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U.S. Department of Labor https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Bureau o f Labor Statistics In this issue: Employment of welfare recipients Welfare reform 4th :z o o i w U.S. Department of Labor Elaine L. Chao, Secretary Bureau of Labor Statistics Katharine G. Abraham, Commissioner The Monthly Labor Review ( usps 987-800) is published monthly by the Bureau o f Labor Statistics o f the U.S. Department of Labor. The Review welcomes articles on the labor force, labor-m anagem ent relations, bu siness con d ition s, industry productivity, com pensation, occupational safety and health, demographic trends, and other economic developments. Papers should be factual and analytical, not polemical in tone. 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Periodicals postage paid at Washington, dc, and at additional mailing addresses. U nless stated otherw ise, articles appearing in this publication are in the public domain and may be reprinted without express permission from the Editor-in-Chief. Please cite the specific issue of the Monthly Labor Review as the source. Information is available to sensory impaired individuals upon request: Voice phone: (202) 691-5200 Federal Relay Service: 1-800-877-8339. Send address changes to Monthly Labor Review, U.S. Government Printing Office, Washington, dc 20402-0001. P ostmaster : Cover designed by Melvin B. M oxley https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis RESEARCH LIBRARY Federal Reserve Bank MO Ndf BL¥-céjià B O3 REVIEW SEP 2 8 2001 Volume 124, Number 7 July 2001 Are single mothers finding jobs without displacing workers? 3 A large influx of single mothers entered the labor force following the passage of welfare reform in 1996 Robert I. Lerman and Caroline Ratcliffe Welfare reform data from SIPP 13 Preliminary data are consistent with those of State-level studies regarding persons who left the welfare rolls and their incomes Richard Bavier Producer prices in 2000: energy goods continue to climb 25 Natural gas prices soared among finished, intermediate and crude goods, resulting in the steepest increase in the finished goods index in 10 years William F. Snyders A state space model-based method of seasonal adjustment 37 This structural method of seasonal adjustment presents certain advantages to seasonally adjust time series R a j K. Jain Reports Expenditures of college-age students and nonstudents 46 Geoffrey D. Paulin Estimates of union density, by State 51 Barry T Hirsch, David A. Macpherson, and Wayne G. Vroman Departments Labor month in review Research summaries Regional trends—Multiple jobholding Précis Book reviews Current Labor Statistics 2 46 56 58 59 61 Editor-in-Chief: Deborah P. Klein • Executive Editor Richard M. Devens • Managing Editor Anna Huffman Hill • Editors: Brian I. Baker, Bonita L. Boles, Richard Hamilton, Leslie Brown Joyner, Lawrence H. Leith • Book Reviews: Roger A. Comer, Chaquita M. Goode • Design and Layout: Catherine D. Bowman, Edith W. Peters • https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Contributors: John Cashman, Ronnie H. Fisher Labor Month in Review The July Review The recent revision of the welfare sys tem to encourage more labor market par ticipation by welfare recipients stimu lated the research in the first two articles. Robert I. Lerman and Caroline Ratcliffe of the Urban Institute investigated the impact of the influx of participants on local labor markets where there might have been some unintended effects on workers for whom welfare recipients m ight be substitutes. Lerman and Ratcliffe find, “Changes in the Nation’s welfare system apparently did not lead to deleterious consequences for the la bor market position of either single moth ers or less educated workers as a whole.” Richard Bavier of the Office of Man agement and Budget takes preliminary stock of the impact of welfare changes on those who leave the welfare rolls. Bavier concludes from the Census Bureau’s Survey of Income and Pro gram Participation (SIPP) that most (about two-thirds) had at least some em ployment in the year post-exit, and many worked at least 50 weeks of the year, but that it is a much smaller group that worked full time and full year. The im pact on incomes is also mixed—some welfare leavers realize income improve ments, but others do not. bls economist William F. Snyders summarizes last year’s developments in producer prices. Natural gas and petro leum-based products posted large price increases, thus driving higher rates of overall increase in producer price in dexes than those that have prevailed in several previous years. Raj K. Jain, a research economist at b l s , outlines research on the statespace model based approach to sea sonal adjustment. Growth, im m igration and education Following a growth rate of 2.6 percent per year in the 1970s, the rate of labor 2 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 force growth fell to 1.6 percent per year in the 1980s and 1.2 percent per year in the 1990s. For 2000-15, the annual rate is projected to be 1.0 percent and for 2015-25, it is projected to be just 0.2 per cent. According to those same projec tions, substantial parts of both net popu lation growth and overall labor force growth will be the result of migration. Among recent immigrants aged 25-34, about 16 percent of workers have a master ’s or higher degree, while about 26 percent have not completed high school. In comparison, U.S.-born work ers aged 25-34 are less than half as likely to have a master’s or higher degree— about 7 percent attained that level of education. Another 7 percent of U.S.born workers in this age group have not received a high school diploma. These are important differences. In 2000, college graduates aged 25 and older earned nearly $400 more per week (at the median) than workers who stopped with a high school diploma. College graduates have experienced growth in real (inflation-adjusted) earn ings since 1979. By contrast, the real earnings of workers who dropped out of high school have declined. Information about these and other long-term labor market trends can be found in Working in the 21st Century, a chartbook produced by the Bureau of Labor Statistics for the Summit on the 21st Century Workforce sponsored by the U.S. Department of Labor. The single poor Among poor consumer households, 61.8 percent contained only a single in dividual in 1999. In comparison, among other households in the expenditure distribution, only 20.4 percent consist of a single individual. Also notable is that husband-andwife type families comprise just over a tenth of households in the poor con sumer group, but more than half of households in the rest of the expenditure distribution. Single-parent families ac- count for 13.5 percent of the poor con sumer households and 7.4 percent of the others. For this analysis, “poor consumers” consist of households in the lowest decile of the expenditure distribution. “Average consumers” are represented by the averages for the remainder of the expenditure distribution. Full-time col lege students and homeowners who no longer have mortgage payments are ex cluded from this study. For additional information, see “Characteristics and spending patterns of consumer units in the lowest 10 percent of the expenditure distribution,” Issues in Labor Statistics, Summary 01-02. Productivity a t full retail Productivity in retail trade, as measured by output per hour, rose 5.2 percent in 1999. Output grew by 7.1 percent, while hours increased by 1.8 percent. During the 1990-99 period, produc tivity in retail trade increased at an an nual rate of 2.3 percent. This reflected output growth of 3.7 percent per year and hours growth of 1.4 percent per year. In each year of the 1990s, productivity in the retail sector either increased or was unchanged. The 1999 increase was the largest of the period. The measure of retail trade produc tivity presented here was introduced by bls this month. In addition, bls now publishes productivity statistics for all of the industries in retail trade that are at the two-digit standard industrial classi fication (SIC) level. See “Productivity and Costs: Service-Producing and Min ing Industries, 1990-99” news release usdl 01-167. □ C om m unications reg ard in g the Monthly Labor Review may be sent to the Editor-in-Chief at the addresses on the inside front cover, or faxed to (202) 691-5899. News releases dis cussed in this issue are available at: http://stats.bls.gov/newsrels.htm Single Mothers and Jobs Are single mothers finding jobs without displacing other workers? Despite a large influx of single mothers into the labor force following the passage o f welfare reform in 1996, metropolitan areas generated more than enough jobs to employ these new entrants without deleterious effects on competing groups of workers Robert I. Lerman and Caroline Ratcliffe Robert I. Lerman is an economist at the Urban Institute and professor of economics at American University, Washington, d c . Caroline Ratcliffe is an economist at the Urban Institute. E-mail: blerman@ui.urban.org https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis oving welfare recipients from welfare to work was the primary goal of the Personal Responsibility and Work Op portunity Reconciliation Act. Four years after the passage of this Act, the Nation had achieved con siderable success in reaching that goal. Together with a thriving economy, the Act has generated unprecedented increases in employment among mothers heading families (single mothers), the group most likely to receive welfare. Despite worries that the economy could not absorb the more than 1 million welfare recipients that were expected to enter the job market,1 enough jobs materialized to employ not only those welfare mothers who began looking for work, but also other single mothers who had been unemployed as well. Between early 1996 and the middle of 1998, when about 741,000 additional never-married mothers entered the labor force,2 the economy generated enough jobs for a 40-percent rise in employment for this group. The 40percent job growth figure dwarfed the 9-percent increase in employment for the economy as a whole.3 Notwithstanding these impressive national gains, three serious concerns have emerged. First, single mothers in large metropolitan areas may not be faring as well as those in the rest of the Nation. A recent study published by the Brookings Institution found that reductions in welfare cases were lower in counties with large central cities than in other counties in the same State.4 As a M result, the 89 urban counties containing the larg est 100 cities increased their share of the Nation’s welfare caseload from 47.5 percent to 58.1 per cent between 1994 and 1999. Second, the increase in jobs for welfare recipients may be coming at the expense of jobs for other, less skilled workers. Third, even if low-skilled jobseekers actually find employment, the enormous inflow of low-skilled single mothers into the job market may be de pressing the wages of all low-skilled workers.5 After developing a detailed analysis and projec tions, Timothy J. Bartik concludes that welfare reform’s stimulus to the low-skilled labor force will exert substantial effects that will lower the wages or employment opportunities of female heads of households and female high school dropouts. Still, he acknowledges that there is little evidence yet of such negative effects.6 The current article builds on an earlier study that examined the potential of 20 large metropoli tan areas to absorb the expected inflow of welfare recipients over the next 5 years.7 Projections from that analysis indicated that, while average growth in low-skilled jobs would be sufficient to employ the inflow of recipients and to reduce the unem ployment rate of low-skilled workers, four areas— Baltimore, the District of Columbia, New York City, and St. Louis—could very well experience rising unemployment. The text that follows describes what actually took place in the labor markets of the same 20 metropolitan areas. The article examines labor Monthly Labor Review July 2001 3 Single Mothers and Jobs market outcomes of single mothers and of low-skilled workers with whom they likely compete. The rationale for focusing on single mothers is twofold: they are the group most likely to have been affected by changes in the welfare program, and the monthly cps data do not specify who among the single mothers are welfare recipients. The following questions are addressed: • Did large metropolitan areas experience substantial in creases in the labor force participation of single mothers? • Were large metropolitan areas able to generate sufficient jobs to employ the rapidly rising number of single moth ers in the labor force? • Was the increased labor force participation of single mothers associated with increased joblessness among competing low-skilled workers, including less educated men? • Did the rapid increase in low-skilled single mothers in the labor market lead to a reduction or growth in their wages or in the wages of subgroups of low-skilled workers? • Which metropolitan areas experienced the most serious problems absorbing the inflow of single mothers and other low-skilled workers? These questions are answered by comparing labor force meas ures prior to the passage of the Personal Responsibility and Work Opportunity Reconciliation Act with the same measures 3 years later. While, certainly, State waiver programs stimu lated substantial increases in work effort among individuals eligible for welfare, it was the passage of national welfare pro visions mandating work, rigorous requirements for remaining eligible for welfare, and time limits that drew, and has contin ued to draw, the most attention and most concern about the implications for the low-skilled labor market.8 The economic context In the 3 years after the enactment of welfare reform, the re markably fast growth of the economy stimulated a rapid in crease in the demand for labor. Real gross domestic product jumped by 12.5 percent between the first three quarters of 1996 and the first three quarters of 1999.9 A decline in the unemployment rate from 5.6 percent to 4.3 percent, together with an increase in the labor force of 5.6 million people, re sulted in 7 million more jobholders. Along with gains in employment came an increase in earn ings. Usual weekly earnings (in current dollars) among full time workers rose from $599 to $665 per week among adult men and from $439 to $494 among adult women. These figures rep resent a rise of about 1.5 percent to 2 percent per year after adjustments for overall price increases.10 4 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 Job and wage data The analysis that follows uses data from the monthly Current Population Survey (cps) for the 12 months prior to the pas sage of the welfare reform act (September 1995 through Au gust 1996) and 3 years later (September 1998 through August 1999).11 The monthly cps provides a wide range of informa tion, including employment and weekly wage statistics for the U.S. population. Although respondents report their welfare status only in the annual March cps, the analysis uses monthly samples for three reasons. First, the March sample covers only a single month in each year and includes a smaller and less representative sample than the 12 months of data per year used in this study. Second, judging the labor market implica tions of welfare changes requires taking account of the added employment of past and potential welfare recipients and not simply those reported to have received welfare during the pre vious year. Therefore, it is best to examine trends among all single mothers and not simply those who report their welfare income during the previous year. Third, because of high and increasing levels of underreporting of respondents’ welfare status, it is difficult to use March cps data alone to learn about employment and wages of welfare recipients.12 The analysis presented in this study covers single mothers and other workers between the ages of 20 and 45. Single mothers entering the labor force Between the year before the passage of the Personal Respon sibility and Work Opportunity Reconciliation Act and the sub sequent 3 years, the percentage of single mothers in the labor force (their labor force participation rate) rose rapidly in the 20 metropolitan areas examined. For the 20 areas as a whole, the share of single mothers working or looking for work jumped from 67 percent to 79 percent, or by about 230,000. During the same 3-year period, the labor force participation rate for all 20to 45-year-olds increased by only 1 percentage point, from 82 percent to 83 percent. The increase in labor force activity among single mothers varied widely, with the labor force participation rate rising be tween 19 percentage points and 20 percentage points in Bos ton and Jacksonville, compared with 0 percentage points to 2 percentage points in San Diego and San Francisco. (See table 1.) In general, a catching-up process took place: those metro politan areas with high initial labor force activity had slower rates of growth than areas with low initial activity. The in creased labor force activity extended to less educated, as well as more educated, single mothers. Single mothers with a high school degree or less raised their rate of labor force participa tion from 59 percent to 72 percent. This sharp growth in the labor force activity of single moth ers accounted for a substantial share of the growth in the total labor force: whereas single mothers in the 20 metropolitan ar eas made up only about 6 percent of the total labor force in the 1995-96 period, they accounted for 20 percent of all labor force growth in the 3 years after the passage of the welfare reform act. Still, as of the period between September 1998 and August 1999, only 7 percent of the labor force in these metropolitan areas consisted of single mothers. In the absence of any in crease in the labor force participation of single mothers, the growth rate of the labor force would have been about 1.31 percent per year, as opposed to the actual growth rate of 1.53 percent per year. The impact on the labor supply would have been even larger but for the reduction in the population of single mothers in these areas. Between the 1995-96 and 1998— 99 periods, single mothers as a proportion of all 20- to 45-yearolds declined from 7.7 percent to 7.2 percent. The contribution of single mothers to the change in the labor force varied widely across metropolitan areas. In 5 of the 20 areas, the total labor force declined slightly in absolute terms, largely as a result of the declining total population, al though only Baltimore experienced an absolute drop in the number of single mothers in the labor force. (See table 1.) The growth in the participation of single mothers in the labor force accounted for more than 20 percent of labor force growth in Atlanta, Boston, Phoenix, St. Louis, and San Antonio. In New York City, an area with a large number of welfare recipients and with a relatively high initial unemployment rate, the inflow of single mothers into the workforce represented only 14 percent of the growth of the total labor force. The effects of welfare reform on single mothers might be expected to influence the job market for less educated adult workers more dramatically than the job market for all workers. The reason is that the single mothers most likely to enter the labor market because of welfare reform have lower educational attainment than the average worker. Their most plausible adult competitors are women and unmarried men with a high school degree or less. While single mothers made up 13 percent of this less educated segment of the workforce, they accounted for 24 percent of its labor force growth. Absorption of added workers into jobs The growth in the number of people looking for work posed a challenge to metropolitan area labor markets. Would jobs suit able for the 230,000 additional single mothers in the workforce materialize? Or would most of the new jobseekers become un employed? As it happened, labor markets responded well: they sup plied the 230,000 jobs necessary to absorb the single mothers entering the labor force, plus an additional 36,000jobs to move unemployed single mothers into employment. While the par ticipation of single mothers in the labor force grew by 14 per cent, the number of jobs going to single mothers increased by https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis an even larger 18 percent. As a result, the unemployment rate of single mothers in these metropolitan areas fell dramatically, from 12 percent in the 1995-96 period to 8 percent in 1998-99. An overwhelming number of single mothers worked full time. The average number of hours worked by single mothers was virtually unchanged, at about 38.6 per week. Three years after the passage of the Personal Responsibil ity and Work Opportunity Reconciliation Act, the percentage of employed single mothers increased in each of the 20 metro politan areas and in all 20 metropolitan areas combined (from 59 percent to 73 percent; see table 2). Double-digit rates of job growth for single mothers took place in 16 of 19 metropolitan areas.13 The exceptions were Baltimore, Detroit, and Minne apolis, areas in which the absolute number of single mothers declined. Thus, where job growth was modest, it resulted from a reduced labor supply and not inadequate demand. Even the largest metropolitan job markets—New York, Los Angeles, Chicago, and Philadelphia—were able to respond to the jump in labor force participation that took place after wel fare reform. These metropolitan areas alone added nearly 80,000 new jobs for single mothers. The case of the New York metropolitan area is especially interesting. Before the passage of the Act, the share of single mothers who were either in the labor force or employed was low, and New York’s overall un employment rate stood at 8 percent, more than 25 percent above the level averaged across the 20 metropolitan areas. Further, single mothers constituted a high share of the 20- to 45-year-old population (11 percent), a proportion 36 percent higher than the 20-metropolitan-area average. As a result, moving a high percentage of single mothers into the workforce would generate a relatively large impact on both the low-skilled labor force and the total labor force. The share of single moth ers with jobs in the 1995-96 period was only 41 percent, the lowest employment rate by far among the 20 areas and 18 per centage points below the average. Given these indicators, it would be reasonable to expect the New York labor market to have great difficulty stimulating large numbers of single moth ers to enter the workforce and absorbing them into jobs if they did begin looking for work. But in fact, over the 3-year period examined, the labor force participation rate of single mothers in New York jumped by 26 percent, from 48 percent to 64 per cent, expanding the single-mother workforce by 10 percent.14 Furthermore, the New York economy generated enough jobs to raise the employment rate of single mothers by 14 percent age points, to 55 percent, and to reduce their unemployment rate from 15 percent to 14 percent. The entry of recipients from the large welfare caseloads in the Los Angeles metropolitan area, along with an above-aver age unemployment rate of 14 percent for single mothers in 1995-96, posed a potential problem similar to the one in New York. However, single mothers in Los Angeles did not make up an unusually high share of the adult population, and the abso- Monthly Labor Review July 2001 5 Single Mothers and Jobs Table 1. Labor force participation of single mothers, 1995-96 and 1998-99 Labor fo rc e p a rtic ip a tio n ra te , 1995-96 M etropolitan a re a Labor fo rc e participation rate, 1998-99 C h a n g e in labor f o r c e ,19 9 5 -9 6 to 1998-99 (thousands) Percent c h a n g e In labor force, 1995-96 to 1998-99 Total.................................................. 0.67 0.79 231.9 13.7 A tla n ta ..................................................... Baltimore.................................................. B o s to n ..................................................... Chicago.................................................... D allas....................................................... D etroit...................................................... H ouston................................................... Indianapolis............................................. Jacksonville............................................ Los A nge le s............................................ .76 .77 .63 .69 .86 .70 .80 .71 .69 .61 .88 .84 .82 .80 .93 .77 .86 .86 .89 .73 32.4 -15.3 19.2 23.0 25.5 1.7 18.7 5.3 7.3 14.2 32.2 -22.8 36.8 12.8 24.9 1.5 18.0 13.9 25.2 7.8 Minneapolis............................................. New Y o rk .................................................. Philadelphia............................................. Phoenix.................................................... San A n to n io ............................................ San D ie g o ................................................ San Francisco......................................... San Jose.................................................. St. Louis................................................... Washington, d c ........................................ .73 .49 .65 .73 .73 .69 .88 .67 .75 .77 .80 .64 .80 .84 .84 .69 .90 .75 .83 .89 1.1 20.5 14.8 12.6 7.7 9.6 2.2 10.4 13.4 19.4 22.6 19.5 2.5 16.6 10.2 8.9 24.7 10.5 Note: Dash indicates too few cases to calculate reliable estimates. These cells had fewer than 100 unweighted observations in at least 1 year. The labor force participation rate is the percentage of the population that is either employed or unemployed. The percent change in the labor force reflects Table 2. _ changes in the tendency of single mothers to work or look for work and changes in the numbers of single mothers. S ource: Authors’ tabulations of data from the Current Population Survey, September 1995-August 1996 and September 1998-August 1999. Employment of single mothers, 1995-96 and 1998-99 Em ploym ent-topopulation ratio, 1995-96 M etropolitan a re a Em ploym ent-topopulation ratio, 1998-99 C h a rg e In em ploym ent, 1995-96 to 1998-99 (thousands) Percent c h a n g e In em ploym ent, 1995-96 to 1998-99 T o ta l.................................................... 0.59 0.73 268.2 17.6 A tla n ta ....................................................... Baltimore.................................................... B o s to n ....................................................... Chicago...................................................... D allas......................................................... D etroit........................................................ H ouston..................................................... Indianapolis................................................ Jacksonville.............................................. Los A nge le s.............................................. .70 .68 .58 .60 .78 .62 .75 .65 .54 .52 .82 .80 .79 .70 .88 .72 .80 .82 .84 .66 31.5 -9 .0 20.8 21.6 28.8 6.2 17.6 6.5 10.9 19.4 33.5 -14.7 42.5 13.7 30.4 6.1 18.3 18.3 43.9 12.0 Minneapolis................................................ New Y ork.................................................... Philadelphia................................................ Phoenix...................................................... San A n to n io .............................................. San D ie g o .................................................. San Francisco........................................... San Jose.................................................... St. Louis..................................................... Washington, d c .......................................... .69 .41 .56 .68 .64 .60 .74 .55 .72 .81 .76 .63 .89 .69 .77 .83 .4 19.3 18.1 14.1 8.0 11.1 4.5 .8 11.5 18.7 22.9 26.3 25.3 16.2 18.4 15.5 30.4 17.8 — .55 .65 .67 Note: Dash indicates too few cases to calculate reliable estimates. These cells had few er than 100 unweighted observations in at least 1 year. The employment-to-population ratio is the proportion of the popula tion that is employed. The change in employment reflects both the change 6 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 _ _ in the tendency for single mothers to have jobs and the change in the number of single mothers. S ource: Authors’ tabulations of data from the Current Population Survey, September 1995-August 1996 and September 1998-August 1999. lute number of single mothers declined between the 1995-96 and 1998-99 periods. In this case, a decline in the absolute number of single mothers meant that only about 13,000 addi tional jobs were required to absorb the new entrants. By rais ing the employment of single mothers by 19,400, the Los An geles labor market ended up lowering the unemployment rate of single mothers from 14 percent to 10 percent. Overall, metropolitan job markets were able to absorb the additional labor force growth induced by changes in the wel fare system. In the 20 metropolitan areas examined, 77,000 single mothers entered the labor force per year, a figure within the 48,000-to-162,000 range projected in an earlier study.15 Growth in the number ofjobs held by single mothers amounted to 89,000 per year in the 20 metropolitan areas, resulting in a decrease in the number of unemployed single mothers by 12,000 peryear. Unemployment among other workers Competition with single mothers could have weakened the market position of other workers, especially less educated ones. To examine this issue, the changes in employment and unemployment of competing groups were compared with the labor force inflows of single mothers. Several groups of adult workers, all with at most a high school degree, are likely to compete with single mothers for jobs: unmarried women who are not mothers, married women, and unmarried men. The unemployment rate and the employment-to-population ratio do not indicate any decline in job availability. (See table 3.) The unemployment rate of all three groups declined be tween 1995-96 and 1998-99, and for two of the three groups the percentage of those holding jobs increased. Only the share of less educated married women who work dropped, even as this group saw its unemployment rate fall. It is possible that, despite falling unemployment among competing groups, some of the jobs taken by single mothers would have gone to other groups in the absence of welfare reform and led to a larger decline in unemployment among their ranks. If employers did substitute single mothers for less educated adults, though, metropolitan areas with the highest increases in the workforce among single mothers would have experienced the lowest improvement in employment outcomes of competing groups. However, the data reveal no such ten dency: there are no significant negative correlations between the increased labor force participation rate of single mothers and the employment of less educated workers. To gain perspective on the magnitude of the employment changes, one can calculate what would have been the increase in the employed population if half of the new jobs going to single mothers went instead to one of the three competing groups. For the 20 metropolitan areas as a whole, the employed share of the population averaged 65.4 percent in 1995-96 and https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 67.3 percent in 1998-99 for the three groups combined. If half the gain in jobs held by single mothers went to either or both of the other two groups, the overall ratio of employment to population could have increased to 68.9 percent, raising the employed share by about 1.6 percentage points. Potential reductions in wages The accumulating evidence of job growth for single mothers and other less educated workers leaves open concerns about wages. Are wages high enough to allow families to raise their incomes? Are the new entrants to the labor force able to trans late their work experience into higher wages over time, or are wages for single parents falling, either because of a shift in the single-parent labor force toward the least skilled or because the added competition for jobs resulting from welfare reform is suppressing the wages of all less educated workers? According to the laws of supply and demand, an upward shift in the supply of workers should increase employment, but lower wages. Because marginal productivity declines with each additional worker, employers will expand their workforces only if they can match the reduction in productivity with a reduction in wages. In a dynamic economy, the increased sup ply of workers may only slow the growth in wages. Still, wages end up lower than what they would have been in the absence of the additions to the labor supply. The macroeconomic context complicates the issue. The sup ply of labor coming from potential welfare recipients raises the Nation’s capacity to produce. If the economy generates enough demand for goods and services, the additional work ers help raise total production, thereby increasing the amounts available for consumption, government spending, and invest ment. In the current context, additions to the supply of labor are necessary for the U.S. economy to continue to grow at rates of 3 percent to 4 percent per year. For the Nation as a whole, the extra growth in labor force participation of single mothers is raising the total growth of the workforce from about 1.2 percent to about 1.4 percent or 1.5 percent per year. This additional capacity is helping the U.S. economy sustain rapid economic growth without increasing inflation. While healthy from the perspective of the overall economy, the flow of welfare recipients into the workforce might flood the market for less educated workers, thereby limiting their job opportunities and wage growth. Such negative impacts would be especially troublesome in the context of the declining real wages experienced by less educated workers. Demographics may help explain the national labor market’s success in absorbing single mothers, as well as other less educated workers, in recent years. Because of the wide gap in educational levels between the relatively less educated retir ing workers and the more educated workers entering the labor force, nearly all of the absolute growth in the labor force has Monthly Labor Review July 2001 7 Single Mothers and Jobs Table 3. Unemployment rates and employment-to-population ratios of less educated workers, 1995-96 and 1998-99 Single w om en with no children and a high school education or less Married wom en with a high school education or less M e trop olitan area 1995-96 1998-99 Unmarried men with a high school ed ucation or less 1995-96 1998-99 1995-96 1998-99 U nem ploym ent rate T o ta l............................... 9.1 7.7 5.8 5.3 12.3 8.7 A tla n ta ................................... Baltimore............................... B o s to n ................................... Chicago................................. D allas..................................... D etroit.................................... H ouston................................ Indianapolis........................... Jacksonville.......................... Los A nge le s.......................... 6.6 10.1 7.5 7.6 6.3 7.7 12.7 6.7 11.3 12.8 8.0 13.5 8.0 9.9 5.8 3.8 6.0 3.4 5.3 4.8 5.0 3.0 4.8 7.9 5.3 6.3 1.9 1.2 3.8 1.1 3.0 5.5 3.0 4.9 5.5 4.1 8.6 8.7 12.6 10.0 15.1 12.3 10.4 12.8 5.5 8.4 11.5 6.5 16.0 5.1 11.6 2.9 7.4 7.5 4.4 4.2 9.5 Minneapolis........................... New Y ork............................... Philadelphia........................... Phoenix.................................. San A n to n io .......................... San D ie g o ............................. San Francisco....................... San Jose............................... St. Louis................................. Washington, d c ..................... 5.4 11.1 12.2 8.9 — 10.1 — 4.1 8.7 9.0 — 6.2 4.5 .9 7.9 6.4 1.9 13.1 8.8 4.1 4.1 5.1 4.5 2.4 8.8 5.4 3.4 9.9 9.3 2.8 8.7 4.3 4.1 8.7 13.9 15.0 11.4 6.1 17.1 11.7 12.2 12.1 13.1 4.9 13.1 11.3 6.5 6.0 7.0 10.1 11.2 7.1 7.2 — — 10.5 6.7 10.5 6.9 6.7 5.6 5.7 — Empk>yment-topo pulatlon ratio Total................................. 65.5 68.7 58.9 57.3 72.6 76.7 A tla n ta ................................... Baltimore............................... B o s to n ................................... Chicago.................................. Dallas..................................... D etroit.................................... H ouston................................. Indianapolis........................... Jacksonville.......................... Los A ngeles.......................... 71.9 69.4 65.2 65.2 77.1 62.0 63.2 — 57.0 74.1 64.2 66.6 65.3 77.2 71.2 72.9 73.1 69.1 63.1 63.9 76.5 67.3 64.6 64.1 57.9 55.4 65.7 66.6 46.3 65.5 66.1 70.3 61.2 58.5 60.5 50.3 57.3 71.6 47.1 70.8 71.8 72.7 71.4 78.4 70.7 75.3 86.7 76.4 75.3 80.8 68.0 84.4 73.9 90.9 78.5 80.4 82.3 85.3 74.5 Minneapolis........................... New Y o rk ............................... Philadelphia........................... Phoenix.................................. San A n to n io .......................... San D ie g o ............................. San Francisco....................... San Jose............................... St. Louis................................ Washington, d c ..................... 