 602 618 600 608 588 2.5 2.2 2.3 2.3 2.3 2.3 South……………………………………… 1,536 1,485 1,386 1,364 1,386 1,440 1,360 3.0 2.9 2.7 2.7 2.7 2.8 2.7 Midwest…………………………………… 749 766 781 752 721 676 647 2.3 2.4 2.4 2.3 2.2 2.1 2.0 West……………………………………… 966 954 918 883 937 789 831 3.0 3.0 2.9 2.8 2.9 2.5 2.6 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. NOTE: The job openings level is the number of job openings on the last business day of the month; the job openings rate is the number of job openings on the last business day of the month as a percent of total employment plus job openings. P = preliminary. 19. Hires levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region Jan. Total2……………………………………………… Percent 2008 Feb. Mar. Apr. 2008 May June Julyp Jan. 3.4 Feb. 3.3 Mar. 3.3 Apr. 3.4 May 3.0 June 3.2 Julyp 4,639 4,586 4,569 4,715 4,123 4,438 4,062 3.0 Total private 2………………………………… 4,227 4,203 4,147 4,311 3,871 4,136 3,792 3.7 3.6 3.6 3.7 3.4 3.6 3.3 Construction……………………………… 319 349 350 385 286 354 267 4.3 4.7 4.8 5.3 3.9 4.9 3.7 Manufacturing…………………………… 326 285 309 300 274 285 253 2.4 2.1 2.3 2.2 2.0 2.1 1.9 Trade, transportation, and utilities……… 916 882 884 943 828 906 893 3.4 3.3 3.3 3.6 3.1 3.4 3.4 Professional and business services…… 897 780 893 858 770 889 788 5.0 4.3 5.0 4.8 4.3 5.0 4.4 Education and health services………… 516 522 501 510 479 485 473 2.8 2.8 2.7 2.7 2.5 2.6 2.5 Leisure and hospitality…………………… 824 868 801 841 847 741 775 6.0 6.4 5.9 6.1 6.2 5.4 5.7 394 387 429 407 329 340 325 1.8 1.7 1.9 1.8 1.5 1.5 1.4 2.6 Industry Government………………………………… Region 3 Northeast………………………………… 767 713 715 743 646 761 658 3.0 2.8 2.8 2.9 2.5 3.0 South……………………………………… 1,814 1,769 1,703 1,725 1,538 1,666 1,507 3.6 3.6 3.4 3.5 3.1 3.4 3.0 Midwest…………………………………… 998 944 986 986 914 966 947 3.2 3.0 3.1 3.1 2.9 3.1 3.0 1,058 1,186 1,170 1,246 1,111 1,084 1,017 3.4 3.8 3.8 4.0 3.6 3.5 3.3 West……………………………………… 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; NOTE: The hires level is the number of hires during the entire month; the hires rate is the number of hires during the entire month as a percent of total employment. p = preliminary. Monthly Labor Review • September 2008 85 Current Labor Statistics: Labor Force Data 20. Total separations levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region Jan. 2 Total ……………………………………………… Percent 2008 Feb. Mar. Apr. 2008 May June p July Jan. 3.2 Feb. 3.3 Mar. 3.2 Apr. 3.2 May 3.1 p June July 4,477 4,503 4,390 4,404 4,313 4,368 4,308 3.2 3.1 Total private 2………………………………… 4,188 4,224 4,100 4,112 4,046 4,115 4,085 3.6 3.7 3.6 3.6 3.5 3.6 3.5 Construction……………………………… 311 329 367 378 393 409 436 4.2 4.5 5.0 5.2 5.4 5.7 6.1 2.3 Industry Manufacturing…………………………… 348 350 304 390 359 353 304 2.5 2.6 2.2 2.9 2.6 2.6 Trade, transportation, and utilities……… 1,005 957 941 1,003 868 1,003 1,025 3.8 3.6 3.5 3.8 3.3 3.8 3.9 Professional and business services…… 790 861 806 739 741 799 756 4.4 4.8 4.5 4.1 4.1 4.5 4.2 Education and health services………… 447 459 449 429 434 417 465 2.4 2.5 2.4 2.3 2.3 2.2 2.5 Leisure and hospitality…………………… 800 854 776 722 801 749 674 5.9 6.2 5.7 5.3 5.8 5.5 4.9 290 278 291 295 269 259 237 1.3 1.2 1.3 1.3 1.2 1.1 1.1 2.9 Government………………………………… Region 3 Northeast………………………………… 697 770 737 709 685 658 750 2.7 3.0 2.9 2.8 2.7 2.6 South……………………………………… 1,699 1,673 1,617 1,666 1,614 1,681 1,602 3.4 3.4 3.3 3.4 3.3 3.4 3.2 Midwest…………………………………… 975 902 918 949 915 954 911 3.1 2.9 2.9 3.0 2.9 3.0 2.9 1,107 1,167 1,101 1,094 1,096 1,089 1,069 3.6 3.8 3.6 3.5 3.5 3.5 3.5 West……………………………………… 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; NOTE: The total separations level is the number of total separations during the entire month; the total separations rate is the number of total separations during the entire month as a percent of total employment. p = preliminary 21. Quits levels and rates by industry and region, seasonally adjusted Levels1 (in thousands) Industry and region Jan. Total2……………………………………………… Percent 2008 Feb. Mar. Apr. 2008 May June p July Jan. 1.8 Feb. 1.8 Mar. 1.7 Apr. 1.8 May 1.7 June Julyp 2,493 2,522 2,375 2,444 2,336 2,365 2,324 1.7 1.7 Total private 2………………………………… 2,355 2,384 2,258 2,301 2,210 2,242 2,212 2.0 2.1 2.0 2.0 1.9 1.9 1.9 Construction……………………………… 113 133 111 127 124 139 144 1.5 1.8 1.5 1.7 1.7 1.9 2.0 Manufacturing…………………………… 183 187 157 182 163 154 134 1.3 1.4 1.2 1.3 1.2 1.1 1.0 Trade, transportation, and utilities……… 598 532 535 550 495 545 561 2.2 2.0 2.0 2.1 1.9 2.1 2.1 Professional and business services…… 351 492 386 385 391 413 403 1.9 2.7 2.1 2.1 2.2 2.3 2.3 Education and health services………… 276 271 279 270 229 246 270 1.5 1.5 1.5 1.4 1.2 1.3 1.4 Leisure and hospitality…………………… 525 539 529 516 547 525 482 3.8 3.9 3.9 3.8 4.0 3.8 3.5 138 135 126 144 126 123 115 .6 .6 .6 .6 .6 .5 .5 Industry Government………………………………… Region 3 Northeast………………………………… 358 410 334 368 327 344 357 1.4 1.6 1.3 1.4 1.3 1.3 1.4 South……………………………………… 1,045 1,021 996 1,001 937 969 916 2.1 2.1 2.0 2.0 1.9 2.0 1.8 Midwest…………………………………… 502 475 491 500 485 515 536 1.6 1.5 1.6 1.6 1.5 1.6 1.7 West……………………………………… 583 632 568 575 584 539 519 1.9 2.0 1.8 1.9 1.9 1.7 1.7 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; 86 Monthly Labor Review • September 2008 NOTE: The quits level is the number of quits during the entire month; the quits rate is the number of quits during the entire month as a percent of total employment. p = preliminary. 22. Quarterly Census of Employment and Wages: 10 largest counties, third quarter 2007. County by NAICS supersector Establishments, third quarter 2007 (thousands) Average weekly wage1 Employment September 2007 (thousands) Percent change, September 2006-072 Third quarter 2007 Percent change, third quarter 2006-072 United States3 .............................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 9,012.8 8,721.6 124.7 895.5 361.4 1,916.9 144.3 871.8 1,484.6 825.8 726.7 1,162.9 291.2 136,246.9 114,790.8 1,931.5 7,774.4 13,845.4 26,299.2 3,033.1 8,123.2 18,017.6 17,506.6 13,562.6 4,433.8 21,456.1 0.9 .9 1.7 -1.0 -2.2 1.2 .0 -.7 1.7 2.9 1.9 1.2 1.0 $818 810 820 876 987 707 1,274 1,200 998 775 348 531 859 4.3 4.5 7.8 5.7 4.3 3.2 4.6 5.9 6.4 3.6 4.2 4.1 3.2 Los Angeles, CA .......................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 401.9 397.9 .5 14.3 15.2 55.3 8.8 25.2 43.4 28.2 27.1 179.8 4.0 4,191.6 3,626.2 12.7 160.4 444.7 811.9 216.3 243.7 608.9 480.4 401.1 246.0 565.4 .4 .1 5.0 -.9 (4) -.1 8.5 -2.6 -.3 1.8 1.8 .0 2.3 925 901 1,095 945 961 765 1,520 1,483 1,051 851 518 439 1,080 3.4 3.1 -8.3 5.4 (4) 2.0 -.3 (4) 6.3 ( 4) 2.8 5.8 (4) Cook, IL ........................................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 138.0 136.6 .1 12.1 7.1 27.6 2.5 15.8 28.2 13.6 11.6 13.8 1.4 2,541.5 2,232.8 1.3 98.2 237.2 472.2 58.4 215.4 441.6 369.2 240.0 95.0 308.7 .0 .2 -7.7 -1.6 -1.9 -.9 .6 -1.5 .9 1.6 2.2 .7 -.9 961 958 1,063 1,207 981 776 1,402 1,547 1,179 843 430 691 985 3.3 3.6 3.5 5.5 3.0 -.5 9.1 7.8 3.1 3.7 4.6 3.0 2.3 New York, NY ............................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 118.0 117.7 .0 2.3 3.1 22.1 4.4 18.7 24.6 8.6 11.2 17.4 .3 2,350.3 1,906.7 .1 35.8 37.5 248.2 135.6 380.0 482.2 283.3 208.5 87.2 443.5 2.0 2.3 -1.9 6.9 -4.7 1.7 1.0 2.0 2.3 2.0 3.3 1.5 .7 1,544 1,667 1,749 1,461 1,158 1,124 1,916 3,047 1,769 1,011 728 889 1,014 8.7 9.6 11.8 5.3 3.0 4.3 4.5 16.3 8.6 4.8 6.1 3.7 1.5 Harris, TX ..................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 95.1 94.5 1.5 6.6 4.6 21.7 1.3 10.5 18.9 10.0 7.3 11.0 .5 2,028.0 1,783.4 78.4 151.5 182.2 424.7 32.8 120.7 341.2 214.7 176.2 58.4 244.6 3.8 4.3 (4) 5.5 3.5 3.9 2.6 2.0 4.9 5.4 3.2 3.9 .6 1,015 1,027 2,580 968 1,290 901 1,258 1,256 1,156 824 366 595 922 6.7 7.1 (4) 6.1 7.7 6.0 9.1 7.3 7.5 1.7 2.2 7.6 3.1 Maricopa, AZ ................................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 99.3 98.6 .5 10.6 3.6 21.6 1.6 12.7 21.8 9.7 7.2 7.2 .7 1,825.1 1,605.3 8.5 165.8 132.2 374.9 30.4 148.6 316.8 198.9 177.6 50.1 219.9 .2 -.1 2.9 -7.6 -3.7 2.0 -.7 -2.4 .3 4.4 1.4 2.2 2.8 822 811 723 834 1,116 777 1,030 1,024 825 879 387 570 908 3.8 4.1 6.0 3.9 3.2 3.5 .4 .0 9.1 5.5 5.7 5.2 1.2 See footnotes at end of table. Monthly Labor Review • September 2008 87 Current Labor Statistics: Labor Force Data 22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, second quarter 2007. County by NAICS supersector Establishments, second quarter 2007 (thousands) Average weekly wage1 Employment June 2007 (thousands) Percent change, June 2006-072 Second quarter 2007 Percent change, second quarter 2006-072 Orange, CA .................................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 94.7 93.3 .2 7.1 5.4 17.8 1.4 11.4 19.2 9.8 7.0 14.0 1.4 1,519.5 1,363.2 6.2 105.6 177.1 278.2 30.1 128.1 274.6 139.6 175.1 48.4 156.3 -1.0 -1.3 -6.8 -3.5 (4) .4 -2.2 -7.7 (4) 2.9 1.7 -.4 1.1 $952 939 588 1,016 1,150 892 1,340 1,445 1,000 833 410 561 1,062 3.4 2.8 10.7 7.2 (4) (4) 7.5 (4) (4) 3.3 5.1 4.1 6.7 Dallas, TX ..................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 67.6 67.1 .6 4.4 3.2 15.0 1.7 8.7 14.4 6.6 5.2 6.4 .5 1,492.6 1,330.0 7.1 84.1 144.2 307.2 48.6 145.7 274.3 144.7 131.2 40.6 162.5 3.2 3.2 -4.7 4.4 -.4 2.3 -4.6 2.8 5.9 6.6 3.6 1.2 2.9 1,011 1,022 2,879 935 1,202 974 1,371 1,331 1,108 968 430 602 920 5.4 5.4 -1.1 1.4 8.1 6.1 7.3 5.2 5.8 6.8 2.6 2.9 5.0 San Diego, CA ............................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 91.7 90.4 .8 7.2 3.2 14.6 1.3 9.9 16.4 8.0 6.9 22.1 1.3 1,334.7 1,108.8 11.6 90.9 102.4 219.8 37.5 81.5 217.9 127.1 163.6 56.6 225.9 .2 -.1 -4.1 -6.5 (4) .3 .5 -3.3 .6 (4) 2.8 1.1 1.7 890 868 540 916 1,190 730 1,873 1,108 1,076 812 389 482 996 4.8 4.7 4.0 6.3 6.6 5.8 1.7 3.5 6.0 4.1 3.5 2.8 4.8 King, WA ...................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 75.9 75.4 .4 6.8 2.5 14.8 1.8 7.0 12.9 6.3 6.0 16.7 .5 1,182.2 1,027.6 3.3 72.9 112.0 219.5 75.8 76.4 188.1 120.6 113.7 45.4 154.6 2.9 3.3 3.4 11.0 1.9 2.0 5.0 -1.0 4.4 2.7 3.9 .9 .6 1,028 1,033 1,224 1,002 1,386 903 1,829 1,272 1,180 812 427 571 995 3.8 3.5 1.4 6.5 .8 6.1 4.1 3.3 1.1 4.5 2.4 7.9 6.0 Miami-Dade, FL ............................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 85.9 85.6 .5 6.2 2.6 23.1 1.5 10.4 17.3 8.9 5.7 7.6 .3 1,002.1 868.2 9.2 53.5 48.0 252.6 20.7 71.6 136.4 135.4 101.8 35.7 133.9 1.0 .8 .3 1.5 -1.7 .9 -.7 -.9 -1.5 3.1 1.3 1.9 2.4 814 788 496 841 735 747 1,163 1,161 949 796 458 525 969 3.8 3.7 6.0 -1.1 1.9 2.3 4.6 5.6 7.5 4.6 2.5 5.8 4.8 1 Average weekly wages were calculated using unrounded data. 2 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Notes on Current Labor Statistics. 3 88 Totals for the United States do not include data for Puerto Rico or the Monthly Labor Review • September 2008 Virgin Islands. 4 Data do not meet BLS or State agency disclosure standards. NOTE: Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. Data are preliminary. 23. Quarterly Census of Employment and Wages: by State, second quarter 2007. State Establishments, second quarter 2007 (thousands) Average weekly wage1 Employment June 2007 (thousands) Percent change, June 2006-07 Second quarter 2007 Percent change, second quarter 2006-07 United States2 ................................... 8,945.9 137,018.2 1.2 $820 4.6 Alabama ............................................ Alaska ............................................... Arizona .............................................. Arkansas ........................................... California ........................................... Colorado ........................................... Connecticut ....................................... Delaware ........................................... District of Columbia ........................... Florida ............................................... 120.1 21.1 158.9 82.7 1,291.3 179.4 112.5 29.1 31.9 604.8 1,965.4 325.8 2,612.4 1,186.5 15,832.5 2,326.9 1,714.2 430.2 683.2 7,894.2 1.1 -.5 1.2 .3 .8 2.2 .9 .0 .8 .2 697 832 786 639 935 832 1,033 870 1,357 743 3.6 5.6 4.4 4.2 5.4 4.8 6.4 2.2 4.3 3.2 Georgia ............................................. Hawaii ............................................... Idaho ................................................. Illinois ................................................ Indiana .............................................. Iowa .................................................. Kansas .............................................. Kentucky ........................................... Louisiana ........................................... Maine ................................................ 270.4 38.6 57.1 358.6 158.2 93.4 85.7 109.8 119.9 50.0 4,091.5 631.2 679.1 5,956.3 2,933.4 1,518.6 1,370.7 1,828.2 1,880.2 619.6 1.4 1.4 3.0 .8 .5 .9 2.0 1.7 3.2 .6 792 736 626 874 702 664 702 700 711 658 6.5 4.2 2.3 4.4 2.6 3.9 4.8 4.2 4.1 4.1 Maryland ........................................... Massachusetts .................................. Michigan ............................................ Minnesota ......................................... Mississippi ......................................... Missouri ............................................. Montana ............................................ Nebraska ........................................... Nevada .............................................. New Hampshire ................................ 164.0 210.1 257.1 170.7 69.7 174.7 42.3 58.7 74.7 49.0 2,584.9 3,300.7 4,252.9 2,730.9 1,137.4 2,764.6 449.8 930.9 1,297.9 643.7 .7 1.2 -1.4 .0 .9 .8 1.7 1.6 1.0 .7 899 1,008 807 834 609 727 611 654 776 823 5.3 4.8 2.9 5.6 3.6 3.4 6.3 3.5 3.7 6.3 New Jersey ....................................... New Mexico ...................................... New York .......................................... North Carolina ................................... North Dakota ..................................... Ohio .................................................. Oklahoma .......................................... Oregon .............................................. Pennsylvania ..................................... Rhode Island ..................................... 278.1 53.7 576.8 251.0 25.1 290.5 99.1 130.8 338.7 36.1 4,066.7 833.3 8,688.8 4,090.5 347.7 5,384.6 1,538.5 1,761.6 5,740.3 492.9 .4 1.1 1.3 3.0 1.5 -.1 1.6 1.7 1.1 .3 989 686 1,020 718 619 740 665 742 802 774 4.3 5.2 5.9 4.1 4.7 3.4 4.1 4.5 4.6 2.5 South Carolina .................................. South Dakota .................................... Tennessee ........................................ Texas ................................................ Utah .................................................. Vermont ............................................ Virginia .............................................. Washington ....................................... West Virginia ..................................... Wisconsin .......................................... 115.8 30.1 140.7 548.7 86.3 24.7 227.4 216.7 48.7 158.2 1,917.4 404.3 2,768.7 10,296.1 1,233.7 306.6 3,731.5 2,989.8 717.1 2,845.8 3.0 2.1 .7 3.4 4.4 -.5 1.0 2.7 .3 .4 665 590 729 827 698 698 859 835 659 709 2.9 4.8 3.6 5.9 6.6 5.0 4.4 4.6 3.6 3.7 Wyoming ........................................... 24.4 288.3 3.3 739 8.0 Puerto Rico ....................................... Virgin Islands .................................... 56.9 3.4 1,020.7 46.9 -1.6 3.4 460 707 6.0 4.1 1 2 Average weekly wages were calculated using unrounded data. Totals for the United States do not include data for Puerto Rico or the Virgin Islands. NOTE: Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. Data are preliminary. Monthly Labor Review • September 2008 89 Current Labor Statistics: Labor Force Data 24. Annual data: Quarterly Census of Employment and Wages, by ownership Year Average establishments Average annual employment Total annual wages (in thousands) Average annual wage per employee Average weekly wage Total covered (UI and UCFE) 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 7,369,473 7,634,018 7,820,860 7,879,116 7,984,529 8,101,872 8,228,840 8,364,795 8,571,144 8,784,027 121,044,432 124,183,549 127,042,282 129,877,063 129,635,800 128,233,919 127,795,827 129,278,176 131,571,623 133,833,834 $3,674,031,718 3,967,072,423 4,235,579,204 4,587,708,584 4,695,225,123 4,714,374,741 4,826,251,547 5,087,561,796 5,351,949,496 5,692,569,465 $30,353 31,945 33,340 35,323 36,219 36,764 37,765 39,354 40,677 42,535 $584 614 641 679 697 707 726 757 782 818 $30,058 31,676 33,094 35,077 35,943 36,428 37,401 38,955 40,270 42,124 $578 609 636 675 691 701 719 749 774 810 $30,064 31,762 33,244 35,337 36,157 36,539 37,508 39,134 40,505 42,414 $578 611 639 680 695 703 721 753 779 816 $32,521 33,605 34,681 36,296 37,814 39,212 40,057 41,118 42,249 43,875 $625 646 667 698 727 754 770 791 812 844 $29,134 30,251 31,234 32,387 33,521 34,605 35,669 36,805 37,718 39,179 $560 582 601 623 645 665 686 708 725 753 $42,732 43,688 44,287 46,228 48,940 52,050 54,239 57,782 59,864 62,274 $822 840 852 889 941 1,001 1,043 1,111 1,151 1,198 UI covered 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 7,317,363 7,586,767 7,771,198 7,828,861 7,933,536 8,051,117 8,177,087 8,312,729 8,518,249 8,731,111 118,233,942 121,400,660 124,255,714 127,005,574 126,883,182 125,475,293 125,031,551 126,538,579 128,837,948 131,104,860 $3,553,933,885 3,845,494,089 4,112,169,533 4,454,966,824 4,560,511,280 4,570,787,218 4,676,319,378 4,929,262,369 5,188,301,929 5,522,624,197 Private industry covered 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 7,121,182 7,381,518 7,560,567 7,622,274 7,724,965 7,839,903 7,963,340 8,093,142 8,294,662 8,505,496 102,175,161 105,082,368 107,619,457 110,015,333 109,304,802 107,577,281 107,065,553 108,490,066 110,611,016 112,718,858 $3,071,807,287 3,337,621,699 3,577,738,557 3,887,626,769 3,952,152,155 3,930,767,025 4,015,823,311 4,245,640,890 4,480,311,193 4,780,833,389 State government covered 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 65,352 67,347 70,538 65,096 64,583 64,447 64,467 64,544 66,278 66,921 4,214,451 4,240,779 4,296,673 4,370,160 4,452,237 4,485,071 4,481,845 4,484,997 4,527,514 4,565,908 $137,057,432 142,512,445 149,011,194 158,618,365 168,358,331 175,866,492 179,528,728 184,414,992 191,281,126 200,329,294 Local government covered 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 130,829 137,902 140,093 141,491 143,989 146,767 149,281 155,043 157,309 158,695 11,844,330 12,077,513 12,339,584 12,620,081 13,126,143 13,412,941 13,484,153 13,563,517 13,699,418 13,820,093 $345,069,166 365,359,945 385,419,781 408,721,690 440,000,795 464,153,701 480,967,339 499,206,488 516,709,610 541,461,514 Federal government covered (UCFE) 1997 .................................................. 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 52,110 47,252 49,661 50,256 50,993 50,755 51,753 52,066 52,895 52,916 NOTE: Data are final. Detail may not add to total due to rounding. 90 Monthly Labor Review • September 2008 2,810,489 2,782,888 2,786,567 2,871,489 2,752,619 2,758,627 2,764,275 2,739,596 2,733,675 2,728,974 $120,097,833 121,578,334 123,409,672 132,741,760 134,713,843 143,587,523 149,932,170 158,299,427 163,647,568 169,945,269 25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, private ownership, by supersector, first quarter 2006 Size of establishments Industry, establishments, and employment Total Fewer than 5 workers1 5 to 9 workers 10 to 19 workers 20 to 49 workers 50 to 99 workers 100 to 249 workers 250 to 499 workers 500 to 999 workers 1,000 or more workers Total all industries2 Establishments, first quarter .................. Employment, March ............................... 8,413,125 111,001,540 5,078,506 7,540,432 Natural resources and mining Establishments, first quarter .................. Employment, March ............................... 123,076 1,631,257 69,188 111,354 23,230 153,676 15,106 203,446 9,842 296,339 3,177 216,952 1,783 267,612 516 177,858 175 115,367 59 88,653 Construction Establishments, first quarter .................. Employment, March ............................... 861,030 7,299,087 558,318 823,891 141,743 929,155 84,922 1,140,245 52,373 1,565,409 15,118 1,027,718 6,762 994,696 1,358 454,918 337 220,788 99 142,267 Manufacturing Establishments, first quarter .................. Employment, March ............................... 362,959 14,098,486 137,311 240,304 61,852 415,575 55,135 757,991 53,364 1,662,309 25,712 1,798,423 19,573 3,006,794 6,423 2,207,979 2,469 1,668,696 1,120 2,340,415 Trade, transportation, and utilities Establishments, first quarter .................. Employment, March ............................... 1,880,255 25,612,515 999,688 1,663,203 380,100 2,529,630 245,926 3,293,292 158,053 4,772,401 53,502 3,695,250 33,590 5,001,143 7,071 2,419,416 1,796 1,166,322 529 1,071,858 Information Establishments, first quarter .................. Employment, March ............................... 142,974 3,037,124 81,209 113,399 21,094 140,632 16,356 223,171 13,313 411,358 5,553 384,148 3,568 544,418 1,141 392,681 512 355,421 228 471,896 Financial activities Establishments, first quarter .................. Employment, March ............................... 836,365 8,102,371 541,333 874,114 151,952 1,002,449 80,853 1,068,474 40,558 1,206,411 12,146 832,505 6,245 936,343 1,890 655,392 928 641,926 460 884,757 Professional and business services Establishments, first quarter .................. Employment, March ............................... 1,403,142 17,162,560 948,773 1,333,479 192,581 1,265,155 121,585 1,639,285 80,222 2,431,806 30,997 2,148,736 20,046 3,038,221 5,849 1,995,309 2,169 1,469,170 920 1,841,399 Education and health services Establishments, first quarter .................. Employment, March ............................... 787,747 16,838,748 375,326 684,886 175,191 1,163,519 112,455 1,512,272 72,335 2,177,055 26,364 1,835,664 18,400 2,754,731 4,106 1,400,469 1,832 1,282,903 1,738 4,027,249 Leisure and hospitality Establishments, first quarter .................. Employment, March ............................... 699,767 12,633,387 270,143 430,588 118,147 796,935 128,663 1,802,270 131,168 3,945,588 38,635 2,583,745 10,459 1,475,115 1,602 540,014 648 437,645 302 621,487 Other services Establishments, first quarter .................. Employment, March ............................... 1,121,269 4,326,368 912,768 1,087,667 118,306 771,276 56,724 747,842 24,734 718,557 5,570 377,961 2,629 388,231 418 139,473 99 63,337 21 32,024 1 Includes establishments that reported no workers in March 2006. 2 Includes data for unclassified establishments, not shown separately. 1,392,481 919,182 636,264 216,815 123,061 30,375 9,219,319 12,406,793 19,195,647 14,903,811 18,408,166 10,383,792 10,965 5,476 7,421,575 11,522,005 NOTE: Data are final. Detail may not add to total due to rounding. Monthly Labor Review • September 2008 91 Current Labor Statistics: Labor Force Data 26. Average annual wages for 2005 and 2006 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 2006 Metropolitan areas4 .............................................................. $42,253 $44,165 4.5 Abilene, TX ............................................................................ Aguadilla-Isabela-San Sebastian, PR ................................... Akron, OH .............................................................................. Albany, GA ............................................................................ Albany-Schenectady-Troy, NY .............................................. Albuquerque, NM ................................................................... Alexandria, LA ....................................................................... Allentown-Bethlehem-Easton, PA-NJ .................................... Altoona, PA ............................................................................ Amarillo, TX ........................................................................... 27,876 18,717 37,471 31,741 39,201 35,665 30,114 38,506 29,642 31,954 29,842 19,277 38,088 32,335 41,027 36,934 31,329 39,787 30,394 33,574 7.1 3.0 1.6 1.9 4.7 3.6 4.0 3.3 2.5 5.1 Ames, IA ................................................................................ Anchorage, AK ...................................................................... Anderson, IN .......................................................................... Anderson, SC ........................................................................ Ann Arbor, MI ........................................................................ Anniston-Oxford, AL .............................................................. Appleton, WI .......................................................................... Asheville, NC ......................................................................... Athens-Clarke County, GA .................................................... Atlanta-Sandy Springs-Marietta, GA ..................................... 33,889 41,712 31,418 29,463 45,820 31,231 34,431 30,926 32,512 44,595 35,331 42,955 32,184 30,373 47,186 32,724 35,308 32,268 33,485 45,889 4.3 3.0 2.4 3.1 3.0 4.8 2.5 4.3 3.0 2.9 Atlantic City, NJ ..................................................................... Auburn-Opelika, AL ............................................................... Augusta-Richmond County, GA-SC ...................................... Austin-Round Rock, TX ......................................................... Bakersfield, CA ...................................................................... Baltimore-Towson, MD .......................................................... Bangor, ME ............................................................................ Barnstable Town, MA ............................................................ Baton Rouge, LA ................................................................... Battle Creek, MI ..................................................................... 36,735 29,196 34,588 43,500 34,165 43,486 30,707 35,123 34,523 37,994 38,018 30,468 35,638 45,737 36,020 45,177 31,746 36,437 37,245 39,362 3.5 4.4 3.0 5.1 5.4 3.9 3.4 3.7 7.9 3.6 Bay City, MI ........................................................................... Beaumont-Port Arthur, TX ..................................................... Bellingham, WA ..................................................................... Bend, OR ............................................................................... Billings, MT ............................................................................ Binghamton, NY .................................................................... Birmingham-Hoover, AL ........................................................ Bismarck, ND ......................................................................... Blacksburg-Christiansburg-Radford, VA ................................ Bloomington, IN ..................................................................... 33,572 36,530 31,128 31,492 31,748 33,290 39,353 31,504 32,196 30,080 35,094 39,026 32,618 33,319 33,270 35,048 40,798 32,550 34,024 30,913 4.5 6.8 4.8 5.8 4.8 5.3 3.7 3.3 5.7 2.8 Bloomington-Normal, IL ......................................................... Boise City-Nampa, ID ............................................................ Boston-Cambridge-Quincy, MA-NH ...................................... Boulder, CO ........................................................................... Bowling Green, KY ................................................................ Bremerton-Silverdale, WA ..................................................... Bridgeport-Stamford-Norwalk, CT ......................................... Brownsville-Harlingen, TX ..................................................... Brunswick, GA ....................................................................... Buffalo-Niagara Falls, NY ...................................................... 39,404 34,623 54,199 49,115 31,306 36,467 71,095 24,893 30,902 35,302 41,359 36,734 56,809 50,944 32,529 37,694 74,890 25,795 32,717 36,950 5.0 6.1 4.8 3.7 3.9 3.4 5.3 3.6 5.9 4.7 Burlington, NC ....................................................................... Burlington-South Burlington, VT ............................................ Canton-Massillon, OH ........................................................... Cape Coral-Fort Myers, FL .................................................... Carson City, NV ..................................................................... Casper, WY ........................................................................... Cedar Rapids, IA ................................................................... Champaign-Urbana, IL .......................................................... Charleston, WV ..................................................................... Charleston-North Charleston, SC .......................................... 31,084 38,582 32,080 35,649 38,428 34,810 37,902 33,278 35,363 33,896 32,835 40,548 33,132 37,065 40,115 38,307 38,976 34,422 36,887 35,267 5.6 5.1 3.3 4.0 4.4 10.0 2.8 3.4 4.3 4.0 Charlotte-Gastonia-Concord, NC-SC .................................... Charlottesville, VA ................................................................. Chattanooga, TN-GA ............................................................. Cheyenne, WY ...................................................................... Chicago-Naperville-Joliet, IL-IN-WI ....................................... Chico, CA .............................................................................. Cincinnati-Middletown, OH-KY-IN ......................................... Clarksville, TN-KY ................................................................. Cleveland, TN ........................................................................ Cleveland-Elyria-Mentor, OH ................................................. 43,728 37,392 33,743 32,208 46,609 30,007 40,343 29,870 32,030 39,973 45,732 39,051 35,358 35,306 48,631 31,557 41,447 30,949 33,075 41,325 4.6 4.4 4.8 9.6 4.3 5.2 2.7 3.6 3.3 3.4 Coeur d’Alene, ID .................................................................. College Station-Bryan, TX ..................................................... Colorado Springs, CO ........................................................... Columbia, MO ........................................................................ Columbia, SC ........................................................................ Columbus, GA-AL .................................................................. Columbus, IN ......................................................................... Columbus, OH ....................................................................... Corpus Christi, TX ................................................................. Corvallis, OR ......................................................................... 28,208 29,032 37,268 31,263 33,386 31,370 38,446 39,806 32,975 39,357 29,797 30,239 38,325 32,207 35,209 32,334 40,107 41,168 35,399 40,586 5.6 4.2 2.8 3.0 5.5 3.1 4.3 3.4 7.4 3.1 See footnotes at end of table. 92 Percent change, 2005-06 2005 Monthly Labor Review • September 2008 26. Average annual wages for 2005 and 2006 for all covered workers1 by metropolitan area — Continued Average annual wages3 Metropolitan area2 Percent change, 2005-06 2005 2006 Cumberland, MD-WV ............................................................ Dallas-Fort Worth-Arlington, TX ............................................ Dalton, GA ............................................................................. Danville, IL ............................................................................. Danville, VA ........................................................................... Davenport-Moline-Rock Island, IA-IL ..................................... Dayton, OH ............................................................................ Decatur, AL ............................................................................ Decatur, IL ............................................................................. Deltona-Daytona Beach-Ormond Beach, FL ......................... $28,645 45,337 32,848 31,861 28,449 35,546 37,922 33,513 38,444 29,927 $29,859 47,525 33,266 33,141 28,870 37,559 39,387 34,883 39,375 31,197 4.2 4.8 1.3 4.0 1.5 5.7 3.9 4.1 2.4 4.2 Denver-Aurora, CO ................................................................ Des Moines, IA ...................................................................... Detroit-Warren-Livonia, MI .................................................... Dothan, AL ............................................................................. Dover, DE .............................................................................. Dubuque, IA ........................................................................... Duluth, MN-WI ....................................................................... Durham, NC ........................................................................... Eau Claire, WI ....................................................................... El Centro, CA ......................................................................... 45,940 39,760 46,790 30,253 33,132 32,414 32,638 46,743 30,763 29,879 48,232 41,358 47,455 31,473 34,571 33,044 33,677 49,314 31,718 30,035 5.0 4.0 1.4 4.0 4.3 1.9 3.2 5.5 3.1 0.5 Elizabethtown, KY ................................................................. Elkhart-Goshen, IN ................................................................ Elmira, NY ............................................................................. El Paso, TX ............................................................................ Erie, PA ................................................................................. Eugene-Springfield, OR ......................................................... Evansville, IN-KY ................................................................... Fairbanks, AK ........................................................................ Fajardo, PR ........................................................................... Fargo, ND-MN ....................................................................... 