80.3 55.3 67.2 74.9 75.4 67.9 82.6 77.2 70.9 66.7 74.6 60.9 64.3 70.9 80.2 71.9 71.0 89.3 73.0 79.0 80.6 46.2 64.7 64.9 53.7 53.2 62.4 62.0 72.3 70.1 75.5 44.9 64.1 55.6 59.2 51.9 68.9 56.3 62.1 74.9 85.0 63.9 67.2 81.3 78.2 69.3 79.6 71.9 75.8 70.9 84.2 63.9 71.2 84.4 77.3 75.9 79.1 78.0 80.9 81.8 — Note: Dash indicates too few cases to calculate reliable estimates for subgroups. These cells had fewer than 100 unweighted observations in the denominator of the ratio. S ource: Authors’ tabulations of data from the Current Population Survey, September 1995-August 1996 and September 1998-August 1999. been among workers with at least some college education. Between 1989 and 1999, of the 17.1 million persons added to the working-age adult population (25- to 64-year-olds), 15.6 million had a postsecondaiy education, while the number with out a high school degree or the equivalent actually declined by 1.9 million.16 Thus, far from flooding the market, the addi tional single mothers in the workforce prevented an even more rapid downward shift in the supply of less educated workers. In examining wage trends, one must take account of compo sitional as well as market effects. Wages might fall or rise espe cially slowly not because of the expanded supply of single mothers, but rather because the new single mothers (and com peting groups) entering the labor market have lower skills than single mothers who are already employed at the beginning of the period. This compositional factor could be particularly im portant for single mothers, because they experienced the most 8 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 rapid increase in the labor force and, potentially, the largest compositional shift. In that context, it would be a mistake to view wage trends as representing the gains or losses of a fixed group of workers. Theoretically, while either result—suppressed wages or growing wages— is possible, the conventional prediction is that the wages of single mothers or their competitors will be clearly lower than they would have been with no welfare re form. The results presented herein do not provide a direct test of this hypothesis, because what is measured is only what did happen, not what would have taken place in the absence of the welfare act or similar reforms. That is, what was observed were actual wage gains—they might have been higher or lower had welfare changes not occurred. Still, the actual wage trends do provide some indication of plausible effects, especially when wage changes among single mothers and less skilled groups are compared with changes across all adult workers. So far, the outcomes look promising. In the 20 metropolitan areas as a whole, all single mothers (including less educated ones) experienced an increase in wages. Single mothers earned an average of $10.59 per hour in 1995-96 and $ 11.67 per hour in 1998-99 (unadjusted for infla tion), a gain of 9.7 percent. The 1998-99 mean earnings level was 77 percent of the hourly rate paid to all 20- to 45-year-old workers. The median hourly rate for single mothers stood at $8.79 before the welfare reform act and then rose to $10.00 3 years later. Among the less educated single mothers, the me dian wage reached $8.00 per hour in 1998-99, up from $7.50 in 1995-%. In all 20 metropolitan areas, some less educated workers saw their wages grow faster than did single mothers. Annual median wage growth was 4.3 percent for all persons, 4.3 per cent for single mothers, 3.6 percent for less educated single women without children, and 6.4 percent for less educated unmarried men. (See chart 1.) The lowest wage group of single mothers (the bottom 25 percent) saw nominal wage increases of 4.1 percent per year, a growth rate that was only slightly less than the average growth rate of 4.2 percent for the lowest 25 percent of the total population of adult workers. Although a full model of metropolitan area wage determi nation is beyond the scope of this article, a test can be per formed for the presence of a negative relationship between large inflows of single mothers into the labor market and wage growth among less skilled workers. To obtain adequate samples of wages in each of the 20 metropolitan areas, two groupings that act as proxies for less skilled workers were used: workers at the 25th percentile of wages and workers with no more than a high school education. Surprisingly, as charts 2 and 3 indicate, there appears to be no connection between labor force inflows and wage growth among these https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis two groups of workers. The correlations were -.12 for work ers at the 25th percentile and -.00 for less educated workers. Thus, wages tended to rise as fast in metropolitan areas with large increases in single mothers joining the labor force as in other areas. In relating the labor force growth of single parents to the wage growth of potential competitors, such as all women with a high school degree or less, again, no wage-depressing effects were found. In the five metropolitan areas with adequate samples to determine the wages of single mothers, the wage trends among working single mothers were similar to trends among all work ers. (See chart 4.) Los Angeles, a metropolitan area with aboveaverage unemployment, generated the weakest growth in nominal wages. Surprisingly, wage growth in Detroit was far above average for all workers and for single mothers. As of 1998-99, the median wage of single mothers varied widely across the five cities, from about $10.59 per hour in Chicago and $12.00 in Washington, DC, to between $9.00 and $9.50 in Los Angeles and New York. Again perhaps surprisingly, the gap in median wages between single mothers in low- and highwage areas was nearly as wide as the gap in median wages between all single mothers and all workers. The current flexibility of labor markets Changes in the Nation’s welfare system apparently did not lead to deleterious consequences for the labor market posi tion of either single mothers or less educated workers as a whole. Despite the substantial flow of single mothers into the job market, metropolitan areas generated more than enough jobs to employ these new entrants, thereby reducing unem ployment rates for single mothers and for their potential com petitors. Nor has any sign of wage erosion among other less educated adults materialized, although in some areas single mothers themselves have experienced slow wage growth. Still, the wages of single mothers kept pace with the average growth in wages. Thus, far from weakening the job market, the increased labor force participation by single mothers came at an oppor tune time. Not all single mothers, though, reaped the benefits of the Nation’s robust economy. Some left welfare without becoming employed.17 Others stayed on welfare and out of the workforce because of health problems, extremely low skills, or other perceived or actual barriers to employment.18 A serious recession would certainly weaken the wage and employment picture for single mothers and other less edu cated workers. Still, the record shows that, at least until now, metropolitan labor markets have been flexible enough to gen erate sufficient jobs for single mothers and other groups with out eroding wages. □ Monthly Labor Review July 2001 9 Single Mothers and Jobs 10 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 11 Single Mothers and Jobs Notes ACKNOWLEDGMENT: This work was financed in part by the Assessing the New Federalism project at the Urban Institute. The views expressed are those o f the authors and do not necessarily reflect those o f the Urban Institute, its board, or its sponsors. The authors thank Jesse Valente, Patrick Sharkey, and Stephanie Riegg for providing excellent research assistance and Pamela Loprest, Alan Weil, and Corinna Nicolaou for useful comments. The work was presented at the 22nd Annual Re search Conference o f the Association for Public Policy and Manage ment, Seattle, Washington, November 2 -4 , 2000. 1 See, for example, Sheldon Danziger and Jeffrey Lehman, “How Will Welfare Recipients Fare in the Labor Market?” Challenge, MarchApril 1996, pp. 3 0 -35; and Peter Edelman, “The Worst Thing Bill Clinton Has Done,” Atlantic Monthly, March 1997, pp. 43-58. 2 The single mothers most likely to participate in welfare programs are those who have never married (as opposed to divorced, separated, or widowed single mothers). 3 The numbers are from unpublished tabulations provided by the Bureau of Labor Statistics. 4 Katherine Allen and Maria Kirby, Unfinished Business: Why Cities Matter to Welfare Reform (Washington, DC, Brookings Institution Center on Urban and Metropolitan Policy, 2000). 5 Robert Solow, Work and Welfare (Princeton, sity Press, 1998). nj , Princeton Univer 6 Timothy J. Bartik, “Displacement and Wage Effects o f Welfare Reform,” in David E. Card and Rebecca M. Blank, Finding Jobs: Work and Welfare Reform (New York, Russell Sage Foundation, 2000), pp. 7 2122 . b e a /n e w sr e l/g « lp 2 0 0 a .h tm . 10 Data are from Usual Weekly Earnings o f Wage and Salary Workers, second quarter 1996 and second quarter 1999 (Bureau o f Labor Statis tics, 1996 and 1999); on the Internet at h ttp ://w w w .b is.gov . 11 Large samples o f single mothers and other low-skilled groups are necessary to yield reliable estimates o f employment and earnings. Even with 12 months o f cps data in each year and sam ples o f 10 ,5 3 2 and 11,877 single mothers in the two study periods, respectively, the sample size was too sm all (few er than 100 cases) to calculate em ploym ent levels for some subgroups in several o f the 20 metropolitan areas. B e cause the CPS asks only one quarter o f each month’s sample about weekly wages, the sample size for w eekly wage data on some subgroups was adequate only in the 5 largest metropolitan areas and all 20 metropoli tan areas combined. 12 Laura Wheaton and Linda Giannarelli, “Underreporting o f MeansTested Transfer Programs in the March CPS,” in 2000 Proceedings o f the Section on Goverment Statistics and Section on Social Statistics (Washington, DC, American Statistical A ssociation). 13 The sample size was too small for the calculation o f reliable esti mates in the San Jose metropolitan area. 14 The 10-percent increase in the single-mother workforce was lower than the 26-percent rise in the participation rate o f single mothers be cause o f a decline in the population o f the group. 15 Lerman, Loprest, and Ratcliffe, Urban Labor Markets. 16 Authors’ calculations from CPS, March 1990 and March 1999. 7 Robert I. Lerman, Pamela Loprest, and Caroline Ratcliffe, How Well Can Urban Labor Markets Absorb Welfare Recipients? Assessing 17 Pamela Loprest, How Families That Left Welfare Are Doing: A National Picture, Assessing the N ew Federalism, No. b -1 (Washington, the New Federalism, no. DC, Urban Institute, 1999). a -33 (Washington, dc, Urban Institute, 1999). 8 Jared Bernstein, Welfare Reform and the Low-Wage Labor Market: Employment, Wages, and Wage Policies, Technical Paper 226 (Wash ington, DC, Economic Policy Institute, 1997). 9 The figure was tabulated with data from National Income and gd p Revised Estimates (Bureau o f Economic Affairs, 2000); on the Internet at http://www.bea.doc.gov/ Product Accounts, Second Quarter 2000 12 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 18 Sandra Danziger, Mary Corcoran, Sheldon Danziger, Colleen Heflin, Ariel Kalil, Judith Levine, Daniel Rosen, Kristin Seefeldt, Kristine Siefert, and Richard Tolman, Barriers to the Employment o f Welfare Recipients (Ann Arbor, Ml, University o f Michigan Poverty Research and Training Center, 2000); on the Internet at h ttp ://w w w .ssw .u m ich .ed ii/p overty/ w esa p p a m .p d f. Welfare reform data from the Survey of Income and Program Participation Preliminary monthly survey data regarding persons who left the welfare rolls and their income show generally consistent findings with those o f the State-level studies and with the March c p s ; however; s ip p data provide additional points o f comparison and detail Richard Bavier Richard Bavier is a policy analyst at the Office of M anagem ent and Budget. The views expressed are the author's personal views and do not represent the views of omb or the Administration. E-mail: Richard_B._Bavier @omb. e o p .g o v https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis n response to the rapid decline in welfare sequently, analysis of welfare reform, using caseloads before and after enactment of the March c p s data has focused on changes in the Personal Responsibility and Work Opportu economic status of female family heads with chil nity Reconciliation Act of 1996 ( p r w o or simply dren—the families most directly affected by wel welfare reform), considerable resources have fare reform.2 been devoted to “leavers studies.” These tracked This article tests key findings from the leavers the employment and income of families that have studies with preliminary findings from the Sur left the welfare rolls-the State programs funded vey of Income and Program Participation (SIPP), by the Temporary Assistance for Needy Familes including information on employment rates, re ( t a n f ) block grant that replaced Aid to Families turns to welfare, and the economic status of per with Dependent Children ( a f d c ). Leavers stud sons once they leave the rolls. Overall, sipp data ies have been conducted by a variety of research support findings from the leavers studies and ers in many States.1 also provide both inter- and intra-temporal con By design, leavers studies could not provide text s ip p data also are shown to be consistent any information about families that may have been with distributional analysis of CPS data. More deterred or diverted from coming onto the welfare over, s i p p ’s monthly data reveal how the income rolls by the new welfare reform policies. In addi of leavers contributes to annual income trends in tion, the leavers studies were mostly limited to the March c p s . measuring the personal income of former welfare recipients, missing possible economic benefits The sipp data set from those living with other household members who receive income. The SIPP, conducted by the Bureau of the Cen Data from the March annual demographic sus, is a panel survey, representative of the nonsupplement to the Current Population Survey institutional population. Field staff return to the (CPS) have been another early source of informa same sample households every 4 months for sev tion about what is happening under welfare re eral years and ask monthly demographic, labor form. With its large sample, detailed question force, income, and program participation ques naire, and timely availability, the March CPS does tions. In addition to core questions asked with not have the major limitations of the leavers stud each visit or “wave,” the Census Bureau creates ies. All household members and their incomes modules devoted to different topics on different are included, not just welfare leavers. However, waves to gather detailed information on a wide until the March 2000 CPS, there was no sure way variety of other subjects. to identify transitions onto or off of welfare. Con The 1996 s ip p panel is large, starting with I Monthly Labor Review July 2001 13 Welfare Reform around 37,000 households. As discussed in an appendix, sample loss is a growing problem with s ip p . By the tenth wave, early in 1999, around one-third of eligible households were providing no information, and around half of those still in the sample had some income imputation. The data set used for most analysis in this article defines a welfare exit as at least 2 consecutive months of a f d c /t a n f receipt followed by at least 2 consecutive months without receiving benefits.3 (Similarly, a welfare return is counted only when a person who leaves the welfare rolls subsequently re ceives 2 consecutive months of welfare benefits.) In addition, the research sample includes only leavers who remained in the sample for at least 12 months after they leave. With the 36 months of data from the 1996 SIPP panel used to create the leavers’ data set, this analysis reflects a cohort who leaves welfare from months 3 through 25 of the panel. Field staff visit one-fourth of the sample each month, so the third month of the 1996 panel corresponds to February 1996, at the earliest, and May 1996, at the latest. Month 25 may be as early as December 1997 or as late as March 1998. For convenience, this group will be termed 1996-97 leavers. During this 1996-97 period, 1,178 persons in the sample left welfare and remained observable in the panel for 12 months or more after they exited, which was around four-fifths of all the sample persons who left welfare during these months. The remaining fifth of leavers could not be followed for 12 post exit months. (The appendix compares those who remained in the sample with those who did not.) In the analysis that fol lows, persons who can be observed for 12 consecutive post exit months are assigned a sample weight for the month of their exit from the SIPP wave files. The result is a complete 12month longitudinal sample of a cohort of leavers. A parallel data set using wave files from the smaller 1993 s ip p panel was used for most comparisons between panels.4 Employment of welfare leavers The U.S. Department of Health and Human Services ( h h s ) found that between 46 percent and 64 percent of 1996-97 leavers in studies from 10 States had some earnings during the first quarter of their exit from the welfare rolls.5 The pro portion of leavers who had earnings within a year of exit ranged from 62 percent to 75 percent. The h h s report notes, “Only about 35 to 40 percent of leavers were employed in all four quarters, according to the three studies reporting this statistic.” In the s ip p data set, about half of leavers had worked in the month they exited welfare, and two-thirds worked at some point within 12 months of their exit. Around 62 percent of those with some earnings, or 41 percent of all leavers, had earnings in every quarter. Of the leavers with any work, 54 14 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 percent worked in every month after they exited welfare and 48 percent worked in 50 or more weeks. Analysis of CPS data has found sharp employment in creases among never-married female family heads.6 Earlier studies had associated longer welfare spells with never-mar ried status, so increased employment rates among this group could result in significant welfare caseload reduction. Of all AFDC/TANF recipients in months 3 to 25 of the 1996 s ip p panel, 45 percent (standard error, 1.4 percent)7 were never married. Never-married recipients represented 41 percent (standard error, 2.0 percent) of leavers during those months. Consistent with the higher employment rates in CPS, 60 percent of these never-married leavers had a job in the exit month— a higher employment rate than that among other leavers. While s ip p data show the leavers studies to be fairly repre sentative of the national experience, they also show that em ployment rates for leavers are not higher than the rates for leavers in earlier years with a strong economy. The following tabulation illustrates the share of a f d c leavers who were em ployed in the month they exited a f d c , based on several SIPP panels.8 Calendar years Percent o f leavers employed in exit month 1984 ............................................................. 1985 .................................................................... 1986 ............................................................. 1987 ............................................................ 1988 .................................................................... 1990 ............................................................. 1991 ............................................................. 1992 ........... ................................................. 1993 .................................................................... 1994 ............................................................ 1995 .................................................................... 1996 ............................................................ ............................................................ 1997 1998 .................................................................... 1999 ............................................................. 52 53 60 48 62 48 58 51 50 52 51 53 53 46 45 Intensity of labor force attachment As noted earlier, of the two-thirds of s ip p leavers with some employment in their first year after leaving welfare, a little less than half worked for 50 weeks or more. About 40 percent of those worked for 35 hours or more in all weeks, and an addi tional 7 percent worked 35 hours or more in at least some of their 50 weeks of employment. A little more than half of the employed s ip p leavers who worked year round did not work full-time in any of those weeks. In 59 percent of all months with any work, leavers worked 35 hours or more in each week. This full-time work was con centrated among leavers who also worked year round. The one-third of leavers who worked in all 12 post-exit months accounted for about three fourths of all full-time months worked. Zero income at exit is not common The leavers studies provided little information about the half of leavers with no employment. Among the cohort of welfare leavers in the 1996 SIPP panel, about 4 percent lived in house holds with no income in the exit month; among leavers who were not employed, 6 percent lived in households with no income in the exit month. Unemployed leavers reported a variety of in come types. More than two-thirds lived with other household members who had income. About half of leavers with no exitmonth earnings received food stamps, and one-fourth received rental assistance, such as public housing or Section 8 certifi cates or vouchers. Receipt of cash benefits other than a f d c / t a n f was not uncommon. (See table 1.) Returns to welfare In the leavers studies summarized by Health and Human Ser vices, between 23 percent and 35 percent of leavers returned Table 1. Income sources of persons leaving Aid to Families with Dependent Children/Temporary Assistance for Needy Families in 1996-97 [In percent] All leavers Employed in exit month Not e m p lo y e d in ex it m onth 3,336,441 1,668,171 1,668,269 Food stamp re cip ient.......... 68.3 69.1 67.4 Medicaid recipient............... 95.2 95.4 95.1 3.6 .9 6.4 62.4 44.4 25.0 11.9 9.3 3.4 55.9 40.7 25.5 14.9 6.0 3.6 68.9 48.1 24.5 9.0 12.6 3.2 8.9 1.7 16.1 5.0 3.4 5.5 4.3 2.3 .5 5.6 4.5 10.6 .3 .7 .2 .9 .3 .4 62.7 56.9 68.6 In c o m e source Leavers (number)......................... In last month on welfare— In exit month— Zero household incom e........ Income from— Other household m em bers. Food stam ps....................... Rental assistance.............. Child s u p p o rt...................... General a ssista nce........... Other w e lfa re ...................... Own Supplementary Security Inco m e.............. Child’s Supplementary Security Inco m e.............. Child’s Social S ecurity....... Own Social S e c u rity.......... Unemployment com pensation..................... Foster c a re ......................... Former adult recipient on m edicaid............................ S ource : 1996 panel of the Survey of Income and Program Participation. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis to welfare within 12 months of exit.9 Of the 1996-97 cohort of leavers who could be followed for 12 months in sipp, 18 per cent returned within 6 months of exit, and 25 percent returned within 12 months of exit. These rates were similar to those in the 1993 panel (19 percent returned within 6 months and 26 percent returned within 12 months). Many persons who do return to welfare do not remain for long. Among sipp returners who could be followed for 12 months after they returned to the rolls, 71 percent had left welfare again within that post-return year. As has been ob served, leaving welfare often takes more than one try.10 Income changes The picture of economic well-being in the leavers studies is mixed. On the one hand, employed leavers have generally sustained their employment rates and earnings over several quarters.11 On the other hand, most leavers appear to have income that is lower than their income on welfare. Examining administrative records from AFDC, the Food Stamp Program, and wages reported to the Unemployment Insurance program, Maria Cancian and her colleagues find that only 36 percent of the recipients who exited welfare in Wisconsin, from August 1995 to July 1996, had average quarterly income (in the year after exit) that exceeded their income in the quarter before exit.12 Using SIPP data, table 2 compares the mean monthly post exit income of leavers over 12 months after they left welfare with the mean monthly pre-exit income received in the 2 months before they left. As with the Cancian measure, the one-fourth of leavers who returned to the rolls within a year of exit are included, although the patterns are unchanged when they are excluded. Counting only personal income, as Cancian and her colleagues did, SIPP data show that only 29 percent of leavers had average post-exit monthly income that exceeded their pre-exit income by $50 or more. By contrast, nearly two-thirds of the welfare leavers had personal income that was lower than their income on the welfare rolls by at least $50. If the income of all members of the leaver’s house hold is included, the economic picture improves consider ably, but still, less than half averaged at least $50 per month more than on welfare. The difference in pre- and post-exit incomes is not trivial. On average, persons who do gain more income receive around 50 percent more than they had re ceived on welfare, while those who lose income receive around two-thirds of their pre-exit income. (The proportions of leavers who gained and lost income in the 1993 panel were very similar— 46 percent winners, 45 percent losers.) Analysis of leavers who are employed in their exit month shows that 48 percent average higher post-exit household income and 40 percent have higher post-exit personal income. If the Earned Income Tax Credit were added to the post-exit Monthly Labor Review July 2001 15 Welfare Reform Table 2. Post-exit income changes of persons who leave Aid to Families with Dependent Children/Temporary Assistance for Needy Families in 1996-97 A v e ra g e m onthly A v e ra g e m onthly in c o m e A v e ra g e m onthly in c o m e in co m e c h a n g e in 2 p re -w e lfa re -e x it m onths in p o s t-w e lfa re -e x ity e a r In c o m e c a te g o ry Percent S tan dard error (p e rc e n t) In co m e S tan dard error (p ercen t) In co m e S tan d ard error (p ercen t) Mean monthly household pre-tax money income plus food stamps In post-exit year: More than $50 higher than months before e x it........................................... Within $50 of months before e x it.............................. More than $50 lower than months before e x it........................................... 44.3 2.0 $1,614 85 $2,450 102 6.8 1.0 1,345 117 1,343 116 48.9 2.0 2,514 118 1,670 79 29.4 1.8 792 39 1,296 49 8.5 1.1 665 53 659 53 62.1 2.0 1,131 44 651 29 Mean monthly personal pre-tax money income plus food stamps in post-exit year: More than $50 higher than months before e x it................. Within $50 of months before e x it........................................... More than $50 lower than months before e x it................. S ource 1996 panel of the Survey of Income and Program Participation. income of eligible earners, the share with income gains would be higher. Similarly, if work expenses and payroll taxes were subtracted, the share with net gains would be lower. On reflection, we should not be too surprised that more employed leavers are not income gainers by this measure. State Temporary Assistance for Needy Families programs have expanded earnings disregards to “make work pay.”13 Rather than reducing benefits by $1 for each dollar earned, benefits are reduced by less than a dollar as a “work incen tive.” Under the T A N F program, the share of recipients with earnings is higher. However, these “work incentives” may last only for several months. If a recipient is classified as a leaver in s ip p because a transitional earnings disregard expires, rather than because her earnings increase, she may appear as an income loser by this measure, even though some might regard her transition as a successful one. This effect is illustrated in results of a logit analysis of characteristics of household income losers. Having a job in the exit month reduced (by 4 percentage points, or about 8 percent) the chance that a leaver’s monthly income in the post-exit year would average more than $50 lower than her last 2 months on the rolls. However, having a job in the last month welfare benefits were received increased the chance of a person losing income by 5 percentage points, or about 10 percent. Other characteristics associated with being an income loser were largely consistent with findings from a three-city study of welfare leavers that gathered much more 16 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 detailed characteristics than earlier state leavers studies.14 That study found lower earnings and household income among leavers with less than a high-school degree, fair or poor health, and longer periods on welfare, compared with other leavers. In the s ip p data, having less than a high school degree or equivalent was associated with income loss after persons exited welfare. (See table 3.) In addition, positive coefficients were associated with exits in States with the high est a f d c / t a n f benefits and among leavers reporting work limitations, though these were not statistically significant. Although long-term welfare recipients might be expected to have less post-exit economic success, having a welfare spell of more than 2 years end with the observed exit was not associated with income loss.15 Caseloads getting “harder to serve”? Earlier analysis of the characteristics of female family heads receiving a f d c found that many had little work experience, low scores on verbal and mathematical tests, health conditions that limited the work they could do, and alcohol-related problems. Among longer term recipients, these conditions were even more prevalent.16 Another po tential employment obstacle, domestic abuse of a f d c / t a n f recipients, also received much atte n tio n .17 As t a n f caseloads dropped by about half since 1994, concern has grown that the remainder might include a higher concen- tration of families that are “hard to serve.” With its detailed topical modules devoted to disability, child care, and work history, s ip p represents a very rich source of data about the employability of a f d c /t a n f recipients. Only a few topical modules from the 1996 panel have been released so far. Based on preliminary analysis, cross-sectional com parisons of the characteristics of a f d c /t a n f recipients in s ip p do not lend strong support to concern that the residual caseload is much harder to serve. Table 4 displays a range of characteristics associated with longer welfare spells. Instead of a larger share of long current spells, as might be expected if the welfare rolls had higher concentrations of the hard-to-serve, current spells appear shorter with later observations. There is no higher concen tration of very low educational attainment or receipt of rental assistance, such as public housing or Section 8 certificates or vouchers, in the later waves. However, by month 36, the proportion of persons reporting work-preventing conditions is significantly larger (21 percent) than that in month 1 (16 percent). The actual number of recipients in this category in s ip p is 33 percent lower in month 48 (370,769) than in month 1 (556,279), but the decline in total caseloads over this period (3,587,754 in month 1 to 1,797,697 in month 48) has been 50 percent. By panel month 36, the proportion of the caseload reporting a work-preventing condition approximately equals the share of the caseload that may be exempted from the Federal 5-year time limit on t a n f benefits.19 Table 3. Predictors of post-exit household income loss of persons leaving Aid to Families with Dependent Children/Temporary Assistance for Needy Families in 1996-97 C haracteristic Estimate Standard error Effect on probability of in c o m e loss (percent) Probability of post-exit income loss with other independents at z e r o ........................ -0.1534 0.1495 Work in the last welfare m onth...................... 1.2859 .2004 10.0 Work in exit month .. -1.1215 .1985 -7 .9 Other household member with in c o m e .................... -.0493 .1278 -.1 States with highest benefit..................... .2004 .1387 7.1 Less than high-school degree..................... .3629 .1293 7.1 Pre-exit welfare spell more than 24 m onths.................... -.1892 .1328 -3 .8 Work lim itation.......... .1689 .1538 8.4 S ource : Income trends 1996 panel of the Survey of Income and Program Participation. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SIPP does not provide direct information about some of the observable characteristics thought to indicate labor mar ket disadvantage, such as low levels of verbal and math skills, alcohol or drug dependence, or domestic violence. More over, unobservable characteristics such as motivation, may be important in successful transitions off of welfare. How ever, if we suppose that these unobservable characteristics are becoming more concentrated in the residual caseload for Temporary Assistance for Needy Families, we can form test able hypotheses about the likely labor market experience of recent leavers, compared with earlier leavers. If persons leaving welfare from the reduced caseloads in 1998 or 1999 have more labor market disadvantages than those leaving in 1996 or 1997, we would expect that they would have lower employment rates and more job loss. How ever, Cancian and her colleagues found that a 1997 cohort of Wisconsin leavers was more likely to be employed at some point in their post-exit year than a 1995 cohort, and that em ployment stability and poverty were fairly similar.20 Among a cohort of a f d c / t a n f recipients who left the rolls during months 4 through 9 of the 1996 s ip p panel (and could be observed for 12 months after they left), 70 percent (standard error, 2.7 percent) worked at some point during that observation year, 47 percent (standard error, 3.6 per cent) of those lost at least one job, and 38 percent of the job losers lost more than one. Among a similar cohort leaving welfare a year later, during months 16 through 21, when na tional employment measures suggest a stronger demand for workers, 75 percent (standard error, 3.1 percent) worked at some point, 50 percent (standard error, 4.3 percent) of those lost at least one job, and 50 percent of those losing a job lost more than one. The differences fall short of statis tical significance at the 90-percent confidence level, al though the difference in the share losing more than one job falls just short. Female family heads with children, the families affected most directly by the Personal Responsibility and Work Opportu nity Reconciliation Act of 1996, have seen strong income gains since 1993.21 In data from the March CPS, these gains are evident all along the income distribution, except that, begin ning in 1996, the bottom fifth of the distribution lost ground before recovering partially in 1999. s ip p data appear to be consistent with main themes from the State leavers studies. They are also broadly consistent with income trend data from the March Current Population Survey, and, importantly, show how welfare leavers are faring. Mean monthly pre-tax money income plus food stamps in the bottom quintile and decile of female family heads with Monthly Labor Review July 2001 17 Welfare Reform Table 4. Characteristics of adult recipients of Aid to Families with Dependent Children/Temporary Assistance for Needy Families in the 1996 panel of the Survey of Income and Program Participation [In percent] Panel month C haracteristic M onth 1 Current spell on welfare (months): 1 to 6 ................................................. 7 to 1 2 .............................................. 13 to 2 4 ............................................ 25 to 3 6 ............................................ 37 to 4 8 ............................................ 49 to 6 0 ............................................ More than 6 0 .................................... M onth 12 M onth 24 M onth 36 M onth 48 19 11 12 11 8 6 33 25 16 13 7 7 5 28 29 18 13 7 4 5 24 28 19 18 7 6 3 20 30 19 16 8 4 4 19 Highest grade completed: Less than 10th g ra d e ...................... Some high school, no diploma or equivalent................... 19 20 19 18 19 24 26 27 27 26 High school diploma or equivalent.................................. Some post secondary...................... 33 25 32 23 31 24 34 22 34 20 Not working due to— Temporary illn e s s ........................... Physical or mental work-limiting condition....................................... Work-preventing conditions........... 1 2 3 2 3 23 16 22 16 26 19 24 21 26 21 Never m arried..................................... Rental assistance.............................. 45 31 47 31 48 32 51 32 51 32 White non-Hispanic............................ Black non-Hispanic............................ Other non-Hispanic............................ Hispanic............................................... 38 36 5 21 35 37 6 22 32 39 6 24 29 38 7 26 29 35 8 29 S outce : 1996 panel of the Survey of Income and Program Participation. children declined fairly steadily from 1993 before leveling off in months 24 through 48 of the 1996 panel, corresponding roughly to calendar years 1998 and 1999. (See chart 1.) As in the CPS data, even in the bottom quintile, female family heads have increased their employment and earnings. However, lower means-tested benefit income has more than offset the earnings gains. For most of the 1996 panel, about one-third of female family heads who left welfare appeared in the bottom income quintile each month. As welfare caseloads dropped, the total number of leavers increased until, towards the end of the panel, leavers made up nearly one-third of the bottom quintile of monthly income. Until the last wave of the 1996 panel, afdc /tanf leavers in the bottom quintile have averaged lower household incomes than others in that quintile. (See chart 2.)22 Their growing num bers have exerted a downward pressure on the quintile mean. Data from the s ip p presented here are generally consistent with findings of the many State-level studies regarding per sons who left the afdc /ta n f rolls in the last several years, and with survey data from the March CPS. SIPP provides some additional points of comparison and detail. Signs of later improvements • Data from the March 2000 CPS show strong improvements in annual income from 1998 to 1999 at the bottom of the income 18 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 distribution of female family heads with children. As in other recent years, employment and earnings increased in the bot tom quintile, while tan f and food stamp benefits declined. However, unlike years since 1995 in the March CPS series, for 1999, earnings gains surpassed means-tested benefit declines. The decline in monthly income of female heads with chil dren in the bottom quintile in s ip p has slowed. (See chart 3.) However, improvement, like we see in the annual CPS data, is not evident. Summary Of a cohort of afd c /t a n f recipients who left the rolls in the first 2 years of the 1996 s ip p panel, and could be observed for 12 consecutive post-exit months, half had earnings in their exit month and two-thirds were employed Chart 1. Monthly pre-tax money income plus food stamps of fem ale family heads with children, 1993 and 1996 panels of the Survey of Income and Program Participation 1999 dollars Chart 2. 1999 dollars Monthly mean househould pre-tax money plus food stamps among the bottom quintile of fem ale family heads with children in the 1996 Survey of Income and Program Participation 1999 dollars 1999 dollars $600 --------$600 Bottom quintile, except leavers 550 - 550 500 \ / 500 \ All female family \ heads in the \ bottom quintile 450 - 450 AFDC/TANF leavers 400 400 350 350 300 _i____i____i____i____I____L 96.5 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 96.10 _l___I___I___I___I___I___I___I___I__ I___I___I___L_ 96.15 96.20 96.25 300 96.30 96.35 96.40 96.45 1966 SIPP panel months Monthly Labor Review July 2001 19 Welfare Reform Chart 3. Bottom quintiles of constant-dollar pre-tax family money income plus food stamps for fem ale family heads with children, 1995-99 Index Index [1995 = 1.0] [1995 = 1.0] 1.05 1.0 0.95 0.9 0.85 0.8 at some point in the observation year. These rates are comparable with the other leavers studies, and also with employment rates among leavers in earlier s ip p panels. • Self-reported work-preventing health conditions appear to be more prevalent among recipients on the TANF rolls in 1999 than 1996. • Of the two-thirds of leavers with some employment in their post-exit year, about half worked 50 weeks or more, and 40 percent of those worked 35 or more hours in all weeks. • • About 4 percent of all leavers reported no household income in the exit month. (Among those with no earnings in the exit month, the share was 6 percent.) Nearly twothirds of all leavers reside with other household members with incomes. Bottom-quintile leavers whose exits are observed in the 1996 s ip p panel had income that averaged less than the income of other households in the bottom quintile for most of the panel. Leavers increased as a share of all households in the bottom quintile, and contributed to income declines among the poorest fifth. • Income improvement like that seen in the 1999 CPS bot tom quintile of female family heads with children is not evident in the last 12 months of the 1996 s ip p panel, al though income declines appear to have slowed. • When household income, rather than personal income, is the measure analyzed, a larger proportion of leavers ex perience income improvements in their post-exit year. However, about half of all leavers averaged lower post exit than pre-exit household incomes. The apparent consistency of these SIPP data with other sources highlights an emerging picture of welfare reform. The s i p p ’s earlier panels and rich content represent a great re source for expanding and detailing this picture. □ Notes 1 State leavers studies are summarized in U.S. Department of Health “Welfare Reform; Information on Former Recipients’ Status,” g ao / and Human Services, “Summary of Research on Welfare Outcomes hehs-99-48 (U.S. General Accounting Office, April 1999). Funded by a spe : Administrative Data Findings from Interim Reports” Also see Pamela Loprest, “Families Who Left Welfare: Who Are (U.S. Department of Health and Human Services, April 2000); and They and How Are They Doing?” Discussion Papers 99-02 (Washing- 20 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 ton, DC, The Urban Institute, 1999). Loprest presents information from the unique National Survey of American Families that asked 2-year retro spective welfare transition questions of a sample designed to provide State-level statistics for 13 States. A summary of research on the earnings of former welfare recipients and data from the National Longitudinal Survey of Youth ( n lsy ) are available in Maria Candan, Robert Haveman, Thomas Kaplan, Daniel Meyer, and Barbara Wolfe, “Work, Earnings, and Well-Being after Welfare: What Do We Know,” Joint Center for Poverty Research Working Paper no. 5 (February 1999). A rich dataset from a three-city study describes characteristics and distinguish levels of depen dence among leavers in Robert Moffitt and Jennifer Roff, “The Diversity of Welfare Leavers,” Policy Brief 00-2, Welfare, Children, and Families Study (Johns Hopkins University, August 2000). 