30,912 35,573 32,989 28,666 32,010 32,295 35,302 39,399 20,011 32,291 32,072 35,878 33,968 29,903 33,213 33,257 36,858 41,296 21,002 33,542 3.8 0.9 3.0 4.3 3.8 3.0 4.4 4.8 5.0 3.9 Farmington, NM ..................................................................... Fayetteville, NC ..................................................................... Fayetteville-Springdale-Rogers, AR-MO ............................... Flagstaff, AZ .......................................................................... Flint, MI .................................................................................. Florence, SC .......................................................................... Florence-Muscle Shoals, AL .................................................. Fond du Lac, WI .................................................................... Fort Collins-Loveland, CO ..................................................... Fort Smith, AR-OK ................................................................. 33,695 30,325 34,598 30,733 37,982 32,326 28,885 32,634 36,612 29,599 36,220 31,281 35,734 32,231 39,409 33,610 29,518 33,376 37,940 30,932 7.5 3.2 3.3 4.9 3.8 4.0 2.2 2.3 3.6 4.5 Fort Walton Beach-Crestview-Destin, FL .............................. Fort Wayne, IN ...................................................................... Fresno, CA ............................................................................ Gadsden, AL .......................................................................... Gainesville, FL ....................................................................... Gainesville, GA ...................................................................... Glens Falls, NY ...................................................................... Goldsboro, NC ....................................................................... Grand Forks, ND-MN ............................................................. Grand Junction, CO ............................................................... 32,976 34,717 32,266 28,438 32,992 33,828 31,710 28,316 28,138 31,611 34,409 35,641 33,504 29,499 34,573 34,765 32,780 29,331 29,234 33,729 4.3 2.7 3.8 3.7 4.8 2.8 3.4 3.6 3.9 6.7 Grand Rapids-Wyoming, MI .................................................. Great Falls, MT ...................................................................... Greeley, CO ........................................................................... Green Bay, WI ....................................................................... Greensboro-High Point, NC ................................................... Greenville, NC ....................................................................... Greenville, SC ....................................................................... Guayama, PR ........................................................................ Gulfport-Biloxi, MS ................................................................. Hagerstown-Martinsburg, MD-WV ......................................... 36,941 28,021 33,636 35,467 34,876 31,433 34,469 23,263 31,688 33,202 38,056 29,542 35,144 36,677 35,898 32,432 35,471 24,551 34,688 34,621 3.0 5.4 4.5 3.4 2.9 3.2 2.9 5.5 9.5 4.3 Hanford-Corcoran, CA ........................................................... Harrisburg-Carlisle, PA .......................................................... Harrisonburg, VA ................................................................... Hartford-West Hartford-East Hartford, CT ............................. Hattiesburg, MS ..................................................................... Hickory-Lenoir-Morganton, NC .............................................. Hinesville-Fort Stewart, GA ................................................... Holland-Grand Haven, MI ...................................................... Honolulu, HI ........................................................................... Hot Springs, AR ..................................................................... 29,989 39,144 30,366 50,154 28,568 30,090 30,062 36,362 37,654 27,024 31,148 39,807 31,522 51,282 30,059 31,323 31,416 36,895 39,009 27,684 3.9 1.7 3.8 2.2 5.2 4.1 4.5 1.5 3.6 2.4 Houma-Bayou Cane-Thibodaux, LA ...................................... Houston-Baytown-Sugar Land, TX ........................................ Huntington-Ashland, WV-KY-OH ........................................... Huntsville, AL ......................................................................... Idaho Falls, ID ....................................................................... Indianapolis, IN ...................................................................... Iowa City, IA .......................................................................... Ithaca, NY .............................................................................. Jackson, MI ........................................................................... Jackson, MS .......................................................................... 33,696 47,157 31,415 42,401 29,795 39,830 34,785 36,457 35,879 33,099 38,417 50,177 32,648 44,659 31,632 41,307 35,913 38,337 36,836 34,605 14.0 6.4 3.9 5.3 6.2 3.7 3.2 5.2 2.7 4.5 See footnotes at end of table. Monthly Labor Review • September 2008 93 Current Labor Statistics: Labor Force Data 26. Average annual wages for 2005 and 2006 for all covered workers1 by metropolitan area — Continued Average annual wages3 Metropolitan area2 2006 Jackson, TN ........................................................................... Jacksonville, FL ..................................................................... Jacksonville, NC .................................................................... Janesville, WI ........................................................................ Jefferson City, MO ................................................................. Johnson City, TN ................................................................... Johnstown, PA ....................................................................... Jonesboro, AR ....................................................................... Joplin, MO ............................................................................. Kalamazoo-Portage, MI ......................................................... $33,286 38,224 24,803 34,107 30,991 29,840 29,335 28,550 29,152 36,042 $34,477 40,192 25,854 36,732 31,771 31,058 29,972 28,972 30,111 37,099 3.6 5.1 4.2 7.7 2.5 4.1 2.2 1.5 3.3 2.9 Kankakee-Bradley, IL ............................................................ Kansas City, MO-KS .............................................................. Kennewick-Richland-Pasco, WA ........................................... Killeen-Temple-Fort Hood, TX ............................................... Kingsport-Bristol-Bristol, TN-VA ............................................ Kingston, NY .......................................................................... Knoxville, TN ......................................................................... Kokomo, IN ............................................................................ La Crosse, WI-MN ................................................................. Lafayette, IN .......................................................................... 31,802 39,749 38,453 30,028 33,568 30,752 35,724 44,462 31,029 35,176 32,389 41,320 38,750 31,511 35,100 33,697 37,216 45,808 31,819 35,380 1.8 4.0 0.8 4.9 4.6 9.6 4.2 3.0 2.5 0.6 Lafayette, LA ......................................................................... Lake Charles, LA ................................................................... Lakeland, FL .......................................................................... Lancaster, PA ........................................................................ Lansing-East Lansing, MI ...................................................... Laredo, TX ............................................................................. Las Cruces, NM ..................................................................... Las Vegas-Paradise, NV ....................................................... Lawrence, KS ........................................................................ Lawton, OK ............................................................................ 34,729 33,728 32,235 35,264 38,135 27,401 28,569 38,940 28,492 28,459 38,170 35,883 33,530 36,171 39,890 28,051 29,969 40,139 29,896 29,830 9.9 6.4 4.0 2.6 4.6 2.4 4.9 3.1 4.9 4.8 Lebanon, PA .......................................................................... Lewiston, ID-WA .................................................................... Lewiston-Auburn, ME ............................................................ Lexington-Fayette, KY ........................................................... Lima, OH ............................................................................... Lincoln, NE ............................................................................ Little Rock-North Little Rock, AR ........................................... Logan, UT-ID ......................................................................... Longview, TX ......................................................................... Longview, WA ........................................................................ 30,704 29,414 31,008 36,683 32,630 32,711 34,920 25,869 32,603 33,993 31,790 30,776 32,231 37,926 33,790 33,703 36,169 26,766 35,055 35,140 3.5 4.6 3.9 3.4 3.6 3.0 3.6 3.5 7.5 3.4 Los Angeles-Long Beach-Santa Ana, CA ............................. Louisville, KY-IN .................................................................... Lubbock, TX .......................................................................... Lynchburg, VA ....................................................................... Macon, GA ............................................................................. Madera, CA ........................................................................... Madison, WI ........................................................................... Manchester-Nashua, NH ....................................................... Mansfield, OH ........................................................................ Mayaguez, PR ....................................................................... 46,592 37,144 30,174 32,025 33,110 29,356 38,210 45,066 32,688 19,597 48,680 38,673 31,977 33,242 34,126 31,213 40,007 46,659 33,171 20,619 4.5 4.1 6.0 3.8 3.1 6.3 4.7 3.5 1.5 5.2 McAllen-Edinburg-Pharr, TX .................................................. Medford, OR .......................................................................... Memphis, TN-MS-AR ............................................................ Merced, CA ............................................................................ Miami-Fort Lauderdale-Miami Beach, FL .............................. Michigan City-La Porte, IN ..................................................... Midland, TX ........................................................................... Milwaukee-Waukesha-West Allis, WI .................................... Minneapolis-St. Paul-Bloomington, MN-WI ........................... Missoula, MT ......................................................................... 25,315 30,502 39,094 30,209 40,174 30,724 38,267 40,181 45,507 29,627 26,712 31,697 40,580 31,147 42,175 31,383 42,625 42,049 46,931 30,652 5.5 3.9 3.8 3.1 5.0 2.1 11.4 4.6 3.1 3.5 Mobile, AL .............................................................................. Modesto, CA .......................................................................... Monroe, LA ............................................................................ Monroe, MI ............................................................................ Montgomery, AL .................................................................... Morgantown, WV ................................................................... Morristown, TN ...................................................................... Mount Vernon-Anacortes, WA ............................................... Muncie, IN ............................................................................. Muskegon-Norton Shores, MI ................................................ 33,496 34,325 29,264 39,449 33,441 31,529 31,215 31,387 32,172 33,035 36,126 35,468 30,618 40,938 35,383 32,608 31,914 32,851 30,691 33,949 7.9 3.3 4.6 3.8 5.8 3.4 2.2 4.7 -4.6 2.8 Myrtle Beach-Conway-North Myrtle Beach, SC .................... Napa, CA ............................................................................... Naples-Marco Island, FL ....................................................... Nashville-Davidson--Murfreesboro, TN ................................. New Haven-Milford, CT ......................................................... New Orleans-Metairie-Kenner, LA ......................................... New York-Northern New Jersey-Long Island, NY-NJ-PA ...... Niles-Benton Harbor, MI ........................................................ Norwich-New London, CT ..................................................... Ocala, FL ............................................................................... 26,642 40,180 38,211 38,753 43,931 37,239 57,660 35,029 42,151 30,008 27,905 41,788 39,320 41,003 44,892 42,434 61,388 36,967 43,184 31,330 4.7 4.0 2.9 5.8 2.2 14.0 6.5 5.5 2.5 4.4 See footnotes at end of table. 94 Percent change, 2005-06 2005 Monthly Labor Review • September 2008 26. Average annual wages for 2005 and 2006 for all covered workers1 by metropolitan area — Continued Average annual wages3 Metropolitan area2 Percent change, 2005-06 2005 2006 Ocean City, NJ ...................................................................... Odessa, TX ............................................................................ Ogden-Clearfield, UT ............................................................. Oklahoma City, OK ................................................................ Olympia, WA .......................................................................... Omaha-Council Bluffs, NE-IA ................................................ Orlando, FL ............................................................................ Oshkosh-Neenah, WI ............................................................ Owensboro, KY ..................................................................... Oxnard-Thousand Oaks-Ventura, CA ................................... $31,033 33,475 31,195 33,142 36,230 36,329 36,466 38,820 31,379 44,597 $31,801 37,144 32,890 35,846 37,787 38,139 37,776 39,538 32,491 45,467 2.5 11.0 5.4 8.2 4.3 5.0 3.6 1.8 3.5 2.0 Palm Bay-Melbourne-Titusville, FL ........................................ Panama City-Lynn Haven, FL ............................................... Parkersburg-Marietta, WV-OH .............................................. Pascagoula, MS .................................................................... Pensacola-Ferry Pass-Brent, FL ........................................... Peoria, IL ............................................................................... Philadelphia-Camden-Wilmington, PA-NJ-DE-MD ................ Phoenix-Mesa-Scottsdale, AZ ............................................... Pine Bluff, AR ........................................................................ Pittsburgh, PA ........................................................................ 38,287 31,894 30,747 34,735 32,064 39,871 46,454 40,245 30,794 38,809 39,778 33,341 32,213 36,287 33,530 42,283 48,647 42,220 32,115 40,759 3.9 4.5 4.8 4.5 4.6 6.0 4.7 4.9 4.3 5.0 Pittsfield, MA .......................................................................... Pocatello, ID .......................................................................... Ponce, PR ............................................................................. Portland-South Portland-Biddeford, ME ................................ Portland-Vancouver-Beaverton, OR-WA ............................... Port St. Lucie-Fort Pierce, FL ................................................ Poughkeepsie-Newburgh-Middletown, NY ............................ Prescott, AZ ........................................................................... Providence-New Bedford-Fall River, RI-MA .......................... Provo-Orem, UT .................................................................... 35,807 27,686 19,660 35,857 41,048 33,235 38,187 29,295 37,796 30,395 36,707 28,418 20,266 36,979 42,607 34,408 39,528 30,625 39,428 32,308 2.5 2.6 3.1 3.1 3.8 3.5 3.5 4.5 4.3 6.3 Pueblo, CO ............................................................................ Punta Gorda, FL .................................................................... Racine, WI ............................................................................. Raleigh-Cary, NC .................................................................. Rapid City, SD ....................................................................... Reading, PA .......................................................................... Redding, CA .......................................................................... Reno-Sparks, NV ................................................................... Richmond, VA ........................................................................ Riverside-San Bernardino-Ontario, CA ................................. 30,165 31,937 37,659 39,465 28,758 36,210 32,139 38,453 41,274 35,201 30,941 32,370 39,002 41,205 29,920 38,048 33,307 39,537 42,495 36,668 2.6 1.4 3.6 4.4 4.0 5.1 3.6 2.8 3.0 4.2 Roanoke, VA ......................................................................... Rochester, MN ....................................................................... Rochester, NY ....................................................................... Rockford, IL ........................................................................... Rocky Mount, NC .................................................................. Rome, GA .............................................................................. Sacramento--Arden-Arcade--Roseville, CA ........................... Saginaw-Saginaw Township North, MI .................................. St. Cloud, MN ........................................................................ St. George, UT ...................................................................... 32,987 41,296 37,991 35,652 30,983 33,896 42,800 36,325 31,705 26,046 33,912 42,941 39,481 37,424 31,556 34,850 44,552 37,747 33,018 28,034 2.8 4.0 3.9 5.0 1.8 2.8 4.1 3.9 4.1 7.6 St. Joseph, MO-KS ................................................................ St. Louis, MO-IL ..................................................................... Salem, OR ............................................................................. Salinas, CA ............................................................................ Salisbury, MD ........................................................................ Salt Lake City, UT .................................................................. San Angelo, TX ..................................................................... San Antonio, TX .................................................................... San Diego-Carlsbad-San Marcos, CA ................................... Sandusky, OH ....................................................................... 30,009 39,985 31,289 36,067 32,240 36,857 29,530 35,097 43,824 32,631 31,253 41,354 32,764 37,974 33,223 38,630 30,168 36,763 45,784 33,526 4.1 3.4 4.7 5.3 3.0 4.8 2.2 4.7 4.5 2.7 San Francisco-Oakland-Fremont, CA ................................... San German-Cabo Rojo, PR ................................................. San Jose-Sunnyvale-Santa Clara, CA .................................. San Juan-Caguas-Guaynabo, PR ......................................... San Luis Obispo-Paso Robles, CA ........................................ Santa Barbara-Santa Maria-Goleta, CA ................................ Santa Cruz-Watsonville, CA .................................................. Santa Fe, NM ........................................................................ Santa Rosa-Petaluma, CA .................................................... Sarasota-Bradenton-Venice, FL ............................................ 58,634 18,745 71,970 23,952 33,759 39,080 38,016 33,253 40,017 33,905 61,343 19,498 76,608 24,812 35,146 40,326 40,776 35,320 41,533 35,751 4.6 4.0 6.4 3.6 4.1 3.2 7.3 6.2 3.8 5.4 Savannah, GA ....................................................................... Scranton--Wilkes-Barre, PA .................................................. Seattle-Tacoma-Bellevue, WA .............................................. Sheboygan, WI ...................................................................... Sherman-Denison, TX ........................................................... Shreveport-Bossier City, LA .................................................. Sioux City, IA-NE-SD ............................................................. Sioux Falls, SD ...................................................................... South Bend-Mishawaka, IN-MI .............................................. Spartanburg, SC .................................................................... 34,104 32,057 46,644 35,067 32,800 31,962 31,122 33,257 34,086 35,526 35,684 32,813 49,455 35,908 34,166 33,678 31,826 34,542 35,089 37,077 4.6 2.4 6.0 2.4 4.2 5.4 2.3 3.9 2.9 4.4 See footnotes at end of table. Monthly Labor Review • September 2008 95 Current Labor Statistics: Labor Force Data 26. Average annual wages for 2005 and 2006 for all covered workers1 by metropolitan area — Continued Average annual wages3 Metropolitan area2 2006 Spokane, WA ......................................................................... Springfield, IL ......................................................................... Springfield, MA ...................................................................... Springfield, MO ...................................................................... Springfield, OH ...................................................................... State College, PA .................................................................. Stockton, CA .......................................................................... Sumter, SC ............................................................................ Syracuse, NY ......................................................................... Tallahassee, FL ..................................................................... $32,621 39,299 36,791 30,124 30,814 34,109 35,030 27,469 36,494 33,548 $34,016 40,679 37,962 30,786 31,844 35,392 36,426 29,294 38,081 35,018 4.3 3.5 3.2 2.2 3.3 3.8 4.0 6.6 4.3 4.4 Tampa-St. Petersburg-Clearwater, FL .................................. Terre Haute, IN ...................................................................... Texarkana, TX-Texarkana, AR .............................................. Toledo, OH ............................................................................ Topeka, KS ............................................................................ Trenton-Ewing, NJ ................................................................. Tucson, AZ ............................................................................ Tulsa, OK ............................................................................... Tuscaloosa, AL ...................................................................... Tyler, TX ................................................................................ 36,374 30,597 31,302 35,848 33,303 52,034 35,650 35,211 34,124 34,731 38,016 31,341 32,545 37,039 34,806 54,274 37,119 37,637 35,613 36,173 4.5 2.4 4.0 3.3 4.5 4.3 4.1 6.9 4.4 4.2 Utica-Rome, NY ..................................................................... Valdosta, GA ......................................................................... Vallejo-Fairfield, CA ............................................................... Vero Beach, FL ...................................................................... Victoria, TX ............................................................................ Vineland-Millville-Bridgeton, NJ ............................................. Virginia Beach-Norfolk-Newport News, VA-NC ..................... Visalia-Porterville, CA ............................................................ Waco, TX ............................................................................... Warner Robins, GA ............................................................... 30,902 25,712 38,431 32,591 34,327 36,387 34,580 28,582 32,325 36,762 32,457 26,794 40,225 33,823 36,642 37,749 36,071 29,772 33,450 38,087 5.0 4.2 4.7 3.8 6.7 3.7 4.3 4.2 3.5 3.6 Washington-Arlington-Alexandria, DC-VA-MD-WV ............... Waterloo-Cedar Falls, IA ....................................................... Wausau, WI ........................................................................... Weirton-Steubenville, WV-OH ............................................... Wenatchee, WA ..................................................................... Wheeling, WV-OH ................................................................. Wichita, KS ............................................................................ Wichita Falls, TX .................................................................... Williamsport, PA .................................................................... Wilmington, NC ...................................................................... 55,525 33,123 33,259 30,596 27,163 29,808 35,976 29,343 30,699 31,792 58,057 34,329 34,438 31,416 28,340 30,620 38,763 30,785 31,431 32,948 4.6 3.6 3.5 2.7 4.3 2.7 7.7 4.9 2.4 3.6 Winchester, VA-WV ............................................................... Winston-Salem, NC ............................................................... Worcester, MA ....................................................................... Yakima, WA ........................................................................... Yauco, PR ............................................................................. York-Hanover, PA .................................................................. Youngstown-Warren-Boardman, OH-PA ............................... Yuba City, CA ........................................................................ Yuma, AZ ............................................................................... 33,787 36,654 41,094 27,334 17,818 36,834 32,176 32,133 27,168 34,895 37,712 42,726 28,401 19,001 37,226 33,852 33,642 28,369 3.3 2.9 4.0 3.9 6.6 1.1 5.2 4.7 4.4 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Includes data for Metropolitan Statistical Areas (MSA) as defined by OMB Bulletin No. 04-03 as of February 18, 2004. 96 Percent change, 2005-06 2005 Monthly Labor Review • September 2008 3 Each year’s total is based on the MSA definition for the specific year. Annual changes include differences resulting from changes in MSA definitions. 4 Totals do not include the six MSAs within Puerto Rico. 27. Annual data: Employment status of the population [Numbers in thousands] Employment status 1997 Civilian noninstitutional population........... Civilian labor force............................…… Labor force participation rate............... Employed............................………… Employment-population ratio.......... Unemployed............................……… Unemployment rate........................ Not in the labor force............................… 1 203,133 136,297 67.1 129,558 63.8 6,739 4.9 66,837 19981 205,220 137,673 67.1 131,463 64.1 6,210 4.5 67,547 19991 20001 20011 2002 2003 2004 2005 2006 2007 207,753 139,368 67.1 133,488 64.3 5,880 4.2 68,385 212,577 142,583 67.1 136,891 64.4 5,692 4 69,994 215,092 143,734 66.8 136,933 63.7 6,801 4.7 71,359 217,570 144,863 66.6 136,485 62.7 8,378 5.8 72,707 221,168 146,510 66.2 137,736 62.3 8,774 6 74,658 223,357 147,401 66 139,252 62.3 8,149 5.5 75,956 226,082 149,320 66 141,730 62.7 7,591 5.1 76,762 228,815 151,428 66.2 144,427 63.1 7,001 4.6 77,387 231,867 153,124 66 146,047 63 7,078 4.6 78,743 Not strictly comparable with prior years. 28. Annual data: Employment levels by industry [In thousands] Industry 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Total private employment............................… 103,113 106,021 108,686 110,996 110,707 108,828 108,416 109,814 111,899 114,184 115,717 Total nonfarm employment…………………… Goods-producing............................……… Natural resources and mining................. Construction............................…………… Manufacturing............................………… 122,776 23,886 654 5,813 17,419 125,930 24,354 645 6,149 17,560 128,993 24,465 598 6,545 17,322 131,785 24,649 599 6,787 17,263 131,826 23,873 606 6,826 16,441 130,341 22,557 583 6,716 15,259 129,999 21,816 572 6,735 14,510 131,435 21,882 591 6,976 14,315 133,703 22,190 628 7,336 14,226 136,174 22,570 684 7,689 14,197 137,969 22,378 722 7,624 14,032 Private service-providing.......................... 79,227 Trade, transportation, and utilities.......... 24,700 Wholesale trade............................……… 5,663.90 Retail trade............................………… 14,388.90 Transportation and warehousing......... 4,026.50 Utilities............................……………… 620.9 Information............................…………… 3,084 Financial activities............................…… 7,178 Professional and business services…… 14,335 Education and health services………… 14,087 11,018 Leisure and hospitality…………………… Other services…………………………… 4,825 81,667 25,186 5,795.20 14,609.30 4,168.00 613.4 3,218 7,462 15,147 14,446 11,232 4,976 84,221 25,771 5,892.50 14,970.10 4,300.30 608.5 3,419 7,648 15,957 14,798 11,543 5,087 86,346 26,225 5,933.20 15,279.80 4,410.30 601.3 3,631 7,687 16,666 15,109 11,862 5,168 86,834 25,983 5,772.70 15,238.60 4,372.00 599.4 3,629 7,807 16,476 15,645 12,036 5,258 86,271 25,497 5,652.30 15,025.10 4,223.60 596.2 3,395 7,847 15,976 16,199 11,986 5,372 86,599 25,287 5,607.50 14,917.30 4,185.40 577 3,188 7,977 15,987 16,588 12,173 5,401 87,932 25,533 5,662.90 15,058.20 4,248.60 563.8 3,118 8,031 16,395 16,953 12,493 5,409 89,709 25,959 5,764.40 15,279.60 4,360.90 554 3,061 8,153 16,954 17,372 12,816 5,395 91,615 26,231 5,897.60 15,319.30 4,465.80 548.5 3,055 8,363 17,552 17,838 13,143 5,432 93,339 26,472 6,005.30 15,382.00 4,531.20 553.5 3,087 8,446 17,920 18,377 13,565 5,472 19,909 20,307 20,790 21,118 21,513 21,583 21,621 21,804 21,990 22,252 Government…………………………………… 19,664 Monthly Labor Review • September 2008 97 Current Labor Statistics: Labor Force Data 29. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm payrolls, by industry Industry 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Private sector: Average weekly hours.......……................................. Average hourly earnings (in dollars)......................... Average weekly earnings (in dollars)........................ 34.5 12.51 431.86 34.5 13.01 448.56 34.3 13.49 463.15 34.3 14.02 481.01 34 14.54 493.79 33.9 14.97 506.72 33.7 15.37 518.06 33.7 15.69 529.09 33.8 16.13 544.33 33.9 16.76 567.87 33.8 17.41 589.36 Goods-producing: Average weekly hours............................................. Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... 41.1 13.82 568.43 40.8 14.23 580.99 40.8 14.71 599.99 40.7 15.27 621.86 39.9 15.78 630.04 39.9 16.33 651.61 39.8 16.8 669.13 40 17.19 688.17 40.1 17.6 705.31 40.5 18.02 729.87 40.5 18.64 755.73 46.2 15.57 720.11 44.9 16.2 727.28 44.2 16.33 721.74 44.4 16.55 734.92 44.6 17 757.92 43.2 17.19 741.97 43.6 17.56 765.94 44.5 18.07 803.82 45.6 18.72 853.71 45.6 19.9 908.01 45.9 20.99 962.54 Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Manufacturing: 38.9 15.67 609.48 38.8 16.23 629.75 39 16.8 655.11 39.2 17.48 685.78 38.7 18 695.89 38.4 18.52 711.82 38.4 18.95 726.83 38.3 19.23 735.55 38.6 19.46 750.22 39 20.02 781.04 38.9 20.94 814.83 Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Private service-providing: 41.7 13.14 548.22 41.4 13.45 557.12 41.4 13.85 573.17 41.3 14.32 590.65 40.3 14.76 595.19 40.5 15.29 618.75 40.4 15.74 635.99 40.8 16.15 658.59 40.7 16.56 673.37 41.1 16.8 690.83 41.2 17.23 710.51 Average weekly hours..………................................ Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... 32.8 12.07 395.51 32.8 12.61 413.5 32.7 13.09 427.98 32.7 13.62 445.74 32.5 14.18 461.08 32.5 14.59 473.8 32.4 14.99 484.81 32.3 15.29 494.22 32.4 15.74 509.58 32.5 16.42 532.84 32.4 17.09 554.47 Trade, transportation, and utilities: Average weekly hours............................................. Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... Wholesale trade: 34.3 11.9 407.57 34.2 12.39 423.3 33.9 12.82 434.31 33.8 13.31 449.88 33.5 13.7 459.53 33.6 14.02 471.27 33.6 14.34 481.14 33.5 14.58 488.42 33.4 14.92 498.43 33.4 15.4 514.61 33.4 15.82 528.22 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Retail trade: 38.8 14.41 559.39 38.6 15.07 582.21 38.6 15.62 602.77 38.8 16.28 631.4 38.4 16.77 643.45 38 16.98 644.38 37.9 17.36 657.29 37.8 17.65 667.09 37.7 18.16 685 38 18.91 718.3 38.2 19.56 747.7 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Transportation and warehousing: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Utilities: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Information: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Financial activities: 38.8 14.41 559.39 38.6 15.07 582.21 38.6 15.62 602.77 38.8 16.28 631.4 38.4 16.77 643.45 38 16.98 644.38 37.9 17.36 657.29 37.8 17.65 667.09 37.7 18.16 685 38 18.91 718.3 30.2 12.8 747.7 39.4 13.78 542.55 38.7 14.12 546.86 37.6 14.55 547.97 37.4 15.05 562.31 36.7 15.33 562.7 36.8 15.76 579.75 36.8 16.25 598.41 37.2 16.52 614.82 37 16.7 618.58 36.9 17.28 637.14 37 17.76 656.95 42 20.59 865.26 42 21.48 902.94 42 22.03 924.59 42 22.75 955.66 41.4 23.58 977.18 40.9 41.1 40.9 41.1 41.4 42.4 23.96 24.77 25.61 26.68 27.42 27.93 979.09 1,017.27 1,048.44 1,095.90 1,136.08 1,185.08 36.3 17.14 622.4 36.6 17.67 646.52 36.7 18.4 675.32 36.8 19.07 700.89 36.9 19.8 731.11 36.5 20.2 738.17 36.2 21.01 760.81 36.3 21.4 777.05 36.5 22.06 805 36.6 23.23 850.81 36.4 23.92 871.03 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Professional and business services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Education and health services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Leisure and hospitality: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Other services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 35.7 13.22 472.37 36 13.93 500.95 35.8 14.47 517.57 35.9 14.98 537.37 35.8 15.59 558.02 35.6 16.17 575.51 35.5 17.14 609.08 35.5 17.52 622.87 35.9 17.94 645.1 35.8 18.8 672.4 35.9 19.66 706.01 34.3 13.57 465.51 34.3 14.27 490 34.4 14.85 510.99 34.5 15.52 535.07 34.2 16.33 557.84 34.2 16.81 574.66 34.1 17.21 587.02 34.2 17.48 597.56 34.2 18.08 618.87 34.6 19.12 662.23 34.8 20.15 700.96 32.2 12.56 404.65 32.2 13 418.82 32.1 13.44 431.35 32.2 13.95 449.29 32.3 14.64 473.39 32.4 15.21 492.74 32.3 15.64 505.69 32.4 16.15 523.78 32.6 16.71 544.59 32.5 17.38 564.95 32.6 18.03 587.2 26 7.32 190.52 26.2 7.67 200.82 26.1 7.96 208.05 26.1 8.32 217.2 25.8 8.57 220.73 25.8 8.81 227.17 25.6 9 230.42 25.7 9.15 234.86 25.7 9.38 241.36 25.7 9.75 250.11 25.5 10.41 265.03 32.7 11.29 368.63 32.6 11.79 384.25 32.5 12.26 398.77 32.5 12.73 413.41 32.3 13.27 428.64 32 13.72 439.76 31.4 13.84 434.41 31 13.98 433.04 30.9 14.34 443.37 30.9 14.77 456.6 30.9 15.22 470.05 Natural resources and mining Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Construction: NOTE: Data reflect the conversion to the 2002 version of the North American Industry Classification System (NAICS), replacing the Standard Industrial Classification (SIC) system. N AICS-based data by industry are not comparable with SIC-based data. 98 Monthly Labor Review • September 2008 30. Employment Cost Index, compensation,1 by occupation and industry group [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 2 Civilian workers ……….