2 See Richard Bavier, “An early look at the effects of welfare reform,” manuscript, April 1999 and “A second look at the effects of welfare reform,” presented at the December 1999 American Enterprise Institute conference, “Child Well Being Under Welfare Reform;” Wendell Primus, Lynette Rawlings, Kathy Larin, and Kathryn Porter, “The Initial Impacts of Welfare Reform on the Economic Well-Being of Single-Mother Fami lies with Children” (Center on Budget and Policy Priorities, August 1999); and Ron Haskins, “Welfare in a Society o f Permanent Work,” manu script, December 1999. All of these studies present descriptive statistics from the March Current Population Survey and find post-1995 income declines in the bottom quintile of female family heads with children despite increased employment. In another study, Robert Schoeni and Rebecca Blank employ cps data to estimate the impact of federal waivers and the Personal Responsibility and Work Opportunity Act of 1996 on welfare participation, employment, family formation, and income. See Robert Schoeni, and Rebecca Blank, “What Has Welfare Reform Accom plished? Impacts on Welfare Participation, Employment, Income, Pov erty, and Family Structure,” manuscript, February 2000. 3 The analysis follows the convention of counting only status changes lasting 2 months or more. Among leavers studies, Loprest “Families Who Left Welfare,” 1999, uses a 1-month status change while the Health and Human Services study, “Summary o f Research on Welfare Outcomes Funded by ASPE,” 2000, explains that the approach it sponsored “ex cludes cases that re-open within 1 or 2 months, because such cases are more related to administrative ‘churning’ than to true exits from wel fare.” Short spells off the rolls clearly are not “true exits from welfare” if that means permanent exits, though they may be part of an exit process that involves one or more returns before a long-term exit. Whether short exits are of analytical interest remains to be seen. The leavers studies that Health and Human Services summarizes usu ally exclude “child-only” cases, in which the needs of the adult caretaker are not included in the grant. See Health and Human Services, “Summary of Research on Welfare Outcomes Funded by aspe,” 2000, table 1. Through most of the 1996 panel, it was not possible to distinguish child-only cases from others. Welfare leavers who are not the biological, adoptive, or step parents of any children covered by the grant, or who receive ssi, are likely to be heads of child-only cases. When such leavers are excluded, employ ment patterns are similar and return rates slightly higher. 4 The Census Bureau plans to release a complete longitudinal file from the 1996 panel in 2001. To support longitudinal analysis, longitu dinal weights will be applied for persons who are in the sample at the beginning and also at the end of the panel. Analysis using these weights will not include persons who are lost to the sample before the end, or who enter sample households in the middle. This approach simplifies weight ing and is necessary if longitudinal analysis requires all 48-panel months, but for cross-sectional analysis, or longitudinal analysis of shorter periods, fewer weighted sample cases are available for analysis than when wave files and weights are employed. The cohort of 1996-97 leavers used in this article includes 178 persons, or 15 percent of all 1,178 observed leavers, who either were not in the sample in the first wave or not still in the sample in month 36. 5 Health and Human Services, “Summary of Research on Welfare Outcomes Funded by a spe ,” 2000, table 2. 6 Gary Burtless, “Can the Labor Market Absorb Three Million Wel- https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis fare Recipients?” (Washington, DC, The Brookings Institution, March 2000), third draft. 7 Standard errors were estimated by generalized variance parameters provided in sipp documentation by the Bureau of the Census. 8 Welfare receipt is measured as variable R 20=l. Exit month em ployment is measured in longitudinal files as the employment status recode variable esr greater or equal to 1 and less than or equal to 5. For the 1993 and 1996 wave files, employment status means at least 1 week in the month with a job, as measured by variable rmwkwjb . The decline in exit-month employment in 1998 and 1999 is not paralleled by a decline in the mean number of months worked in the post-exit year. 9 Health and Human Services, “Summary of Research on Welfare Outcomes Funded by aspe ,” 2000, table 4. 10 Toby Herr, Robert Halpem, with Aimee Conrad, “Changing What Counts: Re-Thinking the Journey Out of Welfare” (Center for Urban Affairs and Policy Research, Northwestern University, April 1991). 11 Health and Human Services, “Summary of Research on Welfare Outcomes Funded by aspe ,” 2000, tables 2 and 3. 12 Cancian, and others “Work, Earnings, and Well-Being after Wel fare,” 1999, table 2. 13 U.S. Department of Health and Human Services, “Temporary Assistance for Needy Families (tanf ) Program, Third Annual Report to Congress” (U.S. Department of Health and Human Services, August 2000), chapt. XIV. 14 Moffitt and Roff, “The Diversity of Welfare Leavers,” 2000. 15 To estimate the marginal effects of predictors on the probability of being an income loser, the logit parameter estimates were applied to the binary values of the corresponding variables of each sample leaver. See William H. Greene, Econometric Analysis, Third Edition (Upper Saddle River, New Jersey, Prentice Hall, 1997). 16 Nicholas Zill, Kristin A. Moore, Christine Winquist Nord, and Thomas Stief, “Welfare Mothers as Potential Employees: A Statistical Profile Based on National Survey Data” (Washington, DC, Child Trends Inc., February 1991). 17 Eleanor Lyon, “Poverty, Welfare and Battered Women: What does the research tell us?” (Office of Justice Programs, U.S. Department of Justice (rev.), January 1998). 18 Also see, Gene Falk and Alice Butler, “Welfare Reform: The Char acteristics of tanf Families in fy 1999,” RL30951 (Congressional Re search Service, May 2001). 19 Sec. 408(a)(7) of the Personal Responsibility and Work Opportu nity Reconciliation Act of 1996 prohibits federally funded assistance to a family that includes an adult who has received assistance for 60 months under the State's tanf program. However, a number of exceptions are provided, including exemption of up to 20 percent of the State's average monthly caseload for a fiscal year. 19 Maria Cancian, Robert Haveman, Daniel Meyer, and Barbara Wolfe, “Before and After tan f : The Economic Well-Being of Women Leaving Welfare” (Madison, wi, Institute for Research on Poverty, May 2000 ). 20 Bavier, “A second look at the effects of welfare reform,”1999; and Primus and others, “The Initial Impacts of Welfare Reform,” 1999. 21 Note that, unlike the preceding analysis of a cohort of leavers, the analysis of the place of leavers in the income distribution is not limited to recipients who leave for at least 2 months and can be observed for at least 12 post-exit months within the first 36 months o f the panel. Rather, a female family head is classified as a leaver if she received afcd / tanf at any earlier point in the panel and is in the sample, but not receiving afdc /tanf in the month of measurement. Monthly Labor Review July 2001 21 Welfare Reform Appendix: Sample loss and item non-response in the 1996 sipp panel Like other household surveys, the Survey of Income and Program Participation ( s ip p ) has suffered increasing sample loss and increas ing item nonresponse. Table A -l displays rates of sample loss and imputation from waves of the 1993 and 1996 panels that correspond roughly to the beginning of calendar years. Not all sample loss is due to refusals to participate. Some of the original eligible persons in the sample either died or moved from the household. Imputation here includes cases in which income amounts are derived from other in formation known about the sample household, and not just cases in which income amounts of similar matched households are assigned to nonreporters. Comparing administrative case counts to survey counts of a f d c / TANF recipients, the author finds that the March cps captured around four-fifths of administrative totals for many years, but has found only a little over two-thirds in recent years.1 s ip p appears to do better, but, as table A-2 shows, this is a result of higher imputation rates in the 1996 panel. The Bureau of the Census has compensated for sample loss by increasing the weights of households remaining in the sample. It compensates for item nonresponse by imputing responses. If lost sample households are like remaining households with matchable characteristics, and if households that do not report some items would have reported like other similar households, the analysis in the article would not be affected by sample loss and item nonresponse. However, although the patterns described in the ar ticle are not significantly changed when the analysis is duplicated without including imputed months of a f d c /t a n f receipt, there is evi dence that leavers who can be followed for 12 consecutive post-exit months are more likely to be employed at the time they exit the welfare system than leavers who are lost to the sample. This suggests that the longitudinal data set used in the article may represent a somewhat more employable and successful subpopulation of leavers.2 Table A - l. When a data set of leavers identified without counting any imputed months of a f d c / t a n f receipt is examined, the charac teristics are very similar to those mentioned in the article. With no imputed months of a f d c / t a n f receipt counted, 67 percent of leavers (2-consecutive months off the rolls and observable for 12 consecutive post-exit months) were employed at some point in the followup year, compared with 66 percent when imputed a f d c / t a n f receipt is counted. Without imputation, 24 percent of leavers return within a year; with imputation, 25 percent return to welfare. In table A-3, the only difference that is statistically signifi cant is the rate of food stamp receipt while receiving a f d c / t a n f . Without counting imputed a f d c / t a n f months of receipt, a f d c / t a n f leavers are more likely to have received food stamps in the months before they exited. While imputation is becoming more common in the 1996 SIPP panel, characteristics of leavers appear similar whether imputed months of a f d c / t a n f are counted or not. Sample loss, on the other hand, appears to create a potentially more serious problem for the analysis in the article. In table A-4, leavers who could be observed for 12 consecutive post-exit months are significantly more likely to have a job in the exit month, suggesting that lost sample households represent a more disadvantaged group. If so, the experience of wel fare leavers may not be as positive as the article finds. Notes to the appendix 1 See Richard Bavier, “An early look at the effects of welfare re form,” manuscript, April 1999. 2 Constance Citro and Graham Kalton (eds.), The Future o f the Survey o f Income and Program Participation (National Research Coun cil, Washington DC, 1993), pp. 103-4. Rates of sipp sample loss 1993-99 [ In percent] Panel w a v e Eligible sa m p le with no d a ta ' Households with d a ta th at h a v e som e im putation 8.9 28.3 37.2 9.6 18.2 33.0 51.2 12.5 24.3 34.5 58.8 14.0 8.4 35.2 43.6 13.8 20.9 46.9 67.8 20.4 29.9 48.6 78.5 21.7 34.0 49.8 83.8 22.3 1993 (93 panel wave 1) ...................... 1994 (93 panel wave 4 ) ...................... 1995 (93 panel wave 7 ) ...................... 1996 (96 panel wave 1) ...................... 1997 (96 panel wave 4 ) ...................... 1998 (96 panel wave 7 ) ...................... 1999 (96 panel wave 1 0 )................... ’ Eligible households not interviewed in wave. 22 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 S ource : S am p le with no d a ta or so m e in c o m e im pu tation1 Total in c o m e im p u ted Survey of Income and Program Participation. Table A-2. Recipients of Aid for Families with Dependent Children/Temporary Assistance for Needy Families, 1993, 1994, 1996, 1997 D a te AFDC/TANF to ta l c a s e s a d m in is tra tiv e re c o rd s AFDCSIPP/ a d m in is tra tiv e (p e r c e n t) SlPP w ithou t im p u ta tio n / SIPP/AFDC/ t a n f r e c ip ie n ts Im p u te d (p e r c e n t) 4,214,108 4,297,566 4,398,595 4,366,193 4,466,265 4,394,291 4,385,749 4,350,579 4,250,952 4,217,728 4,230,108 4,275,707 1.2 1.0 1.1 1.0 1.2 1.4 1.0 .7 .6 .5 .6 .6 4,899,621 4,906,838 4,952,644 4,968,337 4,945,366 4,941,319 4,938,783 4,958,594 4,960,740 4,962,176 4,962,974 4,987,900 86.0 87.6 88.8 87.9 90.3 88.9 88.8 87.7 85.7 85.0 85.2 85.7 85.0 86.7 87.9 87.0 89.2 87.7 87.9 87.1 85.2 84.6 84.7 85.2 4,253,895 4,292,313 4,318,851 4,557,181 .9 .6 .8 1.0 4,990,499 4,986,311 5,036,478 5,018,464 85.2 86.1 85.8 90.8 84.5 85.5 85.1 89.9 3,462,309 3,522,569 3,608,195 3,590,274 3,538,517 3,554,338 3,545,940 3,563,579 3,494,398 3,438,224 3,402,821 3,408,567 4.4 3.7 3.4 4.7 6.5 8.7 10.0 10.2 9.8 10.2 10.8 11.7 4,567,088 4,555,344 4,547,661 4,507,153 4,458,740 4,402,463 4,372,580 4,355,023 4,292,916 4,248,386 4,164,208 4,114,122 75.8 77.3 79.3 79.7 79.4 80.7 81.1 81.8 81.4 80.9 81.7 82.9 72.4 74.4 76.6 75.9 74.2 73.7 73.0 73.5 73.4 72.7 72.9 73.2 3,391,654 3,362,171 3,277,607 3,162,332 3,041,482 2,947,082 2,910,110 2,820,656 2,934,104 12.4 12.7 13.2 14.7 13.9 14.5 15.7 14.2 15.9 4,061,732 4,019,231 3,975,266 3,906,643 3,830,071 3,737,927 3,620,339 3,562,026 3,495,337 83.5 83.7 82.5 80.9 79.4 78.8 80.4 79.2 83.9 73.2 73.0 71.5 69.1 68.3 67.4 67.8 67.9 70.6 a d m in is tra tiv e (p e r c e n t) 1993 January....................................... February...................................... M arch.......................................... A pril.............................................. M a y .............................................. J u n e ............................................ J u ly .............................................. A u g u s t........................................ September................................... O ctober....................................... November.................................... December.................................... 1994 January....................................... February...................................... M arch.......................................... A pril............................................. 1996 January....................................... February...................................... M arch.......................................... A pril.............................................. M a y .............................................. J u n e ............................................ J u ly .............................................. A u g u s t........................................ September................................... O ctober....................................... November.................................... December.................................... 1997 January....................................... February...................................... M arch.......................................... A pril.............................................. M a y ............................................. J u n e ............................................ J u ly .............................................. A u g u s t........................................ September................................... Data are from the Survey of Income and Program Participation, 1993 and 1996 panel wave files and from Administration for Children and Families. (Data do not include U.S. territories). S ource : https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 23 Welfare Reform Table A-3. Characteristics of 1996-97 welfare leavers with and without imputed AFDC/TANF receipt C h a rac teristic With im putation Leavers (num be r).............................................................................................................. 3,336,441 2,958,531 68.3 95.2 3.6 73.7 96.1 3.0 62.4 44.4 25.0 11.9 9.3 3.4 8.9 5.0 3.4 .3 .7 62.7 62.5 45.7 26.8 12.3 4.3 2.8 8.3 5.1 3.9 .4 .6 68.1 Percentage of leavers— Receiving food stamps in pre-exit m o nth..................................................................... Receiving medicaid in pre-exit m onth........................................................................... With zero household income in exit m o n th ................................................................. With income in exit month from— Other household m em bers............................................................................................. Food s ta m p s ................................................................................................................... Rental assista nce........................................................................................................... Child sup port................................................................................................................... General assistance......................................................................................................... Other w elfare................................................................................................................... Own Supplemental Security Insurance........................................................................ Child’s Supplemental Security Insurance..................................................................... Child’s Social S e c u rity ................................................................................................... Unemployment compensation........................................................................................ Foster c a re ....................................................................................................................... Former recipient medicaid in exit m o n th ......................................................................... S ource: No im pu tation 1996 Panel of the Survey of Income and Program Participation. Characteristics of 1996-97 welfare leavers observed for 12 post-exit months and leavers lost to sample C haracteristic Follow ed for 12 months S tan dard error Lost from s a m p le S tan d ard error Leavers (num ber)................................................. 3,336,441 Percentage: Never m arried..................................................... M a le .................................................................... B la ck................................................................... 41 14 34 2.0 1.4 1.9 46 14 36 4.2 2.9 4.1 A t exit: Have a jo b .......................................................... Rental assistance............................................. Three or more ch ild re n ...................................... Related sub -fam ily............................................ 47 25 22 12 2.0 1.8 1.7 1.3 39 25 22 16 4.1 3.7 3.5 3.1 Unrelated sub-fam ily......................................... Less than 9lh g ra d e ........................................... Some high school.............................................. Work-limiting condition...................................... 2 12 26 22 .6 1.3 1.8 1.7 4 14 28 17 1.6 3.0 3.8 3.2 S ource : 24 1996 panel of the Survey of Income and Program Participation. Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 760,116 Producer Prices, 2000 Producer prices in 2000: energy goods continue to climb Soaring natural gas prices sparked higher inflation among finished, intermediate, and crude goods, resulting in the steepest increase in the finished goods index in 10 years William F. Snyders William F. Snyders is an economist in the O ffice of Prices and Living Conditions, Bureau of Labor Statistics. E-mail: snyders_w@bls.gov https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis he Producer Price Index ( p p i ) for Finished Goods advanced 3.6 percent in 2000, the largest annual gain since 1990. Excluding energy goods, the index for finished goods rose 1.5 percent. The p p i for finished consumer foods was up 1.7 percent in 2000. The index for pro ducer prices for finished goods excluding foods and energy advanced 1.3 percent in 2000, fol lowing a 0.9-percent increase in 1999. This in dex includes both consumer goods and capital equipment. Price movements for intermediate goods and crude goods followed a pattern similar to that of finished goods. The index for intermediate goods rose 4.1 percent in 2000, following a 3.7-percent gain in 1999. (Intermediate items in the p pi reflect changing prices for material inputs to the manu facturing process, as well as various supplies consumed in the production process.) The crude goods index advanced 35.5 percent, after rising 15.3 percent in the previous year. (Generally, crude goods are unprocessed goods that are outputs from mining industries and agricultural production.) (See chart 1.) For energy goods at the crude stage of pro cessing, higher inflation was observed in 2000 compared with 1999. However, price increases slowed for both intermediate and finished en ergy goods, while price advances for crude pe troleum and petroleum-based products deceler ated from 1999 to 2000. Prices for foods and food-related materials at the crude and intermediate stages of processing rose in 2000. The intermediate “core” index, which T removes the volatile foods and energy compo nent, slowed to a 1.6-percent increase in 2000, following a 1.9-percent advance a year ago. By contrast, prices for crude core items decreased 5.5 percent, after increasing 14.0 percent in 1999. (See table 1.) Energy goods Skyrocketing natural gas prices and double-digit price increases for many crude petroleum-based items helped push energy prices higher for all three stages of processing in 2000. The index for finished energy goods rose 16.6 percent, follow ing an 18.1-percent advance in 1999. Price in creases were observed for finished energy items, such as residential natural gas, gasoline, resi dential electric power, and home heating oil. Prices for intermediate energy goods advanced 19.0 percent, after having increased 19.6 percent a year earlier. The indexes for jet fuels, commer cial and industrial natural gases, diesel fuel, liq uefied petroleum gas, and commercial electric power continued to increase in 2000. The crude energy goods index jumped 85.6 percent, follow ing a 36.9-percent gain in 1999, as prices contin ued to rise for natural gas and crude petroleum. (See table 2.) Natural gas. Decreasing supplies of natural gas, rising crude oil prices, and weather-related de mand helped push residential, commercial, and industrial natural gas prices to their highest lev els since the publication of these indexes began Monthly Labor Review July 2001 25 Producer Prices, 2000 Chart 1. Annual percent changes for stage of processing indexes, 1990-2000 Percent Percent in December 1990. The producer price index for natural gas posted a record 192.6-percent rate of increase, as demand outpaced supply most of the year. June and December regis tered the two largest gains for the year, rising 38 percent and 42.3 percent respectively. Due to industry regulation, the ma jority of natural gas utility companies are inhibited from pass ing along their higher input costs directly to residential and commercial customers. However, natural gas utility compa nies are able, with little regulatory guidance, to pass on their higher input costs to their industrial customers, who then absorb and pass on these costs indirectly in their own costs of doing business. Residential gas prices increased 41.8 per cent, commercial natural gas prices rose 56 percent, and in dustrial natural gas prices jumped 91.9 percent for the year. (See chart 2.) By spring and early summer, supplies of natural gas tight ened and prices began climbing throughout the rest of the year. Above-average temperatures and reduced electric out put from nuclear power plants in the summer of 2000 meant that utilities had to produce more electricity using natural gas. As colder temperatures arrived in December, natural gas usage shifted to heating. The resulting withdrawals from al ready low inventories pushed prices even higher. As of De cember 2000, natural gas storage levels stood at 1,720 billion cubic feet; 803 billion cubic feet less than the available stor 26 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 age levels in December 1999.1 Petroleum-based products. Led by strong global demand, crude petroleum prices continued to rise for most of the year, but at a much slower pace than in 1999. The p p i for crude petroleum increased 11.0 percent from December 1999 to De cember 2000, after jumping 172.0 percent from December 1998 to December 1999. Throughout the summer, crude petroleum stocks in the United States reached a 24-year low, pushing down domestic supplies.2 Petroleum prices declined some what, however, at the end of 2000, as a result of the Organiza tion of Petroleum Exporting Countries ( o p e c ) decision to in crease oil production by 800,000 barrels a day and the U.S. decision to tap the U.S. Strategic Petroleum Reserve for 30 million barrels of oil. Looking closer at refined petroleum goods, the jet fuels index increased 42.6 percent in 2000, due to the rising cost of oil and diminishing supplies. During the first quarter, prices were higher, because supplies were weak throughout that period. Prices then leveled off through the summer as inven tories rebounded and prices per crude oil decreased, a result of an increase in o p e c production. By September, enough high demand for jet fuels and the return of rising oil costs helped raise jet fuel prices. Diesel fuel prices increased 39.8 percent in 2000, a result 1 A n n u a l p e r c e n t c h a n g e s for m a or c a te g o r ie s o f th e P ro d u c e r P rice In d e x b y s ta g e o f p ro c e s s in g , 1991 - 2 0 0 0 Index 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Finished g o o d s ......................................... Foods...................................................... E n e rg y.................................................... O th e r...................................................... -0.1 -1 .5 -9 .6 3.1 1.6 1.6 -.3 2.0 0.2 2.4 -4.1 .4 1.7 1.1 3.5 1.6 2.3 1.9 1.1 2.6 2.8 3.4 11.7 .6 -1 .2 -.8 -6 .4 .0 0.0 .1 -11.7 2.5 2.9 .8 18.1 .9 3.6 1.7 16.6 1.3 Intermediate materials, supplies, and com ponents.................. Foods and fe e d s ................................ E nergy.................................................. O th e r.................................................... -2 .6 -.2 -11.6 -.8 1.0 -.5 .7 1.2 1.0 5.5 -4.2 1.6 4.4 -4 .5 2.9 5.2 3.3 10.3 1.1 3.2 .7 2.1 11.2 -.9 -.8 -1 .7 -7 .0 .3 -3 .3 -7 .3 -12.1 -1 .6 3.7 —4.2 19.6 1.9 4.1 3.6 19.0 1.6 Crude materials for further processing .. Foodstuffs and fee d stu ffs................ E nergy.................................................. O th e r.................................................... -11.6 -5 .8 -16.6 -7 .6 3.3 3.0 2.3 5.7 .1 7.2 -12.3 10.7 -.5 -9 .4 -.1 17.3 5.5 12.9 3.7 14.7 -1 .0 51.2 -5 .5 -11.3 -4 .0 -23.1 .0 -16.7 -11.0 -23.8 -16.0 15.3 -.1 36.9 14.0 35.5 7.4 85.6 -5.5 of the low supply of distillates and the rising costs of oil. In the first quarter, diesel fuel prices climbed as the supply of distillates plummeted. For the 12 months ended in February 2000, the diesel fuel index more than doubled, which caused a cavalcade of truck drivers to protest by driving through the streets of Washington d c , in search of Federal relief via the immediate removal of diesel fuel taxes. By April and May, prices eased as warmer temperatures decreased the demand for distillates, but then prices increased throughout the third quarter in anticipation of a major winter shortage of distil lates and the return of higher crude oil prices. Gasoline prices increased by 17.2 percent from December 1999 to December 2000, mainly because of an 11 -percent rise in the price of oil over the same time period. Crude oil, gaso line, and home heating oil all showed similar movements over the last 2 years. (See chart 3.) Large price increases for gaso line took place in the first quarter of 2000, as rising oil costs and low inventories put upward pressure on prices. Prices - 4 .2 fell in April, when o p e c announced it would increase oil pro duction by 1.7 million barrels per day to counteract rising global oil prices. By early June, however, gasoline prices rose to their highest levels in nearly 20 years due to rising summer demand. By the end of 2000, gasoline prices began to decline as the release of oil from the Strategic Petroleum Reserve helped lower oil costs. Home heating oil prices increased 37 percent for the 12 months ended in December 2000, driven by rising oil costs, an extremely low supply of distillates, and cold winter tem peratures. The high demand and shortage of gasoline in the summer months caused oil refineries to focus all available resources on gasoline production, thereby reducing the buildup of heating oil supplies. Prices climbed throughout the summer, as refiners anticipated winter shortages, but be ginning in October, prices declined with the supply assis tance of the Strategic Petroleum Reserve. Among other petroleum products, prices for liquefied pe- I Annual percent changes in Producer Price Indexes for selected energy items, 1995-2000 1995 1996 1997 1998 1999 2000 Finished energy g o o d s ........................... Residential natural g a s ....................... G a s o lin e ............................................... Residential electric p o w e r.................. Home heating o il................................... 1.1 -2 .4 2.4 .9 11.9 11.7 11.2 27.1 .6 25.0 -6 .4 2.4 -15.0 -.2 -21.7 -11.7 -2 .4 -33.1 -2 .5 -36.1 18.1 .9 74.8 -.5 89.4 16.6 41.8 17.2 3.2 37.0 Intermediate energy go ods..................... Jet fu e ls ................................................ Commercial natural g a s ...................... Industrial natural g a s .......................... Diesel fu e ls .......................................... Liquefied petroleum g a s ...................... Commercial electric p o w e r................. Industrial electric po w e r...................... 1.1 6.1 -3.9 -4 .6 11.1 3.9 .6 .2 11.2 26.1 16.8 22.3 26.2 71.4 -.1 .0 -7 .0 -22.3 .9 3.1 -22.5 -29.3 .0 .5 -12.1 -35.8 -4 .7 -9 .7 -33.8 -32.6 -1 .8 -1 .3 19.6 90.9 4.1 7.4 86.4 87.0 .6 -,1 19.0 42.6 56.0 91.9 39.8 49.3 4.4 4.9 Crude energy m aterials........................... Natural g a s ........................................... C o a l....................................................... Crude pe troleu m ................................... 3.7 -.3 -.8 10.8 51.2 92.0 -1.1 35.8 -23.1 -27.9 4.9 -28.3 -23.8 -17.8 -1 .2 -48.6 36.9 7.9 -9 .3 172.0 85.6 192.6 .0 11.0 In dex https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 27 Producer Prices, 2000 Chart 2. Residential natural gas, 1998-2000 12-month percent change 12-month percent change 60 40 20 0 -20 -40 troleum gas rose 49.3 percent, following an 87-percent in crease a year earlier. As for many other energy commodities, the 2000 increase in the index was a result of rising oil and natural gas prices. Electric power Residential electric power prices increased 3.2 percent, following a 0.5-percent decline in 1999. Increased weather-related demand and the electricity crisis in California were the main causes for the acceleration. Demand for elec tricity rose, as many regions of the United States experienced hot summer temperatures and colder-than-normal tempera tures throughout the fall. An 83.1-percent jump in prices for natural gas to electric utilities (input costs to electricity in dustries) also contributed to higher residential electricity prices in 2000. As natural gas prices skyrocketed during the year, many electricity producers increased their rates in the form of fuel cost adjustments. In addition to residential elec tricity, the high cost of natural gas also was passed on in electricity prices for commercial and industrial uses. The in dex for commercial electric power rose 4.4 percent, after in creasing 0.6 percent in 1999. Industrial electricity prices ad vanced 4.9 percent in 2000, following a 0.1-percent decline in the previous year. 28 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 Food and related products Producer prices for finished consumer foods advanced 1.7 percent in 2000, following a 0.8-percent gain in the previous year. Nearly one-third of the 2000 increase can be traced to an 8.2-percent rise in beef and veal prices. Moreover, price in creases for eggs for fresh use, dairy products, bakery prod ucts, and pork contributed to higher finished consumer foods prices in 2000. Led by rising prices for prepared animal feeds, the pro ducer price index for intermediate foods and feeds rose 3.6 percent in 2000, after falling 4.2 percent a year ago. Prices for crude foodstuffs and feedstuffs advanced 7.4 percent, after edging downward 0.1 percent in 1999. Contributing to this turnaround were price increases for fluid milk, com, soy beans, and wheat. (See table 3). Chicken eggs. The eggs for fresh use index soared 46.3 percent in 2000, after falling 27.4 percent in the prior year. In 1999, chicken egg producers experienced a period of gross overproduction, caused mainly by a large oversupply of egglaying hens. However, by the year 2000, price levels began to rebound as desperate producers lowered egg production by removing seven million hens from the U.S. flock. This was accomplished by the combination of higher cull rates and drops in the number of egg-laying hens being hatched. Dairy products. The index for dairy products was up 3.2 percent, after falling 11.1 percent in 1999. Prices for fluid milk rose 7.0 percent for the 12 months ended in December 2000. During the winter of 2000, milk production decreased, as a result of cows suffering stress from cold weather. December milk supplies were also lowered by higher energy prices and power-related problems, especially in California, the largest producer of milk in the country. As the State of California experienced numerous power blackouts, farmers and proces sors were forced to remove milk that had spoiled. In addition, processors in California, as well as in other areas of the United States, were operating shorter hours to save on energy costs, which ultimately fiirther lowered milk supplies and raised prices. Grains. Com prices rose 7.8 percent for the 12 months ended in December 2000, compared with a 12.4-percent drop in the previous year. The com futures market had an extremely vola tile year in 2000. Com production totaled 9.97 billion bushels, up 6 percent from 1999, and was the second largest crop behind 1994’s record production of 10.1 billion bushels.3 As Chart 3. a result, the large crop pushed com prices lower in June, July, and August. However, com prices then rebounded through out the remainder of the year. Soybean prices advanced 9.9 percent in 2000, following a 17.5-percent decline a year earlier. This turnaround was due to higher demand for prepared animal feeds, a partially-pro cessed commodity of soybeans. Prices were also higher due to strong exportden and firm the European U rrbn fcu) for products such as soybean meal. The e u has since imple mented a total ban on meat and bone meal, and blood meals in animal feeds due to fears of spreading Bovine Spongiform Encephalopathy (BSE), commonly known as “mad cow dis ease.” e u farmers were compelled to increase their use of alternative animal feeds such as soybean meal to sustain their herds. The index for wheat increased 13.9 percent in 2000, after decreasing at the same rate during 1999. The months of July and August experienced weaker prices, as low com prices and sharp competition from abroad caused the price of wheat to decline. However, the wheat index rebounded in the fall, posting a 6.3-percent rise in September and a 9.7-percent increase in October. This rally was brought on by rising com futures caused by unusually high international demand, which influenced wheat trades. Energy Index levels, monthly, 1998-2000 Index level https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Index level 120 100 80 60 40 20 Monthly Labor Review July 2001 29 Producer Prices, 2000 Collectively, higher prices for grains in 2000 put upward pressure on prices for prepared animal feeds. This index rose 8.3 percent for the year, after decreasing 2.7 percent in 1999. Flour. The price of flour increased 7.9 percent for the year ended in December 2000, compared with a 7.5-percent de cline in 1999. Wheat prices heavily influence flour prices, and the extremely volatile wheat market contributed to the posi tive annual percent change during 2000, and the negative annual change during 1999. Higher prices for flour helped push up the index for bakery products, which increased 2.7 percent in 2000. Meats. After a 266.9-percent surge in 1999, slaughter hog prices rose 14.9 percent in 2000. Slaughter hog prices stayed well above the break-even point for most of 2000, an occur rence not realized since 1997. In the finished and intermediate stages of processing, the pork index increased 5 percent in 2000, after jumping 29.8 percent in the prior year. Overall, pork prices continued their climb from the early 1999 levels by virtue of good domestic demand for meat products and an improvement in the export market. In 2000, prices for slaughter cattle and for beef and veal continued to show upward movements in 2000, rising 9.1 percent and 8.2 percent respectively. These increases were the result of strong domestic demand for beef products, par ticularly for high quality beef products. While beef produc tion was up 1.5 percent in 2000, prices for choice cuts of beef at retail were a record $3.06 a pound. Retail beef prices rose 6.5 percent, more than the 1999 average and 4.6 percent, more than the previous record of $2.93 a pound, set in 1993.4 Among other food items tracked in the p p i , price declines were observed in 2000 for fresh and dry vegetables, roasted coffee, fresh fruits and melons, refined sugar, and crude veg etable oils. Finished goods other than foods and energy As previously mentioned, the p p i for finished goods other than foods and energy— the “core” index— accelerated slightly from a 0.9-percent rate of increase in 1999 to a 1.3percent rise in 2000. This acceleration in prices was broadly based. Prices for finished consumer goods other than foods and energy rose 1.4-percent, following a 1.2-percent increase in 1999. Among this category, prices accelerated for such items as alcoholic beverages, prescription drugs, and light trucks. The capital equipment index rose 1.2 percent for the 2000 calendar year, after gaining just 0.3 percent a year ago. Rising prices were observed for producers of civilian aircraft, commercial furniture, industrial material handling equipment, heavy trucks, agricultural machinery, and construction ma chinery. (See table 4.) Alcohol and tobacco products. Over the course of 2000, the index for alcoholic beverages increased by 4.2 percent. Ac cording to the 1997 Census of Manufactures, beer accounts for 30 percent of the beverage market with $18.2 billion in sales. Wine, brandy, and distilled spirits accounted for 16.6 | Annual percent changes in Producer Price Indexes for selected food items, 1995-2000 In dex 1995 1996 1997 1998 1999 2000 Finished consumer fo o d s ................... Eggs for fresh u s e ............................ Beef and v e a l..................................... Bakery products................................ Processed p o u ltry ............................. P o rk ..................................................... Dairy products.................................... Fresh fruits and m e lo n s ................... Roasted co ffe e .................................. Fresh and dry vegetables................ 1.9 31.5 -1.4 3.3 8.4 15.3 5.4 2.5 -8 .2 -36.0 3.4 15.0 7.4 3.6 2.6 21.9 2.4 37.2 —8.4 -24.3 -0 .8 -15.6 -5 .4 1.1 -6 .3 -13.6 4.7 -8 .2 18.1 21.6 0.1 -6.2 -2 .7 1.0 3.8 -27.3 10.7 -19.0 -9 .5 8.8 0.8 -27.4 10.8 1.6 -3 .7 29.8 -11.1 8.2 -.9 4.4 1.7 46.3 8.2 2.7 1.1 5.0 3.2 -1 .3 -6 .9 -23.7 Intermediate foods and fe e d s ............. Prepared animal fe e d s ...................... F lo u r.................................................... Crude vegetable o ils ......................... Confectionery m a te ria ls................... Refined s u g a r..................................... 10.3 20.6 20.1 -14.1 1.5 .8 2.1 5.4 -9.0 -9.3 2.2 4.2 -1 .7 -3.1 -8.2 13.9 -15.8 -4 .5 -7 .3 -20.4 -5 .6 -2 .7 -1 .0 .6 -4 .2 -2 .7 -7 .5 -37.5 1.7 -2 .2 3.6 8.3 7.9 -1 6.5 .7 -9 .6 Crude foodstuffs and feedstuffs......... Fluid m ilk............................................. C o rn ..................................................... Soybeans ........................................... W h e a t.................................................. Slaughter c a ttle ................................. Slaughter h o g s ................................... 