…….........…………………………………….… 101.6 102.7 103.3 104.2 105.0 106.1 106.7 107.6 108.3 0.7 3.1 Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… 101.6 101.9 101.4 101.6 101.1 101.9 103.0 102.7 103.2 102.4 101.7 102.8 103.7 103.2 104.0 103.0 102.3 103.5 104.7 104.4 104.9 103.8 102.4 104.7 105.5 105.2 105.7 104.8 103.6 105.5 106.7 106.2 107.0 105.5 104.1 106.4 107.2 106.6 107.6 106.4 105.2 107.1 108.3 108.2 108.4 106.8 105.0 108.0 109.0 108.9 109.0 107.7 106.1 108.6 .6 .6 .6 .8 1.0 .6 3.3 3.5 3.1 2.8 2.4 2.9 Natural resources, construction, and maintenance………… Construction and extraction……………………………… Installation, maintenance, and repair…………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 102.0 102.0 102.0 101.1 101.0 101.3 101.4 103.0 103.0 103.0 101.8 101.6 102.2 102.5 103.6 103.7 103.6 102.4 102.0 102.8 103.5 104.1 104.3 103.7 102.7 102.1 103.4 104.8 105.1 105.7 104.4 103.5 102.8 104.4 105.5 106.1 106.5 105.6 104.2 103.3 105.3 106.9 106.8 107.4 106.2 104.7 104.1 105.6 107.7 107.7 108.5 106.7 105.6 104.8 106.6 108.4 108.4 109.6 107.0 106.2 105.3 107.3 109.1 .6 1.0 .3 .6 .5 .7 .6 3.1 3.7 2.5 2.6 2.4 2.8 3.4 Workers by industry Goods-producing……………………………………………… Manufacturing………………………………………………… Service-providing……………………………………………… Education and health services…………………………… Health care and social assistance……………………… Hospitals………………………………………………… Nursing and residential care facilities……………… Education services……………………………………… Elementary and secondary schools………………… 101.3 101.0 101.6 101.3 102.0 101.9 101.4 100.7 100.5 102.0 101.4 102.9 103.5 103.5 103.2 102.6 103.4 103.5 102.5 101.8 103.5 104.2 104.3 104.0 103.7 104.1 104.2 102.9 102.0 104.4 104.9 105.4 105.1 104.5 104.5 104.6 103.9 102.9 105.2 105.5 106.1 105.7 105.0 104.9 105.0 104.4 103.2 106.4 107.2 107.1 106.7 105.6 107.3 107.4 105.0 103.8 107.0 107.9 107.9 107.5 106.3 107.9 107.9 106.1 104.7 107.8 108.6 108.9 108.4 107.3 108.3 108.2 106.8 105.1 108.5 109.2 109.6 109.2 108.2 108.9 108.8 .7 .4 .6 .6 .6 .7 .8 .6 .6 2.8 2.1 3.1 3.5 3.3 3.3 3.0 3.8 3.6 Public administration ……………………………………… 101.2 Workers by occupational group 3 102.4 103.8 105.6 106.6 108.0 109.1 109.7 110.1 .4 3.3 101.7 102.5 103.2 104.0 104.9 105.7 106.3 107.3 108.0 .7 3.0 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… Natural resources, construction, and maintenance………… Construction and extraction………………………………… Installation, maintenance, and repair……………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 101.9 102.0 101.8 101.6 101.1 101.9 102.1 102.2 102.1 101.1 101.0 101.2 101.5 102.9 102.7 103.1 102.3 101.7 102.7 103.0 103.1 103.0 101.7 101.6 102.0 102.3 103.5 103.1 103.9 102.9 102.3 103.4 103.6 103.7 103.4 102.3 102.0 102.6 103.1 104.6 104.3 104.9 103.7 102.4 104.5 104.0 104.4 103.5 102.5 102.1 103.1 104.5 105.5 105.1 105.9 104.7 103.6 105.4 105.0 105.7 104.1 103.3 102.8 104.1 105.2 106.4 106.0 106.7 105.3 104.2 106.0 105.9 106.5 105.2 103.9 103.2 104.9 106.4 106.8 106.3 107.3 106.1 105.2 106.7 106.7 107.4 105.8 104.5 104.0 105.3 107.0 108.1 108.0 108.3 106.6 105.0 107.8 107.6 108.6 106.3 105.5 104.8 106.4 107.8 108.9 108.7 109.0 107.5 106.2 108.5 108.3 109.7 106.6 106.0 105.2 107.2 108.7 .7 .6 .6 .8 1.1 .6 .7 1.0 .3 .5 .4 .8 .8 3.2 3.4 2.9 2.7 2.5 2.9 3.1 3.8 2.4 2.6 2.3 3.0 3.3 Workers by industry and occupational group Goods-producing industries…………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. 101.3 100.7 102.7 101.9 101.0 102.0 101.6 102.1 102.7 101.6 102.5 102.0 102.8 103.3 102.0 102.9 102.7 103.0 104.0 102.1 103.9 103.8 103.7 105.3 102.9 104.4 104.3 104.1 106.1 103.3 105.0 104.4 104.8 107.0 104.0 106.1 106.1 105.1 108.1 104.8 106.8 106.6 106.3 109.0 105.3 .7 .5 1.1 .8 .5 2.8 2.7 2.5 3.5 2.3 Construction………………………………………………… Manufacturing………………………………………………… Management, professional, and related………………… Sales and office…………………………………………… Natural resources, construction, and maintenance…… Production, transportation, and material moving…….. 101.9 101.0 100.5 102.8 100.8 100.9 103.0 101.4 101.3 101.3 101.5 101.5 103.6 101.8 101.4 102.1 102.1 101.9 104.7 102.0 102.0 102.4 101.7 101.9 105.9 102.9 103.3 103.2 102.4 102.6 106.9 103.2 103.3 103.5 102.8 103.1 107.6 103.8 103.5 104.3 103.9 103.8 108.9 104.7 104.9 105.0 104.6 104.5 110.1 105.1 105.2 106.1 104.5 105.0 1.1 .4 .3 1.0 -.1 .5 4.0 2.1 1.8 2.8 2.1 2.3 Service-providing industries………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. Service occupations………………………………………… 101.8 102.2 101.5 102.5 101.3 101.5 102.7 103.2 102.3 103.6 101.9 102.3 103.4 103.8 102.9 104.0 102.6 103.1 104.3 105.0 103.7 104.0 103.0 104.5 105.2 105.9 104.8 104.5 104.0 105.3 106.1 106.8 105.4 105.7 104.7 106.4 106.7 107.3 106.3 106.2 105.2 107.1 107.7 108.5 106.8 106.7 106.4 107.9 108.5 109.3 107.7 107.3 107.0 108.7 .7 .7 .8 .6 .6 .7 3.1 3.2 2.8 2.7 2.9 3.2 Trade, transportation, and utilities………………………… 101.4 102.4 103.0 103.1 104.2 104.7 105.5 106.1 107.3 1.1 3.0 Private industry workers……………………………………… See footnotes at end of table. Monthly Labor Review • September 2008 99 Current Labor Statistics: Compensation & Industrial Relations 30. Continued—Employment Cost Index, compensation,1 by occupation and industry group [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 Wholesale trade…………………………………………… Retail trade………………………………………………… Transportation and warehousing……………………… Utilities……………………………………………………… Information………………………………………………… Financial activities………………………………………… Finance and insurance………………………………… Real estate and rental and leasing…………………… Professional and business services……………………… Education and health services…………………………… Education services……………………………………… Health care and social assistance…………………… Hospitals……………………………………………… Leisure and hospitality…………………………………… Accommodation and food services…………………… Other services, except public administration…………… 100.8 101.2 101.0 109.3 102.1 101.8 102.4 99.3 102.2 101.8 101.5 101.9 102.0 101.3 101.4 102.7 102.4 101.9 101.6 110.1 103.0 102.1 102.6 100.2 102.9 103.2 103.2 103.2 103.2 102.4 102.5 103.6 102.9 102.7 102.2 110.4 103.2 102.5 102.9 100.8 103.5 104.1 104.2 104.1 103.9 103.7 104.0 104.0 103.7 102.9 102.8 102.8 104.3 104.2 104.6 102.2 104.7 105.1 104.5 105.2 105.0 105.3 105.8 105.7 104.6 103.9 104.0 104.7 105.6 104.6 104.9 103.0 105.9 105.7 104.9 105.9 105.6 106.0 106.4 106.1 104.2 105.1 104.5 105.0 105.8 105.4 105.7 104.1 106.9 106.9 106.7 106.9 106.5 107.5 108.1 107.1 105.3 106.1 104.5 105.6 106.1 105.6 106.1 103.7 107.5 107.7 107.5 107.8 107.3 108.1 108.6 107.6 105.7 106.6 105.6 106.5 106.1 106.8 107.0 105.5 109.0 108.6 108.1 108.8 108.2 109.0 109.5 108.7 107.2 107.6 106.4 108.1 106.2 107.3 107.7 105.7 109.9 109.4 109.1 109.4 109.1 109.3 110.0 109.4 1.4 .9 .8 1.5 .1 .5 .7 .2 .8 .7 .9 .6 .8 .3 .5 .6 2.5 3.6 2.3 3.2 .6 2.6 2.7 2.6 3.8 3.5 4.0 3.3 3.3 3.1 3.4 3.1 100.9 103.2 104.1 105.1 105.7 107.6 108.4 108.9 109.4 .5 3.5 Workers by occupational group Management, professional, and related……………………… Professional and related…………………………………… Sales and office………………………………………………… Office and administrative support………………………… Service occupations…………………………………………… 100.8 100.8 101.5 101.6 101.2 103.3 103.4 103.3 103.5 103.1 104.0 104.0 104.1 104.2 104.5 104.9 104.8 105.6 105.7 105.4 105.4 105.3 106.2 106.4 106.3 107.5 107.5 107.9 108.2 108.0 108.3 108.2 108.6 108.9 109.1 108.8 108.6 108.8 109.3 109.7 109.3 109.1 109.3 109.8 110.0 .5 .5 .5 .5 .3 3.7 3.6 2.9 3.2 3.5 Workers by industry Education and health services……………………………… Education services……………………………………… Schools………………………………………………… Elementary and secondary schools……………… Health care and social assistance……………………… Hospitals………………………………………………… 100.8 100.5 100.5 100.5 102.9 101.3 103.7 103.5 103.5 103.6 105.1 103.3 104.3 104.1 104.1 104.2 105.7 104.3 104.8 104.6 104.6 104.7 107.1 105.6 105.3 105.0 104.9 105.0 107.6 106.3 107.5 107.4 107.4 107.4 108.6 107.5 108.2 108.0 108.0 108.0 109.3 108.2 108.6 108.4 108.4 108.3 110.1 109.2 109.1 108.8 108.8 108.8 111.1 109.7 .5 .4 .4 .5 .9 .5 3.6 3.6 3.7 3.6 3.3 3.2 101.2 102.4 103.8 105.6 106.6 108.0 109.1 109.7 110.1 .4 3.3 State and local government workers………………………… 3 Public administration ……………………………………… 1 Cost (cents per hour worked) measured in the Employment Cost Index consists of wages, salaries, and employer cost of employee benefits. 2 Consists of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers. 3 Consists of legislative, judicial, administrative, and regulatory activities. 100 Monthly Labor Review • September 2008 NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 31. Employment Cost Index, wages and salaries, by occupation and industry group [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 1 Civilian workers ……….…….........…………………………………….… 101.5 102.6 103.2 104.3 105.0 106.0 106.7 107.6 108.4 0.7 3.2 Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… 101.6 102.0 101.4 101.6 101.3 101.8 102.9 102.7 103.1 102.4 102.0 102.6 103.6 103.1 103.8 103.0 102.5 103.3 104.7 104.7 104.7 103.8 102.7 104.5 105.4 105.4 105.3 104.8 103.9 105.3 106.6 106.4 106.7 105.4 104.3 106.1 107.1 106.7 107.4 106.2 105.5 106.8 108.2 108.2 108.3 106.7 105.2 107.8 109.0 109.0 109.0 107.7 106.6 108.5 .7 .7 .6 .9 1.3 .6 3.4 3.4 3.5 2.8 2.6 3.0 Natural resources, construction, and maintenance………… Construction and extraction……………………………… Installation, maintenance, and repair…………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 101.8 101.9 101.6 101.2 101.2 101.2 101.2 102.7 102.9 102.6 101.9 101.8 102.1 102.2 103.4 103.7 103.1 102.5 102.3 102.7 103.2 104.3 104.6 103.8 103.2 103.2 103.3 104.6 105.1 105.7 104.4 103.9 103.6 104.2 105.3 106.3 106.6 105.8 104.7 104.3 105.1 106.5 107.1 107.7 106.4 105.1 104.7 105.5 107.3 108.1 109.0 107.0 106.1 105.7 106.6 108.0 109.0 109.9 107.8 106.9 106.5 107.3 108.7 .8 .8 .7 .8 .8 .7 .6 3.7 4.0 3.3 2.9 2.8 3.0 3.2 Workers by industry Goods-producing……………………………………………… Manufacturing………………………………………………… Service-providing……………………………………………… Education and health services…………………………… Health care and social assistance……………………… Hospitals………………………………………………… Nursing and residential care facilities……………… Education services……………………………………… Elementary and secondary schools………………… 101.8 101.7 101.5 101.1 101.8 101.7 101.2 100.5 100.3 102.3 101.9 102.7 103.1 103.2 102.9 102.2 103.0 102.9 102.9 102.3 103.3 103.8 104.1 103.8 103.3 103.5 103.4 103.9 103.3 104.3 104.4 105.1 104.8 104.1 103.7 103.6 104.7 103.9 105.1 104.9 105.9 105.6 104.7 104.0 103.8 105.4 104.5 106.2 106.6 107.1 106.7 105.8 106.2 106.0 106.0 104.9 106.8 107.4 107.9 107.4 106.4 106.9 106.6 107.1 105.9 107.7 108.0 108.9 108.4 107.4 107.3 107.0 108.0 106.7 108.5 108.7 109.6 109.4 108.1 107.9 107.5 .8 .8 .7 .6 .6 .9 .7 .6 .5 3.2 2.7 3.2 3.6 3.5 3.6 3.2 3.8 3.6 Public administration ……………………………………… 101.1 102.0 103.5 104.5 105.2 106.4 107.4 108.2 108.6 .4 3.2 101.7 102.5 103.2 104.3 105.1 106.0 106.6 107.6 108.4 .7 3.1 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… Natural resources, construction, and maintenance………… Construction and extraction………………………………… Installation, maintenance, and repair……………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 102.0 102.2 101.8 101.6 101.3 101.9 101.8 102.0 101.6 101.2 101.2 101.2 101.3 103.0 102.8 103.1 102.4 102.0 102.6 102.8 103.0 102.6 101.8 101.7 102.0 102.0 103.6 103.1 104.0 103.0 102.6 103.3 103.4 103.7 103.0 102.4 102.2 102.6 102.9 104.9 104.7 105.1 103.8 102.8 104.5 104.2 104.7 103.7 103.1 103.1 103.2 104.6 105.8 105.5 106.0 104.8 104.0 105.4 105.1 105.8 104.2 103.8 103.6 104.1 105.3 106.7 106.3 107.0 105.3 104.4 106.0 106.2 106.7 105.6 104.5 104.2 105.0 106.5 107.2 106.6 107.6 106.2 105.5 106.7 107.1 107.8 106.1 105.0 104.6 105.4 107.1 108.5 108.2 108.7 106.7 105.3 107.7 108.1 109.2 106.8 106.0 105.6 106.5 107.9 109.3 109.0 109.5 107.7 106.6 108.5 109.0 110.1 107.6 106.8 106.4 107.4 108.8 .7 .7 .7 .9 1.2 .7 .8 .8 .7 .8 .8 .8 .8 3.3 3.3 3.3 2.8 2.5 2.9 3.7 4.1 3.3 2.9 2.7 3.2 3.3 Workers by industry and occupational group Goods-producing industries…………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. 101.8 101.7 103.4 101.9 101.3 102.3 102.4 102.2 102.7 101.9 102.9 102.8 103.1 103.4 102.4 103.9 104.4 103.4 104.4 103.2 104.7 105.3 104.1 105.6 103.7 105.4 105.9 104.7 106.5 104.4 106.0 106.0 105.5 107.6 104.8 107.1 107.7 105.8 108.8 105.7 108.0 108.4 107.2 109.6 106.6 .8 .6 1.3 .7 .9 3.2 2.9 3.0 3.8 2.8 Construction………………………………………………… Manufacturing………………………………………………… Management, professional, and related………………… Sales and office…………………………………………… Natural resources, construction, and maintenance…… Production, transportation, and material moving…….. 102.0 101.7 101.5 103.8 101.7 101.3 102.9 101.9 102.2 101.1 102.3 101.8 103.7 102.3 102.3 102.0 103.0 102.3 104.9 103.3 103.8 102.4 103.8 103.1 106.0 103.9 104.6 103.2 104.3 103.6 107.0 104.5 105.0 103.9 105.0 104.2 107.8 104.9 105.3 104.7 105.9 104.5 109.0 105.9 106.7 105.5 106.8 105.4 110.0 106.7 107.2 106.9 107.1 106.3 .9 .8 .5 1.3 .3 .9 3.8 2.7 2.5 3.6 2.7 2.6 Service-providing industries………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. Service occupations………………………………………… 101.7 102.0 101.4 101.8 101.0 101.3 102.6 103.1 102.4 103.0 101.7 102.0 103.3 103.7 102.9 103.4 102.4 102.9 104.4 105.0 103.8 103.9 103.0 104.6 105.3 105.9 104.9 104.3 104.0 105.3 106.1 106.8 105.4 105.7 104.6 106.6 106.8 107.4 106.3 106.3 105.2 107.2 107.7 108.6 106.8 106.9 106.3 108.0 108.6 109.4 107.7 108.0 107.1 108.8 .8 .7 .8 1.0 .8 .7 3.1 3.3 2.7 3.5 3.0 3.3 Trade, transportation, and utilities………………………… 100.9 102.1 102.7 103.2 104.3 104.6 105.5 105.9 107.2 1.2 2.8 Workers by occupational group 2 Private industry workers……………………………………… See footnotes at end of table. Monthly Labor Review • September 2008 101 Current Labor Statistics: Compensation & Industrial Relations 31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 Wholesale trade…………………………………………… Retail trade………………………………………………… Transportation and warehousing……………………… Utilities……………………………………………………… Information………………………………………………… Financial activities………………………………………… Finance and insurance………………………………… Real estate and rental and leasing…………………… Professional and business services……………………… Education and health services…………………………… Education services……………………………………… Health care and social assistance…………………… Hospitals……………………………………………… Leisure and hospitality…………………………………… Accommodation and food services…………………… Other services, except public administration…………… 100.7 100.9 100.7 102.1 101.7 102.3 102.8 99.9 102.3 101.6 101.4 101.6 101.8 101.3 101.3 102.6 102.7 101.9 101.4 103.0 102.6 102.5 102.9 100.8 103.0 103.0 103.1 103.0 102.9 102.3 102.2 103.4 103.0 102.8 101.9 103.5 102.4 102.8 103.2 101.4 103.5 104.0 104.1 103.9 103.7 103.7 103.8 103.8 103.8 103.1 102.5 104.3 103.8 104.7 105.4 101.6 104.8 104.8 104.2 104.9 104.6 105.7 106.0 105.7 104.8 104.2 103.7 105.5 104.9 104.9 105.5 102.4 105.9 105.6 104.6 105.8 105.4 106.4 106.5 106.1 104.0 105.1 104.1 106.1 105.2 106.0 106.5 103.6 106.7 106.9 106.4 107.0 106.5 108.1 108.4 107.3 105.2 106.1 104.2 106.8 105.3 105.9 106.6 103.1 107.5 107.7 107.4 107.8 107.2 108.8 109.0 107.9 105.2 106.4 105.0 108.0 105.3 107.2 107.9 104.5 109.1 108.6 107.9 108.7 108.2 109.7 110.0 109.2 107.2 107.6 106.0 109.3 106.3 107.7 108.4 104.7 110.0 109.2 108.6 109.4 109.2 109.9 110.4 109.9 1.9 1.1 1.0 1.2 .9 .5 .5 .2 .8 .6 .6 .6 .9 .2 .4 .6 2.3 3.3 2.2 3.6 1.3 2.7 2.7 2.2 3.9 3.4 3.8 3.4 3.6 3.3 3.7 3.6 100.8 102.8 103.5 104.1 104.6 106.4 107.1 107.7 108.2 .5 3.4 Workers by occupational group Management, professional, and related……………………… Professional and related…………………………………… Sales and office………………………………………………… Office and administrative support………………………… Service occupations…………………………………………… 100.7 100.7 101.2 101.4 100.8 102.9 103.0 102.6 102.7 102.4 103.5 103.6 103.2 103.4 103.9 104.0 103.9 104.5 104.7 104.5 104.3 104.2 104.8 105.0 105.2 106.3 106.3 106.3 106.5 106.5 107.0 107.0 107.0 107.3 107.7 107.6 107.5 107.4 107.8 108.3 108.2 108.1 107.9 108.3 108.6 .6 .6 .5 .5 .3 3.7 3.7 3.0 3.1 3.2 Workers by industry Education and health services……………………………… Education services……………………………………… Schools………………………………………………… Elementary and secondary schools……………… Health care and social assistance……………………… Hospitals………………………………………………… 100.7 100.4 100.4 100.3 103.0 101.4 103.1 103.0 103.0 103.0 104.8 103.1 103.6 103.4 103.4 103.4 105.5 104.4 104.0 103.7 103.6 103.6 106.6 105.7 104.2 103.9 103.9 103.8 107.2 106.5 106.3 106.1 106.1 106.0 108.2 107.6 107.1 106.8 106.8 106.6 109.2 108.6 107.5 107.2 107.2 106.9 110.1 109.8 108.1 107.7 107.7 107.5 111.0 110.3 .6 .5 .5 .6 .8 .5 3.7 3.7 3.7 3.6 3.5 3.6 101.1 102.0 103.5 104.5 105.2 106.4 107.4 108.2 108.6 .4 3.2 State and local government workers………………………… 2 Public administration ……………………………………… 1 Consists of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers. 2 Consists of legislative, judicial, administrative, and regulatory activities. NOTE: The Employment Cost Index data reflect the conversion to the 2002 North 102 Monthly Labor Review • September 2008 American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 32. Employment Cost Index, benefits, by occupation and industry group [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 Civilian workers…………………………………………………. 101.6 102.8 103.6 104.0 105.1 106.1 106.8 107.6 108.1 0.5 2.9 Private industry workers………………………………………… 101.7 102.5 103.1 103.2 104.3 105.0 105.6 106.5 107.0 .5 2.6 Workers by occupational group Management, professional, and related……………………… Sales and office………………………………………………… Natural resources, construction, and maintenance………… Production, transportation, and material moving…………… 101.8 101.6 102.7 101.0 102.8 102.0 103.5 101.6 103.4 102.9 104.0 102.0 103.8 103.4 103.4 101.2 104.9 104.3 104.8 102.4 105.6 105.2 105.3 102.7 106.0 106.0 105.9 103.7 107.3 106.5 106.5 104.4 107.9 107.0 107.0 104.5 .6 .5 .5 .1 2.9 2.6 2.1 2.1 Service occupations…………………………………………… 102.2 103.0 103.6 104.2 105.1 106.0 106.7 107.6 108.5 .8 3.2 Goods-producing……………………………………………… 100.4 Manufacturing………………………………………………… 99.7 Service-providing……………………………………………… 102.3 101.3 100.5 103.0 101.7 100.8 103.7 100.9 99.6 104.1 102.2 101.0 105.2 102.4 100.7 106.0 103.2 101.7 106.6 104.0 102.3 107.6 104.4 102.2 108.1 .4 -.1 .5 2.2 1.2 2.8 104.1 105.2 107.0 108.0 110.3 111.0 111.4 111.8 .4 3.5 Workers by industry State and local government workers………………………… 101.3 NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. Monthly Labor Review • September 2008 103 Current Labor Statistics: Compensation & Industrial Relations 33. Employment Cost Index, private industry workers by bargaining status and region [December 2005 = 100] 2006 Series June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2008 COMPENSATION Workers by bargaining status1 Union………………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 101.8 101.2 100.1 102.2 102.4 101.8 100.5 102.9 103.0 102.2 100.8 103.6 102.7 101.5 99.2 103.7 103.9 102.8 100.0 104.7 104.4 103.1 100.0 105.4 105.1 104.0 101.0 106.0 105.9 104.6 101.4 107.0 106.7 105.6 101.7 107.5 0.8 1.0 .3 .5 2.7 2.7 1.7 2.7 Nonunion…………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 101.7 101.4 101.3 101.8 102.6 102.0 101.7 102.7 103.2 102.5 102.1 103.4 104.2 103.3 102.8 104.4 105.1 104.2 103.7 105.3 105.9 104.8 104.1 106.2 106.5 105.4 104.6 106.8 107.5 106.5 105.6 107.7 108.3 107.1 106.2 108.6 .7 .6 .6 .8 3.0 2.8 2.4 3.1 Workers by region1 Northeast…………………………………………………………… South………………………………………………………………… Midwest……………………………………………………………… West………………………………………………………………… 101.8 101.6 101.7 101.8 102.5 102.8 102.3 102.5 103.3 103.5 102.8 103.0 104.0 104.3 103.3 104.2 105.1 105.3 104.2 104.9 106.2 106.1 104.6 105.7 106.8 106.7 105.3 106.5 107.4 107.8 106.0 107.8 108.1 108.5 107.0 108.4 .7 .6 .9 .6 2.9 3.0 2.7 3.3 Workers by bargaining status1 Union………………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 101.2 101.6 101.2 100.9 101.7 101.9 101.4 101.6 102.3 102.3 101.7 102.2 102.8 102.7 102.0 102.9 103.7 103.6 102.5 103.8 104.4 104.3 102.9 104.6 104.7 104.3 102.6 104.9 105.5 105.2 103.4 105.8 106.7 106.4 104.4 106.9 1.1 1.1 1.0 1.0 2.9 2.7 1.9 3.0 Nonunion…………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 101.8 101.9 101.8 101.7 102.7 102.4 102.0 102.7 103.3 103.0 102.5 103.4 104.5 104.2 103.6 104.6 105.3 105.0 104.2 105.4 106.2 105.8 104.9 106.3 106.9 106.4 105.5 107.0 107.9 107.7 106.6 107.9 108.7 108.4 107.3 108.8 .7 .6 .7 .8 3.2 3.2 3.0 3.2 Workers by region1 Northeast…………………………………………………………… South………………………………………………………………… Midwest……………………………………………………………… West………………………………………………………………… 101.7 101.6 101.4 102.1 102.5 102.9 102.0 102.7 103.1 103.6 102.6 103.2 104.0 104.6 103.6 104.8 105.0 105.6 104.4 105.4 106.1 106.5 105.0 106.2 106.6 107.0 105.6 107.0 107.5 108.1 106.3 108.3 108.2 109.1 107.5 108.9 .7 .9 1.1 .6 3.0 3.3 3.0 3.3 WAGES AND SALARIES 1 The indexes are calculated differently from those for the occupation and industry groups. For a detailed description of the index calculation, see the Monthly Labor Review Technical Note, "Estimation procedures for the Employment Cost Index," May 1982. 104 Monthly Labor Review • September 2008 NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 34. National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 1 2006 All retirement Percentage of workers with access All workers……………………………………………………… 57 59 60 60 White-collar occupations 2 …………………………………… 67 69 70 69 - - - - - 76 64 Management, professional, and related ………………. 61 Sales and office …………………………………………… - - - - Blue-collar occupations 2……………………………………… 59 59 60 62 - - - - - 61 Natural resources, construction, and maintenance...… Production, transportation, and material moving…...… Service occupations…………………………………………… - - - - 65 28 31 32 34 36 Full-time………………………………………………………… 67 68 69 69 70 Part-time……………………………………………………… 24 27 27 29 31 Union…………………………………………………………… 86 84 88 84 84 Non-union……………………………………………………… 54 56 56 57 58 Average wage less than $15 per hour……...……………… 45 46 46 47 47 Average wage $15 per hour or higher……...……………… 76 77 78 77 76 Goods-producing industries………………………………… 70 70 71 73 70 Service-providing industries………………………………… 53 55 56 56 58 Establishments with 1-99 workers…………………………… 42 44 44 44 45 Establishments with 100 or more workers………………… 75 77 78 78 78 All workers……………………………………………………… 49 50 50 51 51 White-collar occupations 2 …………………………………… 59 61 61 60 - - - - - 69 54 Percentage of workers participating Management, professional, and related ………………. Sales and office …………………………………………… - - - - Blue-collar occupations 2……………………………………… 50 50 51 52 - - - - - 51 Natural resources, construction, and maintenance…... Production, transportation, and material moving…...… Service occupations…………………………………………… - - - - 54 21 22 22 24 25 Full-time………………………………………………………… 58 60 60 60 60 Part-time……………………………………………………… 18 20 19 21 23 Union…………………………………………………………… 83 81 85 80 81 Non-union……………………………………………………… 45 47 46 47 47 Average wage less than $15 per hour……...……………… 35 36 35 36 36 Average wage $15 per hour or higher……...……………… 70 71 71 70 69 Goods-producing industries………………………………… 63 63 64 64 61 Service-providing industries………………………………… 45 47 47 47 48 Establishments with 1-99 workers…………………………… 35 37 37 37 37 Establishments with 100 or more workers………………… 65 67 67 67 66 - - 85 85 84 20 21 22 21 21 23 24 25 23 - - - - - 29 19 3 Take-up rate (all workers) …………………………………… Defined Benefit Percentage of workers with access All workers……………………………………………………… 2 White-collar occupations …………………………………… Management, professional, and related ………………. Sales and office …………………………………………… 2 Blue-collar occupations ……………………………………… Natural resources, construction, and maintenance...… - - - - 24 26 26 25 - - - - - 26 26 Production, transportation, and material moving…...… - - - - Service occupations…………………………………………… 8 6 7 8 8 Full-time………………………………………………………… 24 25 25 24 24 Part-time……………………………………………………… 8 9 10 9 10 Union…………………………………………………………… 74 70 73 70 69 Non-union……………………………………………………… 15 16 16 15 15 Average wage less than $15 per hour……...……………… 12 11 12 11 11 Average wage $15 per hour or higher……...……………… 34 35 35 34 33 Goods-producing industries………………………………… 31 32 33 32 29 Service-providing industries………………………………… 17 18 19 18 19 9 9 10 9 9 34 35 37 35 34 Establishments with 1-99 workers…………………………… Establishments with 100 or more workers………………… See footnotes at end of table. Monthly Labor Review • September 2008 105 Current Labor Statistics: Compensation & Industrial Relations 34. Continued—National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 2006 1 Percentage of workers participating All workers……………………………………………………… 2 White-collar occupations …………………………………… Management, professional, and related ………………. Sales and office …………………………………………… Blue-collar occupations 2…………………………………… Natural resources, construction, and maintenance...… Production, transportation, and material moving…...… Service occupations………………………………………… Full-time……………………………………………………… Part-time……………………………………………………… Union…………………………………………………………… Non-union……………………………………………………… Average wage less than $15 per hour……...……………… 20 22 24 7 24 8 72 15 11 21 24 25 6 24 9 69 15 11 21 24 26 7 25 9 72 15 11 20 22 25 7 23 8 68 14 10 20 28 17 25 25 7 23 9 67 15 10 Average wage $15 per hour or higher……...……………… 33 35 34 33 32 Goods-producing industries………………………………… 31 31 32 31 28 Service-providing industries………………………………… 16 18 18 17 18 Establishments with 1-99 workers………………………… 8 9 9 9 9 Establishments with 100 or more workers………………… 33 34 36 33 32 Take-up rate (all workers) 3…………………………………… - - 97 96 95 All workers……………………………………………………… 51 53 53 54 55 White-collar occupations 2 …………………………………… 62 64 64 65 - - - - - 71 60 Defined Contribution Percentage of workers with access Management, professional, and related ………………. - - - - Blue-collar occupations 2…………………………………… Sales and office …………………………………………… 49 49 50 53 - Natural resources, construction, and maintenance...… - - - - 51 56 Production, transportation, and material moving…...… - - - - Service occupations………………………………………… 23 27 28 30 32 Full-time……………………………………………………… 60 62 62 63 64 Part-time……………………………………………………… 21 23 23 25 27 Union…………………………………………………………… 45 48 49 50 49 Non-union……………………………………………………… 51 53 54 55 56 Average wage less than $15 per hour……...……………… 40 41 41 43 44 Average wage $15 per hour or higher……...……………… 67 68 69 69 69 Goods-producing industries………………………………… 60 60 61 63 62 Service-providing industries………………………………… 48 50 51 52 53 Establishments with 1-99 workers………………………… 38 40 40 41 42 Establishments with 100 or more workers………………… 65 68 69 70 70 All workers……………………………………………………… 40 42 42 43 43 White-collar occupations 2 …………………………………… 51 53 53 53 - - - - - 60 47 Percentage of workers participating Management, professional, and related ………………. - - - - Blue-collar occupations 2…………………………………… Sales and office …………………………………………… 38 38 38 40 - Natural resources, construction, and maintenance...… - - - - 40 41 Production, transportation, and material moving…...… - - - - Service occupations………………………………………… 16 18 18 20 20 Full-time……………………………………………………… 48 50 50 51 50 Part-time……………………………………………………… 14 14 14 16 18 Union…………………………………………………………… 39 42 43 44 41 Non-union……………………………………………………… 40 42 41 43 43 Average wage less than $15 per hour……...……………… 29 30 29 31 30 Average wage $15 per hour or higher……...……………… 57 59 59 58 57 Goods-producing industries………………………………… 49 49 50 51 49 Service-providing industries………………………………… 37 40 39 40 41 Establishments with 1-99 workers………………………… 31 32 32 33 33 Establishments with 100 or more workers………………… 51 53 53 54 53 - - 78 79 77 3 Take-up rate (all workers) …………………………………… See footnotes at end of table. 106 Monthly Labor Review • September 2008 34. Continued—National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 1 2006 Employee Contribution Requirement Employee contribution required………………………… Employee contribution not required……………………… Not determinable…………………………………………… - - 61 31 8 61 33 6 65 35 0 Percent of establishments Offering retirement plans…………………………………… Offering defined benefit plans……………………………… Offering defined contribution plans………………………. 47 10 45 48 10 46 51 11 48 48 10 47 46 10 44 1 The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC) System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable. Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system. Only service occupations are considered comparable. 2 The white-collar and blue-collar occupation series were discontinued effective 2007. 3 The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan. Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. Monthly Labor Review • September 2008 107 Current Labor Statistics: Compensation & Industrial Relations 35. National Compensation Survey: Health insurance benefits in private industry by access, particpation, and selected series, 2003-2007 Series Year 2003 2004 2005 2007 2006 1 Medical insurance Percentage of workers with access All workers………………………………………………………………………… 60 69 70 71 2 White-collar occupations ……………………………………………………… 65 76 77 77 - - - - - 85 71 Management, professional, and related ………………………………… Sales and office……………………………………………………………… Blue-collar occupations 2……………………………………………………… Natural resources, construction, and maintenance……………………… 71 - - - - 64 76 77 77 - - - - - 76 Production, transportation, and material moving………………………… - - - - 78 Service occupations…………………………………………………………… 38 42 44 45 46 Full-time………………………………………………………………………… 73 84 85 85 85 Part-time………………………………………………………………………… 17 20 22 22 24 Union……………………………………………………………………………… 67 89 92 89 88 Non-union………………………………………………………………………… 59 67 68 68 69 Average wage less than $15 per hour………………………………………… 51 57 58 57 57 Average wage $15 per hour or higher………………………………………… 74 86 87 88 87 Goods-producing industries…………………………………………………… 68 83 85 86 85 Service-providing industries…………………………………………………… 57 65 66 66 67 Establishments with 1-99 workers……………………………………………… 49 58 59 59 59 Establishments with 100 or more workers…………………………………… 72 82 84 84 84 All workers………………………………………………………………………… 45 53 53 52 52 White-collar occupations 2 ……………………………………………………… 50 59 58 57 - - - - - 67 48 Percentage of workers participating Management, professional, and related ………………………………… Sales and office……………………………………………………………… Blue-collar occupations 2……………………………………………………… Natural resources, construction, and maintenance……………………… - - - - 51 60 61 60 - - - - - 61 Production, transportation, and material moving………………………… - - - - 60 Service occupations…………………………………………………………… 22 24 27 27 28 Full-time………………………………………………………………………… 56 66 66 64 64 Part-time………………………………………………………………………… 9 11 12 13 12 Union……………………………………………………………………………… 60 81 83 80 78 Non-union………………………………………………………………………… 44 50 49 49 49 Average wage less than $15 per hour………………………………………… 35 40 39 38 37 Average wage $15 per hour or higher………………………………………… 61 71 72 71 70 Goods-producing industries…………………………………………………… 57 69 70 70 68 Service-providing industries…………………………………………………… 42 48 48 47 47 Establishments with 1-99 workers……………………………………………… 36 43 43 43 42 Establishments with 100 or more workers…………………………………… 55 64 65 63 62 - - 75 74 73 All workers………………………………………………………………………… 40 46 46 46 46 2 White-collar occupations ……………………………………………………… 47 53 54 53 - - - - - 62 47 3 Take-up rate (all workers) ……………………………………………………… Dental Percentage of workers with access Management, professional, and related ………………………………… Sales and office……………………………………………………………… 2 Blue-collar occupations ……………………………………………………… Natural resources, construction, and maintenance……………………… - - - 47 47 46 - - - - - 43 Production, transportation, and material moving………………………… - - - - 49 Service occupations…………………………………………………………… 22 25 25 27 28 Full-time………………………………………………………………………… 49 56 56 55 56 Part-time………………………………………………………………………… 9 13 14 15 16 Union……………………………………………………………………………… 57 73 73 69 68 Non-union………………………………………………………………………… 38 43 43 43 44 Average wage less than $15 per hour………………………………………… 30 34 34 34 34 Average wage $15 per hour or higher………………………………………… 55 63 62 62 61 Goods-producing industries…………………………………………………… 48 56 56 56 54 Service-providing industries…………………………………………………… 37 43 43 43 44 Establishments with 1-99 workers……………………………………………… 27 31 31 31 30 Establishments with 100 or more workers…………………………………… 55 64 65 64 64 See footnotes at end of table. 