12.9 8.4 49.4 26.7 29.9 -5 .2 40.6 -1 .0 1.1 -21.0 -3 .7 -19.3 -2 .5 23.2 -4.0 2.8 2.2 1.8 -11.3 2.0 -21.7 -11.0 25.6 -22.5 -21.3 -15.0 -12.0 -76.8 -.1 -31.3 -12.4 -17.5 -13.9 19.4 266.9 7.4 7.0 7.8 9.9 13.9 9.1 14.9 30 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 “ 1 Annual percent changes in Producer Price Indexes for selected finished goods other than foods and energy, 1995-2000 Index Finished goods other than foods and e n e rg y .............................. Finished consumer goods less foods and e n e rg y ...................... Alcoholic b e verag es....................... C igarettes........................................ Prescription d ru g s .......................... Light tru c k s ...................................... N ew spapers..................................... Sanitary papers and health p ro d u c ts .................... B ooks................................................ Home electronic equipm ent........... Household a p pliance s.................... Passenger c a r s .............................. Capital equipm ent........................... Civilian a ircra ft................................ Commercial furniture....................... Industrial material handling equipm ent..................................... Heavy tru c k s ................................... Agricultural m achinery................... Construction m achinery................. Communication and related equipm ent..................................... Computers........................................ 1996 1997 1998 1999 2.6 0.6 0.0 2.5 0.9 1.3 2.8 4.2 3.7 4.2 1.5 8.8 .8 3.8 3.3 2.0 .2 4.2 .3 -.5 10.0 3.6 -3 .6 .1 4.2 1.5 49.4 20.9 1.0 1.1 1.2 .6 9.6 .8 .3 1.4 1.4 4.2 1.9 3.0 1.8 4.3 14.3 6.5 -1 .0 .1 1.7 -2 .6 3.2 -1 .3 -.5 -.8 -2 .0 3.3 -3.2 -2 .5 -2 .6 -.6 4.1 -1 .7 -.3 .5 -1 .0 1.8 -2 .3 -.6 1.2 2.7 3.4 -2 .2 -1 .7 -.7 2.2 6.1 3.4 .4 3.2 2.0 -.6 1.2 .0 .5 .1 .3 2.1 1.2 1.2 6.7 1.1 2.1 4.1 4.7 2.5 1.7 -4 .5 1.4 1.8 1.4 .6 1.4 1.9 1.5 3.9 .7 1.7 .9 1.4 1.3 1.4 1.7 .7 1.2 .9 .9 -12.7 1.5 -22.3 .8 -21.5 -1.1 -26.6 -1 .9 -19.7 -1 .3 -14.2 percent, or $7.6 billion. Among tobacco products, cigarette prices rose 1.9 percent in 2000, mostly as a result of a 6cent per pack price hike in August (or $3 per 1000 ciga rettes). Cigarettes make up more than 80 percent of the overall tobacco market, with $29.3 billion in sales. Prescription drugs. In 2000, the rate of increase for prices received by pharmaceutical manufacturers was lower than the rate of inflation measured in finished goods as a whole. Producer prices for prescription drugs increased 3.0 percent, a more typical increase than those of the previous 2 years when the index rose 20.9 percent in 1998, but only 0.8 percent in 1999. Drug prices in 2000 rose moderately, as insurance companies, managed care groups, and pharmacy benefit man agers tightened reimbursement policies to customers, pres suring consumers to find cheaper generic alternatives to ex pensive brand name drugs. Cars and light trucks. Prices for passenger cars fell 0.7 per cent during 2000, after rising 1.2 percent in 1999. Total car sales were up for the year, although sales slowed substan tially in the second half of 2000, due to a drop in consumer confidence. An 18.1-percent jump in sales of small cars was observed for the year, resulting mostly from a 46-percent increase in sales for imported small cars.5 Luxury cars also showed a gain, but both mid-sized and large cars had de https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 2000 1995 .5 creases in sales. The light truck price index rose 1.8 percent during 2000, following a 0.3-percent gain in the prior year. Light truck sales for 2000 were 3.8 percent higher than in 1999, due largely to new crossover vehicles. A few segments of the market, such as small pickups and large luxury suvs, showed over-the-year decreases in sales. Collectively, sales both for cars and light trucks totaled more than 17 million in 2000. Civilian aircraft. Despite the 4.9-percent decrease in overall aircraft industry sales, the 2000 calendar year was the sec ond-best year on record, with industry profits of approxi mately $9.4 billion.6 Prices for civilian aircraft advanced 6.7 percent, after increasing 2.1 percent in 1999. Helicopters and general aviation aircraft sales both showed substantial gains in 2000. Commercialfurniture. Steady price increases were observed for producers of commercial furniture. The p p i for commercial furniture increased 1.1 percent in 2000, following a 1.2-percent gain a year earlier. Prices continued to rise moderately, as consumer purchasing remained healthy throughout 2000. Computers. Due to modern-day advances in technology associated with manufacturing computers and the increases in competition in specific markets, prices in the electronic computer industry continued their downward trend during Monthly Labor Review July 2001 31 Producer Prices, 2000 2000. Producer prices for overall computers fell 14.2 percent, after decreasing 19.7 percent in 1999. Price declines were reg istered in 2000 for large-scale and mid-range computers, per sonal computers/workstations, and portable computers. Intermediate industrial materials The p p i for intermediate materials other than foods and en ergy slightly decelerated, rising 1.6 percent in 2000, following a 1.9-percent gain in the previous year. Price increases also slowed for durable manufacturing materials and construc tion materials. In contrast, the index for nondurable manufac turing materials rose slightly more in 2000 than it did a year ago. (See table 5.) Durable manufacturing materials. The index for durable manufacturing materials edged upward 0.2 percent in 2000, after advancing 2.4 percent in 1999. Prices decreased in 2000 from their 1999 increases for building paper and board and for cement. The indexes for copper cathode and refined cop per and also for copper and brass mill shapes rose less in 2000 than in the previous year. Price declines were larger in 2000 than 1999 for plywood. By contrast, the index for steel mill products fell at a slower rate, compared with its rate of decline a year earlier. The index for building paper and board decreased 9.3 per cent, while cement prices fell 0.9 percent for the 12 months ended in December 2000. During the same period, the index for copper cathode and refined copper was up 8.3 percent, after jumping 21.7 percent a year ago. Rising prices for cop per and brass mill shapes slowed from 8.6 percent in 1999 to 3.8 percent in 2000. The copper market was boosted by re ports of world refined copper being in deficit versus surplus, good demand for the metal, and declining warehouse stocks. Plywood prices declined by 6.2 percent over the course of 2000, after edging down 0.2 percent a year earlier. The down ward trend in plywood prices resulted from fewer housing starts in 2000, with residential construction representing 48 percent of the demand for plywood. In addition, the plywood market suffered from oversupply and bad weather, which in hibited construction activities. The index for steel mill products declined 0.6 percent in 2000, after falling 2.4 percent in the previous year. The con tinued decline in prices was due to the financial collapse of many domestic steel companies in the second half of the year. Excluding the fourth quarter, 2000 was a solid year for the domestic steel industry in terms of production and sales, with prices up slightly from the year before.7 Since the early 1990s, steel mills products were in high demand, but recently mill owners have found it difficult to maintain prices in the face of import competition and surplus global capacity. As a result, many firms in the steel industry filed for bankruptcy in 2000. Construction materials. Prices for materials and components for construction inched upward 0.1 percent in 2000, after ad vancing 2.2 percent in 1999. This deceleration was brought 1 Annual percent changes in Producer Price Indexes for selected intermediate and crude materials other than foods and energy, 1995-2000 in d e x 1995 1996 1997 1998 1999 2 00 0 Intermediate goods other than fo o d s ... and e n e rg y .......................................... 3.2 -0.9 0.3 -1 .6 1.9 1.6 Durable manufacturing m a terials........ Building paper and b o ard................. Copper and brass mill shapes......... Plywood.............................................. C em ent................................................ Steel mill p roducts............................ 1.1 -5.1 2.1 -8 .5 6.0 1.3 -1 .4 -5 .8 -10.6 -1 .3 5.0 -1 .4 .0 -2 .0 -6 .5 -1.1 3.5 .5 -5 .5 -1 .3 -11.5 4.9 5.2 -6 .5 2.4 10.3 8.6 -.2 1.6 -2.4 .2 -9 .3 3.8 -6 .2 -.9 -.6 Nondurable manufacturing materials .. Industrial c he m icals.......................... Paperboard......................................... Nitrogenates....................................... P aper................................................... 5.9 1.1 16.3 5.8 20.5 -3 .3 2.5 -19.0 5.9 -14.2 .3 -1.1 5.8 -13.5 3.8 -5 .3 -5 .7 -8 .0 -19.0 ^f.1 4.0 4.1 13.0 2.2 2.8 4.1 4.8 10.6 44.9 4.1 Construction m a te ria ls......................... Softwood lu m b e r............................... Gypsum products.............................. Plastic construction products.......... Nonferrous wire and c a b le ............... 1.9 -10.3 1.0 1.8 1.6 1.8 19.6 6.6 -1.1 -3.1 1.2 -3 .8 7.1 -2 .0 -2 .2 .1 -10.1 7.3 -2 .2 -4 .6 2.2 10.1 23.1 5.6 .3 .1 -14.5 -27.1 1.6 4.6 Crude nonfood materials less en e rg y. Iron and steel scra p......................... W astepaper....................................... Raw c o tto n ........................................ -4 .2 -4.1 -50.9 4.2 -5 .5 -11.1 -1 .3 -13.0 .0 14.5 11.6 -11.2 -16.0 -39.9 -28.9 -8 .0 14.0 40.0 110.5 -20.8 -5 .5 -28.8 -18.5 30.2 32 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 on by the downturn in the indexes for softwood lumber and and gypsum products. During the same period, rising prices for plastic construction products, millwork, and fabricated structural shapes decelerated from 1999. Conversely, the in dex for nonferrous wire and cable rose more in 2000 than it did a year earlier. Construction demand held up well; the value of new con struction put in place for the year 2000 was $807.8 billion current dollars, 6.0 percent more than the $764.2 billion in 1999. In constant (1996) dollars, the value in 2000 was $704.3 billion, 2 percent above the 1999 figure of $692.5 billion.8 Softwood lumber prices finished the year 14.5 percent be low their 1999 level, taking their biggest hit in May, with a 4.7percent decrease. Prices declined throughout most of 2000, as the softwood lumber market suffered from oversupply and lower demand from the construction industry. The index for gypsum products dropped a record 27.1 percent, for the 12 months ended in 2001. A year earlier, gypsum prices rose 23.1 percent. By early 2000, new plants came online and the short age of gypsum products began to recede. With an eventual oversupply of gypsum wallboard, overall prices started drop ping sharply. The index for plastic construction products rose 1.6 percent in 2000, following a 5.6-percent gain in the prior year. By contrast, prices for nonferrous wire and cable rose 4.6 percent, after edging upward 0.3 percent in 1999. Nondurable manufacturing materials. The index for nondu rable manufacturing materials increased 4.1 percent in 2000, following a 4.0-percent gain in 1999. Rising prices for indus trial chemicals, paperboard, nitrogenates, and paper out weighed price declines for phosphates, inedible fats and oils, and for medicinal and botanical chemicals. The index for industrial chemicals advanced 4.8 percent in 2000, following a 4.1-percent gain a year ago. This increase can be attributed to a 13.1-percent rise in prices for primary basic organic chemicals. The industrial chemicals market ex perienced a long period of declining 12-month percent changes that finally turned positive in September of 1999, the result of higher crude oil prices and recovering world de mand, both of which put upward pressure on prices for or ganic chemicals. Among other chemicals, the index for nitrogenates jumped 44.9 percent in 2000, following a 2.2percent gain in the prior year. The index for paperboard advanced 10.6 percent in 2000, after rising 13.0 percent a year earlier. Due to a strong eco nomic outlook at the beginning of 2000, paperboard produc ers implemented several spring price increases, which ex tended into the summer. By the third quarter, demand dropped somewhat and prices declined for the remainder of the year. Paper prices also accelerated throughout 2000, rising 4.1 per cent, following a 2.8-percent increase in 1999. Paper prices https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis rose steadily throughout the first half of 2000 and then lev eled off for the rest of the year, as orders began to drop and inventories slowly began to build. Crude nonfood materials less energy After jumping 14.0 percent in 1999, the p p i for basic industrial materials—crude nonfood materials less energy— fell 5.5 per cent in 2000. Prices for iron and steel scrap dropped 28.8 percent, following a 40.0-percent surge a year earlier. The indexes for wastepaper, aluminum base scrap, and for soft wood logs, bolts, and timber also fell, after rising in 1999. Conversely, raw cotton prices advanced 30.2 percent in 2000, following a 20.8-percent decline in the prior year. (See table 5.) Iron and steel scrap. Iron and steel scrap metal prices de clined 28.8 percent in 2000, as the domestic steel industry was battered by a flood of low-priced imports. The domestic steel industry has struggled to recover from the Asian eco nomic crisis of 1997-98, when low-cost steel had a negative impact on the domestic market. Wastepaper. The index for the wastepaper in 2000 was down 18.5 percent, compared with a 110.5-percent surge in 1999. After a continual rise in prices for the first 5 months of 2000, the wastepaper industry experienced an extreme “cooling o ff’ period, which began in June and continued throughout the end of the year. The reasons for the fall in paper prices in the second half of 2000 included increased collection, weak ex port demand from Asia, and weak demand from U.S. mills. Prior to this period, the wastepaper index had not shown a decline since late 1998, when it occurred in a much less dra matic fashion. Raw cotton. In the last quarter of 1999, the index for raw cotton had reached its lowest level since November 1986. Prices then rebounded in 2000, rising 30.2 percent for the calendar year. Demand for cotton was heavy by March, be cause merchants and shippers needed cotton to cover com mitments to customers located near the processing facilities. Also adding to higher raw cotton prices was the United States Department of Agriculture forecast of lower world produc tion, higher consumption, and lower stocks for 1999-2000. Many cotton producers abandoned their fields in the last half of the year, due to dry weather throughout the growing season, coupled with poor harvest conditions in the fall. Selected services industries Rising prices were observed for the majority of services in dustries tracked in the p p i . The following indexes rose Monthly Labor Review July 2001 33 Producer Prices, 2000 1Ta£le6I P e r c e n t c h a n g e in P ro d u c e r P ric e In d e x e s fo r th e n e t o u tp u t o f s e le c t e d sic c o d e Industry 1995-96 1996-97 0.0 .0 3.5 .1 3.0 -1 .5 .5 1.4 .0 .7 1.9 1.0 .2 2.6 .6 3.8 2.0 .1 .7 .0 -3 .7 -.6 1.8 -10.1 1.0 2.4 4.6 3.8 -12.4 .4 2.7 _ - s e rv ic e industries, 1 9 9 5 -2 0 0 0 1998-99 1999-2000 0.5 1.7 3.4 .5 4.2 .6 .5 2.9 .0 4.7 .2 0.1 1.1 3.4 .5 3.4 5.3 1.2 2.6 2.2 22.9 1.2 1.8 4.2 6.3 1.4 4.4 1.6 1.7 3.0 .0 12.8 4.8 1.4 -.4 1.2 2.2 -3 .9 3.0 -3 .7 1.2 -1 .4 _ _ .8 -2 .2 1.8 2.8 3.1 3.0 1.4 -1.1 -.6 _ -.1 8.1 1.5 2.9 5.1 3.9 -1 .7 .3 -2 .8 _ _ _ - - - - -.1 9.8 2.6 4.1 8.3 5.8 6.1 1.0 4.5 4.7 6.9 5.2 5.0 1.0 10.0 1.0 -.1 10.8 5.1 -.4 3.1 4.7 -1 .7 .8 3.7 -3 .0 7.7 3.3 -6.1 -1 .7 4.9 5.7 -.6 -.5 2.2 1.4 1.2 2.6 5.7 1.5 1.3 4.6 1.7 2.8 2.5 4.1 3.1 3.0 2.1 1.3 2.5 2.9 5.3 3.0 2.8 2.9 3.1 4.9 3.5 4.0 3.9 3.1 2.5 3.3 .7 5.4 1.5 5.0 2.9 .2 - 1.2 4.2 .5 -6 .7 .6 .9 6.2 2.6 4.4 1.3 .5 2.3 .2 .5 2.1 4.0 1.8 .9 2.7 -.8 4.0 1.6 6.3 3.7 -.6 2.6 4.6 1.0 6.5 2.2 2.6 .9 -1 .6 1.5 2.5 2.6 -2 .3 6.7 2.0 .3 -.3 1.1 2.8 2.6 2.2 1.8 -2 .4 .3 3.8 18.6 8.1 14.6 -.6 1.1 5.7 3.9 2.4 1.2 2.4 4.5 2.8 1997-98 Distribution 4011 4212 4213 4214 4215 4221 4222 4225 4311 4412 4424 4432 4449 4491 4492 4513 4581 4612 4613 4731 5411 5421 5431 5441 5461 5499 5511 Railroads, line-haul operatin g................................................ Local trucking without s to ra g e .............................................. Trucking, except lo c a l............................................................. Local trucking with s to ra g e .................................................... Courier services, except by a ir ............................................. Farm product warehousing and s to ra g e ............................... Refrigerated warehousing and s to ra g e ................................ General warehousing and s to ra g e ........................................ United States Postal S e rv ic e ................................................ Deep sea foreign transportation of fre ig h t........................... Deep sea domestic transportation of fre ig h t....................... Freight transportation on the Great Lakes-St. Lawrence S e a w a y ................................... Water transportation of freight, n.e.c.................................... Marine cargo handling............................................................. Tugging and towing s e rv ic e s .................................................. Air courier s e rv ic e s ................................................................. Airports, flying fields, and airport services.......................... Crude petroleum pipe lines...................................................... Refined petroleum p ip e lin e s ................................................... Freight transportation arrangem ent....................................... Grocery s to re s ........................................................................ Meat and fish (seafood) m a rkets.......................................... Fruit and vegetable m arket..................................................... Candy, nut, and confectionery sto re s.................................. Retail ba keries......................................................................... Miscellaneous food s to re s ..................................................... New car de a le rs....................................................................... 4812 4813 4832 4841 Wireless telecom m unications................................................. Telephone communications, except radiotelephone........... Radio broadcasting.................................................................. Cable and other pay television s ervice s.............................. 6512 6531 Operators and lessors of nonresidential b u ild ings............. Real estate agents and m anagers........................................ 7311 8111 8711 8712 8721 Advertising a g e n c ie s ............................................................... Legal s e rv ic e s ......................................................................... Engineering design, analysis, and consulting s e rv ic e s .... Architectural design, analysis, and consulting services.... Accounting, auditing, and bookkeeping s ervice s............... 8011 8053 8062 8063 8069 8071 8082 Offices of ph y s ic ia n s ............................................................. Skilled and intermediate care fa c ilitie s ................................ General medical and surgical h o s p ita ls ............................... Psychiatric ho s p ita ls ............................................................... Specialty hospitals, except psychiatric............................... Medical laboratories................................................................. Home health care services..................................................... 4512 4522 4724 6311 6331 7011 7349 7361 7363 7372 7513 7514 Air transportation, sche duled................................................ Air transportation, nonscheduled.......................................... Travel agencies....................................................................... Life insurance c a rrie rs ........................................................... Property and casualty insurance.......................................... Hotels and m o tels.................................................................... Building cleaning and maintenance services, n.e.c............ Employment agencies............................................................. Help supply s e rv ic e s.............................................................. Prepackaged softw a re............................................................ Truck rental and leasing, without d riv e rs ............................. Passenger car rental, without d riv e rs .................................. C o m m u n ic a tio n s Real e s ta te Professional, sc ientific, a n d te c h n ic a l H ealth c a r e O th er - 4.8 2.0 1.8 1.4 -.8 -5 .0 - 4.1 1.4 1.0 1.8 - .5 13.7 _ _ 4.2 1.1 2.9 2.2 .9 -.9 -4.0 N ote : Calculations are based on 12-month change from December to December of Indicated years. Dashes indicate index was not used in estimation. 34 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 throughout 2000: scheduled air transportation, general medi cal and surgical hospitals, real estate agents and managers, grocery stores, offices of physicians, skilled and intermedi ate care facilities, legal services, property and casualty insur ance, hotels and motels, nonlocal trucking, and for operators and lessors of nonresidential buildings. On the other hand, price declines were registered for telephone communications (except radiotelephone), life insurance carriers, wireless com munications, and psychiatric hospitals. (See table 6.) During 2000, prices for scheduled air transportation in creased 18.6 percent, following a 6.7-percent gain in 1999. The reason for this acceleration can be attributed to strong demand for air travel and the continued dramatic rise in fuel prices. Rising fuel cost, the airlines industry’s second largest cost after labor, caused airlines to add a passenger fuel sur charge, especially to discounted domestic fares. The sur charges, however, were beneficial for the airlines because while they were subject to Federal taxes, the airlines did not pay commissions to travel agents on the surcharges. Among health services in the p p i , the index for general medical and surgical hospitals advanced 3.7 percent in 2000; a year earlier, this index increased only 1.8 percent. Prices for offices and clinics of doctors of medicine decelerated, rising 1.6 percent in 2000 and 2.1 percent a year ago. Prices for pediatricians and general surgeons rose the most rapidly among single specialty practices. By contrast, the index for general practitioners and internal medicine specialists in creased but at a slower pace in 2000. Prices for skilled and intermediate care facilities accelerated from a 4.0-percent gain in 1999 to a 6.3-percent rate of increase in 2000. By contrast, the index for psychiatric hospitals fell 0.6 percent, after rising 0.9 percent in 1999. Introduced in January 2000, producer prices in grocery stores increased 4.7 percent throughout the year. Most of this increase resulted from the influence of higher margins among supermarkets, primarily within the volatile produce and bakery departments. Also helping push up the index for grocery stores were rising margins for convenience food/ gasoline stores. The p p i for property and casualty insurance increased 1.1 percent for year 2000, the same rate as in the prior year. Ad vancing prices were observed by providers of the following insurance programs: homeowners, commercial auto, com mercial multiple peril, inland marine, and worker’s compensa tion. Increasing claims cost for homeowners insurance was a main factor in propelling the overall index for property and casu alty insurance. A nother factor increasing the homeowners insurance index was the attempt by many insur ers to combat catastrophic losses through higher premiums, https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis especially in catastrophe-prone zones. For the 12 months ended in December 2000, prices for nonlocal trucking services rose 6.3 percent, following a 3.4percent increase in 1999. This acceleration can be attributed to continued retail sales growth in the strong U.S. economy, driver shortages, and the rising cost of equipment. Another factor in higher trucking prices came from rising diesel fuel prices, which subsequently led trucking companies to in crease their fuel surcharges. The index for operators and lessors of nonresidential buildings advanced 1.3 percent in 2000, as the economic con dition created a good opportunity for new construction. Prices increased in both industrial property and office prop erty. Recent industry analysis, for the third quarter 2000, showed that nationwide vacancy rates had declined and that demand had been strong for office space as the economy grew.9 Among other services industries that posted inflation throughout 2000, the index for real estate agents and manag ers advanced 4.6 percent, following a 1.5-percent gain in 1999. Prices for legal services rose 3.9 percent, after increasing 2.9 percent in the previous year. Finally, the index for hotels and motels exhibited a 5.7-percent gain in 2000, continuing from its upward movement of 2.8 percent a year ago. In 2000, falling prices were registered for telecommunica tion services. The index for telecommunications (except ra diotelephone) decreased 1.7 percent, following a 3.0-percent decline in 1999. Prices for wireless communications dropped 6.1 percent. Specifically, the price for cellular and other wire less voice grade services decreased 6.3 percent, while pag ing services fell 4.5 percent. Declining prices for cellular ser vices were the result of increased competition and further development of the wireless telecommunication infrastruc ture. At the same time, more customers gained greater access and wider utility while using the services. Furthermore, prices fell, as carriers formed strategic alliances with other carriers to eliminate roaming charges and, in many cases, long dis tance charges. From December 1999 to December 2000, the index for life insurance carriers decreased 0.6 percent, after falling 0.3 per cent a year earlier. The 2000 decline is evidence of continued competition due to the ability of other financial services com panies to offer similar services. The majority of the overall decrease for life insurance carriers can be accredited to group life insurance policies, which fell 5.4 percent throughout the year. On the other hand, variable-deferred annuities experi enced price gains over 2000 due to increases in overall total returns, although, this increase was not enough to offset the price decline in group life insurance policies. □ Monthly Labor Review July 2001 35 Producer Prices, 2000 Notes 1 See Natural Gas Monthly, (Energy Information Administration, May 2001), Table 9, Underground Natural Gas Storage-All Opera tors, 1995-2001. 2 See Petroleum Supply Monthly, (Energy Information Adminis tration, 1984 to present), Table S2, Crude Oil and Disposition; and h ttp ://w w w .e ia .d o e .g o v /p u b /e n e r g y .o v e r v ie w /a e r l9 9 9 /tx t/ aer0514.txt (visited July 12, 2001). 3 See Agricultural Outlook, ( usda Economic Research Service, May 2001), Table 17— Supply and Utilization. 4 See Agricultural Outlook, ( usda Economic Research Service, May 2001), Table 10— U.S. Meat Supply and Use. 5 See Ward’s Automotive Report for 2000, U.S. Light-Vehicle Sales by Ward’s Segmentation—December 2000. 6 See David H. Napier, Director, 2000 Year-end Review and 2001 Forecast—An Analysis (Aerospace Industries Association). 7 See Year 2000 Selected Steel Industry Data (American Iron and Steel Institute, Steel Works). 8 See Value o f Construction Put In Place Press Release (Census of Construction Industries, December 2000). 9 See CB Richard Ellis, U.S. Vacancy Report, 2nd quarter, 2000, which notes: “Both office and industrial vacancy rates declined sig nificantly in the second quarter of 2000 reflecting the hot US economy, but it is clear that both markets have an element o f ‘phantom or Venture Capital’ absorption.” Where are you publishing your research? The Monthly Labor Review will consider for publication studies of the labor force, labor-management relations, business conditions, industry productivity, compensation, occupational safety and health, demographic trends, and other economic developments. Papers should be factual and analytical, not polemical in tone. We prefer (but do not require) submission in the form of an electronic file in Microsoft Word, either on a diskette or as an attachment to e-mail. Please use separate files for the text of the article; the tables; and charts. We also accept hard copies of manuscripts. Potential articles should be mailed to: Editor-in-Chief, Monthly Labor Review, Bu reau of Labor Statistics, Washington, DC 20212, or by e-mail to mlr@bls.gov 36 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 A state space model-based method of seasonal adjustment A structural state space model-based method o f seasonal adjustment presents certain advantages to seasonally adjust time series Raj K. Jain Raj K. Jain is a research economist in the Office of Prices and Living Conditions, Bureau of Labor Statistics. E-mail: jain_raj@bls.gov https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis he Bureau o f Labor Statistics pub lishes a very large number of economic time series such as the Consumer Price Index, the Producer Price Index, employment and unemployment statistics and many more. Most of these series are published as seasonally un adjusted series as well as seasonally adjusted series. More often, however, it is the seasonally adjusted data series that the business community and government agencies use in evaluating the economic situation. There are several reasons given for the use of seasonally adjusted series. It is suggested that the presence of seasonality1 in time series obscures the stage of the business cycle that the economy is in. In addition, it ob scures the effects of interventions,2 such as a rapid cut in oil production, on a series. At the present time, BLS uses the Census X -ll/X-12 ARIMA methods to seasonally adjust BLS indexes and series that have seasonality.3 In the last 20 years or so, several a r i m a model-based methods have been proposed for seasonal adjustment.4 This article presents a structural model based method of seasonal adjustment called the state space model-based method.5 This articles pre sents research conducted on this method and illustrates the advantages of the method. The research is part of the Bureau's ongoing efforts to explore relevent measurement issues of inter est to the wider statistical community. T A structural model time series; the second component is the sea sonal, which reflects a periodic movement in a series that repeats itself every year; the third component is the cyclical component, which tracks the course of the business cycle; and fi nally, the error component, which is the sum total of the effects of all those factors which are indi vidually insignificant and are not included in the trend, the cyclical, or the seasonal components. If the time series is affected by interventions, which are the results of exogenous shocks to the series, then intervention components are in cluded as separate components. This informa tion is incorporated into an equation called the decomposition equation (illustrated as equation 1). To decompose the time series, each compo nent of the time series is assumed to follow a model. The decomposition equation and the component models, together with the statistical properties as sumed for the error terms is what constitutes a struc tural model of a time series. The following is an ex ample o f a structural model6: y ,= n ,+ y ,+ v ,+ £ , ® M = 2/4- i - M-2 + n, +#,*7,-1 + _2 (2) 11 Y j-i = A , + +Pi«M <3) /=0 I X (4) / = c. 7=0 A time series is assumed to be the sum of four components. The first component is the timetrend, which reflects a long-term movement of a y/t (follows the Trigonmetric Cycle as in Harvey's equation 3.8)7 Monthly Labor Review (5) July 2001 37 Seasonal Adjustment In this model8, y t is the observed series, ¡ULt is the trend, y t is the seasonal, \jft is the cycle, and ¡3t is the slope of the seasonal, all at time t. The random errors, e t and gt in equations (1) and (4) and errors in (5), are assumed to be mutually uncorrelated, each having zero mean and constant variance. The random errors TJt, and COt in equations (2) and (3) respectively are mutually, but not serially uncorrelated. Each of these errors is assumed to follow a moving average pro cess of order two, written as ma (2) process, and each has zero mean and constant variance. The Qi,0 2,cpl, (p2 are parameters of the m a (2) processes in these two equations to be esti mated. Equation (1) is the decomposition equation, equation (2) is the component model for the trend, (3) and (4) are the equations representing the seasonal component model, and (5) represents the cyclical component model. The trend com ponent model in (2) is a local polynomial of order two. The seasonal component model in (3) and (4) assumes that the seasonal component is not constant, but moving in the sense that the seasonal amplitude is not constant over the years. This adds greater flexibility to the estimation of seasonal component. In the structural model previously presented, the important parameters of interest to be estimated are the trend jLLt , the seasonal y t , and the cycle \fft . However, these are not constant parameters in the model above; these are assumed to be random parameters changing over time in the manner of their component models. This feature adds greater flexibility and realism to this kind of model for seasonal adjust ment. The seasonally adjusted series is obtained by subtract ing the seasonal component from the observed series. Estimation of the model Once we specify the structural model, the next step is to esti mate the model. This is done by an iterative technique. To implement this technique, first, the model is put in the “state space” form.9 In this form, the structural model resembles, but is not identical to, a linear model whose parameter vector is constrained by an auto-regressive process of order one writ ten in short as a r (1) process. There are two parts to the esti mation of the structural model in the state space form: (1) Esti mation of the parameter vector called the “state vector” and its covariance matrix, given the initial values of the state vector, its covariance matrix, and the initial value of the matrix of errorvariance parameters, called hyper-parameters. The estimation is done by the iterative technique called “Kalman Filtering and Smoothing”10and (2) Estimation of the matrix of hyper-param eters11 is done by the Expectation Maximization12algorithm13 and by a quasi-Newton14numerical optimization technique. The Kalman filter is initialized with a zero state vector and a diagonal covariance matrix of the state vector, with the diago nal elements being very large. The very large initial variances of the elements of the state vector, indicates that the analyst 38 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 has very little faith in the accuracy of these values. Also, the initial matrix of hyper-parameters is generally assumed to be diagonal, with very small but positive values. With initial val ues for the filter set, the Kalman filtering starts with the first observation and ends with the last observation of the sample. From the last observation, smoothing begins and goes back wards to the beginning of the sample period and one step more beyond that. These smoothed values of the state vector and its covariance matrix, one period before the sample period, are used as the new initial vales for starting the filter for the second iteration. The smoothed residuals and the filtered re siduals are used to obtain the new estimate of the matrix of hyper-parameters for the next iteration. The filtered residuals of the model are also used to estimate the log-likelihood func tion of the model via the Prediction Error Decomposition.15 This iterative process is continued until the decrease in the log-likelihood function is insignificant. At that point, the esti mation of the hyper-parameters and the log-likelihood is switched to a quasi-Newton numerical optimization procedure. Evaluation of the model The next step in implementing the state space model-based method of seasonal adjustment is to evaluate the structural model and its components or their derivatives, especially the trend and the seasonally adjusted series. The structural model (described earlier) is evaluated for (1) its adequacy to explain the observed series; (2) its goodness of fit to the data series; and (3) the forecasting performance of the model with respect to the given series. The quality of seasonal adjustment is evalu ated with respect to the smoothness of the trend and the pres ence of, and the identifiability of the stable and the moving seasonality in the observed series. The adequacy of a structural model is tested, by using Ljung-Box statistics,16 bds statistics as developed by W. A. Brock, W. D. Dechert, and J. S. Scheinkman,17and m bd s statistics, a modification of bds statistics by B. M izrack.18 The goodness of fit of a structural model is judged by the Akaike Information Criterion, (a ic ) 19and Adjusted Coeffi cients of Correlation ( r b a r -s q u ar e ),20 using regular sum of squares of residuals around their mean, differenced sum of squares around the mean of the differenced residuals, and the differenced sum of squares around the seasonal mean of the differenced residual series. For forecasting performance of the structural model, Root Mean Prediction Error Sum of Squares (rmpess ) is used. To evaluate the qual ity of seasonal adjustment, a test is conducted for the pres ence of stable or moving seasonality (or both), using F-tests constructed from the 2-way a n o v a on the trend-adjusted series. Another statistic developed by E. B. Dagum, called m l, which is a function of two F statistics constructed from 2way a n o v a on the trend adjusted series, is used to test for identifiability of seasonality.21 If the m l value lies between zero and one, then the seasonality is identifiable; otherwise, it is not. The relative variance of the trend component is used to judge the smoothness of the trend. If the relative variance is zero or close to it, then the trend is judged as smooth. The structural model presented earlier as an example is one of several models that can be used, depending on the choice of trend component model, choice of seasonal component model, assumptions on the error terms, presence or absence of interventions, and so forth. To determine which model best fits a time-series, Akaike Information Criterion estimated from each model are compared. The model with the minimum value of Akaike Information Criterion, assuming that other statistics are the same for all estimated models, is chosen as the best model for that series. In practice however, this assumption is not always satisfied. In that situation, one or two models which are acceptable, are further refined and estimated, and the choice for the best model, with the minimum criterion, is made from those models. These structural models have been estimated using 8 years of monthly, quarterly, and bimonthly bls time series. A smaller sample size does not necessarily and signifi cantly affect the quality of the estimated components. More over, these models are found to be robust with respect to new data for about 3 years; after that, it is safer to once again search for the best model. Of course, if a time series is subject to external shocks, the choice of model analysis for that series has to be done more frequently. Advantages of structural model This structural model-based approach to seasonal adjustment has several advantages. First, the structural model-based ap proach allows an analyst to use the existing statistical theory to test if a structural model represents the data generation process of a given time-series. Nonmodel-based methods lack formal statistical tests to evaluate the results of seasonal ad justment. Second, the structural model-based method estimates the variance of the seasonally adjusted series at the same time it estimates the seasonally adjusted series. This means that the estimation of the variance is also model based, and hence, subject to statistical scrutiny. In other methods, such as a r im a model-based methods as well as nonmodel-based methods like X -ll and X-12 a r im a methods, variance estimation is done separately from the seasonal adjustment and hence may be less reliable as a measure of the accuracy of the seasonally adjusted series. Third, many economic time-series such as the Consumer Price Indexes for gasoline, published by the Bureau of Labor Statistics, are affected by external interventions such as the limits placed on the production of crude oil by opec and hence, artificial upward increase in the prices of gasoline. In the structural model, a separate observable component is introduced to take account of the effect of an intervention. In https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis other seasonal adjustment methods, the time-series is first subjected to a priori adjustment for those effects and then the intervention-adjusted series is seasonally adjusted. In the structural model-based method, all components are estimated simultaneously. A similar advantage lies with the method when a time series, such as retail sales published by the Census Bureau, is affected by the number of trading days22 in a month or on the day the Easter23 falls which varies from year to year. Fourth, many time-series are contaminated by sampling errors arising from the peculiarity of the sampling design in the col lection of the sample data.24 This problem is handled in the structural model-based method by introducing an unobserved component in the model.25 That component is assumed to fol low a moving average process of small order say two or three. There are no provisions to take care of this situation in other methods of seasonal adjustment. Fifth, trend and cycles can be decomposed in the structural model based method by in troducing a separate component in the structural model for representing the effects of business cycles. This kind of flex ibility, which is liked by many researchers, is not available in methods like X-l l/X-12 a r im a . Finally, the structural modelbased method is a simple, versatile, and very elegant proce dure. All the equations of a structural model are easy to under stand. Economic time-series, which are affected by many dif ferent kinds of influences such as interventions, measurement error, or number of trading days, can be easily seasonally ad justed in one step. The estimation and evaluation designs of the state space model-based method also make it a very neat and elegant procedure. Applications In several studies, the author has applied the structural state space model-based method to several bls series. This method was applied to the cpi for new cars, cpi for girls’ apparel, cpi for gasoline, number of male agricultural workers 20 years and older, unemployment levels of civilians between 16 and 19, and the employment level in retail trade.26 The state space model-based method with intervention analysis was applied to the cpi for gasoline, the cpi for women's dresses, cpi for women's suites, ppi for gasoline, and ppi for crude petroleum.27 The state space model-based method with trading day and Easter adjustment was applied to two census series, the retail sales of men’s and boys’ clothing and wholesale sales of hard ware, plumbing and heating equipment.28 The state space model-based method with measurement errors was applied to the civilian unemployment rate and teenage unemployment rate in a previous study.29 In this article, the model-based method is applied to the cpi of apples.30 The cpi for apples is a monthly time-series, which is quite seasonal. The sample period chosen for application spans 8 years from January 1991 to December 1998. Several structural models were estimated Monthly Labor Review July 2001 39 Seasonal Adjustment using the apple data. The model presented earlier in equations (1) through (5) as an example of a structural model was found to be the best31 amongst those models tested. This model was found to be adequate, had a good fit to the data, and had a good forecasting performance. It may be pointed out that the forecasting performance of a model is not critical for evalua tion of that model for purposes of seasonal adjustment. As pointed out earlier, the adequacy of the model was checked by the Ljung-Box statistics Q*, bds, and the mbds tests. The Q* statistic, which is computed using 36 standardized residuals, has a Chi-Square distribution with 32 degrees of freedom. This statistic was found to be Q*(32)=34.43 and the corresponding p-value=0.35; hence it accepts the null hypothesis of uncorrelatedness of residuals. This implies that there is no systematic pattern left in the residuals because the model has captured all the systematic components in the series; hence the model is adequate. The bds statistics were computed using all 96 smoothed residuals; the test value was bds=1.39. This test also accepted the null hypothesis of independence and hence, uncorrelatedness of residuals, mbds statistic, which is a modifi cation of bds statistic, also accepted the null hypothesis. The three adjusted coefficients of correlation32 were found to be: rbarsq=0.98, rbarsq(diff)=0.89, and rbarsq(seas)=0.56. These values indicate that the fit of the model is quite good; the closer these values are to one, the better the fit of the model. For this model, aic=282.81. There is, however, no bench mark to compare this value with, except that this was one of the smallest values and hence, this model was judged to be a better model than other models under consideration. Next, the estimated components of the structural model is analyzed, starting with the trend component for the structural model based method as presented in chart 1. The relative vari ance of the errors of the trend component model is estimated to be 0.43, which indicates that the trend ought to be very smooth. Chart 1 indicates that the trend is fairly smooth; it is smoother than the trend component obtained for the X-12 arima method depicted in chart 2. In the structural model for the state space model-based method, the trend and cycle are estimated separately, whereas in the X-12 arima method, the trend and cycle are estimated as one component because the latter method has no facility to estimate the two separately. However, even the combined trend plus cycle component of the structural model-based method was found to be smoother than the trend-cycle component of the X-12 arima method. Empirically, the smoothness of trend has been found to be a good indicator of a good model. Seasonal component is another important component of a seasonal time-series. The empirical results for the structural model-based method indicate that, based on F-tests from twoway anova, the stable seasonality is significant at both the 5 percent and 1 percent level, but the moving seasonality is not significant at either the 5 percent or 1 percent level of signifi 40 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 cance. The amplitude of the structural model-based seasonal component in chart 3 varies from -17 to +19 at the beginning of the sample period; but then it keeps on diminishing through out the sample period, and at the end, it varies from -8 to +8. The seasonal component estimated by X-12 a r im a method as shown in chart 4 gives somewhat similar results. As in the case of structural model base method, significant stable sea sonality is present, but moving seasonality is not, in the case of X-12 a r im a method. The amplitude of the seasonal compo nent for the X-12 a r im a method varies from -15 to +17 at the beginning of the sample period, but declines to the range be tween -8 and +9. The statistic, m7,33 which is found to be equal to 0.28 for the state space model-based method indicates that the seasonal ity is identifiable. The same is true for X-12 a r im a method. Finally, a comparison of the seasonally adjusted series obtained by the two methods is presented. The seasonally adjusted series for the state space model-based method is obtained by subtracting the seasonal component from the unadjusted series. Chart 5 displays the unadjusted sample series and the seasonally adjusted series obtained from ap plying the structural model-based method. The seasonally adjusted series has a pattern that is very similar to the trend, except that it has more kinks; but this is to be expected be cause, in addition to trend, it contains cyclical component and residual errors. The seasonally adjusted series for X-12 a r im a depicted in chart 6 is also very similar to its trend, but with kinks. In comparison, the two seasonally adjusted series look very similar and more information is required to assess the superiority of one over the other. In applications to other bls series, the author has shown significant differences in the seasonally adjusted series produced by the two methods.34 s tu d y presented a relatively new method of seasonal adjustment that incorporated several innovations. For ex ample, in the specification of the structural models, the pa rameters of explanatory variables such as intervention vari ables or other exogenous or lag-dependent variables were not assumed to be constant as usual, but assumed to follow a random walk process. This added greater flexibility to the estimation of the effects of such variables. In the estimation of the structural models, the hyperparameters of the models were estimated by two methods: the Expectation Maximiza tion (e m ) algorithm and the quasi-Newton numerical optimi zation method. The Expectation Maximization algorithm takes the estimation towards optimization in a few iterations, but after that, its approach to optimization slows down to a snail's pace. At that point, a switch to a quasi-Newton method quickly leads to optimality. In the evaluation of the estimated struc tural model, two new test statistics, bds and m b d s , were used. These tests are found to be very effective in testing the ad equacy of the structural models. In several conference pa- T his Chart 1. Original sample series and the smooth trend component obtained by using state space 1992 1991 Chart 2. 1993 1994 1995 1996 1997 1998 Original sample series and the final trend component obtained by using X-12 ARIMA method, January 1991 through December 1998 Index Index https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 41 Seasonal Adjustment Chart 3. Smooth seasonal component and its standard error obtained by using the state space model-based method, January 1991 through December 1998 Chart 4. Final seasonal component obtained by using x-12 ARIMA method, January 1991 through December 1998 Index 42 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Index July 2001 Chart 5. Unadjusted sample series and the smooth seasonally adjusted series obtained by using the state space model-based method, January 1991 through December 1998 Index Chart 6. Index Unadjusted sample series and the seasonally adjusted series obtained by using x-12 ARIMA method, January 1991 through December 1998 Index https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis lnc|ex Monthly Labor Review July 2001 43 Seasonal Adjustment pers mentioned earlier, the author has presented the empirical results of the application of this method with all the innova tions mentioned, to various bls and Census Bureau series. The author has written a complete computer program (in gauss ) incorporating various aspects of seasonal adjustment such as “intervention and outlier analysis,” “trading day and Easter adjustment,” “survey sampling error adjustment,” and all other innovations mentioned above. This study has presented a brief outline of this method of seasonal adjustment and its applica tion to the cpi for apples. □ Notes 1 Ted Jaditz, “Seasonality: economic data and model estimation,” Monthly Labor Review, 1994, pp. 17-22. Jaditz has discussed the factors that give rise to seasonality and the rationale o f seasonally adjusting the economic time series. 2 Interventions resulting from external events such as an opec deci sion to reduce total production o f crude oil at a point in time that will almost immediately, or with a slight lag time, affect the retail prices and hence, the CPI o f the gasoline at that time. Unless the effect o f this intervention is separated from other components, the decomposition o f the time series would produce components, which would include some effect o f the intervention and hence be misleading. The approach to separating the effects o f interventions at a certain point in time is called intervention analysis. 3 x-12 arima Reference Manual (Washington, DC, Time Series Staff, Bureau of the Census, 1999) and E. B. Dagum, The x -11arima/ 88 Sea sonal Adjustment Method - Foundations And User's Manual (Time Series Research and Analysis Division Statistics Canada, Ottawa, Canada, 1988). 4 J. P. Burman, “Seasonal Adjustment by Signal Extraction,” Journal o f the Royal Statistical Society, 1980, series A, vol. 143, pp. 321-37 and S. C. Hillmer, and G. C. Tiao, “An ARiMA-Model-Based Approach to Seasonal Adjustment,” Journal o f the American Statistical Association, 1982, vol. 77, pp. 63-70. 5 R- K., Jain, “A State Space Modeling Approach to the Seasonal Adjustment of the Consumer Price and other bls Indexes: Some Empiri cal Results,” bls Working Paper, no. 229 (Bureau of Labor Statistics, 1992) and “Structural Model-Based Seasonal Adjustment of the Bureau of Labor Statistics Series,” bls Working Paper no. 236 (Bureau of Labor Statistics, 1992). 6 Similar structural models, using Kalman Filtering and Smoothing for estimation, are currently being used by the Bureau of Labor Statistics to estimate State and Local Area Employment and Unemployment. For details, see R. Tiller, S. Brown, and A. Tupek, “Bureau of Labor Statistics’ State and Local Area Estimates o f Employment and Unem ployment,” ch. 5, in Indirect Estimators in U.S. Federal Programs, W.L. Schaible ed. (Springer, 1996). Also see R. K. Jain, “Comparative Performance of State Space Model Based and ARIMA Model Based Meth ods of Seasonal Adjustment,” 1995 Proceedings o f the Business and Economic Statistics Section-American Statistical Association-, A. C. Harvey, “A Unified View o f Statistical Forecasting Procedures,” Jour nal o f Forecasting, 1984, vol. 3, pp. 245-75; A. C. Harvey, Forecast ing, Structural Time Series Models and the Kalman Filter (Cambridge, MA, Cambridge University Press, 1990); and G Kitagawa, and W. Gersch “A Smoothness Priors-State Space Modeling of Time Series with Trend and Seasonality,” Journal o f American Statistical Association, 1984, vol. 79, pp. 378-89. 7 A. C. Harvey, “Trends and Cycles in Macroeconomic Time Series,” Journal o f Business and Economic Statistics, 1985, vol. 3, 216-27. 8 In this structural model, no explanatory variable is used because we did not need one. In modeling some other time series, however, we can introduce observable economic variables as well as lag-dependent vari ables as independent variables to increase the explanatory power of the structural models. 44 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 9 Harvey, Forecasting, Structural Time Series Models, 1990. 10 See Harvey, Forecasting, Structural Time Series Models, 1990 and Kitagawa, and Gersch, “A Smoothness Priors-State Space Modeling o f Time Series,” Journal o f American Statistical Association. 11 Hyper-parameters are the variances o f the errors o f the com po nent m odels. 12 Expectation M axim ization (EM) is an alternative nonlinear opti m ization algorithm, which was developed by A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the em algorithm,” Journal o f the Royal Statistical Society, 1977, Series B„ vol. 39, pp. 1-38. 13 R. H. Shumway, and D. S. Stoffer, “An Approach to Time Series Smoothing and Forecasting Using the em Algorithm,” Journal o f Time Series Analysis, 1982, vol. 3, pp. 2 5 3 -6 4 . 14 Q uasi-N ew ton methods are num erical optim ization m ethods in which, unlike that in Newton’s method, the use o f second derivatives in the approxim ation o f the lik elih ood function, are altogether elim i nated. These methods have excellent convergence properties even for ill-behaved functions. 15 Prediction Error D ecom position is a fundamental result in time series. By using it, the joint density o f observations can be written down in such a way that full maximum likelihood estimation o f many com plex series can be done easily. For details see Harvey, Forecasting, Structural Time Series Models, 1990, pp. 125-27. 16 Harvey, Forecasting, Structural Time Series Models, 1990. 17 W. A. Brock, W. D. Dechert, and J. Scheinkm an, “A Test for Independence Based on the Correlation Dim ension,” Econometric Re view, 1996, vol. 15, no.3, pp. 1 9 7-235. 18 bds and mbds tests are specification tests applied to the residuals o f linear or nonlinear models. The maintained hypothesis o f these tests is that the true residuals are independent and independently distributed. These tests in the evaluation o f structural m odels are used to test the adequacy o f the models. See B. Mizrack, “A Simple N on parametric Test for Independence o f Order (P ),” W orking Paper N o. 199 5 -2 3 (N ew Jersey, Rutgers University, 1995). 19 Akaike Information Criterion ( aic ) is a model selection criterion. The model with the lowest a ic is presumed to be the best or optimal model from among the models analyzed. It is defined as: aic = - 2 (log likelihood o f a m odel) + 2 (number o f independent parameters esti mated in the model). A model with large number o f parameters is less likely to be chosen as the optimal model. 20 Harvey, Forecasting, Structural Time Series Models, 1990. 21 Dagum, The X -11arim a /88 Seasonal Adjustment Method, 1988. 22 The number o f trading days in a month varies from month to month. The total sales o f a product in a month are therefore affected by this phenomenon. To correctly estimate various components o f a time the effect o f the number o f trading days in a month has to be separated. The approach to doing that is called trading day adjustment. 23 The Easter holiday falls at different dates each year any day be tween March 22 to April 22. Because sales o f many consumer goods go up around Easter, the effect o f this phenomenon on a time series has also to be separated like that of number of trading days. The approach to doing that is called Easter day adjustment. 24 J. A. Hausman, and M. W. Watson, “Errors in variables and sea sonal adjustment procedures” Journal o f the American Statistical Asso ciation, 1985, vol. 80, 541-52. 25 An example o f such a series is the teenage unemployment rate published by bls . See R. K. Jain, “Measurement Errors and State Space Model Based Method of Seasonal Adjustment,” Proceedings o f the Busi ness and Economic Statistics Section-American Statistical Association, 1998). 26 See R. K. Jain, “A State Space Modeling Approach to the Seasonal Adjustment,” 1992; “Structural Model-Based Seasonal Adjustment of the Bureau of Labor Statistics Series,” BLS Working Paper, 1992; “Com parative Performance o f State Space Model Based and a r im a Model Based Methods of Seasonal Adjustment,” 1995; and “Automatic Outlier Detection in Seasonal Adjustment Methods,” 1997 Proceedings o f the Business and Economic Statistics Section-American Statistical Asso ciation, 1997. 2TSee R. K. Jain, “A State Space Model Based Approach to Interven tion Analysis in the Seasonal Adjustment o f the BLS Series: Some Em pirical Results” bls Working Paper no. 228, 1992 and “Structural ModelBased Seasonal Adjustment,” bls Working Paper, no. 229; and R. K. Jain, “The Seasonal Adjustment o f the Consumer Price Indexes o f Women’s Apparel: An Application o f State Space Model Based Ap proach to Intervention Analysis,” 1993 Proceedings o f the Business tics Section-American Statistical Association (Alexandria, va , 1996). 29 See R. K. Jain, “Measurement Errors and State Space Model Based Method o f Seasonal Adjustment,” 1998 Proceedings o f the Business and Economic Statistics Section-American Statistical Association (Al exandria, VA, 1998). 30 Apple is an item-stratum ( sefk OI) in the consumer price classifica tion structure. It is part of “Fresh Fruits,” which is a larger expenditure category. Although the cpi for apple is directly seasonally adjusted, this item stratum only indirectly enters the All-Item cpi via the aggregate category. 31 The structural model in equations (1) through (5) is the best model in the sense that the Akaike Information Criterion (AIC) for this model was less than other structural models estimated for analysis. About six different structural models were used for comparison. 32 For details see Harvey, Forecasting, Structural Time Series Mod els, 1990, pp. 268-69. 33 m l is a statistic developed in the X - 11 ARIMA method. It is a func tion o f the F-statistics for the stable seasonality and moving seasonal ity. If m l lies between 0 and 1, then the two kinds o f seasonality are identifiable. The experience o f the author with this statistic is that almost every time m l lies within the acceptable bounds for a model, that model turns out to be an acceptable model for that series. See Dagum, The X -1 1 arima / 8 8 Seasonal Adjustment Method, 1988. 34 R. K. Jain, “Structural Model-Based Seasonal Adjustment o f the Bureau of Labor Statistics Series,” Working Paper, 229; “The Seasonal Adjustment of the Consumer Price Indexes of Women’s Apparel: Ameri 28 R. K. Jain, “Trading Day and Easter Adjustment in Seasonal Adjust can Statistical Association; and “Trading Day and Easter Adjustment in Seasonal Adjustment Methods,” American Statistical Association. ment Methods,” 1996 Proceedings o f the Business and Economic Statis and Economic Statistics Section-American Statistical Association, 1993. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 45 Research Summary Expenditures of c o lle g e -a g e students and nonstudents Geoffrey D. Paulin A s the U.S. workforce comes to rely /^ .in c re a sin g ly on computer technol ogy, including the Internet, higher levels of education are becoming necessary to produce efficient users, programmers, and inventors of new systems. The importance of higher education in this “new economy” is underscored by the tremen dous increase in college enrollments over the last 10 years, despite a shrinking col lege-age population: in 1987, there were about 18.8 million persons between the ages of 20 and 24 in the United States; by 1997, that figure dropped to less than 17.5 million. Yet, college enrollments for this age group increased from 4.1 million in 1987 to 5.2 million in 1997. In other words, college participation among mem bers of this age group increased from less than 22 percent to nearly 30 percent in those 10 years.1 While these changes have been oc curring, the cost of a college education has been rising. From 1987 to 1997, the Consumer Price Index for college tu ition and fees rose 111 percent, com pared with 41 percent for all other goods and services. Undoubtedly, this increase in prices has made it more difficult for some potential students to attend col lege on a traditional, consecutive 4-year basis. This group of young people may choose to join the labor force for a pe riod of time in order to save money to ward their continued education. Still other potential students may be forced off the college path altogether. This report examines the group of college students termed “traditional” (that is, those aged 18 to 22 who are Geoffrey D. Paulin is a senior economist in the Division of Consumer Expenditure Surveys, Bu reau of Labor Statistics. E-mail: paulin_g@bls.gov 46 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 enrolled in school full-time) and com pares them with persons in that same age group who work full-time but do not attend school. Using data from the Interview component of the 1996-98 Consumer Expenditure Surveys, demo graphics and expenditure patterns are analyzed. These data should be of in terest to students (and to their parents) who either are in college or are collegebound, and also to those who are mak ing the important decision of whether to attend college or seek employment for a period of time. The sample. Students and nonstudents included in this study shared certain characteristics. In addition to the age re quirement already noted, they must have been members of single-person consumer units, and must never have been married.2 This was done because when a student (or student-age person) lives “at home” (that is, in the consumer unit with the immediate family), it is impossible to separate out expenditures made exclusively for or by the student (or student-age person). Additionally, all persons in the sample had to be quali fied to attend college, meaning, they held at least a high school degree, but did not yet hold a baccalaureate degree. To qualify as students, the participants must have been enrolled at college full time at the time of the interview. Non students had to work full-time: that is, at least 35 hours during a usual week.3 Also, in order to eliminate recent en trants into the workforce, nonstudents had to have worked at least 39 weeks (or three-quarters of the year) prior to the survey. Additionally, nonstudents could not be enrolled in college at all during the interview time period, not even on a part-time basis. This was done to facilitate a clear-cut comparison of groups. Finally, for consistency, all per sons included in the sample rented their homes.4 Eliminating homeowners was expected to reduce the variation in ex penditures across the groups without a large reduction in sample size for ei ther group. Demographics. Demographic and ex penditure information for students and nonstudents are shown in table 1. The sample selected is weighted to reflect the population. There are about 2.5 mil lion students represented in these data. Although many more students are rep resented than nonstudents, the latter group is still not small in number— more than a quarter of a million per sons are included in this category. On average, nonstudents are older than students. Nearly two-thirds of non students are at least 21 years old, com pared with a bit more than one-third of college students. This may be a conse quence of how the sample was defined. There are probably more opportunities for persons 21 and older to find full time, full-year employment than for persons aged 18 to 20. This may help explain why some persons in the 18- to 20-year-age category stay in school rather than seek employment. Those who do not seek a traditional 4-year de gree may still be earning a degree such as an Associate of Arts, which they be lieve will enhance their opportunities for employment at 21 as well. A large proportion of nonstudents work long hours— 44 hours per week on average. Again, the sample was se lected to include only those who work at least 35 hours per week, but obvi ously most work many more hours than this minimum: 31 percent work 45 or more hours a week, and 12 percent re port working at least 55 hours per week. At the same time, 10 percent work 39 hours or less; 57 percent work 40 hours exactly. Similarly, most nonstudents work all year—51 weeks on average. (See table 1.) But students work a sub stantial number of hours as well. About 30 percent of full-time students report working 40 or more hours per week. More than half of full-time students (53 percent) report working 25 hours or Chart 1. Percent of students and nonstudents reporting selected expenditures, 1996-98 Consumer Expenditure Survey, Interview component Percent reporting Percent reporting Food at home Food away from home more per week. On average, they work 26 weeks, or one-half of the year. This means that even if the average student works all summer, he or she also works during a significant part of the school year. Most students and nonstudents work for a wage or salary. About 38 percent of both students and nonstudents are employed as either service workers or sales persons. Nonstudents are most likely to be employed as laborers, tech nicians, or skilled workers (42 percent). Students are most likely to be employed in administrative or professional posi tions (25 percent). Only about one in six students had not worked in the ref erence time period. Looking at educational attainment, about 14 percent of nonstudents have earned, at a minimum, an Associate of https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Shelter and utilities Apparel and services Transportation Health care Arts degree, compared with 3 percent of continuing students. A substantial minority—41 percent—of nonstudents have not attended college at all. The survey data do not reveal why this is true; however, other data may be better suited to show whether or not these nonstudents are at considerable risk of never attending college and, therefore, missing out on the rewards that are ex pected to accrue to recipients of higher education in the “new economy.” The data also show that black and Hispanic consumers are underrepre sented both in the student and nonstu dent populations. It may be that mem bers of these groups are disproportion ately represented in the groups omitted from the study—for example, the un employed, and the part-time students who may work during the day and at Entertainment Travel and vacation tend school at night. However, students are overrepresented in urban areas, while nonstudents are found in urban areas in about the same proportion as the general population. This is undoubt edly because so many colleges and uni versities are located in urban areas as opposed to rural areas. Income. Table 1 also shows the com position of incomes before taxes for stu dents and nonstudents. Because some persons are more likely to report their income than others, only data for com plete income reporters are shown. In general, complete income reporters pro vide a value for a least one major source of income, such as wages and salaries. However, even complete reporters do not necessarily provide a full account ing of all sources of income received. Monthly Labor Review July 2001 47 Research Summary Mean demographic characteristics of students and nonstudents, 1996-98 Consumer Expenditure Survey, Interview component D e m o g r a p h ic S tu d e n t Total (e s tim a te d ).................................................. N o n s tu d e n t 2,510,530 256,364 $6,014 4,113 81 852 $16,425 16,156 121 37 661 307 3 107 25 26 44 51 17.5 24.8 22.8 22.2 12.8 3.3 9.7 24.0 25.5 37.5 F e m a le ....................................................... 51.4 41.3 At least one v e h ic le o w n e d ..................................... 47.9 68.2 O ccup ation type: S e lf-e m p lo y e d ................................................... W orking for w age or s a la r y ................................... A d m in is tra tiv e /p ro fe s s io n a l............................... La borer/technician/skilled w o rk e r.................... S e r v ic e s .............................................. S a le s .................................................................... Not w o r k in g ................................................. .7 82.9 24.7 20.1 17.5 20.6 16.5 .4 99.6 20.4 41.7 19.0 18.5 - E duca tiona l atta in m e n t: High school graduate6 ............................................ A tten ded c o lle g e .................................................... A ssociate of Arts degree (A .A .)............................ 17.7 79.1 3.2 40.8 45.6 13.5 R ace/ethnicity: H is p a n ic ...................................................... W hite, not H is p a n ic .......................................... Black, not H is p a n ic ........................................... O ther race, not H is p a n ic ................................. 3.7 86.4 5.8 4.1 5.4 83.1 10.5 1.2 R esiding in urban a r e a s ....................................... 97.2 91.9 Incom e before taxes (annual)1.................................... W ages and s a la r ie s ......................................... S e lf-e m p lo y m e n t....................................... R egular s u p p o rt from oth er persons2 ..................... S cholarship, fellow ship, and other s tipe nds (not w orkin g)3 ..................................... Interest, d iv id e n d s , and oth er sources4 ................ Hours per w eek w o rk e d ................................... Weeks per year w o rk e d ...................................... Percent: Age 18 y e a r s ........................................................... 19 y e a r s ................................................................ 20 y e a r s ...................................................... 21 y e a r s ..................................................... 22 y e a r s ............................................................ 11ncludes complete income reporters only. 2 Includes income received from persons outside the consumer unit, such as parents or other relatives. 3 Also includes other miscellaneous sources of money income. 4 Includes government assistance, such as welfare and food stamps, and other sources, such as unemployment insurance and workers’ compensation, and other sources where applicable. 5 Includes high school diploma or the equivalent (for example, ged ). N ote : Dash indicates not applicable. As expected, nonstudents receive more total income, on average, than stu dents. However, the composition of in come is more diverse for students than for nonstudents. For example, nearly 70 percent of student income is labor in- 48 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 come, that is, wages and salaries or selfemployment. Still, income from parents or other relatives constitutes 14 percent (or nearly one in every seven dollars of incomes), followed by scholarships, fellowships, and related income at 11 percent. Income from interest, divi dends, and other sources accounts for 5 percent of student incom es. For nonstudents, however, labor income ac counts for 98 percent of their total in come before taxes. Expenditures. Given that nonstudents earn quite a bit more than students, it is not surprising that they spend more on most item categories than students each quarter.5 (See table 2.) Additionally, some items may be purchased for stu dents; for example, parents may pay the school directly for meals, shelter, or other items.6 More interesting to study, then, are expenditure shares themselves (how each group allocates its total ex penditures) and the percent of people reporting expenditures (how many stu dents or nonstudents report purchasing certain goods or services). Students allocate a larger share of their expenditures (13 percent) to food at home expenditures than nonstudents (9 percent), but students are less likely to report expenditures for food at home (90 percent) than nonstudents (97 per cent).7 This may mean that students purchase more restaurant food than do nonstudents, but that it is more likely to be from carry-out or other lowerpriced establishments. Also, restaurants near campus often provide student dis counts, as an incentive to increase their business among students. By contrast, both groups allocate about the same shares for food away from home8 (5 per cent) and other food9 (less than 1 per cent); the percent reporting these foods is also similar for each group (about 7 out of 8 for food away from home, and about 1 out of 20 for other food). Both students and nonstudents allo cate about one-fourth of their expendi tures to basic housing (shelter and utili ties), but while this expenditure is nearly universally reported by nonstu dents (98 percent), far fewer students (85 percent) report such an expenditure. This may be because of parental expen ditures for housing fees, or because of | E x p e n d itu r e s o f stud«snts a n d n o n s tu d e n ts fo r s e le c t e d ite m s , 1 9 9 6 -9 8 C o n s u m e r Ex p e n d it u r e S u rv e y , In t e r v ie w c o m p o n e n t Total e x p e n d itu re E xpenditure share (in p e rce n t) C h a ra c te ris tic Student N onstudent Student N onstudent Total expenditures (quarterly)........ Food, total (less on trip s )............ Food at ho m e........................... Food away from h o m e ............ Other fo o d ................................. $2,584 459 333 115 11 $4,365 648 409 226 13 100.0 17.8 12.9 4.5 .4 100.0 14.8 9.4 5.2 .3 H ousing............................................ Shelter and u tilitie s ...................... 689 592 1,243 1,133 26.7 22.9 28.5 26.0 House furnishings/operations.... 97 110 3.8 2.5 Apparel and s ervice s...................... 174 193 6.7 4.4 Transportation.................................. Vehicle p u rc h a s e s ....................... Vehicle expenses1........................ Gasoline/motor o il........................ Public transportation................... 297 109 97 84 7 1,157 710 296 141 10 11.5 4.2 3.8 3.3 .3 26.5 16.3 6.8 3.2 .2 Health c a r e ...................................... Health insurance.......................... Medical se rv ic e s.......................... Prescription d ru g s ....................... Medical s u p p lie s.......................... 25 5 12 5 4 83 43 31 5 1.0 .2 .5 .2 1.9 1.0 .7 .1 4 .2 .1 E ntertainm ent.................................. 168 231 6.5 5.3 E ducation......................................... 416 37 16.1 .8 Personal insurance/pensions2 ....... 72 317 2.8 7.3 Travel and vaca tion......................... 122 120 4.7 2.7 Other expenditures......................... 161 336 6.2 7.7 11ncludes vehicle finance charges, maintenance and repairs; insurance; and vehicle rentals and licensing fees. 2 Includes Social Security taxes. special arrangements students may have with their schools, such as, when some schools waive housing fees to entice certain students to attend, or provide free housing as a reward for service to the school. Students (73 percent) are also more likely to live with roommates in an apartment, group house, or an other arrangement than are nonstudents (35 percent), which also may reduce housing expenditures for students. Students and nonstudents have very similar expenditure patterns for apparel and services. Despite lower incomes, students spend only $19 less per quar ter than do nonstudents, and have a https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis slightly higher percent reporting (90 percent) than do nonstudents (87 per cent). This may be the result of a gen der effect. Males, whether students (86 percent) or not (85 percent) have a lower percent reporting than females, whether students (93 percent) or not (89 percent). Although females are propor tionately represented in the student population (51 percent), nonstudents are disproportionately male (59 per cent). Given that female students are the most likely to report expenditures for apparel and services (93 percent), they are responsible for raising the overall percent reporting among students; the higher proportion of males among non students, then, holds down the percent reporting for that group. Together, these effects result in the near-equality of percent reporting for students and non students. Students allocate only one-fourth the share of their expenditures to vehicle purchases (4 percent) that nonstudents allocate (16 percent). Fewer than half of students own vehicles, compared with more than two-thirds of nonstu dents. This is probably because stu dents can fulfill most of their demands for food, entertainment, and other ac tivities near their campuses, while non students presumably have to commute to work, and may not live in neighbor hoods where amenities are convenient to access. Despite these factors, each group still allocates about the same share of its expenditures to gasoline and oil (3 percent), and about 1 in 8 per sons studied (students and nonstudents) report expenditures for public transpor tation. Both groups allocate very small shares of expenditures to health care. However, the percent reporting is much smaller for students (23 percent) than nonstudents (42 percent). Although there is some difference in the percent reporting expenditures for medical ser vices (12 percent for students, com pared with 20 percent for nonstudents), the real difference is in reports of insur ance payments: only 3 percent of students report health insurance expenditures, compared with 27 percent of nonstu dents. This could be for a variety of rea sons. For example, students may still be covered under parents’ policies. A lso, many schools have student health centers that charge low fees for medications and services, thus reduc ing the need for student insurance. At $416 per quarter, expenditures for education for students may appear to be low. But it should be remembered that these, like all expenditures de scribed thus far, are “out-of-pocket” expenditures for the students. That is, Monthly Labor Review July 2001 49 Research Summary these are costs the students pay directly themselves. Parents or other agents may pay a substantial amount of the remain ing cost. Additionally, students who receive full (or sizable) scholarships would not report expenditures for edu cation. Still, more than half—57 per cent—of students report an expenditure for education. Thus, for students who report education expenditures, the av erage value reported is about $730 per quarter.10 Finally, despite the near-equality in dollars spent on travel and vacation, stu dents are much more likely to report these expenditures (57 percent) than are nonstudents (42 percent). This is prob ably because students incur expendi tures to visit family and friends during holidays or other break periods. Also, one cannot discount the role of a quintessen tial college experience: the “road trip.” T h is r e p o r t h a s e x a m in e d and compared differences in demographics and expen diture patterns for full-time college stu dents and those persons of similar age, who work full-time instead of attend ing college. Some of the differences found are expected a priori—nonstu dents work more hours and earn more income than do students; additionally, nonstudents are far more likely to be at least 21 years old. Also, students spend far more in both average dollars and as a share of total expenditures on educa tion than do nonstudents. Some differ ences are less easily anticipated. For example, one might expect that nonstu dents would spend more on transporta tion than students. However, the mag nitude—nonstudents spend about $3.90 for transportation for every $1.00 spent by students—is more interesting. This may be because students often live near their school, either on campus itself, or in the immediately adjacent neighbor hoods. And finally, in some cases, it is the similarities that are noteworthy. For example, students and nonstudents spend virtually the same amount on average (about $120 per quarter) for travel and vacation. The decision to attend college or to work instead is one that can have pro found effects throughout one’s life. An important question the potential student might ask is this: is it better to acquire knowledge through traditional educa tion or via on-the-job training? While the analysis here cannot provide the answer to this critical query, the data presented may provide at least some basic information for a better under standing of some of the costs associ ated with following either the education path or the direct work path. □ 4 The Consumer Expenditure Survey defi nition of a “renter” includes those who receive rent as pay, and those who live in universitysponsored housing. for the student. However, if the parent gives the student money to pay school expenses, the student reports the money received as “in come” and the expenses paid to the school are “expenditures” for the student’s consumer unit. Notes 1 Data derived from U.S. Census Bureau, Statistical Abstract o f the United States: 1999, 119th edition (Washington, DC, 1999), p. 202, table 326. The age group described (20 to 24) is the closest in the tables to the one used in this report (18 to 22). 