108 40 Monthly Labor Review • September 2008 35. Continued—National Compensation Survey: Health insurance benefits in private industry by access, particpation, and selected series, 2003-2007 Series Year 2003 2004 2005 2007 2006 1 Percentage of workers participating All workers…………………………………………………………………………… 32 37 36 36 White-collar occupations 2 ……………………………………………………… 37 43 42 41 - Management, professional, and related …………………………………… - - - - 51 33 Sales and office………………………………………………………………… Blue-collar occupations 2………………………………………………………… Natural resources, construction, and maintenance………………………… 36 - - - - 33 40 39 38 - - - - - 36 Production, transportation, and material moving…………………………… - - - - 38 Service occupations……………………………………………………………… 15 16 17 18 20 Full-time…………………………………………………………………………… 40 46 45 44 44 Part-time…………………………………………………………………………… 6 8 9 10 9 Union……………………………………………………………………………… 51 68 67 63 62 Non-union………………………………………………………………………… 30 33 33 33 33 Average wage less than $15 per hour………………………………………… 22 26 24 23 23 Average wage $15 per hour or higher………………………………………… 47 53 52 52 51 Goods-producing industries……………………………………………………… 42 49 49 49 45 Service-providing industries……………………………………………………… 29 33 33 32 33 Establishments with 1-99 workers……………………………………………… 21 24 24 24 24 Establishments with 100 or more workers……………………………………… 44 52 51 50 49 Take-up rate (all workers) 3………………………………………………………… - - 78 78 77 Percentage of workers with access……………………………………………… 25 29 29 29 29 Percentage of workers participating……………………………………………… 19 22 22 22 22 Percentage of workers with access……………………………………………… - - 64 67 68 Percentage of workers participating……………………………………………… - - 48 49 49 Percent of estalishments offering healthcare benefits …………………......… 58 61 63 62 60 Vision care Outpatient Prescription drug coverage Percentage of medical premium paid by Employer and Employee Single coverage Employer share…………………………………………………………………… 82 82 82 82 81 Employee share………………………………………………………………… 18 18 18 18 19 Family coverage Employer share…………………………………………………………………… 70 69 71 70 71 Employee share………………………………………………………………… 30 31 29 30 29 1 The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC) System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable. Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system. Only service occupations are considered comparable. 2 The white-collar and blue-collar occupation series were discontinued effective 2007. 3 The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan. Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. Monthly Labor Review • September 2008 109 Current Labor Statistics: Compensation & Industrial Relations 36. National Compensation Survey: Percent of workers in private industry with access to selected benefits, 2003-2007 Year Benefit 2003 2004 2005 2006 2007 Life insurance…………………………………………………… 50 51 52 52 58 Short-term disabilty insurance………………………………… 39 39 40 39 39 Long-term disability insurance………………………………… 30 30 30 30 31 Long-term care insurance……………………………………… 11 11 11 12 12 Flexible work place……………………………………………… 4 4 4 4 5 Flexible benefits……………………………………………… - - 17 17 17 Dependent care reimbursement account…………..……… - - 29 30 31 Healthcare reimbursement account……………………...… - - 31 32 33 Health Savings Account………………………………...……… - - 5 6 8 Employee assistance program……………………….………… - - 40 40 42 Section 125 cafeteria benefits Paid leave Holidays…………………………………………...…………… 79 77 77 76 77 Vacations……………………………………………..……… 79 77 77 77 77 Sick leave………………………………………..…………… - 59 58 57 57 Personal leave…………………………………………..…… - - 36 37 38 Paid family leave…………………………………………….… - - 7 8 8 Unpaid family leave………………………………………..… - - 81 82 83 Employer assistance for child care…………………….……… 18 14 14 15 15 Nonproduction bonuses………………………...……………… 49 47 47 46 47 Family leave Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. 37. Work stoppages involving 1,000 workers or more Annual average Measure 2006 Number of stoppages: Beginning in period............................. In effect during period…...................... 2007 2007 July Aug. Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. Junep Julyp May 20 23 21 23 1 1 1 1 5 6 3 3 1 2 2 4 0 1 2 3 2 4 1 2 2 4 2 2 1 1 Workers involved: Beginning in period (in thousands)….. 70.1 In effect during period (in thousands)… 191.0 189.2 220.9 1.1 1.1 1.0 1.0 108.3 108.3 41.7 41.7 10.5 14.2 6.5 20.7 .0 10.5 6.2 16.7 5.7 11.9 2.3 6.0 3.4 9.4 4.2 4.2 8.5 8.5 Days idle: Number (in thousands)….................... 2,687.5 1,264.8 6.6 9.0 261.5 73.9 284.0 254.8 220.5 148.8 140.9 104.4 125.0 12.3 42.5 .01 0 0 .01 0 .01 .01 .01 .01 0 0 0 0 0 1 Percent of estimated working time …… .01 1 Agricultural and government employees are included in the total employed and total working time; private household, forestry, and fishery employees are excluded. An explanation of the measurement of idleness as a percentage of the total time 110 Monthly Labor Review • September 2008 worked is found in "Total economy measures of strike idleness," Monthly Labor Review , October 1968, pp. 54–56. NOTE: p = preliminary. 38. Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] Annual average Series 2006 CONSUMER PRICE INDEX FOR ALL URBAN CONSUMERS All items........................................................................... All items (1967 = 100)...................................................... Food and beverages...................................................... Food..................…......................................................... Food at home…........................................................... Cereals and bakery products…................................. Meats, poultry, fish, and eggs…................................ 201.6 603.9 195.7 195.2 193.1 212.8 186.6 1 Dairy and related products ……….………………………… 181.4 Fruits and vegetables…............................................. 252.9 Nonalcoholic beverages and beverage materials….............................................................. Other foods at home…............................................... Sugar and sweets…................................................. Fats and oils…......................................................... Other foods…........................................................... Other miscellaneous foods 1,2 ……….………………… 2008 July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July 207.342 621.106 203.300 202.916 201.245 222.107 195.616 208.299 623.970 203.533 203.121 201.401 223.297 196.690 207.917 622.827 204.289 203.885 202.126 223.981 197.204 208.490 624.543 205.279 204.941 203.193 223.372 198.323 208.936 625.879 206.124 205.796 204.333 224.691 198.474 210.177 629.598 206.563 206.277 204.745 225.668 198.616 210.036 629.174 206.936 206.704 205.208 226.461 198.755 211.080 632.301 208.837 208.618 207.983 228.661 200.035 211.693 634.139 209.462 209.166 208.329 233.389 199.688 213.528 639.636 209.692 209.385 208.203 236.261 199.775 214.823 643.515 211.365 211.102 210.851 240.034 200.770 216.632 648.933 212.251 212.054 211.863 244.192 200.960 218.815 655.474 213.383 213.243 213.171 245.758 202.914 219.964 658.915 215.326 215.299 215.785 250.321 205.075 194.770 197.899 201.739 203.541 205.319 205.959 205.299 206.905 208.166 206.171 207.680 207.778 209.117 213.981 262.628 254.616 252.845 259.100 263.648 268.407 272.482 279.072 272.129 268.446 272.746 276.481 277.957 280.209 147.4 169.6 171.5 168.0 185.0 153.432 173.275 176.772 172.921 188.244 113.9 115.105 115.017 116.072 114.628 114.850 115.396 115.267 115.162 118.182 117.321 118.500 118.744 118.453 120.510 1 Food away from home ……….………………………………… 199.4 1,2 Other food away from home ……….…………………… 136.6 Alcoholic beverages….................................................. 200.7 Housing.......................................................................... 203.2 Shelter...............…....................................................... 232.1 Rent of primary residence…...................................... 225.1 Lodging away from home……………………………… 136.0 3 2007 2007 206.659 144.068 207.026 209.586 240.611 234.679 153.384 174.440 178.235 173.691 189.518 206.931 144.785 207.624 211.286 242.067 234.732 154.791 174.686 178.256 174.251 189.781 207.756 145.376 208.264 211.098 242.238 235.311 155.007 174.201 178.172 174.105 189.076 208.805 146.752 208.408 210.865 241.990 236.058 155.545 174.695 177.236 176.050 189.695 209.275 146.074 209.126 210.701 242.405 237.135 154.299 173.963 178.600 175.327 188.340 209.854 146.628 209.018 210.745 242.207 238.169 153.648 174.057 178.631 176.068 188.325 210.233 145.814 208.704 210.933 242.372 239.102 157.863 176.085 180.193 181.813 190.037 211.070 146.649 210.425 212.244 243.871 239.850 157.805 177.863 180.588 184.878 192.064 211.878 148.385 212.044 213.026 244.786 240.325 158.089 178.238 182.214 182.808 192.597 212.537 148.564 212.407 214.389 245.995 240.874 159.730 181.806 184.878 190.640 195.993 213.083 148.667 213.503 214.890 246.004 241.474 158.336 182.680 185.097 193.364 196.787 213.967 149.666 213.532 215.809 246.069 241.803 158.320 183.804 185.558 196.150 197.888 215.015 149.873 213.912 217.941 247.083 242.640 159.346 185.725 187.067 201.205 199.566 216.376 151.120 214.394 219.610 248.075 243.367 142.813 153.016 150.236 144.480 143.172 136.703 133.545 140.176 144.092 149.434 146.378 145.634 148.621 153.032 238.2 246.235 246.149 246.815 247.487 248.075 248.876 249.532 250.106 250.481 250.966 251.418 251.576 252.170 252.504 116.5 194.7 177.1 234.9 182.1 127.0 119.5 114.1 110.7 117.004 200.632 181.744 251.453 186.262 126.875 118.998 112.368 110.296 116.577 206.140 187.624 245.680 193.184 126.894 113.500 109.568 101.291 116.926 204.334 185.453 246.542 190.710 126.520 114.439 109.032 103.237 116.783 204.264 185.306 252.580 190.158 126.193 119.535 112.380 110.973 116.640 200.836 181.509 261.745 185.337 126.233 121.846 114.953 113.402 116.997 202.161 182.725 291.845 184.753 126.252 121.204 114.807 112.166 117.003 203.006 183.516 299.296 185.155 126.066 118.257 112.026 109.418 117.435 204.796 185.107 306.937 186.475 126.515 115.795 110.691 104.367 117.622 205.795 185.994 308.269 187.376 126.753 117.839 112.917 106.340 117.701 209.221 189.693 332.139 190.105 127.423 120.881 114.994 110.645 118.422 213.302 194.121 342.811 194.379 127.332 122.113 116.653 111.221 118.411 219.881 201.212 363.872 200.999 127.598 120.752 116.479 108.722 119.092 231.412 213.762 389.423 213.375 127.625 117.019 112.011 104.312 118.764 239.039 221.742 395.706 221.805 127.884 114.357 109.669 100.049 116.5 123.5 180.9 177.0 113.948 122.374 184.682 180.778 108.759 119.375 187.690 183.619 110.221 120.329 184.480 180.408 113.611 123.183 184.532 180.586 117.149 124.675 184.952 180.919 117.339 125.005 190.677 186.839 113.779 122.258 189.984 186.134 113.861 121.148 190.839 186.978 115.750 122.377 190.520 186.571 116.037 124.407 195.189 191.067 116.358 126.212 198.608 194.574 114.582 125.537 205.262 201.133 111.555 123.568 211.787 207.257 109.218 122.421 212.806 208.038 2 New and used motor vehicles ……….…………………… 95.6 New vehicles…........................................................ 137.6 1 Used cars and trucks ……….……………………………… 140.0 Motor fuel…............................................................... 221.0 Gasoline (all types)…............................................... 219.9 Motor vehicle parts and equipment…........................ 117.3 Motor vehicle maintenance and repair…................... 215.6 Public transportation...............….................................. 226.6 Medical care................................................................... 336.2 Medical care commodities...............…......................... 285.9 Medical care services...............…................................ 350.6 Professional services…............................................. 289.3 Hospital and related services…................................. 468.1 2 Recreation ……….………………………………………….……… 110.9 1,2 Video and audio ……….……………………………………… 104.6 2 Education and communication ……….……………………… 116.8 94.303 136.254 135.747 239.070 237.959 121.583 222.963 230.002 351.054 289.999 369.302 300.792 498.922 111.443 102.949 119.577 93.961 135.415 136.024 252.909 251.883 121.514 223.487 235.767 351.643 290.257 370.008 301.131 499.400 111.347 102.779 119.025 94.121 135.204 137.138 238.194 237.108 121.730 224.019 233.112 352.961 291.164 371.461 302.259 501.026 111.139 102.311 120.311 93.985 134.927 137.142 239.104 237.993 122.292 224.302 230.694 353.723 291.340 372.432 302.410 504.206 111.400 102.759 121.273 94.201 135.344 136.950 239.048 237.819 123.017 224.939 232.725 355.653 292.161 374.750 303.532 510.006 111.753 103.157 121.557 94.562 136.250 136.616 262.282 260.943 123.487 225.672 233.758 357.041 293.201 376.250 303.780 515.359 111.842 102.719 121.409 94.754 136.664 136.943 258.132 256.790 123.928 226.120 233.408 357.661 293.610 376.940 304.784 515.677 111.705 102.691 121.506 94.834 136.827 137.203 260.523 259.338 124.282 227.732 234.334 360.459 295.355 380.135 306.529 523.313 112.083 102.986 121.762 94.581 136.279 137.248 259.242 257.845 125.225 228.731 235.724 362.155 296.130 382.196 307.928 527.971 112.365 103.171 121.766 94.318 135.727 137.225 278.739 276.497 126.325 229.765 242.929 363.000 297.308 382.872 308.726 528.968 112.731 103.548 121.832 93.973 135.175 136.787 294.291 291.910 126.049 230.528 244.164 363.184 296.951 383.292 309.227 530.144 112.874 103.477 122.073 93.705 134.669 136.325 322.124 319.787 126.824 231.730 251.600 363.396 294.896 384.505 310.917 531.022 112.987 102.988 122.348 93.598 134.516 135.980 347.418 344.981 127.824 233.162 264.681 363.616 295.194 384.685 311.317 531.606 112.991 102.306 122.828 93.650 134.397 135.840 349.731 347.357 129.118 234.788 270.002 363.963 294.777 385.361 311.926 533.558 113.277 102.203 123.445 Owners' equivalent rent of primary residence ……… 1,2 Tenants' and household insurance ……….………… Fuels and utilities…................................................... Fuels...............…...................................................... Fuel oil and other fuels…....................................... Gas (piped) and electricity….................................. Household furnishings and operations…................... Apparel .......................................................................... Men's and boys' apparel…......................................... Women's and girls' apparel….................................... 1 Infants' and toddlers' apparel ……….…………………… Footwear…................................................................ Transportation................................................................ Private transportation...............…................................ 2 Education ……….………………………………………….……… 162.1 Educational books and supplies…........................... 388.9 Tuition, other school fees, and child care…............. 1,2 Communication ……….……………………………………… 1,2 Information and information processing ……….… 1,2 Telephone services ……….…………………………… Information and information processing other than telephone services 1,4 ……….…………… 468.1 84.1 171.388 169.490 172.873 175.486 176.339 176.717 176.927 177.440 177.460 177.407 177.754 177.994 178.385 179.229 420.418 418.394 427.425 430.114 431.432 431.606 434.352 437.822 439.052 439.906 442.160 442.770 443.309 444.382 494.079 488.382 498.071 505.924 508.449 509.605 510.016 511.301 511.253 511.013 511.887 512.579 513.743 516.264 83.367 83.553 83.655 83.690 83.659 83.250 83.282 83.396 83.391 83.502 83.670 83.929 84.394 84.840 81.7 95.8 80.720 98.247 80.840 98.570 80.944 98.813 80.976 98.882 80.946 99.031 80.519 98.775 80.546 98.792 80.642 98.906 80.638 98.837 80.752 99.031 80.921 99.494 81.080 81.513 81.965 99.879 100.677 101.339 12.5 10.597 10.528 10.487 10.477 10.385 10.204 10.215 10.229 10.253 10.246 10.170 10.118 10.071 10.087 Personal computers and peripheral 1,2 120.9 321.7 519.9 108.411 107.439 106.575 105.806 104.336 100.104 100.000 100.998 100.545 100.359 98.853 97.028 95.663 94.711 333.328 333.415 333.325 334.801 335.680 336.379 337.633 339.052 340.191 341.827 343.410 344.709 345.885 346.810 554.184 553.987 555.217 559.636 560.626 561.967 566.696 572.684 575.227 574.890 576.359 581.185 589.904 596.782 1 Personal care ……….………………………………………….… 190.2 1 Personal care products ……….…………………………… 155.8 1 Personal care services ……….…………………………… 209.7 195.622 195.704 195.521 196.202 196.763 197.156 197.643 198.112 198.716 199.982 201.028 201.523 201.537 201.545 158.285 158.457 157.788 157.643 158.381 158.561 158.236 158.201 157.677 158.440 159.398 158.790 158.868 158.989 216.559 216.720 217.028 217.589 217.887 218.604 219.656 219.932 220.848 222.752 222.799 223.649 223.520 223.719 equipment ……….………………………………… Other goods and services.............................................. Tobacco and smoking products...............…................ See footnotes at end of table. Monthly Labor Review • September 2008 111 Current Labor Statistics: Price Data 38. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] Annual average 2006 2007 Series Miscellaneous personal services...............….... July Aug. 2007 Sept. Oct. Nov. Dec. Jan. Feb. Mar. 2008 Apr. May June July 313.6 324.984 324.579 325.566 327.783 328.056 328.610 329.908 332.183 333.826 335.427 337.685 339.824 340.547 340.077 Commodity and service group: Commodities...........…............................................ Food and beverages…......................................... Commodities less food and beverages…............. Nondurables less food and beverages…............ Apparel …......................................................... and apparel…................................................. Durables….......................................................... Services….............................................................. 3 Rent of shelter ……….…………………………………… Transportation services….................................... Other services….................................................. Special indexes: All items less food…............................................ All items less shelter…........................................ All items less medical care…............................... Commodities less food…..................................... Nondurables less food…..................................... Nondurables less food and apparel…................. Nondurables…..................................................... 3 Services less rent of shelter ……….………………… Services less medical care services…................ Energy….............................................................. All items less energy…........................................ All items less food and energy…....................... Commodities less food and energy….............. Energy commodities...................................... Services less energy….................................... 164.0 167.509 167.938 166.955 167.952 168.664 171.043 170.511 171.179 171.530 173.884 175.838 178.341 180.534 181.087 195.7 145.9 176.7 119.5 203.300 147.515 182.526 118.998 203.533 148.016 183.947 113.500 204.289 146.317 180.480 114.439 205.279 147.289 182.902 119.535 206.124 147.924 184.091 121.846 206.563 151.067 190.560 121.204 206.936 150.162 188.635 118.257 208.837 150.303 188.692 115.795 209.462 150.530 189.420 117.839 209.692 153.682 196.185 120.881 211.365 155.690 200.926 122.113 212.251 158.778 207.875 120.752 213.383 161.337 213.489 117.019 215.326 161.301 213.363 114.357 216.3 226.224 231.983 225.694 226.509 227.026 238.067 236.735 238.389 238.297 247.546 254.599 266.943 278.584 280.062 114.5 238.9 241.9 230.8 277.5 112.473 246.848 250.813 233.731 285.559 112.177 248.331 252.358 234.632 284.859 112.036 248.555 252.530 234.563 286.492 111.746 248.700 252.272 234.322 288.469 111.889 248.878 252.713 235.458 289.307 112.103 248.974 252.495 236.449 289.592 112.093 249.225 252.669 236.504 289.945 112.300 250.648 254.239 237.347 290.905 112.094 251.527 255.199 237.929 291.406 112.059 252.817 256.470 239.556 292.218 111.671 253.426 256.463 240.150 293.016 111.362 254.509 256.532 242.343 293.959 111.232 256.668 257.585 245.759 294.668 111.275 258.422 258.637 247.869 295.677 202.7 208.098 209.179 208.607 209.100 209.478 210.846 210.610 211.512 212.136 214.236 215.462 217.411 219.757 220.758 191.9 194.7 148.0 178.2 213.9 186.7 253.3 229.6 196.9 203.7 205.9 140.6 223.0 244.7 196.639 200.080 149.720 184.012 223.411 193.468 260.764 236.847 207.723 208.925 210.729 140.053 241.018 253.058 197.408 201.042 150.225 185.382 228.641 194.326 262.284 238.357 217.274 208.980 210.756 138.757 253.696 253.998 196.803 200.598 148.591 182.170 223.057 192.869 262.588 238.507 209.294 209.399 211.111 138.895 239.885 254.491 197.708 201.159 149.541 184.450 223.802 194.616 263.243 238.604 209.637 210.000 211.628 139.828 241.120 254.706 198.171 201.544 150.180 185.610 224.338 195.646 263.109 238.657 207.588 210.714 212.318 140.501 241.642 255.385 199.998 202.770 153.234 191.668 234.241 199.253 263.599 238.671 219.009 210.888 212.435 140.547 265.420 255.549 199.734 202.600 152.344 189.844 233.014 198.422 263.966 238.894 217.506 210.890 212.356 140.014 261.976 255.785 200.609 203.569 152.531 190.000 234.667 199.346 265.311 240.201 219.465 211.846 213.138 139.845 264.660 257.220 201.110 204.136 152.799 190.781 234.736 200.030 266.154 241.004 219.311 212.545 213.866 140.324 263.508 258.098 203.217 205.992 155.881 197.167 243.109 203.767 267.567 242.310 230.505 213.420 214.866 141.056 283.362 259.249 205.040 207.317 157.870 201.693 249.571 207.096 269.007 242.921 240.194 213.851 215.059 141.156 298.757 259.503 207.566 209.170 160.880 208.233 260.703 211.240 271.467 243.982 257.106 214.101 215.180 140.677 326.414 260.049 210.242 211.408 163.385 213.538 271.235 214.783 275.200 246.219 275.621 214.600 215.553 139.925 351.886 261.216 211.468 212.576 163.364 213.447 272.612 215.628 277.982 248.007 280.833 215.335 216.045 139.535 354.423 262.323 CONSUMER PRICE INDEX FOR URBAN WAGE EARNERS AND CLERICAL WORKERS All items.................................................................... 197.1 202.767 203.700 203.199 203.889 204.338 205.891 205.777 206.744 207.254 209.147 210.698 212.788 215.223 216.304 All items (1967 = 100)............................................... Food and beverages................................................ 587.2 194.9 194.4 192.2 213.1 186.1 180.9 251.0 Food..................….................................................. Food at home….................................................... Cereals and bakery products….......................... Meats, poultry, fish, and eggs…......................... 1 Dairy and related products ……….………………… Fruits and vegetables…...................................... Nonalcoholic beverages and beverage materials…....................................................... Other foods at home…....................................... Sugar and sweets…......................................... Fats and oils….................................................. Other foods…................................................... 1,2 Other miscellaneous foods ……….…………… 1 Food away from home ……….…………………………… 1,2 Other food away from home ……….……………… Alcoholic beverages…........................................... Housing.................................................................... Shelter...............…................................................ Rent of primary residence…............................... 2 Lodging away from home ……….…………………… 3 Owners' equivalent rent of primary residence … 1,2 Tenants' and household insurance ……….…… Fuels and utilities…........................................... Fuels...............….............................................. Fuel oil and other fuels…................................ Gas (piped) and electricity….......................... Household furnishings and operations…............ Apparel ................................................................... Men's and boys' apparel…................................. Women's and girls' apparel…............................. 1 Infants' and toddlers' apparel ……….……………… Footwear…......................................................... Transportation.......................................................... Private transportation...............…......................... 2 New and used motor vehicles ……….……………… See footnotes at end of table. 112 603.982 202.531 202.134 200.273 222.409 195.193 194.474 260.484 606.759 202.823 202.409 200.569 223.663 196.323 198.027 252.703 605.267 203.610 203.207 201.321 224.220 196.844 201.598 251.575 607.324 204.584 204.241 202.351 223.895 197.980 203.464 257.223 608.662 205.428 205.082 203.442 224.897 198.146 205.100 261.774 613.287 205.763 205.451 203.741 225.941 198.325 205.850 265.736 612.948 206.141 205.855 204.141 226.696 198.489 205.149 269.533 615.828 208.055 207.794 206.870 229.105 199.686 206.652 275.843 617.345 208.674 208.317 207.242 233.915 199.141 207.750 268.954 622.985 208.927 208.571 207.196 236.764 199.484 205.660 266.030 627.606 210.559 210.252 209.657 240.663 200.285 207.135 270.169 633.830 211.438 211.200 210.624 244.648 200.501 207.088 274.136 641.082 212.700 212.514 212.079 246.493 202.424 208.510 276.641 644.303 214.662 214.577 214.679 250.972 204.557 213.582 278.885 146.7 152.786 152.829 154.152 154.501 154.873 153.610 152.883 157.130 157.456 157.488 158.799 157.285 157.309 158.527 169.1 170.5 168.7 185.2 114.2 199.1 136.2 200.6 172.630 175.323 173.640 188.405 115.356 206.412 143.462 207.097 173.727 176.736 174.109 189.667 115.355 206.657 144.439 207.647 173.997 176.664 174.872 189.941 116.348 207.533 144.938 208.253 173.463 176.458 175.039 189.110 114.584 208.578 145.783 208.286 174.215 176.248 176.683 189.987 115.378 209.037 144.764 209.176 173.393 176.845 176.101 188.657 115.803 209.518 145.233 208.958 173.511 177.051 176.736 188.646 115.658 209.931 144.454 208.934 175.572 178.902 182.307 190.364 115.658 210.776 145.625 210.473 177.442 179.740 185.292 192.430 118.828 211.517 146.924 212.507 177.713 181.033 183.706 192.832 117.754 212.193 147.188 212.748 181.215 183.725 191.560 196.106 118.751 212.794 147.335 213.633 182.241 184.127 194.228 197.081 119.248 213.723 148.517 213.486 183.342 184.378 197.155 198.153 118.879 214.851 149.306 213.976 185.174 186.054 201.821 199.722 121.015 216.177 150.232 214.440 198.5 224.8 224.2 135.3 216.0 116.8 204.795 232.998 233.806 142.339 223.175 117.366 206.183 233.848 233.855 153.107 223.093 116.912 206.054 234.169 234.457 149.919 223.693 117.287 206.050 234.275 235.175 143.727 224.321 117.142 205.916 234.812 236.259 142.666 224.811 116.982 206.288 235.069 237.288 136.244 225.548 117.370 206.638 235.480 238.216 133.179 226.151 117.396 207.692 236.550 238.955 139.825 226.703 117.740 208.268 237.158 239.419 143.046 227.057 117.921 209.388 237.965 239.932 148.110 227.488 117.999 210.161 238.261 240.507 145.936 227.893 118.683 211.191 238.353 240.818 144.979 228.007 118.615 213.441 239.198 241.623 148.378 228.536 119.293 215.026 239.845 242.276 152.248 228.824 119.006 193.1 174.4 234.0 180.2 122.6 119.1 114.0 110.3 118.6 123.1 198.863 179.031 251.121 184.357 122.477 118.518 112.224 110.202 116.278 122.062 204.272 184.725 245.633 191.010 122.550 113.157 109.580 101.709 110.906 119.278 202.397 182.518 246.382 188.511 122.190 114.146 108.556 103.960 112.879 119.831 202.304 182.357 252.684 187.963 121.820 118.986 111.981 110.847 115.896 122.846 198.796 178.539 261.972 183.172 122.039 121.536 114.710 113.623 119.670 124.372 200.151 179.777 292.098 182.781 122.031 120.920 114.784 112.165 119.897 124.649 200.831 180.379 298.656 183.066 121.880 118.126 112.487 109.375 116.419 122.029 202.663 182.025 306.087 184.522 122.322 115.866 111.494 104.456 116.323 121.137 203.584 182.823 307.599 185.324 122.547 117.883 113.592 106.512 118.442 122.408 206.861 186.315 329.271 188.143 123.184 120.809 115.808 110.712 118.990 124.343 210.912 190.657 339.009 192.434 123.108 121.855 117.136 110.971 119.200 126.150 217.388 197.554 358.947 199.045 123.287 120.407 116.621 108.594 117.213 125.335 228.843 209.843 381.903 211.398 123.434 116.706 112.395 104.062 114.057 123.381 236.381 217.640 388.208 219.612 123.798 113.978 109.969 99.772 111.502 122.380 180.3 184.344 187.606 184.147 184.361 184.639 190.761 189.967 190.918 190.639 195.710 199.556 206.757 213.633 214.533 177.5 181.496 184.684 181.218 181.495 181.717 187.951 187.159 188.093 187.762 192.740 196.641 203.781 210.423 211.201 94.7 93.300 93.042 93.229 93.118 93.268 93.529 93.733 93.842 93.664 93.455 93.158 92.850 92.714 92.686 Monthly Labor Review • September 2008 38. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] 2006 New vehicles…............................................ 1 Used cars and trucks ……….…………………… Motor fuel…................................................... Gasoline (all types)….................................. Motor vehicle parts and equipment…............ Motor vehicle maintenance and repair…....... Public transportation...............…..................... Medical care....................................................... Medical care commodities...............…............ Medical care services...............…................... Professional services…................................. Hospital and related services…..................... 2 Recreation ……….……………………………………… Video and audio 1,2 ……….…………………………… 2 Education and communication ……….…………… 2 2007 2008 2007 Annual average Series July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July 138.6 137.415 136.663 136.414 136.129 136.509 137.372 137.736 137.931 137.445 136.910 136.456 135.933 135.728 135.556 140.8 221.6 220.7 116.9 218.1 225.0 136.586 239.900 238.879 121.356 225.535 228.531 136.880 253.893 252.957 121.350 226.090 233.390 137.999 239.097 238.100 121.584 226.636 231.082 137.996 240.271 239.252 122.144 226.881 229.148 137.798 240.040 238.906 122.830 227.472 231.182 137.457 263.248 262.013 123.302 228.267 231.999 137.791 259.032 257.792 123.786 228.692 231.363 138.052 261.531 260.457 124.416 230.255 232.594 138.094 260.402 259.112 125.238 231.349 233.979 138.070 279.975 277.842 126.330 232.344 240.729 137.616 295.618 293.349 126.032 232.983 241.966 137.145 323.495 321.291 126.742 234.221 249.310 136.790 348.762 346.459 127.750 235.550 261.779 136.639 351.124 348.888 128.997 237.324 266.259 335.7 279.0 351.1 291.7 463.6 350.882 282.558 370.111 303.169 493.740 351.346 282.662 370.696 303.481 493.563 352.704 283.379 372.261 304.677 495.191 353.571 283.712 373.306 304.841 498.533 355.719 284.517 375.899 306.072 505.077 357.165 285.475 377.498 306.300 510.836 357.745 285.913 378.119 307.333 510.961 360.710 287.703 381.507 309.169 518.853 362.329 288.335 383.510 310.426 523.654 363.069 289.254 384.149 311.259 524.534 363.356 288.796 384.753 311.757 526.495 363.462 286.825 385.769 313.294 527.230 363.628 287.033 385.911 313.618 527.948 363.942 286.562 386.560 314.235 529.798 108.2 108.572 108.403 108.179 108.495 108.793 108.805 108.702 109.046 109.315 109.742 109.775 109.876 109.905 110.198 103.9 102.559 102.358 101.923 102.427 102.833 102.465 102.523 102.839 103.028 103.525 103.414 102.958 102.306 102.267 113.9 116.301 115.980 116.981 117.707 117.891 117.686 117.782 118.097 118.079 118.155 118.462 118.737 119.264 119.852 Education ……….……………………………………… Educational books and supplies….............. 160.3 169.280 167.527 170.635 173.060 173.700 174.016 174.276 175.134 175.118 175.101 175.545 175.791 176.148 176.879 390.7 423.730 421.529 431.089 433.670 434.800 434.979 437.391 441.207 441.927 442.639 444.594 445.394 445.740 446.741 Tuition, other school fees, and child care… 453.3 477.589 472.395 480.960 488.199 490.061 491.022 491.554 493.797 493.672 493.546 494.711 495.384 496.449 498.598 86.0 85.782 86.015 86.148 86.184 86.182 85.807 85.834 85.935 85.919 86.016 86.244 86.496 87.017 87.490 1,2 Communication ……….…………………………… 1,2 Information and information processing … 1,2 Telephone services ……….………………… Information and information processing other than telephone services 1,4 ……….… 84.3 83.928 84.111 84.248 84.283 84.282 83.894 83.917 84.008 83.992 84.091 84.320 84.511 95.9 98.373 98.721 98.964 99.024 99.149 98.874 98.887 98.988 98.931 99.090 99.566 99.939 100.723 101.375 85.007 13.0 11.062 11.001 10.965 10.958 10.877 10.710 10.722 10.737 10.754 10.745 10.671 10.621 10.585 85.484 10.600 Personal computers and peripheral 1,2 equipment ……….……………………… Other goods and services.................................. Tobacco and smoking products...............….... 1 Personal care ……….………………………………… 121.0 108.164 107.371 106.531 105.713 104.366 100.257 100.000 101.067 100.582 100.265 98.820 97.010 95.766 94.691 330.9 344.004 344.221 344.214 345.800 346.742 347.427 348.830 350.630 351.979 353.351 354.887 356.523 358.419 359.961 521.6 555.502 555.366 556.517 561.092 562.134 563.435 568.410 574.724 577.359 576.910 578.296 583.296 592.248 599.180 188.3 193.590 193.792 193.598 194.160 194.769 195.122 195.467 195.885 196.564 197.803 198.859 199.367 199.404 199.495 1 155.7 158.268 158.445 157.813 157.654 158.408 158.579 158.407 158.167 157.877 158.730 159.585 158.993 159.052 159.237 1 209.8 216.823 217.040 217.354 217.822 218.149 218.897 219.945 220.324 221.338 223.043 223.088 223.922 223.838 223.994 314.1 326.100 326.135 327.235 329.329 329.706 330.258 330.850 333.154 334.868 336.476 338.851 341.212 341.921 341.763 Personal care products ……….………………… Personal care services ……….………………… Miscellaneous personal services...............… Commodity and service group: Commodities...........…....................................... Food and beverages….................................... Commodities less food and beverages…........ Nondurables less food and beverages…...... Apparel …................................................... 165.7 194.9 148.7 182.6 119.1 169.554 202.531 150.865 189.507 118.518 170.252 202.823 151.724 191.603 113.157 169.122 203.610 149.781 187.515 114.146 170.141 204.584 150.795 189.981 118.986 170.865 205.428 151.448 191.230 121.536 173.489 205.763 155.011 198.661 120.920 172.952 206.141 154.086 196.636 118.126 173.711 208.055 154.345 196.910 115.866 174.083 208.674 154.603 197.606 117.883 176.727 208.927 158.156 205.166 120.809 178.900 210.559 160.488 210.558 121.855 181.837 211.438 164.188 218.794 120.407 184.495 212.700 167.344 225.585 116.706 185.105 214.662 167.376 225.595 113.978 Nondurables less food, beverages, and apparel…............................................ Durables….................................................... Services…......................................................... 3 Rent of shelter ……….……………………………… Transporatation services…............................ Other services…............................................. 226.1 237.858 244.695 237.329 238.345 238.798 251.442 249.863 251.751 251.621 262.252 270.496 285.024 298.593 300.341 114.6 112.640 112.425 112.362 112.114 112.241 112.413 112.450 112.688 112.560 112.549 112.171 111.845 111.769 111.820 234.1 241.696 242.901 243.118 243.436 243.572 243.906 244.275 245.484 246.154 247.197 248.045 249.175 251.365 252.991 216.6 224.617 225.455 225.760 225.867 226.393 226.636 227.035 228.071 228.660 229.443 229.719 229.810 230.620 231.255 230.6 233.420 233.737 233.831 233.868 234.848 235.874 236.020 236.883 237.426 238.496 239.044 240.728 243.395 245.005 268.2 275.218 274.766 276.015 277.702 278.404 278.513 278.783 279.780 280.199 281.017 281.829 282.720 283.449 284.449 Special indexes: All items less food…....................................... All items less shelter…................................... All items less medical care….......................... Commodities less food…............................... Nondurables less food…................................ Nondurables less food and apparel…............ Nondurables…............................................... 3 Services less rent of shelter ……….…………… Services less medical care services…........... Energy…........................................................ All items less energy…................................... All items less food and energy….................. Commodities less food and energy…........ Energy commodities................................. Services less energy…............................... 1 Not seasonally adjusted. 2 Indexes on a December 1997 = 100 base. 3 Indexes on a December 1982 = 100 base. 197.5 189.2 191.3 150.6 183.8 223.0 189.5 202.698 193.940 196.564 152.875 190.698 234.201 196.772 203.750 194.913 197.504 153.730 192.714 240.471 198.000 203.011 194.109 196.949 151.846 188.873 233.817 196.266 203.638 195.018 197.629 152.837 191.210 234.745 198.017 204.015 195.440 198.022 153.499 192.442 235.233 199.075 205.783 197.479 199.565 156.977 199.471 246.726 203.087 205.575 197.174 199.431 156.073 197.551 245.286 202.222 206.371 198.113 200.329 156.365 197.892 247.136 203.268 206.877 198.592 200.800 156.670 198.660 247.188 203.933 209.055 200.904 202.713 160.152 205.843 256.899 208.101 210.583 202.931 204.290 162.455 211.005 264.488 211.757 212.870 205.774 206.423 166.070 218.809 277.717 216.582 215.498 208.817 208.906 169.169 225.276 290.127 220.813 216.407 210.069 210.002 169.213 225.309 291.760 221.740 224.7 225.3 196.8 198.0 199.2 141.1 223.0 239.9 230.876 232.195 208.066 203.002 203.554 140.612 241.257 247.888 232.367 233.415 217.795 202.849 203.310 139.352 254.282 248.434 232.450 233.562 209.441 203.319 203.710 139.557 240.247 248.977 232.982 233.839 209.933 204.037 204.363 140.491 241.692 249.398 232.628 233.850 207.885 204.797 205.107 141.236 241.955 250.127 233.029 234.115 219.861 205.066 205.355 141.254 265.598 250.546 233.314 234.468 218.104 205.155 205.377 140.815 261.928 250.925 234.576 235.557 220.163 205.991 205.992 140.696 264.633 252.103 235.258 236.154 219.983 206.588 206.605 141.238 263.601 252.756 236.483 237.201 231.533 207.296 207.406 141.973 283.359 253.589 237.922 238.048 241.518 207.812 207.687 142.040 298.852 254.031 240.181 239.167 258.903 208.021 207.747 141.558 326.565 254.517 243.780 241.422 277.597 208.458 208.007 140.878 351.873 255.513 246.411 243.071 282.579 209.062 208.317 140.492 354.402 256.365 4 Indexes on a December 1988 = 100 base. NOTE: Index applied to a month as a whole, not to any specific date. Monthly Labor Review • September 2008 113 Current Labor Statistics: Price Data 39. Consumer Price Index: U.S. city average and available local area data: all items [1982–84 = 100, unless otherwise indicated] Pricing All Urban Consumers sched- 2008 ule1 U.S. city average…………………………………………… Feb. Mar. Apr. Urban Wage Earners 2008 May June July Feb. Mar. Apr. May June July M 211.693 213.528 214.823 216.632 218.815 219.964 207.254 209.147 210.698 212.788 215.223 216.304 Northeast urban……….………………………………………….……… M 225.213 226.926 228.133 230.089 232.649 234.545 221.702 223.209 224.794 227.114 229.829 231.488 Size A—More than 1,500,000........................................... M 227.411 229.087 230.038 232.005 234.518 236.460 222.315 223.795 225.144 227.412 230.120 231.808 M 133.511 134.611 135.739 136.913 138.542 139.623 133.893 134.846 136.141 137.624 139.286 140.253 M 201.896 203.723 205.393 207.168 208.968 210.071 197.110 198.989 200.788 202.912 204.867 206.038 M 203.347 205.141 206.590 208.291 209.813 211.003 197.549 199.378 200.989 202.969 204.509 205.761 M 128.922 130.121 131.484 132.682 134.018 134.595 128.695 129.922 131.354 132.867 134.409 135.037 Region and area size2 3 Size B/C—50,000 to 1,500,000 ……….………………………… 4 Midwest urban ……….………………………………………….………… Size A—More than 1,500,000........................................... 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size D—Nonmetropolitan (less than 50,000)…………..... M 197.596 199.472 200.841 202.720 205.122 206.435 195.774 197.864 199.325 201.494 204.023 205.452 South urban…….….............................................................. M 205.060 206.676 208.085 210.006 212.324 213.304 202.291 204.044 205.669 207.912 210.469 211.438 Size A—More than 1,500,000........................................... M 207.605 209.065 209.987 211.846 214.359 215.373 205.588 207.336 208.511 210.748 213.549 214.379 M 130.351 131.442 132.516 133.714 134.980 135.643 129.144 130.243 131.428 132.808 134.222 134.952 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size D—Nonmetropolitan (less than 50,000)…………..... M 205.189 206.933 208.746 211.225 214.739 215.274 205.523 207.600 209.641 212.533 216.357 216.901 West urban…….…............................................................... M 216.339 218.533 219.437 221.009 223.040 223.867 210.816 213.159 214.355 216.029 218.508 219.248 Size A—More than 1,500,000........................................... M 219.799 221.997 222.689 224.704 226.767 227.562 212.614 214.954 216.055 218.141 220.603 221.232 M 131.538 132.896 133.694 134.023 135.283 136.021 131.148 132.640 133.570 134.133 135.738 136.478 M M M 193.685 195.314 196.191 197.898 199.840 200.941 191.982 193.702 194.886 196.844 199.028 200.009 130.728 131.892 132.974 133.997 135.330 136.055 130.092 131.273 132.471 133.729 135.240 135.986 203.803 205.730 207.238 209.308 211.989 212.555 202.292 204.422 205.951 208.246 211.236 211.929 Chicago–Gary–Kenosha, IL–IN–WI………………………….. Los Angeles–Riverside–Orange County, CA……….………… M M 209.526 211.542 212.662 214.932 215.738 217.459 202.497 204.742 205.885 208.403 209.021 211.020 221.431 223.606 224.625 226.651 229.033 229.886 214.231 216.493 217.914 219.702 222.435 223.245 New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA… M 231.020 233.122 233.822 236.151 238.580 240.273 225.281 226.951 228.215 230.923 233.776 235.446 Boston–Brockton–Nashua, MA–NH–ME–CT……….………… 1 – 233.084 – 235.344 – 241.258 – 232.656 – 235.419 – 240.511 Cleveland–Akron, OH…………………………………………… 1 – 202.500 – 204.882 – 206.941 – 192.995 – 195.898 – 198.063 Dallas–Ft Worth, TX…….……………………………………… 1 – 198.596 – 202.357 – 206.413 – 201.892 – 206.258 – 210.830 Washington–Baltimore, DC–MD–VA–WV ……….……………… 1 – 138.090 – 139.649 – 142.065 – 137.544 – 139.332 – 141.622 Atlanta, GA……………………..………………………………… 2 204.166 – 206.371 – 212.032 – 203.473 – 205.801 – 212.013 Detroit–Ann Arbor–Flint, MI…………………………………… 2 202.378 – 205.281 – 207.593 – 197.670 – 201.037 – 203.524 – Houston–Galveston–Brazoria, TX……………………………… 2 187.585 – 188.795 – 193.567 – 185.904 – 188.463 – 193.742 – Miami–Ft. Lauderdale, FL……………...……………………… 2 219.082 – 221.324 – 225.079 – 216.971 – 219.456 – 223.849 – Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD…… 2 220.935 – 223.622 – 228.408 – 220.718 – 223.295 – 228.429 – San Francisco–Oakland–San Jose, CA…….………………… 2 219.612 – 222.074 – 225.181 – 214.913 – 217.913 – 221.454 – Seattle–Tacoma–Bremerton, WA………………...…………… 2 221.728 – 223.196 – 228.068 – 216.332 – 218.483 – 223.573 – 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size classes: 5 A ……….………………………………………….…………..…………… 3 B/C ……………………….….………………………………………….… D…………….…………...................................................... Selected local areas 6 7 1 Foods, fuels, and several other items priced every month in all areas; most other goods and services priced as indicated: M—Every month. 1—January, March, May, July, September, and November. 2—February, April, June, August, October, and December. Report : Anchorage, AK; Cincinnatti, OH–KY–IN; Kansas City, MO–KS; Milwaukee–Racine, WI; Minneapolis–St. Paul, MN–WI; Pittsburgh, PA; Port-land–Salem, OR–WA; St Louis, MO–IL; San Diego, CA; Tampa–St. Petersburg–Clearwater, FL. 2 Regions defined as the four Census regions. 3 Indexes on a December 1996 = 100 base. NOTE: Local area CPI indexes are byproducts of the national CPI program. Each local index has a smaller sample size and is, therefore, subject to substantially more sampling and other measurement error. As a result, local area indexes show greater volatility than the national index, although their long-term trends are similar. Therefore, the Bureau of Labor Statistics strongly urges users to consider adopting the national average CPI for use in their escalator clauses. Index applies to a month as a whole, not to any specific date. Dash indicates data not available. 4 The "North Central" region has been renamed the "Midwest" region by the Census Bureau. It is composed of the same geographic entities. 5 Indexes on a December 1986 = 100 base. 6 In addition, the following metropolitan areas are published semiannually and appear in tables 34 and 39 of the January and July issues of the CPI Detailed 114 Monthly Labor Review • September 2008 7 Indexes on a November 1996 = 100 base. – 40. Annual data: Consumer Price Index, U.S. city average, all items and major groups [1982–84 = 100] Series Consumer Price Index for All Urban Consumers: All items: Index..................……............................................... Percent change............................…………………… Food and beverages: Index................……................................................. Percent change............................…………………… Housing: Index....………………............................................... Percent change............................…………………… Apparel: Index........................……......................................... Percent change............................…………………… Transportation: Index........................………...................................... Percent change............................…………………… Medical care: Index................……................................................. Percent change............................…………………… Other goods and services: Index............……..................................................... Percent change............................…………………… Consumer Price Index for Urban Wage Earners and Clerical Workers: All items: Index....................……………................................... Percent change............................…………………… 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 160.5 2.3 163.0 1.6 166.6 2.2 172.2 3.4 177.1 2.8 179.9 1.6 184.0 2.3 188.9 2.7 195.3 3.4 201.6 3.2 207.342 2.8 157.7 2.6 161.1 2.2 164.6 2.2 168.4 2.3 173.6 3.1 176.8 1.8 180.5 2.1 186.6 3.3 191.2 2.5 195.7 2.4 203.300 3.9 156.8 2.6 160.4 2.3 163.9 2.2 169.6 3.5 176.4 4.0 180.3 2.2 184.8 2.5 189.5 2.5 195.7 3.3 203.2 3.8 209.586 3.1 132.9 .9 133.0 .1 131.3 –1.3 129.6 –1.3 127.3 –1.8 124.0 –2.6 120.9 –2.5 120.4 –.4 119.5 –.7 119.5 .0 118.998 -0.4 144.3 0.9 141.6 –1.9 144.4 2.0 153.3 6.2 154.3 0.7 152.9 –.9 157.6 3.1 163.1 3.5 173.9 6.6 180.9 4.0 184.682 2.1 234.6 2.8 242.1 3.2 250.6 3.5 260.8 4.1 272.8 4.6 285.6 4.7 297.1 4.0 310.1 4.4 323.2 4.2 336.2 4.0 351.054 4.4 224.8 4.4 237.7 5.7 258.3 8.7 271.1 5.0 282.6 4.2 293.2 3.8 298.7 1.9 304.7 2.0 313.4 2.9 321.7 2.6 333.328 3.6 157.6 2.3 159.7 1.3 163.2 2.2 168.9 3.5 173.5 2.7 175.9 1.4 179.8 2.2 184.5 5.1 191.0 1.1 197.1 3.2 202.767 2.9 Monthly Labor Review • September 2008 115 Current Labor Statistics: Price Data 41. Producer Price Indexes, by stage of processing [1982 = 100] Grouping Finished goods....…………………………… Finished consumer goods......................... Finished consumer foods........................ Annual average 2006 2007 2007 July Aug. Sept. Oct. 2008 Nov. Dec. Jan. Feb. Mar. Apr.p Mayp Junep Julyp 160.4 166.0 156.7 166.6 173.5 167.0 168.5 176.2 166.4 166.1 173.0 166.3 167.4 174.8 168.4 168.6 175.9 169.7 171.4 179.4 169.5 170.4 178.2 172.2 172.0 180.1 174.5 172.3 180.4 173.6 175.1 184.2 176.0 176.7 186.0 175.4 179.6 190.1 177.7 182.5 193.9 180.1 185.0 197.1 180.9 excluding foods..................................... Nondurable goods less food................. Durable goods...................................... Capital equipment................................... 169.2 182.6 136.9 146.9 175.6 191.7 138.3 149.5 179.7 198.1 137.6 149.1 175.3 191.8 137.2 149.0 177.0 194.6 136.7 148.9 177.9 194.5 139.8 150.6 182.9 201.5 140.2 151.0 180.1 197.9 139.5 150.7 181.9 200.3 140.1 151.4 182.7 201.4 140.2 151.8 187.1 208.2 139.9 151.8 189.8 211.4 140.7 152.5 194.7 219.6 140.1 152.5 199.1 226.5 139.8 152.7 203.2 232.5 140.3 153.6 Intermediate materials, supplies, and components........………… 164.0 170.7 173.6 171.5 172.2 172.2 176.2 175.7 177.8 179.1 184.5 186.9 192.6 196.9 202.5 for manufacturing...................................... Materials for food manufacturing.............. Materials for nondurable manufacturing... Materials for durable manufacturing......... Components for manufacturing................ 155.9 146.2 175.0 180.5 134.5 162.4 161.4 184.0 189.8 136.3 164.5 163.6 187.1 195.1 136.4 163.4 164.5 185.0 191.8 136.5 163.3 166.6 186.0 189.1 136.5 164.4 166.3 189.4 189.0 136.6 166.1 166.6 195.1 188.6 136.7 166.3 169.8 195.1 188.1 136.8 168.4 173.6 199.3 189.5 137.4 170.1 176.7 201.5 193.1 137.8 173.1 180.0 206.0 200.3 137.9 174.5 179.7 207.7 203.5 138.8 178.8 182.8 214.4 212.8 139.3 181.6 185.7 220.1 216.3 139.9 186.6 187.7 231.9 219.4 141.4 Materials and components for construction......................................... Processed fuels and lubricants................... Containers.................................................. Supplies...................................................... 188.4 162.8 175.0 157.0 192.5 173.9 180.3 161.7 193.5 183.0 180.2 161.9 193.5 175.3 180.5 162.0 193.2 178.4 181.0 162.3 193.2 175.5 182.3 163.0 193.2 189.7 183.2 163.9 193.4 186.3 183.4 164.6 194.4 188.6 185.1 166.8 195.7 189.0 185.7 168.1 197.3 206.1 185.9 170.0 199.3 212.3 187.0 170.5 203.4 227.2 188.0 172.9 206.3 238.6 188.5 174.3 209.9 249.6 191.6 177.7 Crude materials for further processing.......................………………… Foodstuffs and feedstuffs........................... Crude nonfood materials............................ 184.8 119.3 230.6 207.1 146.7 246.3 210.3 150.0 249.2 202.8 147.8 237.6 204.6 151.9 237.4 211.8 150.0 252.0 225.6 152.9 274.1 229.0 158.5 275.4 235.5 162.6 283.8 245.5 165.4 299.9 262.1 169.2 327.7 274.3 166.5 349.9 294.4 172.7 385.4 305.2 178.9 399.6 317.9 179.3 423.3 Special groupings: Finished goods, excluding foods................ Finished energy goods............................... Finished goods less energy........................ Finished consumer goods less energy....... Finished goods less food and energy......... 161.0 145.9 157.9 162.7 158.7 166.2 156.3 162.8 168.7 161.7 168.8 166.4 162.4 168.3 161.4 165.8 155.6 162.5 168.4 161.5 166.9 159.7 163.0 169.2 161.5 168.1 159.1 164.7 170.8 163.2 171.6 170.4 164.9 171.0 163.6 169.6 163.8 165.5 172.0 163.5 171.0 166.6 166.7 173.5 164.4 171.7 167.2 167.0 173.7 165.0 174.6 177.5 167.6 174.7 165.1 176.7 182.6 168.1 174.9 165.9 179.8 193.8 168.8 176.0 166.1 182.8 204.3 169.5 177.0 166.2 185.9 213.0 170.4 177.8 167.1 and energy................................................ Consumer nondurable goods less food 166.7 170.0 169.7 170.0 170.0 171.8 172.2 172.2 173.2 174.0 174.1 175.0 175.3 175.4 176.2 and energy.............................................. 191.5 197.0 197.1 197.9 198.3 199.0 199.3 200.0 201.4 203.0 203.6 204.2 205.9 206.4 207.6 Intermediate materials less foods and feeds.................................................. Intermediate foods and feeds..................... Intermediate energy goods......................... Intermediate goods less energy.................. 165.4 135.2 162.8 162.1 171.5 154.4 174.6 167.6 174.5 155.9 184.2 168.8 172.3 156.3 177.0 168.1 172.9 158.2 179.5 168.2 172.9 159.6 177.4 168.9 177.0 161.4 191.1 170.2 176.3 164.6 187.8 170.4 178.2 170.6 190.5 172.3 179.4 175.0 191.5 173.7 184.7 180.3 208.6 176.0 187.4 178.6 213.8 177.4 193.1 184.8 228.6 181.1 197.4 186.8 240.5 183.4 203.0 194.6 253.0 187.3 and energy................................................ 163.8 168.4 169.6 168.8 168.9 169.5 170.8 170.9 172.5 173.7 175.8 177.5 181.0 183.2 186.9 Crude energy materials.............................. Crude materials less energy....................... Crude nonfood materials less energy......... 226.9 152.3 244.5 232.8 182.6 282.6 236.8 185.5 284.0 221.7 183.8 284.7 219.9 188.3 289.9 237.7 187.4 292.8 267.1 189.2 289.9 268.3 194.1 291.7 273.6 200.9 307.3 291.7 205.9 319.7 325.4 211.7 332.1 344.1 215.4 359.4 389.0 224.4 376.2 409.7 229.1 374.5 437.9 232.2 387.2 Finished consumer goods Materials and components Finished consumer goods less food Intermediate materials less foods p = preliminary. 116 Monthly Labor Review • September 2008 42. Producer Price Indexes for the net output of major industry groups [December 2003 = 100, unless otherwise indicated] NAICS Industry Total mining industries (December 1984=100)............................. 2007 July Aug. Sept. Oct. 2008 Nov. Dec. Jan. Feb. Mar. Apr.p May p June p July p 222.3 269.6 162.4 168.9 212.5 254.1 160.8 168.6 214.3 256.2 162.2 169.7 228.3 279.6 162.4 168.5 249.3 314.8 161.3 168.7 249.5 315.9 161.2 164.9 254.2 321.9 164.9 167.2 263.8 335.0 170.3 168.8 287.2 371.6 174.8 169.8 299.0 390.3 176.4 170.0 328.9 440.5 174.3 171.3 345.9 463.5 185.1 174.6 368.9 499.4 189.3 176.5 164.9 160.4 109.2 108.4 101.5 149.4 108.4 115.4 106.7 283.1 163.0 160.3 109.9 108.6 101.5 149.9 107.8 115.6 106.8 258.0 163.7 160.8 110.3 108.7 101.3 150.0 107.2 116.1 107.0 267.4 164.5 160.7 111.1 108.9 101.5 150.4 106.5 117.1 107.1 266.9 168.0 161.4 111.1 109.1 101.5 150.5 106.1 117.8 107.2 305.5 166.9 162.8 111.2 109.3 101.5 151.1 106.1 118.0 107.4 288.4 168.5 165.8 112.1 110.1 101.8 152.0 105.7 118.5 107.8 294.9 169.6 167.5 112.7 110.3 101.8 152.4 105.5 119.2 108.1 298.4 173.4 169.8 112.7 110.4 102.0 152.6 105.9 119.6 108.2 337.1 175.1 170.9 113.0 110.8 102.2 152.8 106.0 120.2 109.2 347.6 179.3 174.2 114.4 111.7 102.2 152.7 108.3 120.4 109.4 384.1 182.0 176.3 114.2 111.7 102.2 153.9 109.5 120.8 109.5 406.0 185.6 180.1 115.2 112.6 102.4 154.4 109.0 121.6 110.0 428.9 325 326 (December 1984=100)………………………………….………… Chemical manufacturing (December 1984=100)…………………… 203.6 150.4 Plastics and rubber products manufacturing 204.9 151.3 205.0 151.2 206.4 151.6 209.2 152.2 210.4 153.2 213.6 154.8 215.8 155.6 218.4 156.4 220.4 156.3 224.1 158.5 227.8 159.5 233.7 162.7 331 332 333 334 335 336 337 Primary metal manufacturing (December 1984=100)……………… Fabricated metal product manufacturing (December 1984=100)… Machinery manufacturing………………………..…………………… Computer and electronic products manufacturing………………… Electrical equipment, appliance, and components manufacturing Transportation equipment manufacturing…………………………… Furniture and related product manufacturing 196.4 162.3 112.1 94.1 123.0 104.4 165.6 192.1 162.9 112.3 93.5 123.6 104.2 165.7 188.8 162.8 112.5 93.3 123.7 103.8 165.9 188.6 163.3 112.7 93.1 124.2 106.3 166.1 188.9 163.7 113.0 92.8 124.5 106.6 166.6 188.6 164.3 113.1 92.6 124.4 106.0 166.4 190.4 165.6 113.8 92.6 125.2 106.6 167.1 194.2 166.8 114.3 92.8 125.9 106.6 167.8 202.4 168.3 114.6 92.7 127.1 106.1 168.3 210.5 170.6 115.2 92.7 127.3 106.5 169.7 221.6 172.9 115.7 92.8 128.1 106.3 170.6 228.5 174.7 116.5 92.8 128.4 105.9 171.7 233.2 177.3 117.9 93.0 129.0 106.5 172.1 339 Miscellaneous manufacturing………………………………………… 106.9 107.0 107.1 107.2 107.5 107.7 108.5 108.7 109.2 109.5 109.7 110.0 110.4 115.6 116.5 111.6 123.6 81.6 123.1 114.9 119.6 109.8 124.3 71.3 128.3 116.0 119.0 107.8 123.9 73.7 126.0 115.3 120.1 111.1 123.5 78.0 130.2 116.1 121.1 114.9 123.8 73.7 125.7 118.0 119.0 89.3 123.8 66.6 134.7 118.3 119.6 109.0 124.8 67.1 136.0 118.4 118.8 110.2 124.5 61.6 133.8 117.9 120.1 113.4 125.5 60.6 133.1 119.0 119.2 110.9 128.0 65.6 136.2 118.5 118.6 109.5 127.9 60.9 136.9 118.6 119.8 111.3 128.0 67.3 138.0 118.1 120.3 110.1 135.4 80.1 140.9 Air transportation (December 1992=100)…………………………… 188.0 Water transportation…………………………………………………… 113.6 Postal service (June 1989=100)……………………………………… 175.5 189.1 114.7 175.5 180.5 115.3 175.5 187.2 117.2 175.5 189.4 116.5 175.5 187.1 116.4 175.5 192.0 119.0 175.5 191.8 119.2 175.5 198.6 120.6 175.5 199.5 122.1 175.5 201.4 122.3 180.5 211.7 127.0 180.5 211.4 129.3 180.5 130.8 129.3 127.2 126.6 127.4 127.8 129.7 131.1 133.6 135.7 141.1 146.3 122.2 107.0 123.8 158.1 114.9 112.9 122.2 107.7 123.9 158.0 115.7 113.2 122.9 107.6 124.1 158.2 115.8 113.5 122.9 107.7 125.1 161.3 116.4 113.9 121.5 106.7 125.3 161.9 116.5 114.3 122.7 106.7 125.3 161.9 117.0 114.6 123.3 107.3 125.4 162.4 117.9 115.4 123.3 107.3 125.5 162.6 118.0 117.2 123.3 107.3 125.5 162.9 118.3 117.7 122.3 107.4 125.5 162.9 118.2 118.0 123.2 107.4 125.5 162.7 118.1 117.6 123.2 106.6 125.4 162.8 118.1 117.6 123.2 106.9 125.4 163.2 119.1 117.8 108.2 98.7 102.2 100.4 120.5 106.2 111.1 103.8 121.2 153.7 112.2 108.4 98.7 101.3 100.4 120.4 107.9 111.1 103.2 122.3 153.8 112.6 108.4 99.6 102.0 100.4 121.1 109.0 110.7 102.9 117.2 154.3 112.4 108.5 101.0 101.8 100.3 121.4 108.5 110.5 103.5 118.9 154.8 113.1 108.5 102.3 101.2 100.5 124.2 108.5 110.5 106.1 118.4 155.1 112.9 108.5 103.6 100.7 100.4 123.0 110.0 109.9 105.6 119.1 155.1 113.0 109.7 104.4 100.6 100.4 122.5 108.1 110.3 106.6 121.3 159.9 115.6 109.8 104.6 100.9 100.5 122.9 108.2 109.8 106.0 121.3 160.3 114.1 110.4 105.2 100.6 100.5 121.0 109.7 110.0 106.8 125.1 160.7 113.8 110.7 102.4 102.1 100.5 119.2 109.1 110.0 107.1 117.8 160.8 111.9 110.4 103.4 101.3 100.9 120.1 109.2 106.1 107.1 123.2 160.9 114.2 110.2 102.7 101.1 100.9 120.7 109.7 105.4 107.4 125.2 160.9 112.4 110.8 103.3 101.0 101.0 118.8 110.2 107.0 109.7 132.6 161.5 115.8 140.3 105.1 121.8 101.1 105.5 107.3 147.1 140.8 105.1 121.9 101.0 105.5 107.9 147.2 140.7 105.1 122.0 100.9 106.8 108.9 145.0 140.8 105.1 122.4 102.5 106.9 108.9 145.8 140.8 105.1 122.3 101.7 107.1 109.5 144.7 140.8 105.1 122.2 100.2 108.7 108.4 143.7 139.2 105.2 122.3 98.8 108.9 110.7 145.4 140.3 105.3 123.0 98.8 109.1 112.1 145.2 140.3 105.3 123.0 98.8 108.9 112.0 145.3 140.4 106.0 122.3 98.8 109.0 112.3 146.0 140.5 105.8 122.7 98.8 109.7 112.0 144.8 141.9 105.7 122.9 98.8 109.2 112.8 149.6 141.5 105.7 123.1 98.8 109.1 112.1 152.8 211 212 213 311 312 313 315 316 321 322 323 324 Oil and gas extraction (December 1985=100) ............................. Mining, except oil and gas…………………………………………… Mining support activities……………………………………………… Total manufacturing industries (December 1984=100)................ Food manufacturing (December 1984=100)………………………… Beverage and tobacco manufacturing........................................... Textile mills.................................................................................... Apparel manufacturing………………………………...……………… Leather and allied product manufacturing (December 1984=100) Wood products manufacturing……………………………………… Paper manufacturing..................................................................... Printing and related support activities........................................... Petroleum and coal products manufacturing (December 1984=100)………….………………………………… (December 1984=100)……………………………………………… Retail trade 441 442 443 446 447 454 Motor vehicle and parts dealers……………………………………… Furniture and home furnishings stores……………………………… Electronics and appliance stores…………………………………… Health and personal care stores……………………………………… Gasoline stations (June 2001=100)………………………………… Nonstore retailers……………………………………………………… Transportation and warehousing 481 483 491 Utilities 221 Utilities…………………………………………………………………… 131.6 Health care and social assistance 6211 6215 6216 622 6231 62321 Office of physicians (December 1996=100)………………………… Medical and diagnostic laboratories………………………………… Home health care services (December 1996=100)………………… Hospitals (December 1992=100)…………………………………… Nursing care facilities………………………………………………… Residential mental retardation facilities……………………………… Other services industries 511 515 517 5182 523 53112 5312 5313 5321 5411 541211 5413 Publishing industries, except Internet ……………………………… Broadcasting, except Internet………………………………………… Telecommunications…………………………………………………… Data processing and related services……………………………… Security, commodity contracts, and like activity…………………… Lessors or nonresidental buildings (except miniwarehouse)……… Offices of real estate agents and brokers…………………………… Real estate support activities………………………………………… Automotive equipment rental and leasing (June 2001=100)……… Legal services (December 1996=100)……………………………… Offices of certified public accountants……………………………… Architectural, engineering, and related services (December 1996=100)……………………………………………… 54181 Advertising agencies…………………………………………………… 5613 Employment services (December 1996=100)……………………… 56151 Travel agencies………………………………………………………… 56172 Janitorial services……………………………………………………… 5621 Waste collection………………………………………………………… 721 Accommodation (December 1996=100)…………………………… p = preliminary. Monthly Labor Review • September 2008 117 Current Labor Statistics: Price Data 43. Annual data: Producer Price Indexes, by stage of processing [1982 = 100] Index 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Finished goods Total............................................................................... Foods............................…………………………….…… Energy............……………………………………….….… Other…...............................………………………….…… 131.8 134.5 83.4 142.4 130.7 134.3 75.1 143.7 133.0 135.1 78.8 146.1 138.0 137.2 94.1 148.0 140.7 141.3 96.8 150.0 138.9 140.1 88.8 150.2 143.3 145.9 102.0 150.5 148.5 152.7 113.0 152.7 155.7 155.7 132.6 156.4 160.4 156.7 145.9 158.7 166.6 166.9 156.4 161.7 Intermediate materials, supplies, and components Total............................................................................... Foods............……………………………………….….… Energy…...............................………………………….… Other.................…………...………..........………….…… 125.6 123.2 89.0 134.2 123.0 123.2 80.8 133.5 123.2 120.8 84.3 133.1 129.2 119.2 101.7 136.6 129.7 124.3 104.1 136.4 127.8 123.2 95.9 135.8 133.7 134.4 111.9 138.5 142.6 145.0 123.2 146.5 154.0 146.0 149.2 154.6 164.0 146.2 162.8 163.8 170.6 161.5 174.6 168.4 111.1 112.2 87.3 103.5 96.8 103.9 68.6 84.5 98.2 98.7 78.5 91.1 120.6 100.2 122.1 118.0 121.0 106.1 122.3 101.5 108.1 99.5 102.0 101.0 135.3 113.5 147.2 116.9 159.0 127.0 174.6 149.2 182.2 122.7 234.0 176.7 184.8 119.3 226.9 210.0 207.3 146.7 233.0 238.8 Crude materials for further processing Total............................................................................... Foods............................…………………………….…… Energy............……………………………………….….… Other…...............................………………………….…… 44. U.S. export price indexes by end-use category [2000 = 100] Category 2007 July Aug. Sept. Oct. 2008 Nov. Dec. Jan. Feb. Mar. Apr. May June July ALL COMMODITIES…………….................................... 116.1 116.3 116.7 117.6 118.7 119.3 120.7 121.8 123.8 124.4 124.8 126.1 127.9 Foods, feeds, and beverages……………...…………… Agricultural foods, feeds, and beverages…............. Nonagricultural (fish, beverages) food products…… 149.2 151.5 130.2 151.4 153.7 132.2 157.8 160.8 133.0 164.1 167.6 134.2 165.9 169.8 133.1 171.1 175.2 136.1 180.5 185.0 142.0 188.7 193.8 144.7 196.9 202.6 148.3 192.8 198.2 146.4 193.3 198.8 145.2 198.2 204.2 145.8 211.7 219.2 146.5 Industrial supplies and materials……………...………… 148.6 118 148.8 148.8 150.5 153.9 154.1 157.1 159.1 165.5 167.9 169.6 173.3 177.8 Agricultural industrial supplies and materials…........ 138.6 137.4 140.0 142.7 144.9 144.7 146.0 150.6 159.3 157.9 156.9 158.0 162.7 Fuels and lubricants…...............................………… 202.9 197.4 200.9 204.8 224.7 222.8 232.1 225.6 249.5 259.3 275.8 297.6 312.2 Nonagricultural supplies and materials, excluding fuel and building materials…………...… Selected building materials…...............................… 144.6 114.1 145.7 114.0 145.0 114.4 146.5 114.2 147.9 113.8 148.5 113.7 150.9 113.3 154.1 113.8 158.2 114.2 160.1 114.1 160.1 113.9 161.6 113.7 165.1 113.9 Capital goods……………...…………………………….… 99.7 Electric and electrical generating equipment…........ 106.6 Nonelectrical machinery…...............................……… 93.1 99.8 106.7 93.1 99.9 106.7 93.1 100.1 107.1 93.2 100.3 107.2 93.4 100.6 107.5 93.6 100.9 107.7 93.7 101.3 108.3 93.9 101.2 108.6 93.7 101.5 108.7 93.9 101.6 108.6 93.8 101.9 108.6 94.1 101.7 108.6 93.9 Automotive vehicles, parts, and engines……………... 106.2 106.2 106.3 106.5 106.5 106.7 106.9 107.0 107.1 107.5 107.5 107.5 107.6 Consumer goods, excluding automotive……………... 106.1 Nondurables, manufactured…...............................… 107.0 Durables, manufactured…………...………..........…… 104.0 106.3 107.2 104.2 106.2 107.0 104.2 106.4 107.4 104.2 106.8 108.0 104.4 107.3 108.2 105.2 107.3 108.1 105.2 107.4 108.2 105.5 108.0 109.3 105.4 108.1 109.8 105.1 108.1 110.0 105.1 108.2 110.1 105.2 108.6 110.0 106.2 Agricultural commodities……………...………………… Nonagricultural commodities……………...…………… 150.5 113.8 156.8 113.8 162.8 114.4 165.0 115.4 169.3 115.7 177.5 116.6 185.6 117.3 194.3 118.8 190.5 119.6 190.8 120.1 195.4 121.2 208.4 122.2 Monthly Labor Review • September 2008 149.0 113.7 45. U.S. import price indexes by end-use category [2000 = 100] 2007 Category July Aug. Sept. 2008 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July ALL COMMODITIES…………….................................... 121.5 121.1 121.8 123.6 127.5 127.3 129.2 129.5 133.5 137.3 141.2 145.3 147.8 Foods, feeds, and beverages……………...…………… Agricultural foods, feeds, and beverages…............. Nonagricultural (fish, beverages) food products…… 129.4 141.4 102.7 130.1 142.1 103.2 131.8 144.4 103.5 133.2 146.5 103.2 133.4 147.1 102.5 134.4 148.3 103.0 138.1 153.1 104.3 137.8 152.6 104.4 141.8 157.3 106.8 143.7 159.8 107.2 145.0 162.3 105.8 147.5 165.0 107.9 149.7 167.5 109.2 Industrial supplies and materials……………...………… 190.9 188.5 190.7 197.2 212.8 211.3 218.2 219.0 234.5 248.7 264.7 282.2 291.5 Fuels and lubricants…...............................………… Petroleum and petroleum products…………...…… 249.8 260.3 244.0 256.4 250.0 264.4 262.4 277.7 294.8 312.2 290.3 306.7 301.9 319.6 300.0 315.6 329.0 347.5 354.6 375.8 387.6 411.8 421.5 448.4 438.5 466.4 Paper and paper base stocks…............................... 110.3 110.7 111.2 112.2 108.0 109.2 112.5 113.4 114.1 116.2 117.1 117.9 120.0 Materials associated with nondurable supplies and materials…...............................……… Selected building materials…...............................… Unfinished metals associated with durable goods… Nonmetals associated with durable goods…........... 126.6 116.9 215.1 102.1 127.3 116.5 215.3 102.2 128.2 116.9 209.1 102.5 131.4 115.7 211.0 103.0 133.7 115.6 214.8 103.3 135.3 116.0 217.2 103.8 143.6 115.9 215.3 105.4 146.6 113.8 224.5 105.9 147.8 114.1 241.5 105.2 148.7 114.3 259.2 106.2 149.6 116.2 263.7 107.5 152.6 119.2 275.0 107.9 156.3 121.8 277.8 111.7 Capital goods……………...…………………………….… 91.6 Electric and electrical generating equipment…........ 105.8 Nonelectrical machinery…...............................……… 87.4 91.8 106.4 87.6 91.9 106.5 87.7 92.0 106.8 87.7 92.1 107.5 87.7 92.2 107.9 87.7 91.9 107.7 87.4 92.0 108.7 87.4 92.2 109.3 87.5 93.0 111.5 88.0 93.3 111.7 88.4 93.2 112.0 88.2 93.5 113.0 88.4 Automotive vehicles, parts, and engines……………... 104.8 105.0 105.2 105.6 106.2 106.8 107.1 107.2 107.4 107.8 107.8 107.9 108.0 Consumer goods, excluding automotive……………... 101.7 Nondurables, manufactured…...............................… 104.8 Durables, manufactured…………...………..........…… 98.3 Nonmanufactured consumer goods…………...……… 103.1 102.0 104.9 98.8 103.4 102.1 105.0 98.8 103.4 102.2 105.1 99.0 103.3 102.4 105.3 99.2 103.3 102.6 105.5 99.3 103.8 103.1 106.5 99.6 104.0 103.5 106.8 100.0 104.1 104.0 107.5 100.4 104.3 104.6 107.9 101.1 105.6 104.8 108.0 101.3 105.8 104.9 108.0 101.6 106.6 105.2 108.3 101.8 106.9 46. U.S. international price Indexes for selected categories of services [2000 = 100, unless indicated otherwise] Category 2006 June Sept. 2007 Dec. Mar. June 2008 Sept. Dec. Mar. June Import air freight……………........................................... Export air freight……………...…………………………… 135.2 115.9 133.1 117.9 131.2 116.7 130.7 117.0 132.3 117.0 134.2 119.8 141.8 127.1 144.4 132.0 155.4 142.2 Import air passenger fares (Dec. 2006 = 100)…………… Export air passenger fares (Dec. 2006 = 100)…............ 136.7 139.3 130.9 142.4 125.4 137.3 122.9 140.2 144.6 147.3 140.2 154.6 135.3 155.7 131.3 156.4 171.6 169.0 Monthly Labor Review • September 2008 119 Current Labor Statistics: Productivity Data 47. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted [1992 = 100] 2005 Item II 2006 III IV I 134.2 161.6 119.5 120.4 129.5 123.8 135.6 164.1 119.6 121.1 131.6 125.0 135.2 165.8 119.6 122.6 132.4 126.3 136.1 168.0 120.6 123.5 133.4 127.2 133.4 160.8 118.9 120.5 130.8 124.3 134.6 163.2 118.9 121.2 133.2 125.6 134.2 164.7 118.8 122.7 134.2 126.9 143.7 158.6 117.3 110.6 110.4 111.4 166.8 126.2 115.7 142.8 160.8 117.2 113.5 112.6 115.7 152.2 125.5 116.9 172.0 164.2 121.4 95.5 172.9 166.5 121.3 96.3 II 2007 III IV I 136.6 168.1 119.6 123.1 136.2 128.0 135.9 168.9 119.1 124.3 136.2 128.8 135.9 172.6 122.1 127.0 133.4 129.4 135.9 174.7 122.4 128.5 134.3 130.7 135.1 166.8 119.7 123.5 135.5 127.9 135.7 167.1 118.9 123.1 138.6 128.8 134.9 167.9 118.3 124.4 138.3 129.5 135.0 171.7 121.4 127.1 134.9 130.0 144.8 161.2 116.3 111.8 111.4 113.1 177.4 130.3 117.7 146.3 164.5 118.1 112.5 112.4 112.9 182.5 131.5 118.8 146.0 164.5 117.0 113.1 112.6 114.4 183.1 132.8 119.4 147.0 165.1 116.3 112.8 112.3 114.2 193.0 135.3 120.0 172.8 165.3 119.2 95.6 172.6 170.9 122.7 99.0 172.7 169.5 120.7 98.2 174.5 170.3 120.0 97.6 II 2008 III IV I II 137.6 175.5 121.7 127.5 137.4 131.2 139.7 177.1 121.9 126.8 139.7 131.6 139.7 179.0 121.7 128.1 139.2 132.2 140.5 181.2 121.9 128.9 139.5 132.9 141.3 182.9 121.6 129.4 139.2 133.1 135.0 173.7 121.8 128.7 135.2 131.1 136.4 174.1 120.7 127.7 138.2 131.5 138.3 175.5 120.9 126.9 140.3 131.8 138.6 177.8 121.0 128.3 139.8 132.5 139.5 180.1 121.2 129.1 140.3 133.2 140.3 181.7 120.8 129.5 140.0 133.4 146.0 167.8 118.7 115.3 114.9 116.2 173.9 131.6 120.5 146.2 170.3 119.4 116.7 116.5 117.2 171.8 131.8 121.6 147.4 171.3 118.7 116.5 116.2 117.4 172.5 132.2 121.5 148.1 172.5 118.7 116.8 116.5 117.8 166.8 130.9 121.3 148.8 175.0 119.0 117.9 117.6 118.9 155.9 128.8 121.3 149.2 177.1 119.2 118.7 118.7 118.7 149.8 127.0 121.5 175.4 174.6 123.5 99.5 177.0 176.9 124.0 100.0 178.7 176.4 122.3 98.7 180.6 176.4 121.4 97.6 182.5 179.7 122.2 98.5 184.0 182.4 122.8 99.1 Business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfarm business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfinancial corporations Output per hour of all employees................................... Compensation per hour…………………………….