2 A consumer unit consists of members of a particular household who are related by blood, marriage, adoption, or other legal ar rangements; a person living alone or sharing a household with others, but who is financially independent; or two or more persons living together who share responsibility for two of the three follow ing major expenses: food, housing, and other living expenses. Students living away from their families are also con sidered separate consumer units. 3 Based on the Current Population Survey definition. See http://w w w .bls.census.gov/ cps/bconcept.htm (visited July 27, 2000). 50 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 5 Although incomes are collected annually in the Consumer Expenditure Survey, expen ditures are collected quarterly. Because stu dents may cease to be separate consumer units for at least part of the year (that is, they may return “home” during the summer), no attempt to “annualize” expenditures is made. This fa cilitates comparison of expenditures for stu dents while they are “students” compared with nonstudents. 6 Students at college are considered to be distinct consumer units, even though they may receive outside support from their parents. If a parent pays the sch ool directly for a student’s food, housing, or health care, the expenditure is recorded for the parent, but not 7 For students who eat primarily in various campus eating establishments, “food at home” consists of food and nonalcoholic beverages purchased at grocery stores and convenience stores, and board at school. 8 Food and nonalcoholic beverages pur chased at restaurant, cafeterias, drive-ins, and so forth. 9 Catered affairs; school meals for preschool and school age children; and meals as pay. 10 This number is calculated by dividing the average reported for all students ($416) by the percent reporting (0.57). Estimates of union density by State Barry T. Hirsch, David A. Macpherson, and Wayne G. Vroman esearchers, public agencies, labor unions, private analysts, and the m edia are am ong those seeking information on union density, defined here as the percentage of non-agricultural wage and salary employees (including public sector employees) who are union members. This report describ es the d eriv atio n of tim econsistent estimates of union density by State for the 1964-2000 period. It also provides an alternative measure of union d en sity — the percentage of nonagricultural wage and salary workers who are covered by a collective bargaining agreement—for the years 1977-2000. Two sources of data are combined to produce the estimates: compilations from the Current Population Survey ( c p s ) , a m onthly survey of U.S. households, and the now discontinued b l s publication Directory o f National R Unions and Employee Associations (Directory), which contains information reported by labor unions to the Federal G o v ern m en t.1 Beginning in 1973, estimates are calculated directly from the May 1973 through May 1981 c p s or the January 1983 through December 2000 c p s Outgoing Rotation Group ( c p s o r g ) monthly earnings files. Prior to 1973, estimates are calculated based on figures in the b l s Directories, scaled to a level consistent with c p s estimates using information on years in which the two sources overlap. Barry T. Hirsch is professor of economics at Trinity University; David A. Macpherson is professor of economics at Florida State Uni versity; and Wayne G. Vroman is senior re search associate at the Urban Institute in Washington, D.C. The authors alone are respon sible for the results presented in this report. E-mail: bhirsch@trinity.edu https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis union density estimates, 1973-present cps For years 1973 to the present, estimates are based on c p s data. Beginning in 1983, estimates are based on the c p s - o r g earnings files. Each file includes data for all 1 2 months of the c p s , with each month including the quarter sample of the c p s administered supplement containing the union status questions (that is, the outgoing rotation groups or portion of the sample not to be included in the follow ing m o n th ’s survey). Each observation during a year is unique, although overlap is evident in the samples across pairs of years. Sample sizes average about 177,000 during the 1983-95 period and 157,000 since 1996, with a high of 185,030 observations in 1990 and a low of 152,188 in 1996. In 1983, the average sample weight is 508 (that is, each observation represents 508 in the population), but by 2000, the average weight had risen to 750. The 1977-81 union density estimates are calculated using data from the May 1977 through May 1981 c p s . Prior to 1981 (beginning in 1973), the May surveys administered the union status questions to all rotation groups, making sample sizes roughly one-third as large as the fu ll-y ear quarter sam ples beginning in 1983. The May 1981 c p s administered the union questions to just a quarter sample. The 1982 c p s did not include any union status questions; therefore, the 1982 figures are an average of the 1981 and 1983 c p s estimates. Much of the year-to-year variation in c p s union density estimates prior to 1983, particularly for smaller States, results from sample variability. For the years 1973-76, two problems are addressed in order to achieve timeconsistency. First, prior to 1977, the union membership question did not include the phrase “ or em ployee association similar to a union.” Absent any adjustm ent, union membership density in the c p s is measured as in creasing from 22.4 percent in 1976 to 24.1 percent in 1977, despite the fact that membership was falling in years before and after 1977. b l s annual figures based on union financial reports, however, show a 0.4-percentage point decline in union membership density between 1976 and 1977, from 24.5 percent to (coincidentally) the same 24.1 percent found in the c p s .2 Assuming that a timeconsistent c p s series would have fallen by 0.4 percentage points, a multiple of 1.094 is required to adjust upward pre1977 figures to the post-1977 c p s de finition including employee association members (that is, 1.094 times 22.4 percent equals 24.5 percent). The 1.094 national adjustment rate is applied to 1973-76 c p s figures for all States. Second, prior to 1977, c p s State identifiers exist for 12 large States plus the D istrict of Colum bia, with the remaining 38 States combined into ten multi-State groupings. State estimates for these 38 States during 1973-76 are derived as follows: first, by using the May 1977-81 c p s , the ratios of each State’s union density to its State-group union density are calculated. Then each State’s unionization estimates for 197376 are produced by multiplying each year’s State-group union density by the State-to-group ratios calculated for the overall 1977-81 period. Unking bls Directory estimates to the c p s , 1964-72 U nion status questions were not regularly collected in the c p s prior to 1973.3 The approach herein for the 1964-72 period utilizes information from various issues of the form er b l s publication Directory o f National Unions and Employee Associations, scaled to correspond to c p s levels. The Directory provided State-level union density estimates for the even-numbered years between 1964 and 1978.4 Data on union membership were obtained from a mail questionnaire to national unions, Monthly Labor Review July 2001 51 Research Summary employee associations, and a f l - c i o State organizations. State estimates were requested in these surveys, b l s then aggregated the responses to yield overall State estimates of union mem bership. These estimates were com bined with independent estimates of nonagricultural employment to obtain State-level density estimates.5 The Directory and c p s data sources overlap for 3 years— 1974, 1976, and 1978. Generally, the Directory estimates are slig h tly higher than the c p s estimates. When State-specific ratios of cps-to -Directory densities are averaged over the 3 years (1974,1976, and 1978), the range is from a low of 0.72 (Missouri) to a high of 1.41 (South Dakota). The median ratio was 1.02, with 22 of 51 being smaller than 1.0. Only four ratios fell below 0.9 and eight exceeded 1.2. Cross section regressions for the 3 years, with the c p s unionization rate estimates regressed on the Directory estimates, yielded adjusted R2s of 0.865 in 1974,0.859 in 1976 and 0.839 in 1978, and standard errors of 5.0 to 5.1 percentage points. Thus, while the sources of State level estimates for the 3 years of overlap are radically different, the two estimates generally are quite similar. In order to rescale the Directory density figures to a level consistent with the c p s , the State-specific 3-year cps-toDirectory average ratios are applied to the Directory estimates for 1964,1966, 1968,1970, and 1972. Estimates for the odd-numbered intervening years are computed as simple averages of the adjacent even-year estimates. Thus, a State-specific union density series for the years 1964-72 is obtained based on D irectory figures rescaled to correspond w ith c p s levels, while estim ates for 1973-2000 are based directly on the c p s . The overall series thus extends across 36 years for all States plus the District of Columbia.6 The n ational series of union membership density for 1964-2000 and 52 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 coverage density for 1977-2000 are shown in chart 1. Union membership density in nonagricultural wage and salary employment declined throughout the period, from 29.3 percent in 1964 to 24.1 percent in 1977 to 13.6 percent in 2000. Union coverage density declined from 26.9 percent in 1977 to 15.0 percent in 2000. M em bership density figures are shown for 3 selected years, 1964,1984, and2000.7 (See table 1.) Corresponding to the national trend, most States show sizable declines in State unionization. In 2000, the most highly unionized States were New York (25.7 percent) and Hawaii (24.6 percent), while the least unionized States were North Carolina (3.7 percent) and South Carolina (4.1 percent). | Comparison with previous State-level union estimates This section provides a b rief comparison of the database described in this summary with previous Statelevel union density estim ates. The original sources should be consulted for details. Estimates of State union density prior to the c p s rely on the financial reports made by labor unions to the Department of Labor, along with supplemental information obtained from unions and employee associations not reporting. In addition to the published b l s Directories, Leo Troy has used these reports to provide State estimates of full-time equivalent dues-paying membership. His estimates tend to be U n io n m e m b e r s h ip a s a p e r c e n t a g e o f o n a g r ic u lt u r a l e m p lo y m e n t , b y S ta te , 1964, 19 84, a n d 2 0 0 0 1964 1984 2000 All S ta te s ................... 29.3 19.1 13.6 A labam a...................... A la s k a ......................... A rizona........................ A rkansas.................... California..................... 21.1 39.7 17.6 15.0 33.0 15.2 24.2 9.2 10.0 21.6 9.8 21.9 6.6 5.9 16.4 Colorado...................... C onnecticut................ Delaw are..................... District of Columbia ... F lorida......................... 21.2 28.8 29.2 18.4 14.0 13.1 20.5 17.9 17.5 9.6 9.1 16.4 13.4 14.7 6.9 G eo rgia....................... Hawaii.......................... Ida ho........................... Illinois.......................... Ind iana........................ 11.9 21.7 24.8 35.6 40.9 10.3 29.2 9.5 22.6 25.4 6.3 24.6 7.9 18.7 15.7 Iowa............................. K ansas........................ K entucky.................... Louisiana..................... Maine........................... 27.7 21.3 25.0 18.1 23.8 17.4 11.9 17.3 11.1 19.2 13.9 9.1 12.2 7.1 14.3 M aryland..................... M assachusetts.......... Michigan...................... M innesota.................. M ississippi................. 24.7 27.7 44.8 37.0 15.4 18.4 21.4 29.4 23.1 9.7 14.7 14.4 21.0 18.4 6.1 1964 1984 2000 M issouri................. Montana................. N ebraska............... Nevada .................. New Hampshire..... 27.1 37.4 23.0 33.3 24.3 20.0 18.6 14.0 23.9 10.4 13.3 14.3 8.6 17.3 10.5 New Jersey............ New M e xico ........... New Y ork................ North C a ro lin a ....... North D a ko ta ......... 39.4 14.1 35.5 8.4 17.3 25.0 9.8 32.3 7.5 12.7 20.9 8.3 25.7 3.7 6.6 O h io ........................ O klahom a.............. O regon.................... Pennsylvania......... Rhode Is la n d ......... 37.6 15.8 38.9 37.7 26.0 23.9 10.4 25.1 25.0 22.5 17.5 6.9 16.5 17.0 18.3 South C arolina....... South D akota......... Tennessee ............. Texas ...................... U ta h ........................ 7.0 14.1 22.1 13.5 23.8 4.2 11.0 13.5 8.0 13.4 4.1 5.7 8.9 5.9 7.5 V erm ont................. Virginia................... W ashington............ West V irg in ia ......... W isconsin.............. W yom ing................ 18.5 15.8 44.5 36.5 34.0 21.0 11.5 10.8 26.3 24.1 25.0 15.7 10.4 5.7 18.5 14.4 17.9 8.5 N ote : Figures represent the percentage of each State’s nonagricultural wage and salary employ ees who are union members. Estimates for the 1964-2000 period are based on a combination of the 1983-2000 Current Population Survey Outgoing Rotation Group (cps- org ) earnings files, the 19 7 3 S i May cps earnings files, and the bls publication, D ire c to ry o f N a tio n a l U nion s a n d E m p lo ye e A sso cia tio n s for various years. Figures for all years, 1964 to present, are available from the authors. (See note 7.) C h a r t 1. Percent Percent of nonagricultural w a g e an d salary workers w ho a re union m em bers (m e m b e r density), 1964-2000, an d the p e rc e n t c o v e re d by a co lle c tiv e bargaining a g re e m e n t (c o v e ra g e density), 1977-2000 Percent 35 30 25 20 15 10 - Sources: 5 T h e 1 9 8 3 -2 0 0 0 C u rre n t P o p u la tio n S u rv e y O u tg o in g R o ta tio n G ro u p c p s e a rn in g s file s , a n d th e D ir e c t o r y o f ( c p s - o r g ) e a rn in g s file s , th e M a y 1 9 7 3 -8 1 N a tio n a l U n io n s a n d E m p lo y e e A s s o c ia tio n s , v a rio u s ye a rs . smaller than those in the Directories, owing to the b l s use of a less stringent definition of membership. In a 1957 p u b licatio n , Troy provides state estimates of membership for 1939 and 1953. In a 1985 publication, Troy and Neil Sheflin provide revised State figures for 1939 and 1953, as well as estimates for 1960,1975,1980, and 1982.8 C om pilations by researchers of union microdata from the c p s have provided the primary source for recent estimates of union density for States, as well as for metropolitan areas, detailed industry, and detailed occupation. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Richard Freeman and James Medoff provide union m em bership density figures for all private sector wage and salary workers based on the combined 1973-75 May c p s ; Edward Kokkelenberg and Donna Sockell calculate annual State membership density among all wage and salary workers aged 14 and older using the May 1973 through May 1981 c p s ; and Michael Curme, Barry Hirsch, and David Macpherson provide State estimates using the b l s definition of all wage and salary workers aged 16 and older based on the monthly c p s Outgoing Rotation Group earnings files beginning in 1983.9 In addition, Hirsch and M acpherson have provided c p s State union density estimates for all wage and salary workers for each of the years from 1983 to the present, along with separate State estimates for private, public, and private m anu facturing sector workers.10 Their State density figures for all workers and private manufacturing are subsequently reproduced in the annual Statistical Abstract o f the United States, beginning with the 1995 volume (the State table includes 1983 and the most current year, beginning with 1994). None of the above includes c p s State union density for n o n a g ric u ltu ra l wage and salary workers, as measured here and in the earlier b l s Directories. The immediate precursor for the database described in this summary is a study by Wayne Vroman regarding interstate differences in unemployment insurance recipiency rates. He con structed a 1966-98 series of State union density rates based on pu b lish ed figures in the b l s Directories, c p s State density rates for 1973-81 from the work of Kokkelenberg and Sockell, and c p s State density rates for 1983 forward from Hirsch and Macpherson’s annual Data B ook.11 The analysis of this report follows the approach used in Vroman’s study to integrate the b l s Directory and c p s figures, but the database has been extended in time and the methodology has been refined to enhance tim e consistency. In particular, c p s figures are estimated for all years since 1973, with agricultural workers excluded, and the cps figures have been adjusted for 1973-76 to account for the change in the union membership question in 1977. This report has provided a description of the new State union database, which will be avail able to researchers on an on-going basis. Availability of estimates The State-level union density databases described in this report are available Monthly Labor Review July 2001 53 Research Summary |H 3 ^ 0 State union density estimates for the previous calendar year will be compiled and added to the m em bership and coverage databases. N o n a g r ic u lt u r a l w a g e a n d s a la r y w o r k e r s w h o a r e u n io n m e m b e r s a n d th o s e c o v e r e d b y a u n io n c o n tr r a c t, 1 9 6 4 - 2 0 0 0 [In percent] Year Union m em b ers How estimates are calculated C o v e re d b y union c o n tra c t 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 ................. ................. ................. ................. ................. ................. ................. ................. ................. ................. 29.3 28.9 28.4 28.3 28.2 28.0 27.8 27.2 26.6 26.6 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 ................. ................. ................. ................. ................. ................. ................. ................. ................. ................. 26.2 24.6 24.5 24.1 23.4 24.4 23.3 21.7 21.0 20.3 26.9 26.2 27.4 26.1 24.3 24.0 23.6 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 ................. ................. ................. ................. ................. ................. ................. ................. ................. ................. 19.1 18.2 17.7 17.3 17.0 16.6 16.3 16.3 16.0 21.9 20.8 20.2 19.4 19.2 18.8 18.6 18.5 18.1 16.0 18.0 1994 1995 1996 1997 1998 1999 2000 ............... ............... ............... ............... ............... ............... ............... 15.7 15.1 14.7 14.2 14.1 14.0 13.6 17.7 16.9 16.4 15.8 15.6 15.5 15.0 Estimation of State-level union density using the cps follows the methodology used by b l s to calculate published estimates of national union membership and coverage, the only difference being that agricultural workers are excluded here in order to provide consistency with estimates for earlier years derived from the b l s D irectories .13Union membership and coverage are defined as follows. Beginning in 1977, the cps included two questions related to union status. There have been no changes in these questions since 1977. Workers are counted as union members if they respond “ y es” to the follow ing question, asked to employed wage and salary workers: “On this job, i s ___a m ember of a labor union or of an em ployee association sim ilar to a union?” Workers who answer “no” to this question are then asked: “On this job, is ___ covered by a union or em ployee association co n tra ct?” Workers are counted as covered if they are union members or if they are not members but say they are covered by a union contract. Union membership density in State j is calculated as follows: - - _ - S ources : The 1983-2000 Current Popula tion Survey Outgoing Rotation Group (cps- org ) earnings files, the May 1973-81 cps earnings files, and the D ire c to ry o f N a tio n a l U nions a n d E m p lo ye e A sso cia tio n s, various years. from the a u th o rs.12 The data are contained in two spreadsheets, with each row corresponding to a State and the union density figures by year in colum ns (beginning with the most recent year). The membership density database contains figures from 1964 forward. The coverage density database contains figures for 1977 forward. Following release of the c ps each year, 54 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis %Mem.j = 100 (Xw..M JIw .) = ij ij '/ 100(Membership/Employment) where i indexes individual cps respon dents and j indexes the S tate (or metropolitan area, industry, occupation, and so forth) over which density is being calculated. E m ploym ent is measured by ZW , the sum of the sample weights across the i individuals in State j. Included are all employed wage and salary workers, with the exception of workers whose industry of employment July 2001 is agriculture, fishing, or forestry.14 Letting M = 1 if individual i in State j is a union mem ber, then total union membership is measured by £ w M and union density by 100(Zw.M JZw.j. %Cov is calculated identically, except that the dummy variable C.. is substituted for M measuring coverage by a collective bargaining agreement. %Cov.j = 100 (Z w‘j.C ¡jJZ w .) = v '/ 100(Covered / Employment) There are several differences in the union status information available prior to 1977 in the May 1973-76 c p s . First, the m em bership question did not include the phrase “ or em ployee association similar to a union.” Second, there was no union coverage question. And third, not all States were uniquely identified, so many workers have their residence assigned to State groups rather than to a particular State. The addition in 1977 of the phrase “employee association” is estimated to have increased overall union density by about 2 p ercentage points, w ith relatively small effects in the private sector and large effects in the public sector. As described in this report, the change in the cps membership question and the use of State groups prior to 1977 have been addressed in the construction of the union density series. □ Notes 1 Published through 1970 was the U.S. De partment of Labor, Bureau o f Labor Statis tics, Directory o f National and International Labor Unions in the United States. Published beginning in 1972 and ending in 1980 was the U.S. Department of Labor, Bureau o f Labor Statistics, Directory o f National Unions and Employee Associations. 2b ls , 1979, Bulletin 2079, Directory o f Na tional Unions and Employee Associations 1979, #2079, Table 6. Unlike the Directory figures used to form the database of this sum mary (see note 4), this series excludes mem- bers of “single-firm” unions and local unaf filiated unions and, thus, is not directly com parable to the broader-based biennial figures provided nationally and for States. Both Di rectory series exclude Canadian membership. 3 A union status question was asked of pri vate sector workers in the March 1966 cps and o f private and public sector workers in the March 1970 cps . These surveys contain identifiers for large States and State group identifiers for the remaining States. 4The Directory published each year’s figure in the calendar year following the survey, and then “revised” figures two years later in the next Directory. The revised State figures for 1964-76 are used here, along with the origi nal figures for 1978, published in the final Directory. Bulletin numbers, year of data, and source tables are as follows: Directory o f Na tional Unions and Employee Associations 1979, #2079 (data for 1978, 1976 revised, Table 18); 1977, #2044 (1974 revised, Table 18); 1975, #1937 (1972 revised, Table 18); 1973, #Un33l9/973 (1970 revised, Table 18); 1971, #1750 (1968 revised, Table 18); the Directory o f National and International La bor Unions in the United States, 1969, #1665 (1966 revised, Table 10); and 1967, #1596 (1964 revised, Table 9). 5 The bls Directories include series for both membership, and membership and employee associations. The former series is roughly comparable to cps figures that include the phrase “employee association” in the mem bership question, whereas the latter series is about 3 percentage points higher. The Direc tory appears to overstate member and asso ciation membership, whereas respondents in the cps may understate their affiliation with employee associations. For example, the Di rectory includes some members who are re tired, whereas membership in the cps is mea sured only among employed workers. Because this summary is an attempt to construct a series time-consistent with figures based on the post-1977 cps question, the bls Directory numbers based on membership are used https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis throughout. Note that State estimates in the and Labor Relations Review, April 1993, pp. Directory are not precise, owing to record 574-78. The latter paper makes available on request State unionization rates for 1983 through 1991. keeping problems at some union headquarters (for example, for the 1978 data, the Bureau had to develop estimates for 28 percent of the 174 national unions). 6 In the bls Directories the District of Co lumbia and Maryland are lumped together, while in the pre-1977 c p s , Maryland is in cluded as a part of a State group. In order to obtain separate rates for the District of Co lumbia and Maryland for the years 1964-72, the follow ing calculations were performed: the cps union density rate was calculated for the entire 1977-81 period for DC, MD, and DC-MD combined, and then the Directory fig ures were adjusted for DC-MD by the ratio for D C /D C -M D (0.8675) and for M D /D C -M D (1.0199). Calculations then proceeded as de scribed in the text. 7 Because of space, union membership fig ures are not shown for all 36 years. However, these data are available from the authors’ websites at http://www.trinity.edu/bhirsch/ or http://garnet.acns.fsu.edu/~dm acpher. 8 See Leo Troy and Neil Sheflin, U.S. Union Sourcebook: Membership, Finances, Struc ture, Directory (West Orange, NJ), Industrial Relations Data Information Services, 1985), Table 7.1. 9 See Richard B. Freeman and James L. M edoff, “New Estimates o f Private Sector Unionism in the United States,” Industrial and Labor Relations Review, January 1979, pp. 143-74; Edward C. Kokkelenberg and Donna R. Sockell, “Union Membership in the United States, 1973-1981,” Industrial and Labor Relations Review, July 1985, pp. 497543; Michael A. Curme, Barry T. Hirsch, and David A. Macpherson, “Union Membership and Contract Coverage in the United States, 1983-1988,” Industrial and Labor Relations Review, October 1990, pp. 5-33; and Barry T. Hirsch and David A. Macpherson, “Union Membership and Coverage Files from the Cur rent Population Surveys: N ote,” Industrial 10 See Barry T. Hirsch and David A. Macpherson, Union Membership and Earn ings Data Book: Compilations from the Cur rent Population Survey (Washington, D.C., Bureau of National Affairs, annual). 11 See Wayne Vroman, “Low B enefit Recipiency in State Unemployment Insurance Programs,” Draft report to the U.S. Depart ment o f Labor, U nem ploym ent Insurance Service, October 1999; Kokkelenberg and Sockell, “Union Membership in the United States, 1973-1981,” July 1985; and Hirsch and Macpherson, Union Membership and Earn ings Data Book, annual. 12 See note 7 for the authors’ urls . 13 The Bureau of Labor Statistics publishes national estimates from the cps each January for the previous calendar year in its Employ ment and Earnings. The Bureau o f National Affairs publishes an annual Data Book that includes national numbers compiled from the cps identical to published bls figures, plus dis aggregated union and earnings figures begin ning with 1983 for States, metropolitan ar eas, detailed industries, and detailed occupa tions. See Hirsch and Macpherson, Union Membership and Earnings Data Book, an nual. State data for 1995 (the earliest year tabulated) to the present also are available from BLS, provided upon request. Note that the Current Population Survey data are based on place of residence, while data for the Di rectory are based on place of work. Also, the cps covers only employed union members; the Directory data may include retirees. An ad vantage of the State database described in this article is that by making continuous annual figures readily available, users can observe variability in the estimates and use a moving average across years, if deemed appropriate. 14 This follows the bls definition of “nonagricultural” employment. Monthly Labor Review July 2001 55 Regional Trends M ultiple jobholding in States, 2000 Multiple jobholding rates were down in 33 States and the District of Columbia "Regional Trends" is prepared in the Divi sion of Local Area Unemployment Statis tics, Bureau of Labor Statistics. More in form ation is on the Internet at http:// www.stats.bls.gov/lauhome.htm or call (2 0 2 ) 6 9 1 -6 3 9 2 in 2000, reflecting a 0.2-percentage point decrease in the national rate. The larg est over-the-year decline was recorded in Minnesota (-1.6 percentage points). Though that State’s multiple jobholding rate was still relatively high at 8.4 per cent, 2000 marked the first time it dropped below 10.0 percent since State estimates first became regularly avail able in 1994. Colorado (-1.5 points) and Alaska (-1.3 points) experienced the next largest declines, followed by four additional States with decreases of 1.0 percentage point or more. Arkansas and Nebraska recorded the largest increases (0.9 percentage point each). States continued to show consider able variation in multiple jobholding around the U.S. average of 5.6 percent, as well as a clear geographic pattern from North to South. All seven States in the West North Central division had rates at Multiple jobholders as a percentage of total employment by State, 1999 and 2000 annual averages 1999 2000 United S ta te s ....................... A labam a................................. A la s k a .................................... Arizona.................................... A rkan sas............................... 5.8 5.7 8.9 4.5 4.5 5.6 5.1 7.6 4.9 5.4 C alifornia.............................. Colorado............................... C onnecticut.......................... Delaware............................... District of C olum bia............ 5.1 7.5 5.9 6.4 6.3 4.8 6 0 6.5 5.7 6.2 F lo rid a .................................... G eorgia................................... Hawaii..................................... Id a h o ...................................... Illin o is ..................................... 5.0 4.5 9.8 8.3 5.2 3.9 4 2 9.3 7.9 5 4 Indiana.................................... Iow a........................................ Kansas ................................... K entu cky............................... Louisiana............................... 5.9 8.4 8.5 5.1 3.8 6.0 8.1 8.0 5.7 4.2 M aine...................................... Maryland................................ Massachusetts...................... M ichigan................................ Minnesota.............................. Mississippi............................. 8.0 6.4 5.9 5.5 10.0 4.3 8.6 5.8 5 8 5.3 84 4.3 State 56 Monthly Labor https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Review July 2001 1999 2000 Missouri.......................... M ontana......................... N ebraska....................... Nevada .......................... New H am pshire............ 7.9 10.3 9.4 4.6 7.1 7.6 9.8 10.3 5.0 6.3 New Jersey................... 5.2 5 9 52 5.5 10.3 4.2 4 8 5 0 4.9 10.0 6.5 6 3 5.9 6.3 8 1 6.3 6 4 6.4 5.7 7 8 South C aro lina............... South D akota................. Tennessee....................... Texas............................... U ta h ................................ 5.6 9.6 5.3 4.8 7.3 4.5 9.0 5.1 4.7 7.0 V erm ont.......................... V irginia............................ 8.7 5.5 72 4^8 8 2 8.9 9.2 5.6 7 6 5.1 8 0 8.8 State North C arolina............... North D a ko ta ................ O h io ............................... O regon........................... P ennsylvania................ West Virginia.................. W y o m in g ........................ least 2.0 percentage points higher than that of the United States. Nebraska and North Dakota were the only States to record double-digit rates— 10.3 and 10.0 percent, respectively. All six States in New England, which surpassed the West North Central as the division with the lowest annual average unemploy ment rate in 2000, also reported multiple jobholding rates above the national av erage. The northernmost States in the Mountain and Pacific divisions also had above-average multiple jobholding rates. By contrast, 7 of the 11 States with rates below 5.0 percent were along the southern U.S. border, with only New Jer sey among that group in the northern part of the Nation. Of the 17 States in the South region, 12 had rates below the national average; only the District of Columbia and Oklahoma recorded rates above 6.0 percent. Florida, where the multiple jobholding rate dropped by 1.1 percentage points to 3.9 percent, had the lowest rate in the Nation. Louisiana, which had posted the lowest rate in 1999 as well as 3 of the 4 prior years, recorded the second lowest rate in 2000 (4.2 per cent), as did Georgia and New Jersey. Overall, 30 States and the District of Columbia had rates higher than the United States last year, and 19 States had lower rates. □ Multiple jobholding rates by State, 2000 annual averages (U.S rate = 5.6 percent) W est North Central New England Pacific i i i i ,« V i C0 CO LU j p \ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis South Atlantic W est 9 .0 percent or m ore S o u th c e n tra l VM * 7 .0 - 8 .9 percent 5 .0 - 6 .9 percent South Central 4 .9 percent or le s s S ource : Current Population Survey Monthly Labor Review July 2001 57 Précis W elfare, work, and location There are many obstacles to the transi tion from welfare to work. A recent study by Harry J. Holzer and Michael A. Stoll under the auspices of the Brookings Center on Urban & Metro politan Policy explore the impact of the often-divergent locations of low-skill jobs and welfare recipients seeking work. Their paper, “Meeting the De mand: Hiring Patterns of Welfare Recipi ents in Four Metropolitan Areas,” de scribes this “spatial mismatch” as most typically a case of the welfare-recipient population living in segregated innercity neighborhoods, while jobs are most plentiful in suburban neighborhoods. Holzer and Stoll use data from the Census Bureau and the results of a sur vey of employers in Chicago, Cleveland, Milwaukee, and Los Angeles to over lay the locations of new low-skill jobs and the location of populations at high est risk of welfare receipt. They found that, despite the facts that welfare re cipients are often located far from the suburban locations of jobs and that suburban employers were more willing to hire recipients, in fact “employers in the central city and near public transit fill higher proportions of their low-skill jobs with welfare recipients.” In general, the willingness of employ ers to hire welfare recipients in either case is not very high in absolute terms— neither suburban nor central city em ployers reported more than 2 percent of job openings to be available to welfare recipients. Holzer and Stoll observe, however, that these opportunities rep resent “considerable demand” for such workers relative to the number of wel fare recipients actually entering the la bor force. Analyzing skill content Many examinations of the demand for skills in the labor market depend on mea 58 Monthly Labor Review July 2001 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis sures of the educational attainment of job incumbents to measure the level of skills needed for a particular occupa tion. David A. Autor, Frank Levy, and Richard J. Murnane provide a taskbased analysis of skill demands in their NBER working paper, “The Skill Con tent of Recent Technological Change: An Empirical Exploration.” By measuring skills in terms of tasks as defined in the Dictionary o f Occu pational Titles rather than in terms of credentials, they are able to examine more directly how computerization af fects work content. This examination is used to show “the m echanism s undergirding the widely-documented observation that computers and edu cation are relative complements.” In general, the computer allows the more rapid and efficient completion of the routine procedures of the information processing or cognitive tasks that re quire relatively high degrees of educa tional attainment. The task-based metrics also are used to understand how technical change has changed the balance be tween the cognitive and manual con tent of jobs since 1960. They report, “The proportion of the labor force em ployed in occupations that made inten sive use of non-routine cognitive tasks—both interactive and analytic— increases substantially.” These are the tasks that generally require the skills represented by credentials of higher education. Autor, Levy, and Murnane also quantify a sizable impact of these changes in the increased demand for workers with relatively high levels of educational attainment. Measuring ‘core’ inflation Policymakers and economic analysts need good current measures of the un derlying trend in inflation. The overall Consumer Price Index ( c p i ) may some times include unusual price changes in some components that might obscure the underlying trend. Thus is born the need for a measure of “core” inflation that ignores short-term relative price changes and focuses on the common, persistent components that are neces sary for more accurate inflation fore casts. In the Federal Reserve Bank of Kan sas City’s Economic Review, Todd E. Clark evaluates five such measures of core inflation based on c pi data. The measures he studies are the c pi exclud ing food and energy, the c p i excluding energy only, the m edian CPI, a “trimmed” mean CPI (the components largest and smallest changes for the month are excluded), and a CPI exclud ing the eight components with the his tories of highest volatility. While Clark admits that none of these indicators are perfect, his analysis sug gest that the CPI excluding energy and the trimmed mean c pi best meet the joint requirements of tracking current trend inflation, predicting future inflation at 1- and 2-year horizons, and being easy to communicate to the public. The trimmed mean was the most accurate tracker of current trend inflation and a powerful predictor of future inflation, but would be somewhat more difficult to explain to the public. The CPI exclud ing energy would be much more trans parent and is also a powerful predictor of future inflation, but does not track current trend inflation as well as the trimmed mean. rn We are interested in your feedback on this column. Please let us know what you have found most interesting and what essential readings we may have missed. W rite to: Executive E ditor, Monthly Labor Review, Bureau of Labor Statistics, Washington, DC, 20212, or e-mail, mlr@bls.gov Book Reviews Occupational social work Social Services in the Workplace: Repositioning Occupational Social Work in the New Millennium. Edited by Michael E. Mor Barak and David Bargal. New York, The Haworth Press, Inc., 2000,223 pp. This book provides an overview of the occupational social work field and its emergence and role within the current working world. This volume encom passes the scope of the field, its theo retical underpinnings and conceptual justification, research findings appli cable to occupational social workers, and position papers on future directions within the profession. This edited col lection of 12 research papers, essays, and theoretical papers is divided into seven major topics: 1) Introduction; 2) Innova tive Organizational Intervention; 3) Di versity in the Workforce; 4) International Perspectives of the Workforce; 5) Occu pational Social Work Roles; 6) Broaden ing the Occupational Social Work Do main; and 7) Epilogue. The introductory article by the vol ume editors serves to set the context for occupational social work, as well as de lineate its history, mission, and course for its future. Citing numerous trends w ithin the w orkplace, including downsizing, rightsizing, mergers, global ization, and acquisitions, the editors point out that workers are suffering in creasing duress relative to their worklife. They believe these trends necessitate the provision of social work services to individuals and their families who are em ployed, in need of employment, or dis placed. In addition, organizations, in cluding those in transition, can benefit as clients of occupational social work ers. Occupational social workers are also uniquely positioned to assist former welfare recipients obtain jobs. The editors articulate the challenge for occupational social work as: 1) im proving the fit between individuals, families, work organizations, and com https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis munities; 2) helping people transition to gainful employment; 3) introducing so cial work values and principles to the workplace; and 4) generating knowledge about the relationship between social work and work that will inform research and policy. They also point out that the occupational social work field is some times viewed as an important new arena for social work, and other times as aver sive to the profession’s social con sciousness. Two articles on workforce diversity address issues of theoretical perspec tives on diversity, inclusion-exclusion, and personal and organizational out comes. The diversity problem in the workforce is reframed as “How can di versity work for organizations?” The pa per on incorporating employees with an alternative sexual orientation in the work place provides a useful example. Both papers provide useful guidelines and ex amples for occupational social workers. Two research papers are included to provide direction to occupational social workers on how to create successful and satisfying work environments and de sign appropriate interventions for em ployees. Two other papers address populations traditionally served by so cial workers, persons with severe men tal illness, and welfare recipients, and attempt to place these client groups within the work context, describing means by which occupational social workers can facilitate the success of this process. A paper seeking to delineate a future direction for occupational social work acknowledges that professionalization is essential to its acceptance and suc cess as a field of endeavor. Impediments to professionalization stem from lack of certification requirements, possible claims of other professions to meet cli ent needs, and lack of ongoing profes sional communication. A need for a strong professional identity, a researchbased theoretical foundation, recogni tion by professional organizations, and a clearly defined niche of professional specialization could be added to this list. The second opinion piece points out that social work practitioners are increas ingly less motivated by social justice and more attracted by status, professional autonomy and advancement, and finan cial security. The author captures the essence of this issue by asking, “Whose agent are we?” “Is social work inher ently incompatible with occupational so cial work and the goals of corporate cul ture and values?” The author believes occupational social work can continue the social work service tradition in work place settings. The final paper attempts to reposi tion occupational social work within the new millennium by situating the field be tween workplace realities and workforce needs. The author dictates that occu pational social work needs to permit cross-fertilization between practice in workplace settings and more traditional social work settings to create a more ef fective practice. This paper provides a fitting end to a volume attempting to codify existing knowledge and set a fu ture course for a relatively new field seek ing a professional identity. Anyone in terested in social work and its potential applications in the workplace will find that this volume provides numerous ex amples of effective interventions and a blueprint of its future direction. — Ronnie H. Fisher Professor, Social Work and Psychology Miami-Dade Community College Labor union organizing Organizing the Shipyards: Union Strat egy in Three Northeast Ports, 19331945. By David Palmer. Ithaca, NY, Cornell University Press, 1999.264pp. $39.95. Studies of workers and workers’ institu tions have often neglected the actual process of organizing individuals into unions, and particularly the experiences Monthly Labor Review July 2001 59 Book Reviews of the organizers themselves. David Palmer’s Organizing the Shipyards helps fill that gap. Palmer chronicles the his tory of union organizing by members of the Industrial Union of Marine and Ship building Workers of America (Marine and Shipbuilding Union). Focusing on shipyards operated by large corpora tions in three major Northeast ports— New York Shipbuilding in Camden, New Jersey, Federal Shipbuilding in Kearney, New Jersey, and Bethlehem Fore River Shipyard in Quincy, Massachusetts— Palmer traces the evolution of organiz ers’ experiences from the depths of the Great Depression to the booming expan sion of World War II. Representing a quarter of a million members at its peak, the Marine and Shipbuilding Union for a time was one of the largest of the Con gress of Industrial Organization’s (CIO) unions that sought to organize workers ignored by the American Federation of Labor (AFL). Palmer approaches his subject not as a disinterested bystander, but as one who fervently believes in the importance of rank-and-file labor organization. As a former United Electrical, Radio and Ma chine Workers of America organizer, Palmer is forthright about the connec tion between historical events and the present “crisis in organizing” that plagues unions at the end of the 20th century. Palmer integrates employers and the government into his analysis of workers and their institutions, and through these three overlapping and in terrelated perspectives provides a more complete picture of the obstacles en countered by organizers. By shifting his focus from the workers’ communities surrounding the shipyards to corporate boardrooms and halls of government, Palmer describes the complex genesis of shipyard labor organizing. This in-depth appraisal explains the evolution of orga 60 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 nizers and their tactics, from underdogs in the early 1930s to bureaucratic stickin-the-muds by the end of World War II. The Marine and Shipbuilding Union rose to power in 1934 when a carefully planned strike by predominantly social ist and Scottish workers at New York Shipbuilding in Camden (across the Dela ware River from Philadelphia) halted con struction on U.S. Navy vessels. New York Shipbuilding’s weak company union, lack of political savvy, and lack luster managers provided an opening for the Camden-Philadelphia region’s leftist and socialist workers to organize the Marine and Shipbuilding Union. Grass roots organizing together with govern ment pressure to resume defense pro duction legitimized union activity and hastened recognition. The radical orga nizers who founded the Marine and Ship building Union immediately sought to expand it to other shipyards. Federal Shipbuilding in Kearney was similar in many ways to New York Shipbuilding, as it was part of an enormous complex of maritime industries making up the larger Port of New York. The port region con tains 750 miles of docks and coastline within a 25-mile radius of the Statue of Liberty. Drawing on the region’s radical tradition and history of unionization in maritime industries, organizers at Fed eral ship were very successful in estab lishing the Marine and Shipbuilding Union. By contrast, workers at the Fore River Shipyard in Quincy faced a vastly dif ferent set of circumstances. As Palmer points out, Quincy was a relatively small community located on the fringes of Boston’s metropolitan area, and was not a part of a larger maritime industrial com plex. Quincy also echoed the Boston area’s Protestant-Yankee and IrishCatholic conservatism, and lacked a large pool of politically left activists that con tributed to the Marine and Shipbuilding U n io n ’s success in C am den and Kearney. Also, Fore River Shipyard workers did not benefit from government intervention, and Bethlehem’s stronger management and more successful com pany union aggressively fought outside organizers. Palmer uses these differ ences to demonstrate union successes and failures. Readers should be forewarned that they will find little information in Orga nizing the Shipyards on shipbuilding and the work process—as the title sug gests, Palmer focuses on labor organiz ing, not shipbuilding. In examining the experiences of rank-and-file labor orga nizers, Palmer relies heavily on oral his tory interviews with workers, former union officials, and the organizers them selves. Corroborating and supplement ing these interviews is a rich and varied collection of sources, including manu scripts, newspapers, and published documents from labor unions, employ ers, and the Federal Government. There is an index, but the bibliography unfor tunately includes only primary sources, so those looking for secondary sources or additional reading will have to scan the ample footnotes. There are many tables and some maps and photographs, although they are few in number. Read ers unfamiliar with the plethora of orga nizations may be overwhelmed by the “alphabet soup” of acronym s, and would likely have benefited from an ap pendix listing the abbreviations. These are minor criticisms, and Palmer should be applauded for opening this new vein for other others to mine. Labor histori ans as well as those interested in the history of the Great Depression and World War II will find this a valuable work. —John Cashman Boston College C urrent Labor Statistics Notes on labor statistics ................. 62 Comparative indicators 1. Labor market indicators...................................................... 2. Annual and quarterly percent changes in compensation, prices, and productivity....................... 3. Alternative measures of wages and compensation changes..................................................... 72 Labor com pensation and collective bargaining data— continued 26. Participants in benefits plans, small firms and government................................................................ 95 27. Work stoppages involving 1,000 workers or m o re ........... 96 73 73 Price data 28. Consumer Price Index: U.S. city average, by expenditure 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 States, seasonally adjusted.......................................................... 11. Employment of workers by States, 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. Annual data: Employment status of the population....... 19. Annual data: Employment levels by industry.................. 20. Annual data: Average hours and earnings levels by industry...................................... 74 75 76 77 77 78 79 79 97 100 101 102 103 104 105 106 107 108 108 80 82 83 84 85 86 87 87 88 Labor compensation and collective bargaining data 21. Employment Cost Index, compensation, by occupation and industry group................................. 89 22. Employment Cost Index, wages and salaries, by occupation and industry group................................. 91 23. Employment Cost Index, benefits, private industry workers, by occupation and industry group................. 92 24. Employment Cost Index, private nonfarm workers, by bargaining status, region, and area s iz e .................... 93 25. Participants in benefit plans, medium and large firm s..... 94 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis category and commodity and service groups.............. 29. Consumer Price Index: U.S. city average and local data, all items.................................................... 30. Annual data: Consumer Price Index, all items and major groups....................................................... 31. Producer Price Indexes by stage of processing............... 32. Producer Price Indexes for the net output of major industry groups......................................................... 33. Annual data: Producer Price Indexes by stage of processing................................................ 34. U.S. export price indexes by Standard International Trade Classification................................................... 35. U.S. import price indexes by Standard International Trade Classification................................................... 36. U.S. export price indexes by end-use category............... 37. U.S. import price indexes by end-use category.............. 38. U.S.intemational price indexes for selected categories of services.................................................. Productivity data 39. Indexes of productivity, hourly compensation, and unit costs, data seasonally adjusted........................ 40. Annual indexes of multifactor productivity...................... 41. Annual indexes of productivity, hourly compensation, unit costs, and p rice s....................................................... 42. Annual indexes of output per hour for selected industries........................................................................... 109 110 Ill 112 International comparisons data 43. Unemployment rates in nine countries, data seasonally adjusted.................................................. 115 44. Annual data: Employment status of the civilian working-age population, 10 countries............................ 116 45. Annual indexes of productivity and related measures, 12 countries...................................................................... 117 Injury and illness data 46. Annual data: Occupational injury and illness incidence rates.................................................................. 118 47. Fatal occupational injuries by event or exposure............................................................................ 120 Monthly Labor Review July 2001 61 Notes on Current Labor Statistics This section of the Review presents the prin cipal statistical series collected and calcu lated by the Bureau of Labor Statistics: series on labor force; employment; unem ployment; labor compensation; consumer, producer, and international prices; produc tivity; 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 addi tional 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 cli matic conditions, industry production sched ules, opening and closing of schools, holi day 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 es timated on the basis of past experience. When new seasonal factors are computed each year, revisions may affect seasonally adjusted data for several preceding years. Seasonally adjusted data appear in tables 1-14,16-17,39, and 43. Seasonally adjusted labor force data in tables 1 and 4-9 were re vised in the February 2001 issue of the Re view. Seasonally adjusted establishment sur vey data shown in tables 1, 12-14 and 1617 were revised in the July 2000 Review and reflect the experience through March 2000. A brief explanation of the seasonal adjust ment methodology appears in “Notes on the data.” Revisions in the productivity data in table 45 are usually introduced in the September issue. Seasonally adjusted indexes and per cent changes from month-to-month and quarter-to-quarter are published for numer ous Consumer and Producer Price Index se ries. 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 ef fect of changes in price. These adjustments are made by dividing current-dollar values by the Consumer Price Index or the appro priate component of the index, then multi plying by 100. For example, given a current hourly wage rate of $3 and a current price 62 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 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 values) are described as “real,” “constant,” or “ 1982” dollars. Sources of information Data that supplement the tables in this sec tion are published by the Bureau in a variety of sources. Definitions of each series and notes on the data are contained in later sec tions of these Notes describing each set of data. For detailed descriptions of each data series, see b l s Handbook o f Methods, Bul letin 2490. Users also may wish to consult Major Programs o f the Bureau o f Labor Sta tistics, Report 919. News releases provide the latest statistical information published by the Bureau; the major recurring releases are published according to the schedule appear ing on the back cover of this issue. More information about labor force, em ployment, and unemployment data and the household and establishment surveys under lying the data are available in the Bureau’s monthly publication, Employment and Earn ings. Historical unadjusted and seasonally adjusted data from the household survey are available on the Internet: http ://stats.bls.gov/cpshome.htm Historically comparable unadjusted and sea sonally adjusted data from the establishment survey also are available on the Internet: http ://stats.bls.gov/ceshome.htm Additional information on labor force data for areas below the national level are pro vided in the BLS annual report, Geographic Profile o f Employment and Unemployment. For a comprehensive discussion of the Employment Cost Index, see Employment Cost Indexes and Levels, 1975-95, BLS Bul letin 2466. The most recent data from the Employee Benefits Survey appear in the fol lowing 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 pro ducer prices are published in the monthly periodicals, The c p i Detailed Report and Producer Price Indexes. For an overview of the 1998 revision of the cpi , see the Decem ber 1996 issue of the Monthly Labor Review. Additional data on international prices ap pear in monthly news releases. Listings of industries for which produc tivity indexes are available may be found on the Internet: July 2001 http ://stats.bls.gov/iprhome.htm For additional information on interna tional comparisons data, see International Comparisons o f Unemployment, BLS Bulle tin 1979. Detailed data on the occupational injury and illness series are published in Occupa tional Injuries and Illnesses in the United States, by Industry, a BLS annual bulletin. Finally, the Monthly Labor Review car ries analytical articles on annual and longer term developments in labor force, employ ment, and unemployment; employee com pensation and collective bargaining; prices; productivity; international comparisons; and injury and illness data. Symbols n.e.c. = not elsewhere classified, n.e.s. = not elsewhere specified. p = preliminary. To increase the time liness of some series, preliminary figures are issued based on repre sentative but incomplete returns, r = revised. Generally, this revision reflects the availability of later data, but also may reflect other ad justments. Comparative Indicators (Tables 1-3) Comparative indicators tables provide an overview and comparison of major BLS sta tistical 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 em ployment measures from two major surveys and information on rates of change in com pensation provided by the Employment Cost Index (ECi) program. The labor force partici pation rate, the employment-to-population ratio, and unemployment rates for major de mographic groups based on the Current Population (“household”) Survey are pre sented, while measures of employment and average weekly hours by major industry sec tor are given using nonfarm payroll data. The Employment Cost Index (compensation), by major sector and by bargaining status, is cho sen from a variety of bls compensation and wage measures because it provides a com prehensive 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 compensa tion and wages from the Employment Cost Index program are provided for all civ il ian nonfarm w orkers (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 com pensation 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. 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. Employment and Unemployment Data (Tables 1; 4-20) Household survey data Description of the series E mployment data in this section are ob tained 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 con sists of about 50,000 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 regu lar jobs because of illness, vacation, indus trial 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 ill ness and had looked for jobs within the pre https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis ceding 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 num ber 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 noninstitu tional 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 employ ment as a percent of the civilian nonin stitutional population. Notes on the 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 de scription of these adjustments and their ef fect on the various data series appears in the Explanatory Notes of Em ploym ent and Earnings. Labor force data in tables 1 and 4-9 are seasonally adjusted. Since January 1980, national labor force data have been season ally adjusted with a procedure called X -ll arima which was developed at Statistics Canada as an extension of the standard X11 method previously used by bls . A de tailed description of the procedure appears in the X -ll a r i m a Seasonal Adjustment Method, by Estela Bee Dagum (Statistics Canada, Catalogue No. 12-564E, January 1983). At the beginning of each calendar year, historical seasonally adjusted data usually are revised, and projected seasonal adjust ment factors are calculated for use during the January-June period. The historical sea sonally adjusted data usually are revised for only the most recent 5 years. In July, new seasonal adjustment factors, which incorpo rate the experience through June, are pro duced for the July-December period, but no revisions are made in the historical data. F or additional information on na tional household survey data, contact the Division of Labor Force Statistics: (202) 691-6378. Establishment survey data Description of the series E mployment, hours , and earnings data in this section are compiled from payroll records reported monthly on a voluntary ba sis to the Bureau of Labor Statistics and its cooperating State agencies by about 300,000 establishments representing all industries except agriculture. Industries are classified in accordance with the 1987 Standard In dustrial Classification (SIC) Manual. 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 necessar ily a firm; it may be a branch plant, for ex ample, or warehouse.) Self-employed per sons and others not on a regular civilian payroll are outside the scope of the sur vey because they are excluded from estab lishment records. This largely accounts for the difference in employment figures be tween the household and establishm ent surveys. Definitions An establishment is an economic unit which produces goods or services (such as a fac tory or store) at a single location and is en gaged 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 in cluding the 12th day of the month. Per sons 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 manufacturing include working supervisors and nonsupervisory workers closely associated with pro duction operations. Those workers men tioned in tables 11-16 include production workers in manufacturing and mining; con struction workers in construction; and nonsupervisory workers in the following in dustries: transportation and public utilities; wholesale and retail trade; finance, insur ance, and real estate; and services. These groups 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 Monthly Labor Review July 2001 63 Current Labor Statistics for overtime or late-shift work but exclud ing irregular bonuses and other special paym ents. 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 U rban W age E arners and C lerical Workers (CPI-W). Hours represent the average weekly hours of production or nonsupervisory work ers for which pay was received, and are dif ferent from standard or scheduled hours. Overtime hours represent the portion of av erage weekly hours which was in excess of regular hours and for which overtime premi ums 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 Bu reau practice, data for the 1-, 3-, and 6-month spans are seasonally adjusted, while those for the 12-month span are unadjusted. Data are centered within the span. Table 17 pro vides an index on private nonfarm employ ment based on 356 industries, and a manu facturing index based on 139 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 ad justed to comprehensive counts of employ ment (called “benchmarks”). The latest ad justment, which incorporated March 1999 benchmarks, was made with the release of May 2000 data, published in the July 2000 issue of the Review. Coincident with the benchmark adjustment, historical seasonally adjusted data were revised to reflect updated seasonal factors. Unadjusted data from April 1999 forward and seasonally adjusted data from January 1996 forward are subject to revision in future benchmarks. In addition to the routine benchmark revi sions and updated seasonal factors introduced with the release of the May 2000 data, all esti mates for the wholesale trade division from April 1998 forward were revised to incorpo rate a new sample design. This represented the first major industry division to convert to a probability-based sample under a 4-year phase-in plan for the establishment survey sample redesign project. For additional infor mation, see the the June 2000 issue of Employ ment and Earnings. Revisions in State data (table 11) oc curred with the publication of January 2000 data. Beginning in June 1996, the bls uses the X-12 arima methodology to seasonally ad 64 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis just establishment survey data. This proce dure, developed by the Bureau of the Cen sus, controls for the effect of varying sur vey 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 pe riod, 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 pre liminary in the tables (12-17 in the Review). When all returns have been received, the es timates are revised and published as “final” (prior to any benchmark revisions) in the third month of their appearance. Thus, De cember data are published as preliminary in January and February and as final in March. For the same reasons, quarterly establish ment data (table 1) are preliminary for the first 2 months of publication and final in the third month. Thus, fourth-quarter data are published as preliminary in January and February and as final in March. For additional information on estab lishment survey data, contact the Division of Monthly Industry Employment Statis tics: (202) 691-6555. Unemployment data by State Description of the series Data presented in this section are obtained from the Local Area Unemployment Statis tics (LAUS) program, which is conducted in cooperation with State employment secu rity agencies. Monthly estimates of the labor force, employment, and unemployment for States and sub-State areas are a key indicator of lo cal 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 Partner ship Act. Seasonally adjusted unemployment rates are presented in table 10. Insofar as possible, the concepts and definitions under lying 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 July 2001 (202) 691-6559 (table 11). Compensation and Wage Data (Tables 1-3; 21-27) Compensation and wage data are gathered by the Bureau from business establishments, State and local governments, labor unions, collective bargaining agreements on file with the Bureau, and secondary sources. Employment Cost Index Description of the series The Employment Cost Index (ECl) is a quar terly measure of the rate of change in com pensation per hour worked and includes wages, salaries, and employer costs of em ployee benefits. It uses a fixed market basket of labor— similar in concept to the Consumer Price Index’s fixed market basket of goods and services— to measure change over time in employer costs of employing labor. Statistical series on total compensation costs, on wages and salaries, and on benefit costs are available for private nonfarm work ers excluding proprietors, the self-employed, and household workers. The total compensa tion costs and wages and salaries series are also available for State and local government workers and for the civilian nonfarm economy, which consists of private industry and State and local government workers combined. Fed eral workers are excluded. The Employment Cost Index probability sample consists of about 4,400 private non farm establishments providing about 23,000 occupational observations and 1,000 State and local government establishments provid ing 6,000 occupational observations selected to represent total employment in each sector. On average, each reporting unit provides wage and compensation information on five well-specified occupations. Data are col lected each quarter for the pay period includ ing the 12th day of March, June, September, and December. Beginning with June 1986 data, fixed employment weights from the 1980 Census of Population are used each quarter to calculate the civilian and private indexes and the index for State and local govern ments. (Prior to June 1986, the employment weights are from the 1970 Census of Popu lation.) These fixed weights, also used to derive all of the industry and occupation series indexes, ensure that changes in these indexes reflect only changes in compensa tion, not employment shifts among indus tries or occupations with different levels of wages and compensation. For the bargaining status, region, and metropolitan/non-metropolitan area series, however, employment data by industry and occupation are not available from the census. Instead, the 1980 employment weights are reallocated within these series each quarter based on the cur rent sample. Therefore, these indexes are not strictly comparable to those for the aggre gate, industry, and occupation series. Definitions Total compensation costs include wages, salaries, and the employer’s costs for em ployee benefits. Wages and salaries consist of earnings before payroll deductions, including produc tion bonuses, incentive earnings, commis sions, and cost-of-living adjustments. Benefits include the cost to employers for paid leave, supplemental pay (includ ing nonproduction bonuses), insurance, retire ment and savings plans, and legally required benefits (such as Social Security, workers’ compensation, and unemployment insurance). Excluded from wages and salaries and em ployee benefits are such items as payment-in kind, free room and board, and tips. Notes on the data The Employment Cost Index for changes in wages and salaries 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 govern ment sector and in the civilian nonfarm economy (excluding Federal employees) were published beginning in 1981. Histori cal indexes (June 1981=100) are available on the Internet: http://stats.bls.gov/ecthome.htm F or additional information on the Employment Cost Index, contact the Office of Compensation Levels and Trends: (202) 691-6199. Employee Benefits Survey Description of the series Employee benefits data are obtained from the Employee Benefits Survey, an annual survey of the incidence and provisions of selected benefits provided by employers. The survey collects data from a sample of approxim ately 9,000 private sector and State and local government establishments. The data are presented as a percentage of em ployees who participate in a certain benefit, or https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis as an average benefit provision (for example, the average number of paid holidays provided to employees per year). Selected data from the survey are presented in table 25 for medium and large private establishments and in table 26 for small private establishments and State and local government. The survey covers paid leave benefits such as holidays and vacations, and personal, funeral, jury duty, military, family, and sick leave; short-term disability, long-term dis ability, and life insurance; medical, dental, and vision care plans; defined benefit and defined contribution plans; flexible benefits plans; reimbursement accounts; and unpaid family leave. Also, data are tabulated on the inci dence of several other benefits, such as severance pay, child-care assistance, well ness programs, and employee assistance programs. 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 em ployee also are included. For example, long term care insurance and postretirement life insurance paid entirely by the employee are included because the guarantee of insurabil ity and availability at group premium rates are considered a benefit. Participants are workers who are covered by a benefit, whether or not they use that benefit If the benefit plan is financed wholly by employers and requires employees to complete a minimum length of service for eligibility, the workers are considered participants whether or not they have met the requirement. If workers are required to contribute towards the cost of a plan, they are considered participants only if they elect the plan and agree to make the required contributions. Defined benefit pension plans use prede termined 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 partici pants, and benefits are based on amounts credited to these accounts. Tax-deferred savings plans are a type of defined contribution plan that allow par ticipants to contribute a portion of their sal ary 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 Surveys of employees in medium and large establishments conducted over the 1979—86 p eriod in cluded estab lish m en ts that employed at least 50, 100, or 250 workers, depending on the industry (most service industries were excluded). The survey conducted in 1987 covered only State and local g overnm ents w ith 50 or m ore employees. The surveys conducted in 1988 and 1989 included m edium and large establishments with 100 workers or more in private industries. All surveys conducted over the 1979-89 period excluded establishments in Alaska and Hawaii, as well as part-time employees. Beginning in 1990, surveys of State and local governm ents and small private establishments were conducted in evennumbered years, and surveys of medium and large establishments were conducted in oddnumbered years. The small establishment survey includes all private nonfarm establishments with fewer than 100 workers, while the State and local government survey includes all governments, regardless of the number of workers. All three surveys include full- and part-time workers, and workers in all 50 States and the District of Columbia. F or additional information on the Employee Benefits Survey, contact the Of fice of Compensation Levels and Trends on the Internet: http ://stats.bls.gov/ebshome.htm Work stoppages Description of the series Data on work stoppages measure the num ber 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 27. Data are largely from a variety of pub lished sources and cover only establish ments 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 work ers or more and lasting a full shift or longer. Workers involved: The number of Monthly Labor Review July 2001 65 Current Labor Statistics workers directly involved in the stoppage. Number of days idle: The aggregate number of workdays lost by workers in volved 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 in volving six workers or more. For additional information on work stoppages data, contact the Office of Com pensation and Working Conditions: (202) 691-6282, or the Internet: http ://stats.bls.gov/cbahome.htm Price Data Notes on the data (Tables 2; 28-38) P rice data are gathered by the Bureau o f Labor Statistics from retail and p ri mary markets in the United States. Price indexes are given in relation to a base pe riod— 1982 = 100 for many Producer Price Indexes, 1982-84 = 100 for many Con sum er Price Indexes (unless otherw ise noted), and 1990 = 100 for International Price Indexes. Consumer Price Indexes Description of the series The Consumer Price Index (CPI) is a mea sure of the average change in the prices paid by urban consumers for a fixed market bas ket of goods and services. The CPI is calcu lated 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 ur ban households. The wage earner index (CPiW) 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 representa tive index became apparent. The all-urban consumer index (CPi-U), introduced in 1978, is representative of the 1993-95 buying hab its 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 cleri cal workers, the CPi-U covers professional, managerial, and technical workers, the selfemployed, short-term workers, the unem ployed, retirees, and others not in the labor force. 