……… Real compensation per hour……………………………… Total unit costs…...............................…………………… Unit labor costs............................................................. Unit nonlabor costs...................................................... Unit profits...................................................................... Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… – – – – – – – – – Manufacturing Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… NOTE: Dash indicates data not available. 120 Monthly Labor Review • September 2008 183.3 184.5 122.7 100.6 48. Annual indexes of multifactor productivity and related measures, selected years [2000 = 100, unless otherwise indicated] Item 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Private business Productivity: Output per hour of all persons......…………….............. 87.4 Output per unit of capital services……………………… 104.6 Multifactor productivity…………………………………… 93.7 Output…...............................………………………….…… 79.2 90.0 104.7 95.3 82.8 91.7 104.9 96.2 87.2 94.3 103.5 97.5 91.5 97.2 102.3 98.7 96.2 100.0 100.0 100.0 100.0 102.8 96.0 100.1 100.5 107.1 94.8 101.8 102.0 111.2 95.6 104.4 105.2 114.5 97.5 107.0 109.7 116.8 98.6 108.8 113.8 118.0 99.1 109.4 117.4 120.2 98.1 110.1 120.1 88.8 75.7 84.4 83.6 90.7 79.1 86.9 85.9 94.2 83.2 90.6 87.4 96.4 88.4 93.9 91.1 99.0 94.1 97.5 95.0 100.0 100.0 100.0 100.0 98.6 104.6 100.3 107.0 97.2 107.6 100.2 112.9 97.0 110.0 100.7 116.3 98.4 112.5 102.5 117.4 100.2 115.4 104.6 118.4 102.8 118.5 107.4 119.1 103.8 122.3 109.2 122.3 Productivity: Output per hour of all persons........……………………… 88.2 Output per unit of capital services……………………… 105.6 94.5 Multifactor productivity…………………………………… Output…...............................………………………….…… 79.3 90.5 105.5 95.9 82.8 92.0 105.3 96.5 87.2 94.5 103.9 97.8 91.5 97.3 102.5 98.8 96.3 100.0 100.0 100.0 100.0 102.7 96.0 100.1 100.5 107.1 94.7 101.8 102.1 111.0 95.4 104.3 105.2 114.2 97.3 106.8 109.6 116.4 98.3 108.6 113.7 117.6 98.7 109.0 117.4 119.7 97.9 109.7 120.1 88.2 75.0 83.9 83.5 90.2 78.5 86.4 85.8 93.9 82.7 90.3 87.3 96.2 88.1 93.6 91.0 99.0 93.9 97.4 94.9 100.0 100.0 100.0 100.0 98.7 104.7 100.5 107.0 97.2 107.8 100.2 113.1 97.1 110.3 100.8 116.4 98.6 112.7 102.6 117.4 100.4 115.6 104.7 118.4 103.1 118.9 107.6 119.1 104.1 122.8 109.4 122.4 Productivity: Output per hour of all persons...………………………… Output per unit of capital services……………………… Multifactor productivity…………………………………… Output…...............................………………………….…… 79.8 98.7 90.8 80.3 82.7 98.0 91.2 83.1 87.3 100.6 93.8 89.2 92.0 100.7 95.9 93.8 96.1 100.4 96.7 97.4 100.0 100.0 100.0 100.0 101.6 93.5 98.7 94.9 108.6 92.3 102.4 94.3 115.3 93.2 105.2 95.2 117.9 95.4 108.0 96.9 123.5 98.9 108.4 100.4 125.0 100.2 110.1 102.3 – – – – Inputs: Hours of all persons..................................................... Capital services…………...………..........………….…… Energy……………….………......................................... Nonenergy materials.................................................... Purchased business services....................................... Combined units of all factor inputs…………...………... 100.6 81.4 113.7 78.9 88.8 88.5 100.4 84.8 110.4 86.0 88.5 91.1 102.2 88.7 108.2 92.9 92.1 95.1 101.9 93.2 105.4 97.7 95.0 97.8 101.3 97.0 105.5 102.6 100.0 100.7 100.0 100.0 100.0 100.0 100.0 100.0 93.5 101.5 90.6 93.3 100.7 96.2 86.8 102.1 89.3 88.4 98.2 92.1 82.6 102.1 84.4 87.7 99.1 90.5 82.2 101.6 84.0 87.3 97.0 89.7 81.3 101.5 91.6 92.4 104.5 92.7 81.8 102.0 86.6 91.5 106.6 92.9 – – – – – – Inputs: Labor input................................................................... Capital services…………...………..........………….…… Combined units of labor and capital input……………… Capital per hour of all persons.......................…………… Private nonfarm business Inputs: Labor input................................................................... Capital services…………...………..........………….…… Combined units of labor and capital input……………… Capital per hour of all persons......………………………… Manufacturing [1996 = 100] NOTE: Dash indicates data not available. Monthly Labor Review • September 2008 121 Current Labor Statistics: Productivity Data 49. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years [1992 = 100] Item 1962 1972 1982 1992 1999 2000 2001 2002 2003 2004 2005 2006 2007 Business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… 52.9 15.1 65.2 28.5 26.1 27.6 71.2 26.7 83.3 37.4 35.7 36.8 80.1 63.6 90.6 79.4 70.1 75.9 100.0 100.0 100.0 100.0 100.0 100.0 112.8 125.8 108.1 111.5 109.4 110.7 116.1 134.7 112.0 116.0 107.2 112.7 119.1 140.3 113.5 117.9 110.0 114.9 123.9 145.3 115.7 117.3 114.2 116.1 128.7 151.2 117.7 117.5 118.3 117.8 132.4 156.9 119.0 118.5 124.7 120.8 135.0 163.2 119.7 120.9 130.8 124.5 136.4 169.6 120.5 124.4 134.6 128.2 139.0 178.3 123.2 128.3 135.4 131.0 55.9 15.6 67.3 27.8 25.8 27.1 73.1 26.9 84.0 36.8 34.9 36.1 80.8 63.9 91.1 79.1 69.3 75.5 100.0 100.0 100.0 100.0 100.0 100.0 112.5 125.2 107.6 111.3 110.9 111.1 115.7 134.2 111.6 116.0 108.7 113.3 118.6 139.5 112.8 117.7 111.6 115.4 123.5 144.6 115.1 117.1 116.0 116.7 128.0 150.4 117.1 117.5 119.6 118.3 131.6 155.9 118.2 118.5 125.5 121.1 134.1 162.1 118.9 120.9 132.4 125.1 135.4 168.5 119.7 124.5 136.4 128.9 137.9 177.1 122.3 128.4 136.2 131.3 60.4 17.4 75.1 27.3 28.7 23.4 54.5 31.7 29.7 74.2 28.8 90.0 37.5 38.8 33.9 54.1 39.3 39.0 83.1 66.5 94.7 80.4 80.0 81.3 75.2 79.7 79.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 117.9 124.2 106.7 104.0 105.3 100.4 129.1 108.0 106.2 122.5 133.0 110.6 107.4 108.6 104.2 108.7 105.4 107.5 124.7 138.6 112.1 111.6 111.2 112.6 82.2 104.5 108.9 129.7 143.6 114.3 110.7 110.7 110.8 98.0 107.4 109.6 134.6 149.5 116.4 111.0 111.0 111.1 109.9 110.7 110.9 139.6 153.9 116.7 110.0 110.3 109.3 144.8 118.8 113.1 141.6 159.8 117.2 112.7 112.9 112.2 154.4 123.5 116.4 142.6 165.4 117.5 115.4 116.0 113.8 162.9 126.9 119.7 144.8 173.4 119.8 118.5 119.8 114.9 153.5 125.2 121.6 – – – – – – – – – – – – – – – – – – 100.0 100.0 100.0 100.0 100.0 100.0 133.7 123.5 106.1 92.4 102.9 99.5 139.1 134.7 112.0 96.9 103.5 101.4 141.2 137.8 111.5 97.6 102.0 100.6 151.0 147.8 117.7 97.9 100.3 99.5 160.4 158.2 123.2 98.7 102.9 101.5 163.9 161.5 122.4 98.5 110.2 106.4 171.9 168.3 123.5 97.9 121.1 113.5 173.8 173.0 122.8 99.5 126.2 117.4 179.7 182.6 126.1 101.6 – – Nonfarm business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfinancial corporations Output per hour of all employees................................... Compensation per hour…………………………….……… Real compensation per hour……………………………… Total unit costs…...............................…………………… Unit labor costs............................................................. Unit nonlabor costs...................................................... Unit profits...................................................................... Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Manufacturing Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Dash indicates data not available. 122 Monthly Labor Review • September 2008 50. Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS Industry Mining 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 85.5 80.1 80.1 69.8 58.5 71.2 88.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 103.6 101.2 101.2 104.5 106.5 109.3 101.3 111.4 107.9 107.9 105.8 110.3 112.3 101.2 111.0 119.4 119.4 106.3 115.8 122.0 96.2 109.1 121.6 121.6 109.0 114.6 131.9 99.3 113.6 123.8 123.8 110.9 112.4 138.6 103.6 116.0 130.1 130.1 113.6 113.2 142.8 108.1 106.8 111.7 111.7 115.9 112.8 137.4 114.2 96.0 107.8 107.8 114.0 107.6 130.0 118.2 87.2 100.3 100.3 110.6 100.0 123.4 118.7 - 65.6 67.8 100.0 100.0 103.7 99.0 103.5 102.7 107.0 113.2 106.4 110.1 102.9 115.4 105.1 114.1 107.5 118.3 114.3 122.2 115.4 119.0 - 21 211 2111 212 2121 2122 2123 Mining…………………………………………………. Oil and gas extraction………………………………… Oil and gas extraction………………………………… Mining, except oil and gas…………………………… Coal mining…………………………………………… Metal ore mining……………………………………… Nonmetallic mineral mining and quarrying………… 2211 2212 Power generation and supply………………………… Natural gas distribution……………………………… 311 3111 3112 3113 3114 Food…………………………………………………. Animal food…………………………………………… Grain and oilseed milling……………………………… Sugar and confectionery products…………………… Fruit and vegetable preserving and specialty……… 94.1 83.6 81.1 87.6 92.4 100.0 100.0 100.0 100.0 100.0 103.9 109.0 107.5 103.5 107.1 105.9 110.9 116.1 106.5 109.5 107.1 109.7 113.1 109.9 111.8 109.5 131.4 119.5 108.6 121.4 113.8 142.7 122.4 108.0 126.9 116.8 165.8 123.9 112.5 123.0 117.3 149.5 130.3 118.2 126.2 123.3 165.5 133.0 130.7 132.0 121.1 150.4 130.7 129.2 126.9 - 3115 3116 3117 3118 3119 Dairy products………………………………………… 82.7 Animal slaughtering and processing………………… 97.4 Seafood product preparation and packaging……… 123.1 Bakeries and tortilla manufacturing………………… 100.9 Other food products…………………………………… 97.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 120.2 103.8 107.8 93.6 101.2 131.6 108.6 111.4 95.9 102.6 140.5 108.3 112.6 97.1 103.7 153.0 109.9 106.2 105.0 107.3 169.8 108.9 111.9 110.5 106.6 173.2 109.3 118.8 107.4 108.0 162.2 113.8 119.3 109.6 117.4 186.1 115.4 116.2 110.2 116.9 203.8 110.5 116.3 - 312 3121 3122 313 3131 Beverages and tobacco products…………………… Beverages……………………………………………… Tobacco and tobacco products……………………… Textile mills…………………………………………… Fiber, yarn, and thread mills………………………… 78.1 77.1 71.9 73.7 66.5 100.0 100.0 100.0 100.0 100.0 97.6 99.0 98.5 102.6 102.1 87.3 90.7 91.0 106.2 103.9 88.3 90.8 95.9 106.7 101.3 89.5 92.7 98.2 109.5 109.1 82.6 99.4 67.0 125.3 133.3 90.9 108.3 78.7 136.1 148.8 94.7 114.1 82.4 138.6 154.1 100.5 120.3 93.1 152.8 143.5 94.0 112.0 94.9 150.5 139.7 - 3132 3133 314 3141 3149 Fabric mills…………………………………………… Textile and fabric finishing mills……………………… Textile product mills…………………………………… Textile furnishings mills……………………………… Other textile product mills…………………………… 68.0 91.3 93.0 91.2 92.2 100.0 100.0 100.0 100.0 100.0 104.2 101.2 98.7 99.3 96.7 110.0 102.2 102.5 99.1 107.6 110.1 104.4 107.1 104.5 108.9 110.3 108.5 104.5 103.1 103.1 125.4 119.8 107.3 105.5 105.1 137.3 125.1 112.7 114.4 104.2 138.6 127.7 123.4 122.3 120.4 164.2 139.8 128.0 125.7 128.9 170.5 126.2 121.1 117.3 126.1 - 315 3151 3152 3159 316 Apparel………………………………………………… Apparel knitting mills………………………………… Cut and sew apparel………………………………… Accessories and other apparel……………………… Leather and allied products………………………… 71.9 76.2 69.8 97.8 71.6 100.0 100.0 100.0 100.0 100.0 101.8 96.1 102.3 109.0 106.6 111.7 101.4 114.6 99.3 112.7 116.8 108.9 119.8 98.3 120.3 116.5 105.6 119.5 105.2 122.4 102.9 112.0 103.9 76.1 97.7 112.4 105.6 117.2 78.7 99.8 103.4 96.6 108.4 70.8 109.5 110.9 120.0 113.5 74.0 123.6 114.0 123.7 117.6 67.3 132.5 - 3161 3162 3169 321 3211 Leather and hide tanning and finishing……………… Footwear……………………………………………… Other leather products………………………………… Wood products………………………………………… Sawmills and wood preservation…………………… 94.0 76.7 92.3 95.0 77.6 100.0 100.0 100.0 100.0 100.0 100.3 102.1 113.3 101.2 100.3 98.1 117.3 110.4 102.9 104.7 100.1 122.3 122.8 102.7 105.4 100.3 130.7 117.6 106.1 108.8 81.2 102.7 96.2 113.6 114.4 82.2 104.8 100.3 114.7 121.3 93.5 100.7 127.7 115.6 118.2 118.7 105.6 149.7 123.1 127.3 118.1 115.4 174.6 124.9 129.7 - 3212 3219 322 3221 3222 Plywood and engineered wood products…………… 99.7 Other wood products………………………………… 103.0 Paper and paper products…………………………… 85.8 Pulp, paper, and paperboard mills…………………… 81.7 Converted paper products…………………………… 89.0 100.0 100.0 100.0 100.0 100.0 105.1 101.0 102.3 102.5 102.5 98.7 104.5 104.1 111.1 100.1 98.8 103.0 106.3 116.3 101.1 105.2 104.7 106.8 119.9 100.5 110.3 113.9 114.2 133.1 105.6 107.0 113.9 118.9 141.4 109.6 102.9 119.6 123.4 148.0 112.9 110.2 126.3 124.5 147.7 114.8 117.4 125.3 127.3 151.1 116.6 - 323 3231 324 3241 325 Printing and related support activities……………… Printing and related support activities……………… Petroleum and coal products………………………… Petroleum and coal products………………………… Chemicals……………………………………………… 97.6 97.6 71.1 71.1 85.9 100.0 100.0 100.0 100.0 100.0 100.6 100.6 102.2 102.2 99.9 102.8 102.8 107.1 107.1 103.5 104.6 104.6 113.5 113.5 106.6 105.3 105.3 112.1 112.1 105.3 110.2 110.2 118.0 118.0 114.2 111.1 111.1 119.2 119.2 118.4 114.5 114.5 123.4 123.4 125.8 119.5 119.5 123.8 123.8 134.1 121.1 121.1 122.8 122.8 137.5 - 3251 3252 3253 3254 3255 Basic chemicals……………………………………… Resin, rubber, and artificial fibers…………………… Agricultural chemicals………………………………… Pharmaceuticals and medicines…………………… Paints, coatings, and adhesives…………………… 94.6 77.4 80.4 87.3 89.4 100.0 100.0 100.0 100.0 100.0 102.8 106.0 98.8 93.8 100.1 115.7 109.8 87.4 95.7 100.3 117.5 109.8 92.1 95.6 100.8 108.8 106.2 90.0 99.5 105.6 123.8 123.1 99.2 97.4 108.9 136.0 122.2 108.4 101.5 115.2 154.4 121.9 117.4 104.1 119.1 165.2 130.5 132.5 110.0 120.8 169.3 134.9 130.7 115.0 115.4 - 3256 3259 326 3261 3262 Soap, cleaning compounds, and toiletries………… Other chemical products and preparations………… Plastics and rubber products………………………… Plastics products……………………………………… Rubber products……………………………………… 84.4 75.4 80.9 83.1 75.5 100.0 100.0 100.0 100.0 100.0 98.0 99.2 103.2 104.2 99.4 93.0 109.3 107.9 109.9 100.2 102.8 119.7 110.2 112.3 101.7 106.0 110.4 112.3 114.6 102.3 124.1 120.8 120.8 123.8 107.1 118.2 123.0 126.0 129.5 111.0 135.3 121.3 128.7 131.9 114.4 153.1 123.5 132.6 135.6 118.7 162.9 118.1 132.8 133.8 124.9 - 327 3271 3272 3273 Nonmetallic mineral products………………………… Clay products and refractories……………………… Glass and glass products…………………………… Cement and concrete products……………………… 87.6 86.9 82.4 93.6 100.0 100.0 100.0 100.0 103.7 101.2 101.3 105.1 104.3 102.7 106.7 105.9 102.5 102.9 108.1 101.6 100.0 98.4 102.9 98.0 104.6 99.7 107.5 102.4 111.2 103.5 115.3 108.3 108.7 109.2 113.8 102.8 115.3 114.6 123.1 106.5 114.6 111.9 132.9 103.1 - Utilities Manufacturing Monthly Labor Review • September 2008 123 Current Labor Statistics: Productivity Data 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS 124 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 3274 3279 331 3311 3312 Lime and gypsum products…………………………… Other nonmetallic mineral products………………… Primary metals………………………………………… Iron and steel mills and ferroalloy production……… Steel products from purchased steel………………… Industry 88.2 83.0 81.0 64.8 79.7 100.0 100.0 100.0 100.0 100.0 114.9 99.0 102.0 101.3 100.6 104.4 95.6 102.8 104.8 93.8 98.5 96.6 101.3 106.0 96.4 101.8 98.6 101.0 104.4 97.9 99.0 106.9 115.2 125.1 96.8 107.1 113.6 118.2 130.4 93.9 104.7 110.6 132.0 164.9 88.6 119.3 118.9 135.5 163.1 90.8 116.5 116.3 134.3 163.5 86.1 - 3313 3314 3315 332 3321 Alumina and aluminum production………………… Other nonferrous metal production………………… Foundries……………………………………………… Fabricated metal products…………………………… Forging and stamping………………………………… 90.5 96.8 81.4 87.3 85.4 100.0 100.0 100.0 100.0 100.0 101.5 111.3 101.2 101.3 103.5 103.5 108.4 104.5 103.0 110.9 96.6 102.3 103.6 104.8 121.1 96.2 99.5 107.4 104.8 120.7 124.5 107.6 116.7 110.9 125.0 126.8 120.6 116.3 114.4 133.1 137.3 123.1 123.9 113.4 142.0 154.4 122.3 128.6 116.9 147.6 151.7 115.7 131.8 119.7 152.7 - 3322 3323 3324 3325 3326 Cutlery and handtools………………………………… Architectural and structural metals………………… Boilers, tanks, and shipping containers…………… Hardware……………………………………………… Spring and wire products…………………………… 86.3 88.7 86.0 88.7 82.2 100.0 100.0 100.0 100.0 100.0 99.9 100.9 100.0 100.5 110.6 108.0 102.0 96.5 105.2 111.4 105.9 100.6 94.2 114.3 112.6 110.3 101.6 94.4 113.5 111.9 113.4 106.0 98.9 115.5 125.7 113.2 108.8 101.6 125.4 135.3 107.6 105.4 93.6 126.0 133.8 114.1 109.2 95.7 131.8 143.2 116.6 113.5 96.6 131.1 140.6 - 3327 3328 3329 333 3331 Machine shops and threaded products……………… Coating, engraving, and heat treating metals……… Other fabricated metal products……………………… Machinery……………………………………………… Agriculture, construction, and mining machinery… 76.9 75.5 91.0 82.3 74.6 100.0 100.0 100.0 100.0 100.0 99.6 100.9 101.9 102.9 103.3 104.2 101.0 99.6 104.7 94.3 108.2 105.5 99.9 111.5 100.3 108.8 107.3 96.7 109.0 100.3 114.8 116.1 106.5 116.6 103.7 115.7 118.3 111.6 125.2 116.1 114.6 125.3 111.2 127.0 125.4 116.3 136.5 112.5 134.1 129.4 117.1 135.5 117.7 137.4 129.1 - 3332 3333 3334 3335 3336 Industrial machinery…………………………………… Commercial and service industry machinery……… HVAC and commercial refrigeration equipment…… Metalworking machinery……………………………… Turbine and power transmission equipment……… 75.1 87.0 84.0 85.1 80.2 100.0 100.0 100.0 100.0 100.0 95.1 106.3 106.2 99.1 105.0 105.8 110.0 110.2 100.3 110.8 130.0 101.3 107.9 106.1 114.9 105.8 94.5 110.8 103.3 126.9 117.6 97.8 118.6 112.7 130.7 117.0 104.7 130.0 115.2 143.0 126.5 106.5 132.8 117.1 126.4 122.4 115.1 137.1 127.3 132.5 135.3 122.3 133.4 128.3 128.5 - 3339 334 3341 3342 3343 Other general purpose machinery…………………… Computer and electronic products…………………… Computer and peripheral equipment………………… Communications equipment………………………… Audio and video equipment………………………… 83.5 28.4 11.0 39.8 61.7 100.0 100.0 100.0 100.0 100.0 103.7 118.4 140.4 107.1 105.4 106.0 149.5 195.9 135.4 119.6 113.7 181.8 235.0 164.1 126.3 110.5 181.4 252.2 152.9 128.4 117.9 188.0 297.4 128.2 150.1 128.1 217.2 373.4 143.1 171.0 127.1 244.3 415.1 148.4 239.3 138.4 259.6 543.3 143.7 230.2 143.8 282.2 715.7 178.2 240.7 - 3344 3345 3346 335 3351 Semiconductors and electronic components……… Electronic instruments………………………………… Magnetic media manufacturing and reproduction… Electrical equipment and appliances………………… Electric lighting equipment…………………………… 17.0 70.2 85.7 75.5 91.1 100.0 100.0 100.0 100.0 100.0 125.8 102.3 106.4 103.9 104.4 173.9 106.7 108.9 106.6 102.8 232.2 116.7 105.8 111.5 102.0 230.0 119.3 99.8 111.4 106.7 263.1 118.1 110.4 113.4 112.4 321.6 125.3 126.1 117.2 111.4 360.0 145.4 142.6 123.3 122.7 381.6 146.6 142.1 130.0 130.3 380.4 150.6 137.7 129.4 136.7 - 3352 3353 3359 336 3361 Household appliances………………………………… Electrical equipment…………………………………… Other electrical equipment and components……… Transportation equipment…………………………… Motor vehicles………………………………………… 73.3 68.7 78.8 81.6 75.4 100.0 100.0 100.0 100.0 100.0 105.2 100.2 105.8 109.7 113.4 104.0 98.7 114.7 118.0 122.6 117.2 99.4 119.7 109.4 109.7 124.6 101.0 113.1 113.6 110.0 132.3 101.8 114.0 127.4 126.0 146.7 103.4 116.2 137.5 140.7 159.6 110.8 115.6 134.9 142.1 164.5 118.5 121.6 140.9 148.4 173.2 118.1 115.7 142.4 163.8 - 3362 3363 3364 3365 3366 Motor vehicle bodies and trailers…………………… Motor vehicle parts…………………………………… Aerospace products and parts……………………… Railroad rolling stock………………………………… Ship and boat building………………………………… 85.0 78.7 87.2 55.6 95.5 100.0 100.0 100.0 100.0 100.0 102.9 104.9 119.1 103.3 99.3 103.1 110.0 120.8 116.5 112.0 98.8 112.3 103.4 118.5 122.0 88.7 114.8 115.7 126.1 121.5 105.4 130.5 118.6 146.1 131.0 109.8 137.0 119.0 139.8 133.9 110.7 138.0 113.2 131.5 138.7 114.2 144.1 125.0 137.3 131.7 110.9 143.7 117.9 148.0 127.3 - 3369 337 3371 3372 3379 Other transportation equipment……………………… Furniture and related products……………………… Household and institutional furniture………………… Office furniture and fixtures…………………………… Other furniture related products……………………… 73.8 84.8 85.2 85.8 86.3 100.0 100.0 100.0 100.0 100.0 111.5 102.0 102.2 100.0 106.9 113.8 101.6 103.1 98.2 102.0 132.4 101.4 101.9 100.2 99.5 140.2 103.4 105.5 98.0 105.0 150.9 112.6 111.8 115.9 110.2 163.0 117.0 114.7 125.2 110.0 168.3 118.4 113.6 130.7 121.3 184.1 125.0 120.8 134.9 128.3 197.8 127.8 124.0 134.4 130.8 - 339 3391 3399 Miscellaneous manufacturing………………………… Medical equipment and supplies…………………… Other miscellaneous manufacturing………………… 81.1 76.3 85.4 100.0 100.0 100.0 105.2 109.0 102.1 107.8 111.1 105.0 114.7 115.5 113.6 116.6 120.7 111.8 124.2 129.1 118.0 132.7 138.9 124.7 134.9 139.5 128.6 144.6 148.5 137.8 149.8 152.8 143.2 - 42 423 4231 4232 4233 4234 Wholesale trade……………………………………… 73.2 Durable goods………………………………………… 62.3 Motor vehicles and parts……………………………… 74.5 Furniture and furnishings…………………………… 80.5 Lumber and construction supplies…………………… 109.1 Commercial equipment……………………………… 28.0 100.0 100.0 100.0 100.0 100.0 100.0 103.4 107.1 106.4 99.9 105.4 125.5 111.2 119.2 120.4 102.3 109.3 162.0 116.5 125.0 116.7 112.5 107.7 181.9 117.7 128.9 120.0 110.7 116.6 217.9 123.3 140.2 133.4 116.0 123.9 264.9 127.5 146.6 137.6 123.9 133.0 299.1 134.8 161.5 143.5 130.0 139.4 352.8 135.8 167.4 146.5 127.1 140.2 402.0 138.6 174.5 162.7 130.6 135.4 447.3 141.5 178.4 161.8 131.1 124.5 508.5 4235 4236 4237 4238 4239 424 Metals and minerals…………………………………… 101.7 Electric goods………………………………………… 42.8 82.2 Hardware and plumbing……………………………… Machinery and supplies……………………………… 74.1 Miscellaneous durable goods………………………… 89.8 Nondurable goods…………………………………… 91.0 100.0 100.0 100.0 100.0 100.0 100.0 100.9 105.9 101.8 104.3 100.8 99.1 94.0 127.5 104.4 102.9 113.7 100.8 93.9 152.8 103.7 105.5 114.7 105.1 94.4 147.6 100.5 102.9 116.8 105.1 96.3 159.5 102.6 100.3 124.6 105.8 97.5 165.7 103.9 103.4 119.6 110.5 106.3 194.1 107.3 112.4 135.0 113.6 104.2 204.6 104.5 117.6 135.5 114.3 99.9 222.1 105.6 121.2 122.3 113.1 94.4 235.1 105.8 121.5 118.4 115.0 Wholesale trade Monthly Labor Review • September 2008 2007 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS Industry 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 85.6 70.7 86.3 87.9 81.6 100.0 100.0 100.0 100.0 100.0 98.4 94.2 103.6 101.1 94.3 100.1 93.1 105.1 101.0 101.6 100.9 85.9 108.8 102.4 105.1 104.6 84.9 115.2 101.9 102.1 116.6 89.8 122.8 98.6 98.1 119.7 100.2 125.9 104.9 98.2 130.9 105.8 131.0 104.1 109.3 141.7 112.1 140.8 103.4 111.0 136.9 109.7 146.6 103.8 117.9 146.5 104.3 148.3 109.7 125.1 4246 4247 4248 4249 425 4251 Chemicals……………………………………………… 90.4 Petroleum……………………………………………… 84.4 Alcoholic beverages…………………………………… 99.3 Miscellaneous nondurable goods…………………… 111.2 Electronic markets and agents and brokers………… 64.3 Electronic markets and agents and brokers………… 64.3 100.0 100.0 100.0 100.0 100.0 100.0 97.1 88.5 106.5 105.4 102.4 102.4 93.3 102.9 105.6 106.8 112.3 112.3 87.9 138.1 108.4 115.0 120.1 120.1 85.3 140.6 106.4 111.9 110.7 110.7 89.1 153.6 106.8 106.1 109.8 109.8 92.2 151.1 107.9 109.8 104.5 104.5 91.2 163.2 103.1 120.7 101.6 101.6 87.4 153.3 104.0 124.1 91.5 91.5 85.1 149.4 107.4 121.9 95.0 95.0 86.4 149.1 108.5 117.1 98.3 98.3 44-45 441 4411 4412 4413 Retail trade…………………………………………… Motor vehicle and parts dealers……………………… Automobile dealers…………………………………… Other motor vehicle dealers………………………… Auto parts, accessories, and tire stores…………… 79.2 78.4 79.2 74.1 71.8 100.0 100.0 100.0 100.0 100.0 105.7 106.4 106.5 109.6 105.1 112.7 115.1 116.3 114.8 107.6 116.1 114.3 113.7 115.3 108.4 120.1 116.0 115.5 124.6 101.3 125.6 119.9 117.2 133.6 107.7 131.6 124.3 119.5 133.8 115.1 137.9 127.3 124.7 143.3 110.1 141.3 126.7 123.5 134.6 115.5 147.3 129.3 125.8 142.6 115.9 152.7 132.2 129.8 146.9 112.0 442 4421 4422 443 4431 Furniture and home furnishings stores……………… Furniture stores………………………………………… Home furnishings stores……………………………… Electronics and appliance stores…………………… Electronics and appliance stores…………………… 75.1 77.3 71.3 38.0 38.0 100.0 100.0 100.0 100.0 100.0 104.1 104.3 104.1 122.6 122.6 110.8 107.5 115.2 150.6 150.6 115.9 112.0 121.0 173.7 173.7 122.4 119.7 126.1 196.7 196.7 129.3 125.2 134.9 233.5 233.5 134.6 128.8 142.6 292.7 292.7 146.7 139.2 156.8 334.1 334.1 150.5 142.3 161.4 367.5 367.5 158.2 151.1 168.3 412.0 412.0 168.7 156.6 184.6 471.1 471.1 444 4441 4442 445 4451 Building material and garden supply stores………… 75.8 Building material and supplies dealers……………… 77.6 Lawn and garden equipment and supplies stores… 66.9 Food and beverage stores…………………………… 110.8 Grocery stores………………………………………… 111.1 100.0 100.0 100.0 100.0 100.0 107.4 108.3 102.4 99.9 99.6 113.8 115.3 105.5 101.9 102.5 113.3 115.1 103.1 101.0 101.1 116.8 116.7 118.4 103.8 103.3 120.8 121.3 118.3 104.7 104.8 127.1 127.4 125.7 107.2 106.7 134.6 134.0 140.1 112.9 112.2 134.8 134.9 134.7 117.9 116.8 137.9 138.0 138.3 120.6 118.2 142.2 140.0 162.1 123.8 120.6 4452 4453 446 4461 447 Specialty food stores………………………………… 138.5 Beer, wine, and liquor stores………………………… 93.6 Health and personal care stores…………………… 84.0 Health and personal care stores…………………… 84.0 Gasoline stations……………………………………… 83.9 100.0 100.0 100.0 100.0 100.0 100.5 104.6 104.0 104.0 106.7 96.4 99.1 107.1 107.1 110.7 98.5 105.7 112.2 112.2 107.7 108.2 107.1 116.2 116.2 112.9 105.3 110.1 122.9 122.9 125.1 112.2 117.0 129.5 129.5 119.9 120.3 127.8 134.3 134.3 122.2 125.3 139.8 133.4 133.4 124.7 139.4 146.1 139.3 139.3 124.9 145.4 156.8 139.0 139.0 129.3 4471 448 4481 4482 4483 Gasoline stations……………………………………… Clothing and clothing accessories stores…………… Clothing stores………………………………………… Shoe stores…………………………………………… Jewelry, luggage, and leather goods stores……… 83.9 66.3 67.1 65.3 64.5 100.0 100.0 100.0 100.0 100.0 106.7 106.3 108.7 94.2 108.7 110.7 114.0 114.2 104.9 122.5 107.7 123.5 125.0 110.0 130.5 112.9 126.4 130.3 111.5 123.9 125.1 131.3 136.0 125.2 118.7 119.9 138.9 141.8 132.5 132.9 122.2 139.1 140.9 124.8 144.3 124.7 147.6 153.0 132.0 138.9 124.9 162.4 169.4 145.1 148.3 129.3 176.6 186.9 141.6 162.9 451 4511 4512 452 4521 Sporting goods, hobby, book, and music stores…… Sporting goods and musical instrument stores…… Book, periodical, and music stores………………… General merchandise stores………………………… Department stores…………………………………… 74.9 73.2 78.9 73.5 87.2 100.0 100.0 100.0 100.0 100.0 107.9 111.5 101.0 105.3 100.4 114.0 119.8 103.2 113.4 104.5 121.1 129.4 105.8 120.2 106.2 127.1 134.5 113.0 124.8 103.8 127.6 136.0 111.6 129.1 102.0 131.5 141.1 113.7 136.9 106.8 151.1 166.0 123.6 140.7 109.0 163.5 179.3 134.3 145.0 110.0 170.5 191.4 132.4 149.8 112.7 167.8 189.2 128.3 152.5 107.0 4529 453 4531 4532 4533 Other general merchandise stores………………… Miscellaneous store retailers………………………… Florists………………………………………………… Office supplies, stationery and gift stores…………… Used merchandise stores…………………………… 54.8 65.1 77.6 61.4 64.5 100.0 100.0 100.0 100.0 100.0 114.7 108.9 102.3 111.5 119.1 131.0 111.3 116.2 119.2 113.4 147.3 114.1 115.2 127.3 116.5 164.7 112.6 102.7 132.3 121.9 179.3 119.1 113.8 141.5 142.0 188.8 126.1 108.9 153.9 149.7 192.9 130.8 103.4 172.8 152.6 199.8 139.2 123.7 182.4 156.6 204.8 155.0 145.1 204.8 167.6 219.3 160.8 132.9 224.5 182.0 4539 454 4541 4542 4543 Other miscellaneous store retailers………………… Nonstore retailers……………………………………… Electronic shopping and mail-order houses………… Vending machine operators………………………… Direct selling establishments………………………… 68.3 50.7 39.4 95.5 70.8 100.0 100.0 100.0 100.0 100.0 105.3 114.3 120.2 106.3 101.9 103.0 128.9 142.6 105.4 104.3 104.4 152.2 160.2 111.1 122.5 96.9 163.6 179.6 95.7 127.9 94.4 182.1 212.7 91.3 135.1 99.9 195.5 243.6 102.3 127.0 96.9 215.5 273.0 110.5 130.3 101.6 220.6 290.1 114.4 119.6 114.0 261.9 355.9 125.7 127.5 115.4 290.8 397.2 132.4 138.4 481 482111 48412 48421 491 4911 Air transportation……………………………………… 81.1 Line-haul railroads…………………………………… 58.9 General freight trucking, long-distance……………… 85.7 Used household and office goods moving………… 106.7 U.S. Postal service…………………………………… 90.9 U.S. Postal service…………………………………… 90.9 100.0 100.0 100.0 100.0 100.0 100.0 97.6 102.1 99.4 91.0 101.6 101.6 98.2 105.5 99.1 96.1 102.8 102.8 98.1 114.3 101.9 94.8 105.5 105.5 91.9 121.9 103.2 84.0 106.3 106.3 102.1 131.9 107.0 81.6 106.4 106.4 112.8 142.0 110.7 86.2 107.8 107.8 126.9 146.4 110.7 88.6 110.0 110.0 135.5 138.4 113.2 88.3 111.2 111.2 142.5 142.8 112.3 87.0 111.3 111.3 - 492 493 4931 49311 49312 Couriers and messengers…………………………… 148.3 Warehousing and storage…………………………… Warehousing and storage…………………………… General warehousing and storage………………… Refrigerated warehousing and storage……………… - 100.0 100.0 100.0 100.0 100.0 112.6 106.4 106.4 112.1 97.9 117.6 107.7 107.7 112.9 103.4 122.0 109.3 109.3 115.8 95.4 123.4 115.3 115.3 126.3 85.4 131.1 122.1 122.1 136.1 87.2 134.0 124.8 124.8 138.9 92.3 126.8 122.5 122.5 131.0 99.3 125.1 124.9 124.9 132.2 97.5 128.6 122.3 122.3 127.9 88.5 - 100.0 116.1 116.3 117.1 116.6 117.2 126.4 130.7 136.5 142.7 - 4241 4242 4243 4244 4245 Paper and paper products…………………………… Druggists' goods……………………………………… Apparel and piece goods…………………………… Grocery and related products………………………… Farm product raw materials………………………… 511 Retail trade Transportation and warehousing Information Publishing industries, except internet 64.1 Monthly Labor Review • September 2008 125 Current Labor Statistics: Productivity Data 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 5111 5112 51213 515 5151 5152 Newspaper, book, and directory publishers………… 105.0 Software publishers…………………………………… 10.2 90.7 Motion picture and video exhibition………………… Broadcasting, except internet………………………… 99.5 Radio and television broadcasting…………………… 98.1 Cable and other subscription programming………… 105.6 Industry 100.0 100.0 100.0 100.0 100.0 100.0 103.9 134.8 99.8 100.8 91.5 136.2 104.1 129.2 101.8 102.9 92.6 139.1 107.7 119.2 106.5 103.6 92.1 141.2 105.8 117.4 101.6 99.2 89.6 128.1 104.7 122.1 99.8 104.0 95.1 129.8 109.5 138.1 100.4 107.9 94.6 146.0 106.6 160.6 103.6 112.5 96.6 158.7 107.6 173.7 102.4 117.7 100.9 164.6 110.8 177.0 105.7 125.5 109.5 169.9 - 5171 5172 5175 Wired telecommunications carriers………………… 56.9 Wireless telecommunications carriers……………… 75.6 Cable and other program distribution……………… 105.2 100.0 100.0 100.0 107.7 110.5 97.1 116.7 145.2 95.8 122.7 152.8 91.6 116.7 191.9 87.7 124.1 217.9 95.0 130.5 242.6 101.3 131.7 292.2 113.8 138.2 381.9 110.6 146.2 435.9 110.6 - 52211 Commercial banking………………………………… 72.8 100.0 97.0 99.8 102.7 99.6 102.1 103.6 108.4 108.5 114.2 - 92.7 60.3 77.0 100.0 100.0 100.0 100.1 115.4 113.2 112.2 120.9 129.4 112.3 121.7 134.9 111.1 113.5 133.3 114.6 114.0 130.3 121.1 115.8 148.5 118.2 136.6 154.5 110.2 145.1 144.2 111.8 162.2 176.4 - 82.9 90.0 90.2 95.9 98.1 100.0 100.0 100.0 100.0 100.0 107.6 111.4 98.2 89.2 124.8 105.8 106.8 98.0 97.9 109.8 100.9 107.6 102.0 107.5 108.9 94.4 111.0 100.1 106.9 102.2 111.4 107.6 100.5 113.1 97.6 110.0 112.6 100.5 121.1 104.1 99.9 118.3 107.8 133.5 93.0 103.6 120.8 115.4 131.5 93.5 99.7 119.1 116.2 132.8 95.3 - 89.3 75.1 100.0 100.0 100.0 86.8 111.4 95.3 93.2 115.5 98.6 89.8 119.4 101.0 99.6 115.2 102.1 116.8 127.6 105.6 115.4 147.2 118.8 119.8 167.2 116.6 115.9 182.4 121.5 122.9 189.9 115.6 - - 100.0 100.0 100.0 118.8 117.2 121.4 124.7 121.4 129.7 131.9 127.4 139.9 135.3 127.7 148.3 137.6 123.1 163.3 140.8 128.6 160.0 140.8 130.7 153.5 137.9 126.0 154.0 140.1 128.2 156.3 - Finance and insurance Real estate and rental and leasing 2007 532111 53212 53223 Passenger car rental………………………………… Truck, trailer, and RV rental and leasing…………… Video tape and disc rental…………………………… 541213 54131 54133 54181 541921 Tax preparation services……………………………… Architectural services………………………………… Engineering services………………………………… Advertising agencies………………………………… Photography studios, portrait………………………… 56131 56151 56172 Employment placement agencies…………………… Travel agencies……………………………………… Janitorial services……………………………………… 6215 621511 621512 Medical and diagnostic laboratories………………… Medical laboratories…………………………………… Diagnostic imaging centers…………………………… 71311 71395 Amusement and theme parks……………………… Bowling centers……………………………………… 112.0 106.0 100.0 100.0 110.5 89.9 105.2 89.4 106.0 93.4 93.0 94.3 106.5 96.4 113.2 102.4 101.4 107.9 109.9 106.1 97.7 110.6 - 7211 722 7221 7222 7223 7224 Traveler accommodation……………………………… 85.1 Food services and drinking places………………… 96.0 Full-service restaurants……………………………… 92.1 Limited-service eating places………………………… 96.5 Special food services………………………………… 89.9 Drinking places, alcoholic beverages……………… 136.7 100.0 100.0 100.0 100.0 100.0 100.0 100.1 101.0 100.9 101.2 100.6 99.7 105.6 100.9 100.8 100.4 105.2 98.8 111.8 103.5 103.0 102.0 115.0 100.6 107.6 103.8 103.6 102.5 115.3 97.6 112.1 104.4 104.4 102.7 114.9 102.9 114.4 106.3 104.2 105.4 117.6 118.6 120.4 107.0 104.8 106.8 118.0 112.2 115.0 107.9 105.2 107.5 119.2 121.6 111.8 109.7 106.0 109.8 118.7 135.7 109.2 105.1 108.6 120.2 145.2 8111 81211 81221 8123 81292 Automotive repair and maintenance………………… 85.9 Hair, nail, and skin care services…………………… 83.5 Funeral homes and funeral services………………… 103.7 Drycleaning and laundry services…………………… 97.1 Photofinishing………………………………………… 95.8 100.0 100.0 100.0 100.0 100.0 103.6 108.6 106.8 100.1 69.3 106.1 108.6 103.3 105.0 76.3 109.4 108.2 94.8 107.6 73.8 108.9 114.6 91.8 110.9 81.2 103.7 110.4 94.6 112.5 100.5 104.1 119.7 95.7 103.8 100.5 112.0 125.0 92.9 110.6 102.0 111.9 129.9 93.2 120.5 112.4 112.8 122.3 99.7 119.6 114.4 - Professional and technical services Administrative and waste services Health care and social assistance Arts, entertainment, and recreation Accommodation and food services Other services NOTE: Dash indicates data are not available. 126 Monthly Labor Review • September 2008 51. Unemployment rates, approximating U.S. concepts, 10 countries, seasonally adjusted [Percent] 2006 Country 2006 2007 I II 2007 III IV I II 2008 III IV I United States……… 4.6 4.6 4.7 4.7 4.7 4.4 4.5 4.5 4.7 4.8 Canada……………… 5.5 5.3 5.7 5.4 5.6 5.4 5.4 5.3 5.2 5.2 5.2 Australia…………… 4.8 4.4 5.0 4.9 4.7 4.5 4.5 4.3 4.3 4.3 4.1 Japan………………… 4.2 3.9 4.2 4.2 4.2 4.1 4.0 3.8 3.8 3.9 3.9 France……………… 9.5 8.6 9.8 9.7 9.5 9.2 9.0 8.8 8.5 8.2 8.1 Germany…………… 10.4 8.7 11.1 10.6 10.1 9.6 9.3 8.9 8.5 8.2 7.7 Italy………………… 6.9 6.1 7.3 6.9 6.7 6.4 6.3 6.1 6.0 6.0 - Netherlands………… 3.9 3.2 4.3 3.9 3.8 3.8 3.6 3.2 3.0 3.0 - Sweden……………… 7.0 6.1 7.3 7.3 6.7 6.5 6.4 6.1 5.8 5.9 5.8 United Kingdom…… 5.5 5.4 5.3 5.5 5.6 5.5 5.5 5.4 5.4 5.2 - NOTE: Dash indicates data not available. Quarterly figures for France, Germany, Italy, and the Netherlands are calculated by applying annual adjustment factors to current published data and therefore should be viewed as less precise indicators of unemployment under U.S. concepts than the annual figures. Quarterly figures for Sweden are BLS seasonally adjusted estimates derived from Swedish not seasonally adjusted data. For further qualifications and historical annual data, see the BLS report Comparative Civilian Labor Force Statistics, 10 Countries (on the 4.9 Internet at http://www.bls.gov/fls/flscomparelf.htm ). For monthly unemployment rates, as well as the quarterly and annual rates published in this table, see the BLS report Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted (on the Internet at http://www.bls.gov/fls/flsjec.pdf ). Unemployment rates may differ between the two reports mentioned, because the former is updated semi-annually, whereas the latter is updated monthly and reflects the most recent revisions in source data. Monthly Labor Review • September 2008 127 Current Labor Statistics: International Comparisons 52. Annual data: employment status of the working-age population, approximating U.S. concepts, 10 countries [Numbers in thousands] Employment status and country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 137,673 15,135 9,339 67,240 25,434 39,752 23,004 7,744 4,401 28,474 139,368 15,403 9,414 67,090 25,791 39,375 23,176 7,881 4,423 28,777 142,583 15,637 9,590 66,990 26,099 39,302 23,361 8,052 4,482 28,952 143,734 15,891 9,744 66,860 26,393 39,459 23,524 8,199 4,522 29,085 144,863 16,366 9,893 66,240 26,646 39,413 23,728 8,345 4,537 29,337 146,510 16,733 10,079 66,010 26,851 39,276 24,020 8,379 4,557 29,559 147,401 16,955 10,221 65,770 26,937 39,711 24,084 8,439 4,571 29,791 149,320 17,108 10,506 65,850 27,092 40,760 24,179 8,459 4,694 30,126 151,428 17,351 10,699 65,960 27,322 41,250 24,395 8,541 4,748 30,586 153,124 17,696 10,948 66,080 27,509 24,459 8,686 4,823 30,774 67.1 65.1 64.3 63.2 55.6 57.3 47.3 61.1 63.2 62.5 67.1 65.4 64.3 62.8 56.0 57.7 47.7 61.8 62.8 62.5 67.1 65.9 64.0 62.4 56.3 56.9 47.9 62.5 62.7 62.8 67.1 66.0 64.4 62.0 56.6 56.7 48.1 63.4 63.7 62.9 66.8 66.1 64.4 61.6 56.7 56.7 48.3 64.0 63.6 62.7 66.6 67.1 64.3 60.8 56.8 56.4 48.5 64.7 63.9 62.9 66.2 67.7 64.6 60.3 56.8 56.0 49.1 64.6 63.8 63.0 66.0 67.7 64.6 60.0 56.6 56.4 49.1 64.8 63.6 63.0 66.0 67.4 65.3 60.0 56.5 57.6 48.7 64.7 64.8 63.1 66.2 67.4 65.6 60.0 56.6 58.2 48.9 65.1 65.0 63.5 66.0 67.7 66.0 60.0 56.7 48.6 65.9 65.3 63.4 United States……………………………………………… 129,558 Canada…………………………………………………… 13,637 Australia…………………………………………………… 8,444 Japan……………………………………………………… 64,900 France…………………………………………………… 22,176 Germany………………………………………………… 35,508 Italy………………………………………………………… 20,169 Netherlands……………………………………………… 7,189 Sweden…………………………………………………… 3,969 United Kingdom………………………………………… 26,413 131,463 13,973 8,618 64,450 22,597 36,059 20,370 7,408 4,033 26,686 133,488 14,331 8,762 63,920 23,080 36,042 20,617 7,605 4,110 27,051 136,891 14,681 8,989 63,790 23,714 36,236 20,973 7,813 4,222 27,368 136,933 14,866 9,086 63,460 24,167 36,350 21,359 8,014 4,295 27,599 136,485 15,223 9,264 62,650 24,312 36,018 21,666 8,114 4,303 27,813 137,736 15,586 9,480 62,510 24,373 35,615 21,972 8,069 4,293 28,075 139,252 15,861 9,668 62,640 24,354 35,604 22,124 8,052 4,271 28,372 141,730 16,080 9,975 62,910 24,493 36,185 22,290 8,056 4,334 28,665 144,427 16,393 10,186 63,210 24,717 36,978 22,721 8,205 4,416 28,917 146,047 16,767 10,470 63,510 25,135 22,953 8,408 4,530 29,120 63.8 59.6 59.0 61.0 49.1 51.6 41.9 57.7 56.8 58.2 64.1 60.4 59.3 60.2 49.7 52.3 42.2 59.1 57.6 58.5 64.3 61.3 59.6 59.4 50.4 52.1 42.6 60.3 58.3 59.1 64.4 62.0 60.3 59.0 51.4 52.2 43.2 61.5 60.0 59.4 63.7 61.9 60.0 58.4 51.9 52.2 43.8 62.6 60.4 59.5 62.7 62.4 60.2 57.5 51.8 51.5 44.3 62.9 60.6 59.6 62.3 63.1 60.7 57.1 51.5 50.8 44.9 62.2 60.1 59.8 62.3 63.3 61.1 57.1 51.1 50.6 45.1 61.8 59.4 60.0 62.7 63.4 62.0 57.3 51.1 51.2 44.9 61.6 59.9 60.1 63.1 63.6 62.5 57.5 51.2 52.2 45.5 62.5 60.4 60.1 63.0 64.2 63.1 57.6 51.8 45.6 63.8 61.3 60.0 6,739 1,248 759 2,300 2,940 3,907 2,584 423 445 1,987 6,210 1,162 721 2,790 2,837 3,693 2,634 337 368 1,788 5,880 1,072 652 3,170 2,711 3,333 2,559 277 313 1,726 5,692 956 602 3,200 2,385 3,065 2,388 239 260 1,584 6,801 1,026 658 3,400 2,226 3,110 2,164 186 227 1,486 8,378 1,143 629 3,590 2,334 3,396 2,062 231 234 1,524 8,774 1,147 599 3,500 2,478 3,661 2,048 310 264 1,484 8,149 1,093 553 3,130 2,583 4,107 1,960 387 300 1,419 7,591 1,028 531 2,940 2,599 4,575 1,889 402 361 1,462 7,001 958 512 2,750 2,605 4,272 1,673 336 332 1,669 7,078 929 478 2,570 2,374 1,506 278 293 1,654 4.9 8.4 8.3 3.4 11.7 9.9 11.4 5.6 10.1 7.0 4.5 7.7 7.7 4.1 11.2 9.3 11.5 4.4 8.4 6.3 4.2 7.0 6.9 4.7 10.5 8.5 11.0 3.5 7.1 6.0 4.0 6.1 6.3 4.8 9.1 7.8 10.2 3.0 5.8 5.5 4.7 6.5 6.8 5.1 8.4 7.9 9.2 2.3 5.0 5.1 5.8 7.0 6.4 5.4 8.8 8.6 8.7 2.8 5.2 5.2 6.0 6.9 5.9 5.3 9.2 9.3 8.5 3.7 5.8 5.0 5.5 6.4 5.4 4.8 9.6 10.3 8.1 4.6 6.6 4.8 5.1 6.0 5.1 4.5 9.6 11.2 7.8 4.8 7.7 4.9 4.6 5.5 4.8 4.2 9.5 10.4 6.9 3.9 7.0 5.5 4.6 5.3 4.4 3.9 8.6 8.7 6.2 3.2 6.1 5.4 Civilian labor force United States……………………………………………… 136,297 Canada…………………………………………………… 14,884 Australia…………………………………………………… 9,204 Japan……………………………………………………… 67,200 France…………………………………………………… 25,116 Germany………………………………………………… 39,415 Italy………………………………………………………… 22,753 Netherlands……………………………………………… 7,612 Sweden…………………………………………………… 4,414 United Kingdom………………………………………… 28,401 Participation rate1 United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France…………………………………………………… Germany………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom………………………………………… Employed Employment-population ratio2 United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France…………………………………………………… Germany………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom………………………………………… Unemployed United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France…………………………………………………… Germany………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom………………………………………… Unemployment rate United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France…………………………………………………… Germany………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom………………………………………… 1 Labor force as a percent of the working-age population. 2 Employment as a percent of the working-age population. NOTE: Dash indicates data not available. There are breaks in series for the United States (1998, 1999, 2000, 2003, 2004), Australia (2001), Germany (1999, 2005), the Netherlands (2000), and Sweden (2005). For further qualifications and historical annual data, see the BLS report Comparative 128 Monthly Labor Review • September 2008 Civilian Labor Force Statistics, 10 Countries (on the Internet at http://www.bls.gov/fls/flscomparelf.htm). Unemployment rates may differ from those in the BLS report Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted (on the Internet at http://www.bls.gov/fls/flsjec.pdf), because the former is updated semi-annually, whereas the latter is updated monthly and reflects the most recent revisions in source data. 53. Annual indexes of manufacturing productivity and related measures, 16 economies [1996 = 100] Measure and economy 1980 1990 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Output per hour United States……………………… Canada………………………….…… Australia…………………….……… Japan………………………………… Korea, Rep. of……………………… Taiwan……………………………… Belgium…………………………...… Denmark…………………………… France……………………………… Germany………………………...…… Italy……………………………...…… Netherlands…………………...…… Norway……………………………… Spain……………………………….. Sweden…………………………….. United Kingdom……………….…… 58.6 66.5 72.6 54.8 – 40.4 57.2 75.3 56.9 67.1 60.1 58.7 77.3 62.8 60.0 55.9 80.1 85.2 91.1 81.3 58.0 73.9 84.7 90.3 84.2 86.1 82.5 81.4 96.8 86.8 73.9 87.8 88.1 94.0 96.2 87.6 75.9 83.4 89.6 92.0 90.0 89.1 87.2 86.2 98.3 94.9 82.6 100.1 92.7 99.3 98.7 89.0 82.8 86.6 94.4 103.4 95.9 95.8 94.9 94.1 98.3 97.8 91.1 102.7 96.2 100.5 97.2 95.6 90.9 93.0 98.6 103.4 99.7 97.3 99.5 97.9 97.1 101.2 96.8 101.0 104.2 104.5 102.2 103.5 112.8 104.1 109.8 108.0 105.9 105.9 102.0 100.3 100.2 101.0 109.1 102.0 111.5 109.6 107.3 104.5 125.7 109.2 111.2 107.4 111.4 106.3 100.6 103.2 97.7 102.7 115.6 102.9 117.1 114.2 109.0 107.3 139.8 116.0 110.2 109.1 116.2 108.9 101.4 107.4 101.1 104.5 126.2 107.8 126.1 121.1 115.2 113.0 151.7 122.2 114.1 113.0 124.5 116.5 106.7 115.2 104.2 105.6 134.8 115.2 127.4 118.5 117.9 110.6 150.6 127.7 115.3 113.2 127.0 119.5 107.0 115.7 107.1 108.0 131.0 119.4 140.9 120.5 123.2 114.7 165.3 139.2 119.1 113.9 132.4 120.7 105.7 119.2 110.2 108.4 145.3 122.4 149.8 121.1 125.5 122.5 176.8 143.6 122.0 118.7 138.4 125.0 103.5 121.7 119.7 111.1 157.1 128.2 159.0 123.1 127.2 131.0 197.2 150.9 127.6 125.5 142.2 129.7 105.0 129.9 126.8 113.2 173.9 136.0 162.4 127.8 128.1 139.6 212.1 162.3 131.5 126.9 148.7 134.6 106.4 135.8 131.2 115.4 184.7 140.2 165.9 127.7 129.4 142.2 233.5 173.9 134.4 133.4 154.6 144.1 105.9 140.2 135.0 117.7 195.6 147.0 172.7 130.4 133.4 146.2 253.9 189.0 137.3 134.3 158.5 151.3 105.4 144.0 134.7 122.2 197.3 150.8 Output United States…………………..…… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 60.5 71.2 80.2 59.0 20.5 38.2 74.8 85.6 83.2 92.3 74.7 70.5 96.7 75.5 67.1 80.3 80.7 88.7 93.1 94.3 63.2 76.7 96.6 94.7 97.5 107.2 92.6 89.2 92.9 94.6 80.4 96.9 85.7 87.7 92.7 93.5 75.5 85.0 92.8 90.3 93.8 99.9 89.9 90.2 93.2 92.4 74.1 93.4 92.2 94.4 97.5 92.1 84.1 90.1 97.0 100.0 96.8 103.1 95.9 95.0 95.7 94.0 85.5 97.8 96.4 98.7 96.9 95.9 94.0 95.0 99.6 104.8 100.3 102.1 100.5 98.6 96.1 97.6 96.8 99.3 106.1 106.3 102.3 102.5 104.9 105.7 108.2 108.2 104.7 104.4 101.5 101.4 104.3 106.4 107.8 101.8 113.2 111.7 105.2 97.1 96.6 109.1 110.1 109.1 109.7 105.6 102.4 104.8 103.6 112.9 116.7 102.4 118.1 121.0 105.0 96.7 117.6 117.1 110.2 110.0 113.4 106.6 102.2 108.7 103.5 119.3 127.6 103.4 125.5 133.1 109.9 101.8 137.6 125.7 114.9 113.9 118.6 113.9 106.5 116.0 102.9 124.6 138.1 105.8 118.5 128.0 108.9 96.2 140.6 116.4 114.9 114.0 119.8 115.8 106.2 115.8 102.2 128.6 134.9 104.5 121.8 129.0 114.2 94.7 151.2 126.7 114.0 110.7 119.7 113.4 105.0 115.9 101.6 128.4 143.4 101.7 123.2 128.3 116.2 99.8 159.6 133.5 112.5 107.6 121.9 114.2 102.2 114.6 105.0 130.0 150.4 101.9 130.1 131.4 116.3 105.6 177.3 146.5 116.6 109.3 123.0 118.3 103.0 118.5 111.0 130.9 164.2 104.0 131.4 133.5 115.8 111.1 189.8 156.7 116.3 105.9 125.9 120.0 102.5 120.9 115.9 132.4 171.8 102.8 135.2 132.2 114.7 115.8 205.9 168.4 119.4 111.7 127.2 127.0 103.7 124.1 123.9 134.8 180.6 104.4 138.3 130.8 118.6 119.0 219.3 185.8 122.4 116.2 128.8 135.0 104.8 128.1 129.3 138.6 185.2 105.0 Total hours United States……………………… 103.3 Canada……………………………… 107.0 Australia……………………………… 110.5 Japan………………………………… 107.6 Korea, Rep. of……………………… – Taiwan……………………………… 94.5 Belgium……………………………… 130.9 Denmark…………………………… 113.7 France……………………………… 146.3 Germany…………………………… 137.4 Italy…………………………………… 124.3 Netherlands………………………… 120.1 Norway……………………………… 125.1 Spain……………………………….. 120.3 Sweden……………………………… 111.8 United Kingdom…………………… 143.8 100.7 104.1 102.2 115.9 109.0 103.7 114.1 104.8 115.8 124.6 112.2 109.6 96.0 109.0 108.8 110.4 97.3 93.3 96.4 106.7 99.5 101.9 103.5 98.1 104.1 112.1 103.1 104.6 94.8 97.4 89.7 93.3 99.5 95.1 98.7 103.5 101.6 104.0 102.8 96.7 101.0 107.6 101.1 100.9 97.3 96.1 93.9 95.2 100.2 98.3 99.7 100.4 103.3 102.2 101.0 101.4 100.6 105.0 100.9 100.7 99.0 96.4 100.0 98.3 101.8 101.6 100.1 99.1 93.0 101.6 98.6 100.2 98.9 98.6 99.5 101.0 104.1 105.4 98.8 99.8 101.5 101.9 98.1 92.9 76.8 99.9 98.9 101.5 98.5 99.4 101.8 101.5 106.1 109.9 100.9 99.6 100.9 105.9 96.3 90.2 84.1 101.0 100.0 100.8 97.6 97.9 100.8 101.2 102.4 114.1 101.1 95.9 99.6 109.9 95.4 90.1 90.7 102.9 100.6 100.8 95.3 97.7 99.9 100.7 98.8 118.0 102.4 91.8 93.0 107.9 92.3 87.0 93.3 91.1 99.6 100.7 94.3 96.9 99.3 100.1 95.4 119.0 103.0 87.5 86.5 107.1 92.7 82.6 91.5 91.1 95.7 97.2 90.4 94.0 99.3 97.2 92.3 118.4 98.7 83.1 82.2 105.9 92.6 81.4 90.2 92.9 92.2 90.7 88.1 91.4 98.8 94.1 87.7 117.0 95.7 79.5 81.8 106.7 91.4 80.6 89.9 97.1 91.4 87.1 86.5 91.2 98.1 91.2 87.5 115.6 94.4 76.5 80.9 104.4 90.4 79.6 89.5 96.5 88.5 83.5 84.7 89.2 96.4 89.0 88.4 114.7 93.0 73.3 81.5 103.5 88.7 81.5 88.2 96.8 88.9 83.7 82.3 88.1 97.9 88.5 91.8 114.6 92.4 71.0 80.1 100.3 88.9 81.4 86.4 98.3 89.2 86.5 81.2 89.2 99.4 88.9 96.0 113.4 93.9 69.6 82.7 82.4 79.5 83.0 36.1 66.5 81.4 83.1 78.9 72.3 70.5 79.0 81.2 65.9 77.4 82.8 93.3 93.5 89.3 94.1 61.6 82.6 94.8 90.9 91.8 86.7 85.1 91.7 89.2 90.3 85.8 96.2 96.3 96.2 90.4 96.0 70.8 86.6 95.5 94.1 95.3 90.6 89.6 95.7 91.9 93.6 88.0 98.6 98.1 98.5 95.7 99.2 85.9 93.8 98.2 96.0 98.1 95.5 94.9 98.3 96.0 97.6 92.8 100.3 102.6 102.4 103.0 103.3 108.7 103.1 103.8 103.4 102.9 102.0 104.7 102.3 104.5 102.4 105.4 104.4 108.6 107.7 107.3 105.9 118.4 107.0 105.3 106.1 103.7 103.4 102.8 106.7 110.6 103.2 109.4 112.3 112.9 110.0 111.7 105.7 119.0 108.9 106.7 108.8 107.0 105.8 105.4 110.5 116.9 102.9 112.8 118.9 123.2 113.6 116.3 105.1 127.1 111.0 108.6 110.9 112.8 111.3 108.1 116.1 123.5 104.5 117.2 126.2 126.1 116.7 123.6 106.5 131.1 118.1 114.3 116.2 115.8 114.7 111.8 121.4 130.9 108.7 122.8 131.8 135.2 120.6 129.3 107.2 144.4 114.4 119.3 121.2 122.8 117.5 115.0 128.4 138.8 111.8 129.4 139.1 144.7 125.5 134.5 104.9 151.5 116.3 122.8 129.4 125.7 120.2 119.3 133.5 144.5 117.4 135.2 146.1 147.7 129.1 141.6 105.9 173.0 118.2 125.4 134.4 129.7 120.9 123.4 139.0 149.2 121.5 138.9 153.7 150.5 135.4 150.7 106.8 186.8 122.8 129.8 143.6 134.4 122.4 127.4 141.1 156.2 127.3 143.6 159.7 156.7 138.0 160.3 105.3 202.9 125.2 132.5 148.0 140.9 127.5 129.9 145.0 165.1 132.7 147.7 171.0 162.2 143.2 169.9 105.0 218.6 127.2 136.0 150.5 145.0 129.7 132.7 149.3 172.9 139.2 152.9 175.3 Hourly compensation (national currency basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… See notes at end of table. 51.2 43.8 – 53.7 – 23.1 47.5 39.5 34.6 43.3 22.6 52.4 34.3 23.1 32.9 33.4 Monthly Labor Review • September 2008 129 Current Labor Statistics: International Comparisons 53. Continued– Annual indexes of manufacturing productivity and related measures, 16 economies Measure and economy 1980 1990 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Unit labor costs (national currency basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 87.4 65.9 – 98.0 33.6 57.1 83.0 52.5 60.9 64.5 37.6 89.4 44.4 36.8 54.9 59.8 103.3 96.7 87.3 102.1 62.3 89.9 96.1 91.9 93.7 84.0 85.4 97.0 83.9 76.0 104.8 94.3 106.0 99.5 92.8 107.5 81.2 99.1 105.7 98.9 102.0 97.3 97.5 106.4 90.7 95.1 103.9 96.1 103.9 96.9 91.5 107.9 85.5 100.0 101.2 91.0 99.4 94.6 94.4 101.7 93.4 95.7 96.6 96.0 102.0 98.0 98.4 103.8 94.5 100.9 99.6 92.9 98.5 98.2 95.3 100.4 98.9 96.5 95.8 99.4 98.5 98.0 100.7 99.8 96.4 99.0 94.5 95.7 97.2 96.3 102.7 102.0 104.2 101.4 96.6 102.4 97.4 98.3 100.0 101.3 94.2 97.9 94.7 98.8 93.1 97.3 102.2 103.3 113.2 100.4 94.7 109.2 96.4 96.3 102.4 98.6 85.1 93.9 96.9 99.7 92.1 97.1 104.0 102.8 115.7 98.5 89.4 110.3 97.7 93.8 100.9 93.0 83.8 90.9 95.1 98.1 90.6 95.5 101.4 100.8 118.5 99.0 86.9 109.5 99.0 98.5 104.8 96.2 87.0 92.5 99.1 102.7 91.2 96.0 104.5 104.9 122.2 100.6 93.8 110.4 96.0 100.0 105.0 93.5 87.3 82.2 100.2 106.4 92.8 97.4 108.7 107.7 126.0 103.1 89.1 113.7 96.6 103.6 107.1 85.6 85.7 81.0 100.6 109.0 90.8 96.1 115.3 109.7 120.7 105.6 86.1 113.9 92.9 104.9 111.3 80.8 87.8 78.4 98.3 107.0 91.2 93.2 117.6 107.0 117.6 107.3 79.9 113.0 92.6 106.0 117.6 76.5 88.1 75.7 98.7 113.1 90.4 91.0 119.8 103.9 119.1 110.3 77.8 113.9 94.4 108.1 123.9 74.0 86.9 72.0 98.6 110.9 91.2 88.5 122.6 103.5 122.3 112.7 75.5 116.3 93.9 109.8 127.4 71.8 86.1 67.3 99.1 112.1 91.5 85.7 125.8 103.6 128.3 113.9 77.5 116.2 Unit labor costs (U.S. dollar basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 87.4 76.8 – 47.0 44.6 43.6 87.9 54.1 73.7 53.4 67.7 75.8 58.1 65.0 87.0 89.1 103.3 113.1 87.1 76.6 70.5 91.8 89.1 86.2 88.0 78.2 110.0 89.8 86.6 94.4 118.7 107.8 106.0 105.2 80.6 105.2 81.1 103.0 94.7 88.4 92.1 88.5 95.6 96.6 82.6 94.5 89.4 92.5 103.9 96.7 85.5 114.8 85.3 103.8 93.7 83.1 91.7 87.8 90.4 94.3 85.5 90.5 84.0 94.3 102.0 97.4 93.1 120.2 98.4 104.6 104.7 96.2 101.0 103.2 90.2 105.6 100.8 98.0 90.0 100.5 98.5 96.5 95.7 89.7 81.9 94.5 81.7 84.0 85.2 83.5 93.0 88.1 95.0 87.6 84.7 107.4 97.4 90.4 80.4 84.1 54.1 80.2 80.8 85.5 80.7 83.2 90.8 87.8 96.8 85.1 79.8 116.0 96.4 88.4 84.5 94.3 57.6 79.8 79.2 82.7 76.5 79.6 88.2 83.8 95.7 79.9 72.5 114.3 97.7 86.1 75.0 93.9 59.6 79.9 67.4 70.3 65.2 67.8 74.6 71.2 86.9 69.6 63.6 106.4 99.0 86.7 69.2 86.1 54.2 75.1 68.1 71.5 63.7 66.1 74.5 71.9 87.8 68.6 60.8 101.9 96.0 86.9 72.9 81.2 56.2 65.4 72.7 78.2 68.4 70.8 81.9 77.9 101.9 74.2 61.4 109.5 96.6 100.9 89.3 80.3 57.9 64.6 87.4 96.1 80.2 83.7 104.0 95.0 110.1 91.1 71.5 119.3 92.9 109.9 104.7 81.3 61.7 64.5 93.9 103.7 88.5 89.2 116.5 101.8 112.7 101.6 72.9 132.7 92.6 119.3 114.6 75.6 69.3 64.7 94.3 109.5 87.8 87.1 118.8 98.9 119.4 104.5 69.8 132.9 94.4 130.0 119.3 69.2 73.3 60.8 95.1 108.3 89.3 85.5 122.7 99.5 123.2 107.8 68.7 137.4 93.9 139.5 136.6 66.3 74.6 56.3 104.3 119.5 97.8 90.5 137.5 108.7 141.6 118.9 77.0 149.1 NOTE: Data for Germany for years before 1993 are for the former West Germany. Data for 1993 onward are for unified Germany. Dash indicates data not available. 130 Monthly Labor Review • September 2008 54. Occupational injury and illness rates by industry, 1 United States Industry and type of case Incidence rates per 100 full-time workers 3 2 1989 1 1990 1991 1992 1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 2000 4 2001 4 5 PRIVATE SECTOR 8.6 4.0 78.7 8.8 4.1 84.0 8.4 3.9 86.5 8.9 3.9 93.8 8.5 3.8 – 8.4 3.8 – 8.1 3.6 – 7.4 3.4 – 7.1 3.3 – 6.7 3.1 – 6.3 3.0 – 6.1 3.0 – 5.7 2.8 – Agriculture, forestry, and fishing Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 10.9 5.7 100.9 11.6 5.9 112.2 10.8 5.4 108.3 11.6 5.4 126.9 11.2 5.0 – 10.0 4.7 – 9.7 4.3 – 8.7 3.9 – 8.4 4.1 – 7.9 3.9 – 7.3 3.4 – 7.1 3.6 – 7.3 3.6 – Mining Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 8.5 4.8 137.2 8.3 5.0 119.5 7.4 4.5 129.6 7.3 4.1 204.7 6.8 3.9 – 6.3 3.9 – 6.2 3.9 – 5.4 3.2 – 5.9 3.7 – 4.9 2.9 – 4.4 2.7 – 4.7 3.0 – 4.0 2.4 – Construction Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 14.3 6.8 143.3 14.2 6.7 147.9 13.0 6.1 148.1 13.1 5.8 161.9 12.2 5.5 – 11.8 5.5 – 10.6 4.9 – 9.9 4.5 – 9.5 4.4 – 8.8 4.0 – 8.6 4.2 – 8.3 4.1 – 7.9 4.0 – General building contractors: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 13.9 6.5 137.3 13.4 6.4 137.6 12.0 5.5 132.0 12.2 5.4 142.7 11.5 5.1 – 10.9 5.1 – 9.8 4.4 – 9.0 4.0 – 8.5 3.7 – 8.4 3.9 – 8.0 3.7 – 7.8 3.9 – 6.9 3.5 – Heavy construction, except building: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 13.8 6.5 147.1 13.8 6.3 144.6 12.8 6.0 160.1 12.1 5.4 165.8 11.1 5.1 – 10.2 5.0 – 9.9 4.8 – 9.0 4.3 – 8.7 4.3 – 8.2 4.1 – 7.8 3.8 – 7.6 3.7 – 7.8 4.0 – Special trades contractors: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 14.6 6.9 144.9 14.7 6.9 153.1 13.5 6.3 151.3 13.8 6.1 168.3 12.8 5.8 – 12.5 5.8 – 11.1 5.0 – 10.4 4.8 – 10.0 4.7 – 9.1 4.1 – 8.9 4.4 – 8.6 4.3 – 8.2 4.1 – Manufacturing Total cases ............................…………………………. Lost workday cases..................................................... 13.1 5.8 13.2 5.8 12.7 5.6 12.5 5.4 12.1 5.3 12.2 5.5 11.6 5.3 10.6 4.9 10.3 4.8 9.7 4.7 9.2 4.6 9.0 4.5 8.1 4.1 Lost workdays........………........................................... 113.0 120.7 121.5 124.6 – – – – – – – – – Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 14.1 6.0 116.5 14.2 6.0 123.3 13.6 5.7 122.9 13.4 5.5 126.7 13.1 5.4 – 13.5 5.7 – 12.8 5.6 – 11.6 5.1 – 11.3 5.1 – 10.7 5.0 – 10.1 4.8 – – – – 8.8 4.3 – Lumber and wood products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.4 9.4 177.5 18.1 8.8 172.5 16.8 8.3 172.0 16.3 7.6 165.8 15.9 7.6 – 15.7 7.7 – 14.9 7.0 – 14.2 6.8 – 13.5 6.5 – 13.2 6.8 – 13.0 6.7 – 12.1 6.1 – 10.6 5.5 – Furniture and fixtures: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 16.1 7.2 – 16.9 7.8 – 15.9 7.2 – 14.8 6.6 128.4 14.6 6.5 – 15.0 7.0 – 13.9 6.4 – 12.2 5.4 – 12.0 5.8 – 11.4 5.7 – 11.5 5.9 – 11.2 5.9 – 11.0 5.7 – Stone, clay, and glass products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 15.5 7.4 149.8 15.4 7.3 160.5 14.8 6.8 156.0 13.6 6.1 152.2 13.8 6.3 – 13.2 6.5 – 12.3 5.7 – 12.4 6.0 – 11.8 5.7 – 11.8 6.0 – 10.7 5.4 – 10.4 5.5 – 10.1 5.1 – Primary metal industries: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.7 8.1 168.3 19.0 8.1 180.2 17.7 7.4 169.1 17.5 7.1 175.5 17.0 7.3 – 16.8 7.2 – 16.5 7.2 – 15.0 6.8 – 15.0 7.2 – 14.0 7.0 – 12.9 6.3 – 12.6 6.3 – 10.7 5.3 11.1 Fabricated metal products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.5 7.9 147.6 18.7 7.9 155.7 17.4 7.1 146.6 16.8 6.6 144.0 16.2 6.7 – 16.4 6.7 – 15.8 6.9 – 14.4 6.2 – 14.2 6.4 – 13.9 6.5 – 12.6 6.0 – 11.9 5.5 – 11.1 5.3 – Industrial machinery and equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 12.1 4.8 86.8 12.0 4.7 88.9 11.2 4.4 86.6 11.1 4.2 87.7 11.1 4.2 – 11.6 4.4 – 11.2 4.4 – 9.9 4.0 – 10.0 4.1 – 9.5 4.0 – 8.5 3.7 – 8.2 3.6 – 11.0 6.0 – Electronic and other electrical equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 9.1 3.9 77.5 9.1 3.8 79.4 8.6 3.7 83.0 8.4 3.6 81.2 8.3 3.5 – 8.3 3.6 – 7.6 3.3 – 6.8 3.1 – 6.6 3.1 – 5.9 2.8 – 5.7 2.8 – 5.7 2.9 – 5.0 2.5 – Transportation equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 17.7 6.8 138.6 17.8 6.9 153.7 18.3 7.0 166.1 18.7 7.1 186.6 18.5 7.1 – 19.6 7.8 – 18.6 7.9 – 16.3 7.0 – 15.4 6.6 – 14.6 6.6 – 13.7 6.4 – 13.7 6.3 – 12.6 6.0 – Instruments and related products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 5.6 2.5 55.4 5.9 2.7 57.8 6.0 2.7 64.4 5.9 2.7 65.3 5.6 2.5 – 5.9 2.7 – 5.3 2.4 – 5.1 2.3 – 4.8 2.3 – 4.0 1.9 – 4.0 1.8 – 4.5 2.2 – 4.0 2.0 – Miscellaneous manufacturing industries: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 11.1 5.1 97.6 11.3 5.1 113.1 11.3 5.1 104.0 10.7 5.0 108.2 10.0 4.6 – 9.9 4.5 – 9.1 4.3 – 9.5 4.4 – 8.9 4.2 – 8.1 3.9 – 8.4 4.0 – 7.2 3.6 – 6.4 3.2 – Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 5 Durable goods: See footnotes at end of table. Monthly Labor Review • September 2008 131 Current Labor Statistics: Injury and Illness Data 54. Continued—Occupational injury and illness rates by industry,1 United States Industry and type of case2 Incidence rates per 100 workers 3 1989 1 1990 1991 1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 2000 4 2001 4 1992 Nondurable goods: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 11.6 5.5 107.8 11.7 5.6 116.9 11.5 5.5 119.7 11.3 5.3 121.8 10.7 5.0 – 10.5 5.1 – 9.9 4.9 – 9.2 4.6 – 8.8 4.4 – 8.2 4.3 7.8 4.2 – 7.8 4.2 – 6.8 3.8 – Food and kindred products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 18.5 9.3 174.7 20.0 9.9 202.6 19.5 9.9 207.2 18.8 9.5 211.9 17.6 8.9 – 17.1 9.2 – 16.3 8.7 – 15.0 8.0 – 14.5 8.0 – 13.6 7.5 12.7 7.3 – 12.4 7.3 – 10.9 6.3 – Tobacco products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 8.7 3.4 64.2 7.7 3.2 62.3 6.4 2.8 52.0 6.0 2.4 42.9 5.8 2.3 – 5.3 2.4 – 5.6 2.6 – 6.7 2.8 – 5.9 2.7 – 6.4 3.4 - 5.5 2.2 – 6.2 3.1 – 6.7 4.2 – Textile mill products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 10.3 4.2 81.4 9.6 4.0 85.1 10.1 4.4 88.3 9.9 4.2 87.1 9.7 4.1 – 8.7 4.0 – 8.2 4.1 – 7.8 3.6 – 6.7 3.1 – 7.4 3.4 – 6.4 3.2 – 6.0 3.2 – 5.2 2.7 – Apparel and other textile products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 8.6 3.8 80.5 8.8 3.9 92.1 9.2 4.2 99.9 9.5 4.0 104.6 9.0 3.8 – 8.9 3.9 – 8.2 3.6 – 7.4 3.3 – 7.0 3.1 – 6.2 2.6 - 5.8 2.8 – 6.1 3.0 – 5.0 2.4 – Paper and allied products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 12.7 5.8 132.9 12.1 5.5 124.8 11.2 5.0 122.7 11.0 5.0 125.9 9.9 4.6 – 9.6 4.5 – 8.5 4.2 – 7.9 3.8 – 7.3 3.7 – 7.1 3.7 – 7.0 3.7 – 6.5 3.4 – 6.0 3.2 – Printing and publishing: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 6.9 3.3 63.8 6.9 3.3 69.8 6.7 3.2 74.5 7.3 3.2 74.8 6.9 3.1 – 6.7 3.0 – 6.4 3.0 – 6.0 2.8 – 5.7 2.7 – 5.4 2.8 – 5.0 2.6 – 5.1 2.6 – 4.6 2.4 – Chemicals and allied products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 7.0 3.2 63.4 6.5 3.1 61.6 6.4 3.1 62.4 6.0 2.8 64.2 5.9 2.7 – 5.7 2.8 – 5.5 2.7 – 4.8 2.4 – 4.8 2.3 – 4.2 2.1 – 4.4 2.3 – 4.2 2.2 – 4.0 2.1 – Petroleum and coal products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 6.6 3.3 68.1 6.6 3.1 77.3 6.2 2.9 68.2 5.9 2.8 71.2 5.2 2.5 – 4.7 2.3 – 4.8 2.4 – 4.6 2.5 – 4.3 2.2 – 3.9 1.8 – 4.1 1.8 – 3.7 1.9 – 2.9 1.4 – Rubber and miscellaneous plastics products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 16.2 8.0 147.2 16.2 7.8 151.3 15.1 7.2 150.9 14.5 6.8 153.3 13.9 6.5 – 14.0 6.7 – 12.9 6.5 – 12.3 6.3 – 11.9 5.8 – 11.2 5.8 – 10.1 5.5 – 10.7 5.8 – 8.7 4.8 – Leather and leather products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 13.6 6.5 130.4 12.1 5.9 152.3 12.5 5.9 140.8 12.1 5.4 128.5 12.1 5.5 – 12.0 5.3 – 11.4 4.8 – 10.7 4.5 – 10.6 4.3 – 9.8 4.5 – 10.3 5.0 – 9.0 4.3 – 8.7 4.4 – Transportation and public utilities Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 9.2 5.3 121.5 9.6 5.5 134.1 9.3 5.4 140.0 9.1 5.1 144.0 9.5 5.4 – 9.3 5.5 – 9.1 5.2 – 8.7 5.1 – 8.2 4.8 – 7.3 4.3 – 7.3 4.4 – 6.9 4.3 – 6.9 4.3 – Wholesale and retail trade Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 8.0 3.6 63.5 7.9 3.5 65.6 7.6 3.4 72.0 8.4 3.5 80.1 8.1 3.4 – 7.9 3.4 – 7.5 3.2 – 6.8 2.9 – 6.7 3.0 – 6.5 2.8 – 6.1 2.7 – 5.9 2.7 – 6.6 2.5 – Wholesale trade: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 7.7 4.0 71.9 7.4 3.7 71.5 7.2 3.7 79.2 7.6 3.6 82.4 7.8 3.7 – 7.7 3.8 – 7.5 3.6 – 6.6 3.4 – 6.5 3.2 – 6.5 3.3 – 6.3 3.3 – 5.8 3.1 – 5.3 2.8 – Retail trade: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 8.1 3.4 60.0 8.1 3.4 63.2 7.7 3.3 69.1 8.7 3.4 79.2 8.2 3.3 – 7.9 3.3 – 7.5 3.0 – 6.9 2.8 – 6.8 2.9 – 6.5 2.7 – 6.1 2.5 – 5.9 2.5 – 5.7 2.4 – Finance, insurance, and real estate Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 2.0 .9 17.6 2.4 1.1 27.3 2.4 1.1 24.1 2.9 1.2 32.9 2.9 1.2 – 2.7 1.1 – 2.6 1.0 – 2.4 .9 – 2.2 .9 – .7 .5 – 1.8 .8 – 1.9 .8 – 1.8 .7 – Services Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 5.5 2.7 51.2 6.0 2.8 56.4 6.2 2.8 60.0 7.1 3.0 68.6 6.7 2.8 – 6.5 2.8 – 6.4 2.8 – 6.0 2.6 – 5.6 2.5 – 5.2 2.4 – 4.9 2.2 – 4.9 2.2 – 4.6 2.2 – - - 1 Data for 1989 and subsequent years are based on the Standard Industrial Classification Manual, 1987 Edition. For this reason, they are not strictly comparable with data for the years 1985–88, which were based on the Standard Industrial Classification Manual, 1972 Edition, 1977 Supplement. N = number of injuries and illnesses or lost workdays; EH = total hours worked by all employees during the calendar year; and 200,000 = base for 100 full-time equivalent workers (working 40 hours per week, 50 weeks per year). 2 Beginning with the 1992 survey, the annual survey measures only nonfatal injuries and illnesses, while past surveys covered both fatal and nonfatal incidents. To better address fatalities, a basic element of workplace safety, BLS implemented the Census of Fatal Occupational Injuries. 4 Beginning with the 1993 survey, lost workday estimates will not be generated. As of 1992, BLS began generating percent distributions and the median number of days away from work by industry and for groups of workers sustaining similar work disabilities. 5 Excludes farms with fewer than 11 employees since 1976. 3 The incidence rates represent the number of injuries and illnesses or lost workdays per 100 full-time workers and were calculated as (N/EH) X 200,000, where: 132 Monthly Labor Review • September 2008 NOTE: Dash indicates data not available. 55. Fatal occupational injuries by event or exposure, 1996-2005 20053 1996-2000 (average) 2001-2005 (average)2 All events ............................................................... 6,094 5,704 5,734 100 Transportation incidents ................................................ Highway ........................................................................ Collision between vehicles, mobile equipment ......... Moving in same direction ...................................... Moving in opposite directions, oncoming .............. Moving in intersection ........................................... Vehicle struck stationary object or equipment on side of road ............................................................. Noncollision ............................................................... Jack-knifed or overturned--no collision ................. Nonhighway (farm, industrial premises) ........................ Noncollision accident ................................................ Overturned ............................................................ Worker struck by vehicle, mobile equipment ................ Worker struck by vehicle, mobile equipment in roadway .................................................................. Worker struck by vehicle, mobile equipment in parking lot or non-road area .................................... Water vehicle ................................................................ Aircraft ........................................................................... 2,608 1,408 685 117 247 151 2,451 1,394 686 151 254 137 2,493 1,437 718 175 265 134 43 25 13 3 5 2 264 372 298 378 321 212 376 310 335 274 335 277 175 369 345 318 273 340 281 182 391 6 6 5 6 5 3 7 129 136 140 2 171 105 263 166 82 206 176 88 149 3 2 3 Assaults and violent acts ............................................... Homicides ..................................................................... Shooting .................................................................... Suicide, self-inflicted injury ............................................ 1,015 766 617 216 850 602 465 207 792 567 441 180 14 10 8 3 Contact with objects and equipment ............................ Struck by object ............................................................ Struck by falling object .............................................. Struck by rolling, sliding objects on floor or ground level ......................................................................... Caught in or compressed by equipment or objects ....... Caught in running equipment or machinery .............. Caught in or crushed in collapsing materials ................ 1,005 567 364 952 560 345 1,005 607 385 18 11 7 77 293 157 128 89 256 128 118 94 278 121 109 2 5 2 2 Falls .................................................................................. Fall to lower level .......................................................... Fall from ladder ......................................................... Fall from roof ............................................................. Fall to lower level, n.e.c. ........................................... 714 636 106 153 117 763 669 125 154 123 770 664 129 160 117 13 12 2 3 2 Exposure to harmful substances or environments ..... Contact with electric current .......................................... Contact with overhead power lines ........................... Exposure to caustic, noxious, or allergenic substances Oxygen deficiency ......................................................... 535 290 132 112 92 498 265 118 114 74 501 251 112 136 59 9 4 2 2 1 Fires and explosions ...................................................... Fires--unintended or uncontrolled ................................. Explosion ...................................................................... 196 103 92 174 95 78 159 93 65 3 2 1 Event or exposure1 Number Percent 1 Based on the 1992 BLS Occupational Injury and Illness Classification Manual. 2 Excludes fatalities from the Sept. 11, 2001, terrorist attacks. 3 The BLS news release of August 10, 2006, reported a total of 5,702 fatal work injuries for calendar year 2005. Since then, an additional 32 job-related fatalities were identified, bringing the total job-related fatality count for 2005 to 5,734. NOTE: Totals for all years are revised and final. Totals for major categories may include subcategories not shown separately. Dashes indicate no data reported or data that do not meet publication criteria. N.e.c. means "not elsewhere classified." SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, in cooperation with State, New York City, District of Columbia, and Federal agencies, Census of Fatal Occupational Injuries. Monthly Labor Review • September 2008 133 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS BLS Introduces New Employment Cost Indexes for 14 Metropolitan Areas by Albert E. Schwenk Bureau of Labor Statistics Originally Posted: September 24, 2008 This article presents a first look at new estimates from the National Compensation Survey (NCS): Employment Cost Index (ECI) 12-month change in total compensation and in wages and salaries for private industry for 14 selected metropolitan areas. The article also provides a description of how the areas were selected and an overview of what the data show. For the year ended June 2008, BLS reported that across the Nation the cost of compensation (wages, salaries, and benefits) had risen 3.0 percent in private industry.1 Among 14 selected metropolitan areas, however, the increases ranged from 1.5 percent in Detroit to 4.4 percent in Philadelphia. The ECI is a Principal Federal Economic Indicator of the economy of the United States.2 National estimates on wage and salary trends in private industry were developed in the early 1970s to provide an index of the change in the cost of labor as a factor of production.3 In an effort to make the index more useful, BLS increased the number of published series over time, broadening the scope of ECI national estimates in the early 1980s to include State and local government and all civilian workers as well as estimates of benefits and total compensation.4 The ECI also expanded its industry detail in serviceproducing industries such as hospitals and nursing homes in the 1980s. In addition, in March 2006, when the ECI switched to the North American Industry Classification System (NAICS) and the Standard Occupational Classification (SOC) system, BLS began publishing employment cost data for new industry and occupational categories.5 From the beginning, BLS has sought to provide ECI data users with greater geographic detail than the national estimates. Data for the four geographic regions defined by the Census Bureau--Northeast, South, Midwest, and West--have been published since the 1970s. In 2006, at the same time that it switched to NAICS and SOC, the ECI expanded geographic detail to include nine census divisions within the census regions.6 Still, users of ECI data requested even greater geographic detail. In response, BLS has explored the possibility of publishing measures of change in labor costs for specific Metropolitan Statistical Areas (MSAs) or Consolidated Statistical Areas (CSAs).7 Selection Of Areas To Publish As a starting point, using employment data from the 2000 Census of Population, the NCS identified the largest metropolitan areas in the United States. The next step in the selection process was to determine whether data for each of these areas met BLS publication standards, based on a review of sample sizes, standard errors,8 and historical data on rates of change in total compensation and in wages and salaries. After this review, it was determined that estimates for the 12-month changes in compensation and in wages and salaries would be published for the following 14 areas: Atlanta-Sandy Springs-Gainesville, GA-AL CSA; Boston-WorcesterManchester, MA-NH CSA; Chicago-Naperville-Michigan City, IL-IN-WI CSA; Dallas-Forth Worth, TX CSA; Detroit-WarrenFlint, MI CSA; Houston-Baytown-Huntsville, TX CSA; Los Angeles-Long Beach-Riverside, CA CSA; Miami-Fort LauderdalePompano Beach, FL MSA; Minneapolis-St. Paul-St. Cloud, MN-WI CSA; New York-Newark-Bridgeport, NY-NJ-CT-PA CSA; Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA; Phoenix-Mesa-Scottsdale, AZ MSA; San Jose-San Francisco-Oakland, CA CSA; and Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA.9 (In this article, shortened titles are used to refer to particular metropolitan areas, but in all cases the full CSA or MSA is intended.) Weighting Data For ECI Locality Estimates The estimates of locality ECI 12-month changes were constructed in essentially the same manner as are the national ECI series of 12-month changes.10 Like the national series, the locality ECI series use fixed employment weights. The fixed industry-occupation employment weights used to construct each localitys 12-month change estimates were based on Page 1 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS employment for the locality, rather than on national total employment. Because the relative weight of each industryoccupation cell used to estimate rates of change in total compensation and wages and salaries differs across areas, variation among localities in rates of wage or compensation change reflects both differences in industry and occupation composition of the work force and differences in rates of change for a fixed market basket of labor services.11 Review Of The Estimates Table 1 shows 12-month changes in total compensation costs by quarter for the United States as a whole and for the selected 14 metropolitan areas, as well as the associated standard errors for total compensation; table 2 shows the same for the cost of wages and salaries. Table 1. Employment Cost Index, private industry workers, compensation, United States and selected metropolitan areas (Not seasonally adjusted) Compensation Metropolitan area and year 12-month percent changes for period ended-Mar. June Sep. 12-month standard errors for period ended-- Dec. Mar. June Sep. Dec. United States 2006 2.6 2.8 3.0 3.2 (-) (-) (-) 0.2 2007 3.2 3.1 3.1 3.0 0.2 0.2 0.2 0.2 2008 3.2 3.0 (-) (-) 0.2 0.2 (-) (-) Atlanta-Sandy Springs-Gainesville, GA-AL CSA 2006 (-) (-) (-) 2.5 (-) (-) (-) 0.6 2007 3.7 4.0 3.6 3.3 0.5 0.3 0.3 0.3 3.1 1.9 (-) (-) 0.3 0.5 (-) (-) 2008 Boston-Worcester-Manchester, MA-NH CSA 2006 (-) (-) (-) 3.6 (-) (-) (-) 0.8 2007 3.5 3.5 3.8 3.2 0.7 0.6 0.6 0.6 2008 3.0 2.5 (-) (-) 0.7 0.2 (-) (-) Chicago-Naperville-Michigan City, IL-IN-WI CSA 2006 (-) (-) (-) 3.6 (-) (-) (-) 0.6 2007 2.9 2.6 2.3 2.5 0.5 0.6 0.5 0.5 2008 2.9 3.4 (-) (-) 0.5 0.3 (-) (-) Dallas-Fort Worth, TX CSA 2006 (-) (-) (-) 3.1 (-) (-) (-) 0.7 2007 3.3 2.6 2.3 2.6 0.6 0.5 0.2 0.4 2008 3.3 2.7 (-) (-) 0.4 0.4 (-) (-) 2006 (-) (-) (-) 1.8 (-) (-) (-) 0.5 2007 2.0 1.7 1.2 0.9 0.4 0.5 0.4 0.4 2008 2.2 1.5 (-) (-) 0.3 0.3 (-) (-) Detroit-Warren-Flint, MI CSA Houston-Baytown-Huntsville, TX CSA 2006 (-) (-) (-) 3.8 (-) (-) (-) 0.3 2007 3.1 3.0 3.3 2.6 0.3 0.3 0.7 0.7 2008 2.9 2.4 (-) (-) 0.5 0.2 (-) (-) Dashes indicate no data available. Page 2 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Compensation Metropolitan area and year 12-month percent changes for period ended-Mar. June Sep. 12-month standard errors for period ended-- Dec. Mar. June Sep. Dec. Los Angeles-Long Beach-Riverside, CA CSA 2006 (-) (-) (-) 3.1 (-) (-) (-) 0.4 2007 3.8 3.8 3.9 3.6 0.3 0.3 0.5 0.6 2008 3.5 2.6 (-) (-) 0.7 0.6 (-) (-) 2006 (-) (-) (-) 5.7 (-) (-) (-) 0.3 2007 5.8 5.5 3.7 3.8 0.3 0.6 0.4 0.6 2008 4.4 3.2 (-) (-) 0.3 0.5 (-) (-) Miami-Fort Lauderdale-Pompano Beach, FL MSA Minneapolis-St.Paul-St.Cloud, MN-WI CSA 2006 (-) (-) (-) 1.0 (-) (-) (-) 0.2 2007 2.5 2.1 2.3 2.3 0.3 0.3 0.3 0.3 2008 2.5 2.5 (-) (-) 0.3 0.2 (-) (-) 2006 (-) (-) (-) 3.3 (-) (-) (-) 0.4 2007 3.2 3.4 3.4 3.5 0.2 0.3 0.3 0.3 2008 3.2 3.0 (-) (-) 0.5 0.4 (-) (-) New York-Newark-Bridgeport, NY-NJ-CT-PA CSA Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA 2006 (-) (-) (-) 4.2 (-) (-) (-) 0.3 2007 3.0 3.0 3.1 3.0 0.3 0.3 0.4 0.4 2008 3.8 4.4 (-) (-) 0.3 0.8 (-) (-) Phoenix-Mesa-Scottsdale, AZ MSA 2006 (-) (-) (-) 1.7 (-) (-) (-) 1.5 2007 4.7 3.8 4.0 3.6 1.9 0.5 0.8 1.4 2008 0.5 3.6 (-) (-) 1.7 0.8 (-) (-) San Jose-San Francisco-Oakland, CA CSA 2006 (-) (-) (-) 4.6 (-) (-) (-) 0.4 2007 4.7 3.2 3.4 3.8 0.4 0.7 0.5 0.7 2008 3.7 3.6 (-) (-) 0.5 0.3 (-) (-) Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA 2006 (-) (-) (-) 3.8 (-) (-) (-) 0.3 2007 3.4 3.6 3.2 2.7 0.3 0.3 0.2 0.3 2008 3.1 2.7 (-) (-) 0.3 0.5 (-) (-) Dashes indicate no data available. Page 3 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Table 2. Employment Cost Index, private industry workers, wages and salaries, United States and selected metropolitan areas (Not seasonally adjusted) Wages and salaries Metropolitan area and year 12-month percent changes for period ended-Mar. June Sep. 12-month standard errors for period ended-- Dec. Mar. June Sep. Dec. United States 2006 2.4 2.8 3.0 3.2 (-) (-) (-) 0.1 2007 3.6 3.3 3.4 3.3 0.2 0.2 0.2 0.2 2008 3.2 3.1 (-) (-) 0.2 0.2 (-) (-) Atlanta-Sandy Springs-Gainesville, GA-AL CSA 2006 (-) (-) (-) 3.0 (-) (-) (-) 0.6 2007 3.3 3.6 3.2 2.7 0.5 0.2 0.4 0.5 2008 2.8 2.0 (-) (-) 0.3 0.4 (-) (-) Boston-Worcester-Manchester, MA-NH CSA 2006 (-) (-) (-) 4.0 (-) (-) (-) 0.4 2007 3.8 3.8 4.0 3.6 0.5 0.6 0.7 0.7 3.2 2.7 (-) (-) 0.8 0.2 (-) (-) 2008 Chicago-Naperville-Michigan City, IL-IN-WI CSA 2006 (-) (-) (-) 2.6 (-) (-) (-) 0.6 2007 3.8 3.0 3.1 3.6 0.5 0.9 0.6 0.7 2008 2.8 3.5 (-) (-) 0.7 0.2 (-) (-) 2006 (-) (-) (-) 3.3 (-) (-) (-) 0.6 2007 3.6 2.9 2.1 2.4 0.3 0.3 0.3 0.4 2008 3.0 2.5 (-) (-) 0.4 0.5 (-) (-) Dallas-Fort Worth, TX CSA Detroit-Warren-Flint, MI CSA 2006 (-) (-) (-) 1.5 (-) (-) (-) 0.5 2007 2.6 2.3 1.9 1.0 0.3 0.2 0.3 0.3 2008 1.6 1.8 (-) (-) 0.3 0.2 (-) (-) 2006 (-) (-) (-) 3.8 (-) (-) (-) 0.4 2007 3.3 3.6 4.2 3.2 0.5 0.3 0.7 0.4 3.6 2.6 (-) (-) 0.4 0.4 (-) (-) Houston-Baytown-Huntsville, TX CSA 2008 Los Angeles-Long Beach-Riverside, CA CSA 2006 (-) (-) (-) 3.8 (-) (-) (-) 0.3 2007 4.2 3.6 4.3 3.7 0.2 0.3 0.5 0.7 2008 3.0 2.5 (-) (-) 0.9 0.8 (-) (-) Miami-Fort Lauderdale-Pompano Beach, FL MSA 2006 (-) (-) (-) 5.6 (-) (-) (-) 0.4 2007 6.0 5.6 3.5 3.1 0.4 0.7 0.5 0.5 3.8 4.6 (-) (-) 0.2 0.6 (-) (-) (-) (-) (-) 0.2 2008 Minneapolis-St.Paul-St.Cloud, MN-WI CSA 2006 (-) (-) (-) Dashes indicate no data available. Page 4 1.1 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Wages and salaries Metropolitan area and year 12-month percent changes for period ended-Mar. 2007 3.4 2008 1.7 June Sep. Dec. 12-month standard errors for period ended-Mar. June Sep. Dec. 2.5 2.3 2.1 0.4 0.3 0.2 0.3 2.3 (-) (-) 0.3 0.3 (-) (-) New York-Newark-Bridgeport, NY-NJ-CT-PA CSA 2006 (-) (-) (-) 3.2 (-) (-) (-) 0.5 2007 3.2 3.3 3.1 3.5 0.2 0.4 0.4 0.5 2008 3.0 3.0 (-) (-) 0.4 0.3 (-) (-) Philadelphia-Camden-Vineland, PA-NJ-DE-MD CSA 2006 (-) (-) (-) 3.8 (-) (-) (-) 0.4 2007 3.5 3.6 3.8 3.5 0.3 0.3 0.4 0.4 2008 3.7 4.6 (-) (-) 0.3 1.0 (-) (-) Phoenix-Mesa-Scottsdale, AZ MSA 2006 (-) (-) (-) 1.5 (-) (-) (-) 1.7 2007 5.2 3.6 4.2 3.6 2.2 0.5 1.1 1.9 2008 -0.2 3.7 (-) (-) 2.1 0.8 (-) (-) San Jose-San Francisco-Oakland, CA CSA 2006 (-) (-) (-) 4.2 (-) (-) (-) 0.7 2007 5.1 3.3 3.9 4.5 0.5 0.8 0.5 0.7 2008 3.5 3.6 (-) (-) 0.5 0.4 (-) (-) 2006 (-) (-) (-) 3.9 (-) (-) (-) 0.3 2007 3.4 3.8 3.5 2.8 0.3 0.3 0.2 0.2 2008 3.1 2.7 (-) (-) 0.3 0.5 (-) (-) Washington-Baltimore-Northern Virginia, DC-MD-VA-WV CSA Dashes indicate no data available. Several things are evident from these two tables. First, for most areas, both total compensation and wage and salary percent changes vary more from period to period than they do for the Nation as a whole. Second, the standard errors for the Nation as a whole are consistently lower than for any particular area. The lower standard errors probably reflect the larger sample size. Those smaller standard errors may also help explain the smaller variability from period to period in the rates of change for the Nation as a whole. By area, the largest standard errors for both total compensation and wages and salaries are from the Phoenix metropolitan area, due largely to the impact of incentive workers in the area--when such workers are excluded, the standard errors drop sharply. (Incentive workers are those whose wages are at least partially based on productivity payments such as piece rates, commissions, and production bonuses.) Table 3 presents average annual percent changes in total compensation costs and in wages and salaries over the entire period from December 2005 to June 2008, sorted in descending order of the size of the compensation cost change. Table 3. Average annual percent changes in total compensation costs and in wages and salaries, December 2005-June 2008 Metropolitan area Total compensation costs Wages and salaries Miami-Fort Lauderdale-Pompano Beach, FL 4.5 4.8 San Jose-San Francisco-Oakland, CA 4.2 4.2 Page 5 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Metropolitan area Total compensation costs Wages and salaries Philadelphia-Camden-Vineland, PA-NJ-DE-MD 3.8 3.8 Washington-Baltimore-Northern Virginia, DC-MD-VA-WV 3.4 3.4 New York-Newark-Bridgeport, NY-NJ-CT-PA 3.4 3.3 Phoenix-Mesa-Scottsdale, AZ 3.2 3.0 Chicago-Naperville-Michigan City, IL-IN-WI 3.1 3.1 Houston-Baytown-Huntsville, TX 3.1 3.4 Los Angeles-Long Beach-Riverside, CA 3.1 3.4 United States 3.1 3.3 Boston-Worcester-Manchester, MA-NH 3.1 3.4 Dallas-Forth Worth, TX 2.8 2.8 Atlanta-Sandy Springs-Gainesville, GA-AL 2.6 2.7 Minneapolis-St. Paul-St. Cloud, MN-WI 2.0 2.0 Detroit-Warren-Flint, MI 1.5 1.7 The magnitude of the changes during particular time periods depends on a number of factors, including initial total compensation cost levels, industry and occupational composition of the work force, and economic conditions. As table 3 shows, the largest average annual percent increases in total compensation costs were in Miami, San Jose-San Francisco, and Philadelphia. This relationship holds for wages and salaries as well as for total compensation costs. In contrast, the smallest increases were in Dallas, Atlanta, Minneapolis, and Detroit. These areas also had the smallest wage and salary increases. Table 4 shows percent changes in total compensation costs and in wages and salaries for the United States as a whole and for 14 metropolitan areas for three periods: December 2005 to December 2006, December 2006 to December 2007, and December 2007 to June 2008. Table 4. Measures of change in total compensation cost and wage and salary changes over selected time periods, for the United States and by geographic region, industry division, and locality. Percent change over selected time periods Area Total compensation cost Wages and salaries Dec. 2005Dec. 2006 Dec. 2006Dec. 2007 Dec. 2007June 2008 Dec. 2005Dec. 2006 Dec. 2006Dec. 2007 Dec. 2007June 2008 United States 3.2 3.0 1.6 3.2 3.3 1.7 Northeast 3.3 3.4 1.2 3.1 3.4 1.5 3.1 2.9 0.9 3.1 3.1 1.2 3.6 3.2 0.9 4.0 3.6 1.0 3.3 3.7 1.4 3.1 3.5 1.6 New York-Newark-Bridgeport, NY-NJ-CT-PA 3.3 3.5 1.6 3.2 3.5 1.6 Philadelphia-Camden-Vineland, PA-NJ-DE-MD 4.2 3.0 2.3 3.8 3.5 2.2 3.5 3.1 1.7 3.6 3.3 2.0 3.8 3.4 1.7 3.9 3.5 1.9 New England Boston-Worcester-Manchester, MA-NH Middle Atlantic South South Atlantic Page 6 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Percent change over selected time periods Area Total compensation cost Wages and salaries Dec. 2005Dec. 2006 Dec. 2006Dec. 2007 Dec. 2007June 2008 Dec. 2005Dec. 2006 Dec. 2006Dec. 2007 Dec. 2007June 2008 Washington-BaltimoreNorthern Virginia, DC-MD-VAWV 3.8 2.7 2.0 3.9 2.8 1.8 Atlanta-Sandy SpringsGainesville, GA-AL 2.5 3.3 0.8 3.0 2.7 0.9 Miami-Fort LauderdalePompano Beach, FL 5.7 3.8 1.6 5.6 3.1 3.3 East South Central 2.3 3.0 1.7 3.1 3.1 1.5 West South Central 3.4 2.6 2.0 3.4 3.1 2.1 Dallas-Forth Worth, TX 3.1 2.6 1.3 3.3 2.4 1.3 Houston-Baytown-Huntsville, TX 3.8 2.6 1.4 3.8 3.2 1.6 2.8 2.4 1.6 2.6 2.9 1.8 2.8 2.1 1.4 2.5 2.7 1.6 Detroit-Warren-Flint, MI 1.8 0.9 1.2 1.5 1.0 1.7 Chicago-Naperville-Michigan City, IL-IN-WI 3.6 2.5 1.8 2.6 3.6 1.5 2.7 3.1 2.4 2.7 3.5 2.4 1.0 2.3 1.6 1.1 2.1 1.7 3.0 3.4 1.8 3.2 3.7 1.8 3.1 4.3 1.8 3.2 4.5 1.9 1.7 3.6 2.8 1.5 3.6 2.5 Midwest East North Central West North Central Minneapolis-St. Paul-St. Cloud, MN-WI West Mountain Phoenix-Mesa-Scottsdale, AZ Pacific 3.0 3.0 1.9 3.3 3.4 1.7 Los Angeles-Long BeachRiverside, CA 3.1 3.6 1.1 3.8 3.7 1.0 San Jose-San FranciscoOakland, CA 4.6 3.8 2.1 4.2 4.5 1.7 To provide some perspective, table 4 also shows data for the four census regions and nine census divisions.12 The estimates by census region and census division are of course affected by total compensation cost changes in metropolitan areas located within those regions and divisions. In general, the larger the proportion of region or division employment accounted for by an area, the greater impact that area will have on region or division estimates. As table 4 shows, estimates by area were generally consistent with the estimates for the associated census divisions and geographic regions. One strong exception to the general pattern is Minneapolis, a metropolitan area in which both wage and salary and total compensation cost increases were substantially lower than the increase for the West North Central region of which it is a part. Information on the future publication of locality employment cost data will be announced in the next ECI news release, scheduled for 8:30 a.m., EDT, October 31, 2008; the news release will be posted on the Internet at www.bls.gov/ncs/ect. Albert E. Schwenk Senior Labor Economist, Division of Compensation Data Estimation, Office of Compensation and Working Conditions, Bureau of Labor Statistics. Telephone: (202) 691-6203; E-mail: Schwenk.Albert@bls.gov. Page 7 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Notes 1 In the ECI, total compensation includes wages and salaries plus the employer cost for 18 individual employee benefits. The following kinds of benefits are covered by the ECI: paid leave, such as vacations, holidays, sick leave, and personal leave; supplemental pay, such as premium pay for work in addition to the regular work schedule (overtime, weekends, and holidays), shift differentials, and nonproduction bonuses (such as year-end, referral, and attendance bonuses); insurance benefits, such as life, health, short-term disability, and long-term disability insurance; retirement and savings benefits (defined benefit and defined contribution plans); and legally required benefits (Social Security, Medicare, Federal and State unemployment insurance, and workers compensation). 2 For more on the Principal Federal Economic Indicators, see Federal Register, Sept. 25, 1985, available on the Internet at http:// www.bea.gov/about/pdf/federalregister09251985.pdf. 3 For a more complete description of the ECI, see John W. Ruser, "Employment Cost Index: What is it?," Monthly Labor Review, September 2001, pp. 3-16; available on the Internet at http://www.bls.gov/opub/mlr/2001/09/art1full.pdf. 4 In the National Compensation Survey (NCS), the civilian sector includes workers in private industry and in State and local government. This excludes Federal government, agricultural, and household workers. 5 For more on the history of the ECI since it was introduced in December 1975, see Fehmida Sleemi, "Employment Cost Index publication plans," Monthly Labor Review, April 2006, pp. 6-11; available on the Internet at http://www.bls.gov/opub/mlr/2006/04/art2full.pdf. 6 The New England and Middle Atlantic divisions are in the Northeast region; the South Atlantic, East South Central, and West South Central divisions are in the South region; East North Central and West North Central divisions are in the Midwest region; and the Mountain and Pacific divisions are in the West. The census divisions comprise the States as follows: the New England division consists of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont; the Middle Atlantic division consists of New Jersey, New York, and Pennsylvania; the South Atlantic division consists of Delaware, the District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, and West Virginia; the East South Central division consists of Alabama, Kentucky, Mississippi, and Tennessee; the West South Central: division consists of Arkansas, Louisiana, Oklahoma, and Texas; the East North Central division consists of Illinois, Indiana, Michigan, Ohio, and Wisconsin; the West North Central division consists of Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota; the Mountain division consists of Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming; and the Pacific division consists of Alaska, California, Hawaii, Oregon, and Washington. Metropolitan areas are sometimes located in more than one State, and some of those States are located in different census divisions, in which case parts of a metropolitan area may be assigned to more than one census division. 7 Experimental data for these new series were published in Michael K. Lettau and Christopher J. Guciardo, "Experimental Estimates of Compensation Levels and Trends for Workers in the 15 Largest Metropolitan Areas, 2004-05," Compensation and Working Conditions Online, September 17, 2007, on the Internet at http://www.bls.gov/opub/cwc/cm20070912ar01p1.htm. The present article presents data only on compensation cost trends by metropolitan area, not compensation cost levels. 8 For a discussion of standard errors for the ECI, see Karen OConor and William Wong, "Measuring the Precision of the Employment Cost Index," Monthly Labor Review, March 1989, pp. 29-36, on the Internet at http://www.bls.gov/opub/mlr/1989/03/rpt1full.pdf. 9 Note that some of these areas are Consolidated Statistical Areas (CSAs) and others are Metropolitan Statistical Areas (MSAs). The NCS is in its second year of a 6-year transition from a sample of areas based on the December 1993 Office of Management and Budget (OMB) area definitions to a new sample of areas based on the December 2003 area definitions. The NCS is phasing in new metropolitan and micropolitan areas as defined by OMB and county clusters defined specifically for the NCS; at the same time, some areas under the December 1993 OMB definitions are being phased out of the sample. For more information on metropolitan area definitions, visit the U.S. Census Bureaus Metropolitan and Micropolitan Statistical Areas page on the Internet at http://www.census.gov/population/www/metroareas/metrodef.html. 10 For a more complete description of how the estimates for the ECI and other NCS products are computed, see "National Compensation Measures," BLS Handbook of Methods, ch. 8, on the Internet at http://www.bls.gov/opub/hom/homch8_a.htm. 11 Note that in estimating compensation cost changes by census region and census division, fixed weights are not used. Rather, the fixed employment weights by industry and occupation are reallocated among the census region and division series each quarter based on the current ECI sample. For a discussion of the alternative ways of constructing ECIs, see Donald G. Wood, "Estimation procedures for the Employment Cost Index," Monthly Labor Review, May 1982, pp. 40-42, on the Internet at http://www.bls.gov/opub/mlr/1982/05/rpt3full.pdf. 12 As noted previously, the regions and census divisions are defined by State, while metropolitan areas often span more than one State. For table 4, the metropolitan areas were organized with the region or census division where most of its employment was found. U.S. Bureau of Labor Statistics | Division of Information and Marketing Services, PSB Suite 2850, 2 Massachusetts Avenue, NE Washington, DC 20212-0001 | www.bls.gov/OPUB | Telephone: 1-202-691-5200 | Contact Us Page 8 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Major Union Mergers, Alliances, and Disaffiliations, 1995-2007 by Elizabeth A. Ashack Bureau of Labor Statistics Originally Posted: September 24, 2008 U.S. labor unions have made moves toward maintaining their membership base through mergers that are still occurring, although at a slower pace than in past decades. Over the period from 1995 to 2007, union membership in the United States declined by about 4.2 percent, from approximately 16.4 million members to 15.7 million members.1 During the same period, the level of employment rose by about 17 percent--from 117 million in 1995 to 138 million in 2007.2 As a result, the percentage of U.S. workers represented by unions has declined, as well as the absolute number of union workers. These declines in membership have prompted union organizations to consider union mergers as a strategy for improving their bargaining power.3 This article summarizes the union mergers, alliances, and disaffiliations that have occurred since 1995.4 Types Of Mergers Over the years, the American Federation of Labor and Congress of Industrial Organizations (AFL-CIO) has encouraged and actively promoted mergers, stressing that mergers should involve unions representing workers in the same or related industries in order to build union power and conserve resources, while at the same time benefiting from the increased economy of scale.5 For this article, union mergers are grouped into three types: • Mergers occurring among unions already affiliated with the AFL-CIO • An independent union merging with an AFL-CIO union, and • Two or more independent unions merging The AFL-CIO has also maintained that union mergers must be voluntary and subject to the democratic processes of the unions involved. Mergers From 1995 to 2007, there were 31 union mergers in the United States.6 Twenty-two of these mergers were among AFL-CIO affiliates, 6 occurred between the AFL-CIO and independent unions, and 3 mergers were among two or more independent unions. In terms of membership, the largest merger occurred in 2005, when the Paper, Allied-Industrial, Chemical and Energy Workers International Union (PACE) merged with the United Steelworkers of America (USWA). The merger increased the size of the USWA to 860,000 members, making it the largest industrial union in the United States. In 2004, another merger of two major unions took place, uniting the Union of Needletrades, Industrial and Textile Employees (UNITE) and the Hotel Employees and Restaurant Employees International Union (HERE), forming UNITE HERE, which has a combined membership of 440,000 workers. (See exhibit.) Disaffiliations And Strategic Alliances During the 1995-2007 period, there were nine major union disaffiliations (splits) from the AFL-CIO. The first major union disaffiliation occurred in 2001, when the United Brotherhood of Carpenters (UBC) severed its relationship with the AFL-CIO. Then, in 2003, the International Union of Journeymen, Horseshoers, and Allied Trades disaffiliated with the AFL-CIO. In 2005, six of the largest unions joined with the United Brotherhood of Carpenters (UBC) in disaffiliating with the AFL-CIO and created a strategic alliance called the Change to Win Federation.7 The six disaffiliated unions were the United Food and Commercial Workers Union (UFCW), the International Brotherhood of Teamsters (IBT), the Laborers International Union (LIUNA), UNITE HERE, the United Farm Workers (UFW), and the Service Employees International Union (SEIU). The Page 1 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Change to Win Federation states that it is conducting campaigns to increase union membership in each of the affiliated unions core industries in order to rebuild worker power and unite millions in the growth industries of the 21st century.8 In 2006, the International Union of Operating Engineers (IUOE) disaffiliated from the AFL-CIO's Building and Construction Trades Department (BCTD) and joined with the following unions to form a strategic alliance called the National Construction Alliance (NCA)9: the Laborers International Union of North America (LIUNA), the United Brotherhood of Carpenters (UBC), International Association of Bridge, Structural, Ornamental, and Reinforcing Iron Workers (BSOIW), and the International Union of Bricklayers and Allied Craftworkers (BAC). The NCA represents more than 1.8 million union workers. Another notable alliance that formed during the 1995-2007 period is the Merchant Officers Labor Alliance (MOLA), an agreement reached in 2007 between the International Organization of Masters, Mates, and Pilots and the Marine Engineers Beneficial Association (MEBA).10 Similarly, in 2005, the Communication Workers of America (CWA) and the International Brotherhood of Teamsters (IBT) formed a joint alliance of passenger service workers at U.S. Airways. Union Merger Activity, 1956-2007 The table that follows summarizes the three types of mergers and their yearly distribution for the period from 1956--the year following the merger of the American Federation of Labor (AFL) and the Congress of Industrial Organizations (CIO)--to 2007. The table shows that 48 mergers occurred during the two decades following the AFL-CIO amalgamation (1956-75), averaging about 2.4 a year. The next decade (1976-85) marked the busiest activity period with 45 mergers, or about 4.5 a year. Merger activity slowed down slightly from 1986 to 1994, with a total of 40 mergers or an average of 4.4 per year. During the most recent period (1995-2007), there were only 31 mergers or about 2.4 per year. In the recent period, the highest level of union merger activity occurred in 2003, when there were 6 mergers; the lowest number occurred in 1997, when there was 1 merger. Table. Union mergers, 1956–2007 Year Total: 1956-2007 Total mergers AFL-CIO only AFL-CIO and independent Independent only 164 92 57 15 2007 2 0 2 0 2006 2 2 0 0 2005 2 2 0 0 2004 2 2 0 0 2003 6 3 0 3 2002 2 0 2 0 2001 2 1 1 0 2000 4 4 0 0 1999 2 2 0 0 1998 2 2 0 0 1997 1 1 0 0 1996 2 1 1 0 1995 2 2 0 0 1994 5 4 1 0 1993 7 2 3 2 1992 5 3 2 0 1991 5 2 3 0 1990 1 0 1 0 1989 5 4 1 0 Page 2 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Year Total mergers AFL-CIO only AFL-CIO and independent Independent only 1988 4 3 1 0 1987 3 1 2 0 1986 5 3 2 0 1985 6 2 3 1 1984 5 2 3 0 1983 5 2 3 0 1982 6 3 3 0 1981 3 2 1 0 1980 6 4 1 1 1979 5 3 2 0 1978 3 2 1 0 1977 3 2 0 1 1976 3 2 1 0 1975 3 1 1 1 1974 1 1 0 0 1973 2 1 1 0 1972 5 3 2 0 1971 3 2 1 0 1970 1 0 1 0 1969 6 2 4 0 1968 4 3 0 1 1967 1 0 1 0 1966 1 0 0 1 1965 1 1 0 0 1964 1 0 1 0 1963 0 0 0 0 1962 3 0 1 2 1961 3 2 1 0 1960 4 1 2 1 1959 3 2 1 0 1958 1 1 0 0 1957 2 1 0 1 1956 3 3 0 0 Exhibit. Chronology of major union mergers, 1995-2007 1995 The United Rubber Workers Union (URW) merged into the United Steelworkers of America (USWA). With the merger, the URW added approximately 94,000 members to the rolls of the USWA, bringing the total membership of the combined union to more than 700,000. The International Ladies Garment Workers Union and the Amalgamated Clothing and Textile Workers Union merged to become the Union of Needletrades, Industrial and Textile Employees (UNITE). 1996 The Independent Federation of Flight Attendants representing 5,400 Trans World Airline attendants merged with the 40,000 member Association of Flight Attendants. Page 3 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS International Chemical Workers Union merged with The United Food and Commercial Workers Union (UFCW) bringing 40,000 members that became the International Chemical Workers Union Council of the UFCW. 1997 The Newspaper Guild merged with the Communication Workers of America (CWA). 1998 The United Paperworkers International Union (UPIU) merged with the Oil, Chemical and Atomic Workers International Union. The new 330,000-member union is known as the Paper, Allied-Industrial, Chemical and Energy Workers International Union (PACE). The United Representatives Guild, Inc., and the Production Service and Sales District Council both merged with the United Food and Commercial Workers Union (UFCW). 1999 The Bakery, Confectionery and Tobacco Workers Union merged with the American Federation of Grain Millers, becoming the Bakery, Confectionery, Tobacco Workers and Grain Millers Union (BCTGM). The 11,000-member Laundry and Dry Cleaning International Union affiliated with the Service Employees International Union (SEIU), which has about 1.3 million members. 2000 The Textile Processors Union affiliated with the United Food and Commercial Workers Union (UFCW). The local unions representing 7,200 members of the Textile Processors merged with the Union of Needletrades Industrial and Textile Employees (UNITE). The International Union of Electronic, Electrical, Salaried, Machine and Furniture Workers (IUE) merged into the Communications Workers of America (CWA). The Chicago Truck Drivers Union, with 5,000 members, affiliated with International Brotherhood of Teamsters (IBT). 2001 The Independent Association of Continental Pilots merged with the Air Line Pilots Association (ALPA), with 7,000 Continental pilots joining 58,000 ALPA pilots. The United Transportation Union (UTU) merged with the Brotherhood of Locomotive Engineers (BLE). The merged union was named the United Transportation Union-Brotherhood of Locomotive Engineers (UTU-BLE). 2002 The Independent FedEx Pilots Association, with 4,200 member pilots, merged with the Air Line Pilots Association (ALPA). In 2002, prior to the merger, ALPA represented 69,200 pilots at 43 different airlines. The Independent Baton Rouge Oil and Chemical Workers Union (OCAW) merged into the Paper, Allied-Industrial, Chemical and Energy Workers International Union (PACE). 2003 The American Flint Glass Workers, with 12,500 members, merged with the United Steelworkers of America (USWA). The 35,000-member United Service Workers (USW) disaffiliated from the Transportation Communications International Union and merged with the International Union of Journeymen Horseshoers and Allied Trades. The 10,000-member Independent National Public Employees Union (NPEU) also merged with the International Union of Journeymen Horseshoers and Allied Trades. The 10,000-member Independent National Organization of Industrial Trade Unions (NOITU) merged with the International Union of Journeymen Horseshoers and Allied Trades. The Association of Flight Attendants merged into the Communications Workers of America (CWA). The CWA previously had 700,000 members, and the AFA added another 33,881 members. The Brotherhood of Locomotive Engineers (BLE) in the United States and Canada merged with the International Brotherhood of Teamsters (IBT), bringing rail employees into the Teamsters for the first time. 2004 The Union of Needletrades, Industrial and Textile Employees (UNITE) and the Hotel Employees and Restaurant Employees International Union (HERE) merged to become UNITE HERE, a new union of 440,000 members. The Brotherhood of Maintenance of Way Employees merged with International Brotherhood of Teamsters (IBT). 2005 The Graphic Communications International Union merged with International Brotherhood of Teamsters (IBT). The GCIU has 60,000 members in the United States. The United Steel Workers of America (USWA) and Paper, Allied-Industrial, Chemical and Energy Workers International Union (PACE) merged to create an 860,000-member union called USWA. The USWA is now the largest industrial union in the United States. 2006 Page 4 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS The Professional Flight Attendants Association (PFAA) affiliated with the Transport Workers Union (TWU). At the time, PFAA represented 9,500 Northwest Airlines employees, and TWU represented 135,000 workers. New York State United Teachers, a 525,000-member affiliate of the American Federation of Teachers (AFT), merged with the National Educational Association/New York. The new combined union is known as New York State Teachers NEA/AFT, with 560,000 members. 2007 The Independent Steelworkers Union (ISU) merged with the United Steelworkers of America (USWA). The International Organization of Masters, Mates and Pilots and the Marine Engineers Beneficial Association united to form the Merchant Officers Labor Alliance. Elizabeth A. Ashack Economist, Division of Compensation Data Analysis and Planning, Office of Compensation and Working Conditions, Bureau of Labor Statistics. Telephone: (202) 691-5178; E-mail: Ashack.Elizabeth@bls.gov. Notes 1 See Union Members in 2007, USDL 08-0092 (U.S. Department of Labor), January 25, 2008, on the Internet at http://www.bls.gov/ news.release/archives/union2_01252008.pdf; and Union Members in 1995, USDL 96-41, February 9, 1996, on the Internet at http:// www.bls.gov/news.release/History/union2_020996.txt. 2 Employment data from the BLS Current Employment Statistics (CES) survey. For more information, visit the CES home page at http:// www.bls.gov/ces/. 3 A Plan to Help Workers Win: Uniting Our Power to Build a Stronger, Growing Labor Movement, Resolution 1 (AFL-CIO Executive Council), p. 5; available on the Internet at: http://www.aflcio.org/aboutus/thisistheaflcio/convention/2005/upload/res1.pdf (visited April 15, 2008). 4 For more information on union mergers during the previous 10-year period, see Lisa Williamson, "Union mergers: 1985-94 update," Monthly Labor Review, February 1995, pp. 18-25; available on the Internet at http://www.bls.gov/opub/mlr/1995/02/art2full.pdf. 5 A Plan to Help Workers Win: Uniting Our Power to Build a Stronger, Growing Labor Movement, Resolution 1 (AFL-CIO Executive Council), p. 1. 6 Daily Labor Report archives, 1995-2007 (Bureau of National Affairs), on the Internet at http://www.bna.com. (visited March 18, 2008). 7 "Uniting for the American Dream," Resolution (Change to Win: The American Dream for Americas Workers), available on the Internet at http://www.changetowin.org/fileadmin/pdf/convention-2007-resolution-american_dream.pdf (visited August 12, 2008). For more information, visit the Change to Win website at http://www.changetowin.org/. 8 Ibid., 2007. 9 For more information on the National Construction Alliance (NCA), visit the organizations website at http://www.ncabuild.org/. 10 More information on the formation of the Merchant Officers Labor Alliance can be found in the "Whats New?" section of the International Organization of Masters, Mates, and Pilots website, on the Internet at www.bridgedeck.org. A copy of the agreement between the Masters, Mates, and Pilots and the Marine Engineers Beneficial Association can be found at http://www.bridgedeck.org/WhatsNew/MOLA.pdf. 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