66 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis The cpi is based on prices of food, cloth ing, 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 associ ated with the purchase and use of items are included in the index. Data collected from more than 23,000 re tail 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 pre sented in table 29. The areas listed are as in dicated 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. July 2001 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 home-owner ship so that the index would reflect only the cost of shelter services provided by owneroccupied homes. An updated cpi-u and cpiw were introduced with release of the Janu ary 1987 and January 1998 data. F or additional information on con sumer prices, contact the Division of Con sumer Prices and Price Indexes: (202) 691-7000. Producer Price indexes Description of the series Producer Price Indexes (PPi) measure av erage changes in prices received by domes tic producers of commodities in all stages of processing. The sample used for calcu lating these indexes currently contains about 3,200 commodities and about 80,000 quo tations per month, selected to represent the movement of prices of all commodities pro duced in the manufacturing; agriculture, for estry, and fishing; mining; and gas and elec tricity and public utilities sectors. The stageof-processing structure of ppi organizes products by class of buyer and degree of fabrication (that is, finished goods, interme diate goods, and crude materials). The tradi tional commodity structure of ppi organizes products by similarity of end use or mate rial composition. The industry and product stru ctu re of ppi org an izes data in accordance with the Standard Industrial Clas sification (SIC) and the product code exten sion of the sic developed by the U.S. Bu reau of the Census. To the extent possible, prices used in calculating Producer Price Indexes apply to the first significant commercial transac tion in the United States from the produc tion or central marketing point. Price data are generally collected monthly, primarily by mail questionnaire. M ost 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 im plicit 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. F or additional information on pro ducer prices, contact the Division of In dustrial 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 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. (“Resi dents” is defined as in the national income accounts; it includes corporations, busi nesses, 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 manufac tures, 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. border for imports. For nearly all products, the prices refer to transactions completed dur ing the first week of the month. Survey re spondents are asked to indicate all discounts, allowances, and rebates applicable to the re ported 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 (SITC), and the four digit level of detail for the Harmonized System. Aggregate import indexes by coun try or region of origin are also available. publishes indexes for selected catego ries o f internationally traded services, calcu lated on an international basis and on a balance-of-payments basis. bls Notes on the data The export and import price indexes are weighted indexes of the Laspeyres type. Price relatives are assigned equal importance within each harmonized group and are then aggregated to the higher level. The values as signed to each weight category are based on trade value figures compiled by the Bureau of the Census. The trade weights currently used to compute both indexes relate to 1995. Because a price index depends on the same items being priced from period to period, it is necessary to recognize when a product’s speci fications or terms of transaction have been modified. For this reason, the Bureau’s ques tionnaire 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, dis counts, credit terms, packaging, class of buyer or seller, and so forth. When there are changes in either the specifications or terms of trans action 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 em ployed which allows for the continued repric ing of the item. For the export price indexes, the preferred pricing is f.a.s. (free alongside ship) U.S. port of exportation. When firms report export prices f.o.b. (free on board), production point information is collected which enables the Bureau to calculate a shipment cost to the port of exportation. An attempt is made to collect two prices for imports. The first is the import price f.o.b. at the foreign port of exportation, which is consistent with the basis for valua tion of imports in the national accounts. The second is the import price c.i.f.(costs, insur ance, and freight) at the U.S. port of importa tion, which also includes the other costs as https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis sociated with bringing the product to the U.S. border. It does not, however, include duty charges. For a given product, only one price basis series is used in the construction of an index. For additional information on inter national prices, contact the Division of Inter national Prices: (202) 691-7155. Productivity Data (Tables 2; 39-42) Business sector and major sectors Description of the series The productivity measures relate real output to real input. As such, they encompass a fam ily of measures which include single-factor input measures, such as output per hour, out put per unit of labor input, or output per unit of capital input, as well as measures of mul tifactor productivity (output per unit of com bined labor and capital inputs). The Bureau indexes show the change in output relative to changes in the various inputs. The mea sures cover the business, nonfarm business, manufacturing, and nonfinancial corporate sectors. Corresponding indexes of hourly com pensation, unit labor costs, unit nonlabor payments, and prices are also provided. Definitions Output per hour of all persons (labor pro ductivity) is the quantity of goods and ser vices produced per hour of labor input. Out put per unit of capital services (capital pro ductivity) is the quantity of goods and ser vices produced per unit of capital services input. Multifactor productivity is the quan tity of goods and services produced per com bined inputs. For private business and pri vate nonfarm business, inputs include labor and capital units. For manufacturing, in puts include labor, capital, energy, non-en ergy materials, and purchased business ser vices. Compensation per hour is total compen sation divided by hours at work. Total com pensation 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 cor porations in which there are no self-em ployed). Real compensation per hour is com pensation per hour deflated by the change in the Consumer Price Index for All Urban Consumers. Unit labor costs are the labor compen sation 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 out put. They are computed by subtracting compensation of all persons from currentdollar value of output and dividing by out put. Unit nonlabor costs contain all the components of unit nonlabor payments ex cept unit profits. Unit profits include corporate profits with inventory valuation and capital con sumption 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 ad justed for the effects of changes in the edu cation 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 Tomquist 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. Pri vate business and private nonfarm business further exclude government enterprises. The measures are supplied by the U.S. Department of Commerce’s Bureau of Economic Analy sis. Annual estimates of manufacturing sectoral output are produced by the Bureau of Labor Statistics. Quarterly manufacturing output in dexes from the Federal Reserve Board are ad justed 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 mea sures in tables 39-42 describe the relationMonthly Labor Review July 2001 67 Current Labor Statistics ship between output in real terms and the labor and capital inputs involved in its pro duction. They show the changes from period to period in the amount of goods and ser vices produced per unit of input. Although these measures relate output to hours and capital services, they do not mea sure 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 invest ment; level of output; changes in the utiliza tion of capacity, energy, material, and research and development; the organization of produc tion; 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 b l s industry productivity data supplement the measures for the business economy and major sectors with annual measures of labor productivity for selected industries at the three- and four-digit levels of the Standard Industrial Classification system. In addition to labor productivity, the industry data also include annual measures of compensation and unit labor costs for three-digit industries and measures of multifactor productivity for three-digit m anufacturing industries and railroad transportation. The industry measures differ in methodology and data sources from the productivity measures for the major sectors b ecause the industry m easures are developed independently of the National Income and Product Accounts framework used for the major sector measures. put. Labor compensation includes pay roll as well as supplemental payments, in cluding both legally required expenditures and payments for voluntary programs. Multifactor productivity is derived by dividing an index of industry output by an index of the combined inputs consumed in producing that output. Combined inputs include capital, labor, and intermediate pur chases. The measure of capital input used represents the flow of services from the capital stock used in production. It is devel oped from measures of the net stock of physical assets— equipment, structures, land, and inventories. The measure of in termediate 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 Statis tics and the Bureau of the Census,with addi tional data supplied by other government agencies, trade associations, and other sources. For most industries, the productivity indexes refer to the output per hour of all employees. For some trade and services in dustries, indexes of output per hour of all persons (including self-employed) are con structed. For some transportation indus tries, only indexes of output per employee are prepared. FOR ADDITIONAL INFORMATION on this se ries, contact the Division of Industry Produc tivity Studies: (202) 691-5618. International Comparisons (Tables 43-45) Labor force and unemployment Definitions Output per hour is derived by dividing an index Description of the series of industry output by an index of labor input. For most industries, output indexes are de rived from data on the value of industry out put adjusted for price change. For the remain ing industries, output indexes are derived from data on the physical quantity of production. The labor input series consist of the hours of all employees (production workers and non production workers), the hours of all persons (paid employees, partners, proprietors, and unpaid family workers), or the number of em ployees, depending upon the industry. Unit labor costs represent the labor compensation costs per unit of output pro duced, and are derived by dividing an index of labor compensation by an index of out Tables 43 and 44 present comparative meas ures of the labor force, employment, and un employment— approxim ating U.S. con cepts—for the United States, Canada, Aus tralia, Japan, and several European countries. The unemployment statistics (and, to a lesser extent, employment statistics) published by other industrial countries are not, in most cases, comparable to U.S. unemployment statistics. Therefore, the Bureau adjusts the figures for selected countries, where neces sary, for all known major definitional differ ences. Although precise comparability may not be achieved, these adjusted figures pro vide a better basis for international compari 68 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 sons than the figures regularly published by each country. For further information on ad justm ents and com parability issues, see Constance Sorrentino, “International unem ployment rates: how comparable are they?” Monthly Labor Review, June 2000, pp. 3-20. Definitions For the principal U.S. definitions of the labor force, employment, and unemployment, see the Notes section on Employment and Unem ployment Data: Household survey data. Notes on the data The adjusted statistics have been adapted to the age at which compulsory schooling ends in each country, rather than to the U.S. stan dard of 16 years of age and older. Therefore, the adjusted statistics relate to the popula tion aged 16 and older in France, Sweden, and the United Kingdom; 15 and older in Australia, Japan, Germany, Italy from 1993 onward, and the Netherlands; and 14 and older in Italy prior to 1993. An exception to this rule is that the Canadian statistics for 1976 onward are adjusted to cover ages 16 and older, whereas the age at which compulsory schooling ends remains at 15. The institu tional population is included in the denomi nator of the labor force participation rates and employment-population ratios for Japan and Germany; it is excluded for the United States and the other countries. In the U.S. labor force survey, persons on layoff who are awaiting recall to their jobs are classified as unemployed. European and Japanese layoff practices are quite different in nature from those in the United States; therefore, strict application of the U.S. defi nition has not been made on this point. For further information, see Monthly Labor Re view, December 1981, pp. 8-11. The figures for one or more recent years for France, Germany, Italy, the Netherlands, and the United Kingdom are calculated using adjustment factors based on labor force sur veys for earlier years and are considered pre liminary. The recent-year measures for these countries, therefore, are subject to revision whenever data from more current labor force surveys become available. There are breaks in the data series for the United States (1990,1994,1997,1998,1999, 2000), Canada (1976) France (1992), Ger many (1991), Italy (1991, 1993), the Neth erlands (1988), and Sweden (1987). For the United States, the break in series reflects a major redesign of the labor force survey questionnaire and collection method ology introduced in January 1994. Revised population estimates based on the 1990 cen sus, adjusted for the estimated undercount, also were incorporated. In 1996, previously published data for the 1990-93 period were revised to reflect the 1990 census-based population controls, adjusted for the un dercount. In 1997, revised population con trols were introduced into the household sur vey. Therefore, the data are not strictly conparable with prior years. In 1998, new composite estimation procedures and minor revisions in population controls were intro duced into the household survey. Therefore, the data are not strictly comparable with data for 1997 and earlier years. See the Notes sec tion on Employment and Unemployment Data of this Review. BLS recently introduced a new adjusted series for Canada. Beginning with the data for 1976, Canadian data are adjusted to more closely approximate U.S. concepts. Adjust ments are made to the unemployed and labor force to exclude: (1) 15-year-olds; (2) pas sive jobseekers (persons only reading news paper ads as their method of job search); (3) persons waiting to start a new job who did not seek work in the past 4 weeks; and (4) persons unavailable for work due to personal or family responsibilities. An adjustment is made to include full-tine students looking for full-time work. The impact of the adjust ments was to lower the annual average unem ployment rate by 0.1-0.4 percentage point in the 1980s and 0.4-1.0 percentage point in the 1990s. For France, the 1992 break reflects the substitution of standardized European Union Statistical Office (E u r o s t a t ) unemployment statistics for the unemployment data esti mated according to the International Labor Office ( il o ) definition and published in the Organization for Economic Cooperation and Development ( o e c d ) annual yearbook and quarterly update. This change was made be cause the e u r o s t a t data are more up-to-date than the o e c d figures. Also, since 1992, the e u r o s t a t definitions are closer to the U.S. definitions than they were in prior years. The impact of this revision was to lower the un employment rate by 0.1 percentage point in 1992 and 1993, by 0.4 percentage point in 1994, and 0.5 percentage point in 1995. For Germany, the data for 1991 onward refer to unified Germany. Data prior to 1991 relate to the former West Germany. The im pact of including the former East Germany was to increase the unemployment rate from 4.3 to 5.6 percent in 1991. For Italy, the 1991 break reflects a revi sion in the method of weighting sample data. The impact was to increase the unemploy ment rate by approximately 0.3 percentage point, from 6.6 to 6.9 percent in 1991. In October 1992, the survey methodol ogy was revised and the definition of unem ployment was changed to include only those who were actively looking for a job within the 30 days preceding the survey and who https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis were available for work. In addition, the lower age limit for the labor force was raised from 14 to 15 years. (Prior to these changes, b l s adjusted Italy’s published unemploy ment rate downward by excluding from the unemployed those persons who had not actively sought work in the past 30 days.) The break in the series also reflects the incor poration of the 1991 population census re sults. The impact of these changes was to raise Italy’s adjusted unemployment rate by approximately 1.2 percentage points, from 8.3 to 9.5 percent in fourth-quarter 1992. These changes did not affect employment significantly, except in 1993. Estimates by the Italian Statistical Office indicate that em ployment declined by about 3 percent in 1993, rather than the nearly 4 percent indi cated by the data shown in table 44. This difference is attributable mainly to the incor poration of the 1991 population benchmarks in the 1993 data. Data for earlier years have not been adjusted to incorporate the 1991 census results. For the Netherlands, a new survey ques tionnaire was introduced in 1992 that allowed for a closer application of il o guidelines. e u r o s t a t has revised the Dutch series back to 1988 based on the 1992 changes. The 1988 revised unemployment rate is 7.6 percent; the previous estimate for the same year was 9.3 percent. There have been two breaks in series in the Swedish labor force survey, in 1987 and 1993. Adjustments have been made for the 1993 break back to 1987. In 1987, a new questionnaire was introduced. Questions re garding current availability were added and the period of active workseeking was re duced from 60 days to 4 weeks. These changes lowered Sweden’s 1987 unemploy ment rate by 0.4 percentage point, from 2.3 to 1.9 percent. In 1993, the measurement period for the labor force survey was changed to represent all 52 weeks of the year rather than one week each month and a new adjustment for population totals was intro duced. The impact was to raise the unem ployment rate by approximately 0.5 per centage point, from 7.6 to 8.1 percent. Sta tistics Sweden revised its labor force survey data for 1987-92 to take into account the break in 1993. The adjustment raised the Swedish unemployment rate by 0.2 percent age point in 1987 and gradually rose to 0.5 percentage point in 1992. Beginning with 1987, BLS has adjusted the Swedish data to classify students who also sought work as unemployed. The impact of this change was to increase the adjusted un employment rate by 0.1 percentage point in 1987 and by 1.8 percentage points in 1994, when unemployment was higher. In 1998, the adjusted unemployment rate had risen from 6.5 to 8.4 percent due to the adjustment to include students. The net effect of the 1987 and 1993 changes and the b l s adjustment for students seeking work lowered Sweden’s 1987 unem ployment rate from 2.3 to 2.2 percent. FOR ADDITIONAL INFORMATION on this se ries, contact the Division of Foreign Labor Statistics: (202) 691-5654. Manufacturing productivity and labor costs Description of the series Table 45 presents comparative indexes of manufacturing labor productivity (output per hour), output, total hours, compensation per hour, and unit labor costs for the United States, Canada, Japan, and nine European countries. These measures are trend compari sons—that is, series that measure changes over time— rather than level comparisons. There are greater technical problems in com paring the levels of manufacturing output among countries. b l s constructs the comparative indexes from three basic aggregate measures— output, total labor hours, and total compensation. The hours and compensation measures refer to all employed persons (wage and salary earners plus self-employed persons and un paid family workers) in the United States, Canada, Japan, France, Germany, Norway, and Sweden, and to all employees (wage and salary earners) in the other countries. Definitions Output, in general, refers to value added in manufacturing from the national accounts of each country. However, the output series for Japan prior to 1970 is an index of indus trial production, and the national accounts measures for the United Kingdom are essen tially identical to their indexes of industrial production. The 1977-97 output data for the United States are the gross product originating (value added) measures prepared by the Bureau of Economic Analysis of the U.S. Department of Commerce. Comparable manufacturing output data currently are not available prior to 1977. U.S. gross product originating is a chaintype annual-weighted series. (For more in formation on the U.S. measure, see Robert E. Yuskavage, “Improved Estimates of Gross Product by Industry, 1959-94,” Survey o f Current Business, August 1996, pp. 133— 55.) The Japanese value added series is based upon one set of fixed price weights for the years 1970 through 1997. Output series for the other foreign economies also employ fixed price weights, but the weights are updated periodically (for example, every 5 or 10 years). Monthly Labor Review July 2001 69 Current Labor Statistics To preserve the comparability of the U.S. measures with those for other economies, b l s uses gross product originating in manufac turing for the United States for these com parative measures. The gross product origi nating series differs from the manufacturing output series that b l s publishes in its news releases on quarterly measures of U.S. pro ductivity and costs (and that underlies the measures that appear in tables 39 and 41 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 labor hours refers to hours worked in all countries. The measures are developed from statistics of manufacturing employment and average hours. The series used for France (from 1970 forward), Norway, and Sweden are official series published with the national accounts. Where official total hours series are not available, the measures are developed by b l s using employment figures published with the national accounts, or other comprehen sive employment series, and estimates of annual hours worked. For Germany, BLS uses estimates of average hours worked developed by a research institute connected to the Min istry of Labor for use with the national ac counts employment figures. For the other countries, BLS constructs its own estimates of average hours. Denmark has not published estimates of average hours for 1994-97; therefore, the b l s measure of labor input for Denmark ends in 1993. Total compensation (labor cost) includes all payments in cash or in-kind made directly to employees plus employer expenditures for legally required insurance programs and con tractual and private benefit plans. The mea sures are from the national accounts of each country, except those for Belgium, which are developed by b l s using statistics on employ ment, average hours, and hourly compensa tion. For Canada, France, and Sweden, com pensation is increased to account for other sig nificant taxes on payroll or employment. For the United Kingdom, compensation is reduced between 1967 and 1991 to account for em ployment-related subsidies. Self-employed workers are included in the all-employed-persons measures by assuming that their hourly compensation is equal to the average for wage and salary employees. Notes on the data In general, the measures relate to total manu facturing as defined by the International Stan dard Industrial Classification. However, the measures for France (for all years) and Italy (beginning 1970) refer to mining and manu facturing less energy-related products, and the measures for Denmark include mining 70 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis and exclude manufacturing handicrafts from 1960 to 1966. The measures for recent years may be based on current indicators of manufactur ing output (such as industrial production in dexes), employment, average hours, and hourly compensation until national accounts and other statistics used for the long-term measures become available. F o r a d d i t i o n a l in f o r m a t io n on this se ries, contact the Division of Foreign Labor Statistics: (202) 691-5654. Survey of Occupational Injuries and Illnesses cludes acute and chronic illnesses or disease which may be caused by inhalation, absorp tion, 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, b l s measures of the number and incidence rate of lost workdays were dis continued 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. Description of the series Notes on the data Occupational Injury and Illness Data (Tables 46-47) The Survey of Occupational Injuries and Ill nesses collects data from employers about their workers’ job-related nonfatal injuries and ill nesses. 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 coopera tive program with an independent sample selected for each participating State. A strati fied random sample with a Neyman alloca tion is selected to represent all private in dustries 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 in volve 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 re sults from a work-related event or a single, in stantaneous exposure in the work environment. Occupational illness is an abnormal con dition or disorder, other than one resulting from an occupational injury, caused by exposure to factors associated with employment. It in July 2001 The definitions of occupational injuries and illnesses are from Recordkeeping Guidelines fo r Occupational Injuries and Illnesses (U.S. Department of Labor, Bureau of Labor Sta tistics, September 1986). Estimates are made for industries and em ployment size classes for total recordable cases, lost workday cases, days away from work cases, and nonfatal cases without lost work days. These data also are shown separately for injuries. Illness data are available for seven cat egories: occupational skin diseases or disorders, dust diseases of the lungs, respiratory condi tions due to toxic agents, poisoning (systemic effects of toxic agents), disorders due to physi cal agents (other than toxic materials), disor ders associated with repeated trauma, and all other occupational illnesses. The survey continues to measure the num ber of new work-related illness cases which are recognized, diagnosed, and reported dur ing 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 recog nized and reported. These long-term latent ill nesses are believed to be understated in the survey’s illness measure. In contrast, the over whelming majority of the reported new ill nesses are those which are easier to directly relate to workplace activity (for example, con tact dermatitis and carpal tunnel syndrome). Most of the estimates are in the form of incidence rates, defined as the number of in juries and illnesses per 100 equivalent full time workers. For this purpose, 200,000 em ployee 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 b l s Of fice of Safety, Health and Working Condi tions. Many of these States publish data on State and local government employees in ad dition to private industry data. Mining and railroad data are furnished to b l s by the Mine Safety and Health Adminis tration and the Federal Railroad Administra tion. Data from these organizations are in cluded in both the national and State data published annually. With the 1992 survey, b l s began publish ing details on serious, nonfatal incidents re sulting 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 cir cumstances of their injuries and illnesses (na ture 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 de tailed industries and for individual States at more aggregated industry levels. F o r a d d i t i o n a l in f o r m a t io n on occu pational injuries and illnesses, contact the Office of Occupational Safety, Health and Working Conditions at (202) 691-6180, or access the Internet at: A fatal work injury is any intentional or unin Twenty-eight data elements are collected, coded, and tabulated in the fatality program, including information about the fatally in jured worker, the fatal incident, and the ma chinery or equipment involved. Summary worker demographic data and event charac teristics are included in a national news re lease 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 o r a d d i t i o n a l i n f o r m a t i o n on the Census of Fatal Occupational Injuries con tact the b l s Office of Safety, Health, and Working Conditions at (202) 691-6175, or the Internet at: http ://www.bls.gov/oshhome.htm tentional wound or damage to the body result http ://www.bls.gov/oshhome.htm Census of Fatal Occupational Injuries The Census of Fatal Occupational Injuries compiles a complete roster of fatal job-re lated 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 Administra tion and Mine Safety and Health Administra tion 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 mem bers, and Federal, State, and local govern ment workers are covered by the program. To be included in the fatality census, the decedent must have been employed (that is w orking for pay, co m pensation, or profit) at the time of the event, engaged in a legal work activity, or present at the site of the incident as a requirem ent of his or her job. Definition ing in death from acute exposure to energy, such as heat or electricity, or kinetic energy from a crash, or from the absence of such es sentials 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 workrelated illnesses, which can be difficult to identify due to long latency periods. Notes on the data Bureau of Labor Statistics Internet The Bureau of Labor Statistics World Wide Web site on the Internet contains a range of data on consumer and producer prices, employment and unemployment, occupational com pensation, employee benefits, workplace injuries and illnesses, and productivity. The homepage can be accessed using any Web browser: http://stats.bls.gov Also, some data can be accessed through anonymous f t p or Gopher at stats.bls.gov https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 71 Current Labor Statistics: Comparative Indicators 1. Labor market indicators S e le c te d in d ic a to rs 1 999 1 999 2000 2000 II III IV 1 II 2001 III IV I Employment data Employment status of the civilian noninstitutionalized population (household survey ) : 1 67.1 67.2 67.1 67.1 67 1 67 4 67 3 67 0 67 1 67 2 64.3 64.5 64.2 64.2 64.3 64.6 64.6 64.3 64.4 64.4 Unemployment rate............................................................................. 4.2 4.0 4.3 4.2 4.1 4.1 4.0 4.0 4.0 4.2 Men..................................................................................................... 4.1 3.9 4.2 4.1 4.0 3.9 3.9 4.0 10.3 9.7 10.5 10 1 10 3 97 9 8 3.9 9.8 3.0 2 .8 3.0 30 29 2 8 2 8 2 8 29 3J 4.3 4.1 4.4 43 42 4.2 4 1 4? 4n 4^2 9.5 8.9 92 9.6 94 95 9.0 8 6 8 6 8 6 3.3 3.2 3.5 3.3 3 1 32 3.2 3.3 3.0 3.3 Employment-population ratio............................................................ 25 years and over........................................................................... 9 6 4.3 m 6 Employment, nonfarm (payroll data), in thousands : 1 Total........................................................................................................ 128,916 131,759 128,430 129,073 129,783 130,984 131,854 131,927 132,264 132,559 108,709 111,079 108,319 108 874 109 507 110 456 110 917 111 293 111 669 111 8 8 6 Goods-producing............................................................................ 25,507 25,709 25,454 25,459 25,524 25,704 25,711 25,732 25,704 25,621 Manufacturing.............................................................................. 18,552 18,469 18,543 18,516 18,482 18,504 18,510 18,487 18,378 18,188 Service-producing........................................................................... 103,409 106,050 102,976 103,614 104,259 105,280 106,143 106,195 106,560 106,938 Average hours: Private sector..................................................................................... 34.5 34.5 34.5 34.5 34.5 34.5 34.5 34.4 34.3 34.3 Manufacturing.................................................................................. 41.7 41.6 41.7 41.8 41.7 41.8 41.8 41.5 41.1 41.0 Overtime........................................................................................ 4.6 4.6 4.6 4.6 4.7 4.7 4.7 4.5 4.3 4.1 All workers (excluding farm, household and Federal workers)...... 3.4 4.1 1 .0 1.1 1.3 Private industry workers.................................................................. 3.4 4.4 1.1 Goods-producing 3 ........................................................................ 3.4 4.4 3.4 4.4 3.4 3.0 Employment Cost Index2 Percent change in the ECI, compensation: Service-producing 3 ....................................................................... .9 1.3 1 .0 1 .0 .7 .9 .9 1.5 1 .2 .9 .7 1.4 .7 .9 1 .0 1 .6 1 .2 .9 .6 1.3 1.3 .4 .9 .8 1.4 1 .2 1 .0 .7 1.4 1.5 1 .0 .6 3 1.3 .7 .9 Workers by bargaining status (private industry): Union...................................................................................................... 2.7 4.0 .7 .9 .7 1.3 1 .0 1 .2 .5 .7 Nonunion................................................................................................ 3.6 4.4 1 .2 .9 1 .0 1.5 1 .2 1 .0 .7 1.5 1 Quarterly data seasonally adjusted. 2 Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter. 3 Goods-producing Industries include mining, construction, and manufacturing. Service-producing industries include all other private sector industries. 72 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 2. Annual and quarterly percent changes in compensation, prices, and productivity 1 99 9 S e le c te d m e a s u re s 1 999 2000 2000 I II III IV II I III IV Compensation data1’2 Employment Cost Index— compensation (wages, salaries, benefits): Civilian nonfarm........................................................................ 3.4 4.1 0.4 1 .0 Private nonfarm.................................................................... 3.4 4.4 .4 1 .1 3.5 3.8 .5 1 .0 3.5 3.9 .5 1 .2 .9 2.7 1 .0 .7 .7 1 .0 .2 1.1 .9 0.9 1.3 1 .0 1 .0 0.7 .9 1.5 1 .2 .9 .7 .8 1 .1 1 .0 1 .1 .6 .9 1 .2 1 .0 1 .0 .6 1.7 .7 .8 Employment Cost Index— wages and salaries: Private nonfarm.................................................................... 1 .1 Price data1 Consumer Price Index (All Urban Consumers): All Items...... -.1 Producer Price Index: Finished goods........................................................................... 2.9 1 .0 .0 1 .2 1.5 .1 1.4 1.3 .6 1 .0 3.8 1 .0 .0 1 .8 2 .2 -.2 1 .8 1 .8 .7 1 .0 Capital equipment.................................................................. .3 1 .0 -.1 - .4 - .4 1 .2 .1 .0 .0 Intermediate materials, supplies, and components............... 3.7 1 .0 -.2 1.9 1.9 .1 1.9 1 .6 1 .0 -.1 Crude materials........................................................................... 15.3 1 .2 -.1 9.4 1 0 .2 -3 .5 9.1 1 1 .2 .3 1 .1 I.O Productivity data3 Output per hour of all persons: Business sector........................................................................... 2 .8 4.3 2.7 .5 4.7 7.6 1.7 7.0 2.4 2..9 Nonfarm business sector.......................................................... 2 .6 4.3 2 .0 .2 5.0 8 .0 2 .1 6.3 3.0 2 ,0 Nonfinancial corporations 4 ........................................................ 3.5 4.2 3.0 2.7 4.4 5.8 3.1 5.6 4.4 1 Annual changes are December-to-December changes. cent changes reflect annual rates of change in quarterly indexes. The Quarterly changes are data are seasonally adjusted. calculated using the last month of each quarter. Compensation and price data are not seasonally adjusted, and the price data are not compounded. 3. 4 2 Excludes Federal and private household workers. 3 Annual rates of change are computed by comparing annual averages. Quarterly per- .3 Output per hour of all employees. Alternative measures of wage and compensation changes Q u a r te rly a v e ra g e C o m p o n e n ts 1 999 IV F o u r q u a r te rs e n d in g 2000 I II III IV 2001 1 99 9 I IV 2000 I II 2001 III IV I Average hourly compensation : 1 All persons, nonfarm business sector.............................................. 3.8 3.7 7.1 5.7 7.5 5.2 4.9 5.0 6 .0 6.3 4.1 6 .0 6 .2 6 .6 5.1 4.5 4.4 4.3 4.2 4.5 4.9 5.1 5.7 6 .0 .9 .9 1.3 1 .0 1 .0 4.1 3.4 4.6 4.3 4.6 4.1 .9 4.3 4.6 4.4 1 .2 1.3 1.4 3.4 1.5 4.4 .7 2.7 4.0 3.6 3.9 4.6 4.2 1.5 .9 3.6 4.7 4.2 3.4 4.7 4.4 4.3 3.4 3.6 3.5 3.3 3.0 3.3 4.0 4.0 4.0 4.1 3.8 4.1 3.8 3.8 Employment Cost Index— compensation: Civilian nonfarm 2 .................................................................................. State and local governments........................................................... .7 .7 .7 1.3 1 .0 1 .2 1 .0 1.5 1 .2 1 .0 .5 .7 1 .0 .6 .3 1.3 .7 Employment Cost Index—wages and salaries: Civilian nonfarm 2 .................................................................................. .8 1.1 1 .0 1.1 .6 1.1 .9 1 .2 1 .0 1 .0 .6 1 .2 3.5 3.5 .6 .5 Nonunion........................................................................................... .9 1.3 State and local governments........................................................... .9 .6 .9 1.1 .3 1 Seasonally adjusted. "Quarterly average" is percent change from a quarter ago, at an annual rate. 2 Excludes Federal and household workers. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1.1 .9 .6 2 .6 1 .0 .6 1 .2 3.6 4.2 2.7 4.4 1.7 .7 .7 3.6 3.8 2 .8 4.3 3.7 Monthly Labor Review 3.2 4.3 3.5 3.9 3.4 4.0 3.3 July 2001 3.6 3.9 3.5 73 Current Labor Statistics: 4. Labor Force Data Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] Em ploym ent status Annual average 1999 2001 2000 2000 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. M ay 209,699 140,863 67.2 135,208 209,371 209,543 140,757 67.2 135,183 209,727 209,935 210,161 210,378 210,577 140,724 67.0 134,939 140,847 67.0 135,310 141,000 67.0 135,464 141,136 67.0 135,478 210,743 141,489 67.1 135,836 210,889 141,049 66.9 134,462 211,026 141,238 66.9 134,774 211,171 140,546 67.0 134,898 211,348 141,073 66.7 135,122 211,525 141,048 67.4 135,923 64.5 5,574 4.0 68,786 64.3 5,648 4.0 69,181 64.3 5,785 4.1 69,211 64.4 5,537 3.9 69,314 64.4 5,536 3.9 69,378 64.3 5,658 4.0 69,441 64.5 5,653 4.0 69,254 63.8 6,587 4.7 69,841 63.9 644 4.6 69,788 6,453 4.6 69,421 63.9 5,951 4.2 70,275 63.9 5,846 4.1 70,477 TOTAL Civilian noninstitutional population1........................ 207,753 Civilian labor force............. 139,368 Participation rate........ 67.1 Employed....................... 133,488 Employment-pop 64.3 ulation ratio2............ 5,880 Unemployed.................. Unemployment rate.... 4.2 Not in the labor force....... 68,385 64.5 5,655 4.0 68,836 140,573 67.1 134,843 64.4 5,730 4.1 68,798 141,751 67.1 135,298 64.1 Men, 20 years and over Civilian noninstitutional population1 ......................... Civilian labor force............. Participation rate........ Employed....................... Employment-pop 91,555 92,580 92,408 92,546 92,642 92,754 92,863 92,969 93,061 93,117 69,841 69,788 69,421 70,275 70,477 79,104 76.7 67,761 70,930 76.6 68,580 70,666 76.5 68,315 70,785 76.5 68,489 70,782 76.4 68,495 71,029 76.6 68,710 71,053 76.5 68,728 71,155 76.5 68,774 71,135 76.4 68,683 71,289 76.6 68,848 93,184 76.7 68,916 93,227 76.5 68,761 93,285 76.4 68,534 93,410 76.6 68,706 93,541 76.3 68,595 74.0 74.0 73.8 73.1 73.5 73.6 74.0 74.1 2,028 2,252 73.9 2,228 2,262 73.9 2,280 74.1 2,276 2,350 74.0 2,219 2 ,1 2 2 73.9 2,232 73.1 1,907 73.1 1,906 1,987 65,517 2,433 3.5 66,328 2,350 3.3 66,087 2,347 3.3 66,227 2,296 3.2 66,215 2,287 3.2 66,434 2,319 3.3 66,378 2,325 3.3 66,555 2,381 3.3 66,561 2,452 3.4 66,616 2,441 3.4 66,194 3,060 4.3 66,208 3,025 4.3 66,184 3,080 4.3 66,523 2,765 3.9 66,492 2,588 3.6 population1 ........................ Civilian labor force............. Participation rate........ Employed....................... Employment-pop 100,158 101,078 100,929 101,007 101,209 101,321 101,448 101,533 101,612 101,643 1 0 1 ,6 8 6 101,779 101,870 101,938 60,840 60.7 58,555 61,565 60.9 59,352 61,582 61.0 59,264 61,561 60.9 59,282 61,535 60.9 59,273 61,265 60.5 58,992 61,486 60.7 59,344 61,528 60.6 59,425 61,625 60.7 59,506 61,819 60.8 59,708 62,164 61.2 59,760 62,335 61.3 60,005 62,731 61.6 60,447 62,091 61.0 59,915 62,049 60.9 59,804 ulation ratio2............ Agriculture.................. Nonagricultural industries................. Unemployed.................. Unemployment rate.... 58.5 803 58.7 58.7 58.6 797 58.8 822 58.8 852 59.0 839 819 58.8 847 58.7 748 58.6 797 59.4 808 58.6 764 58.6 846 58.7 829 58.3 818 57,752 2,285 3.8 58,535 58,453 2,279 3.7 58,476 2,262 3.7 58,184 2,273 3.7 58,580 2,142 3.5 58,677 2,103 3.4 58,709 2,119 3.4 58,886 3.6 58,418 2,318 3.8 3.4 59,042 2,404 3.9 59,093 2,329 3.7 59,359 2,285 3.6 58,895 2,175 3.5 58,943 2,245 3.6 population1........................ Civilian labor force............. Participation rate........ Employed....................... Employment-pop 16,040 16,042 16,034 15,991 15,974 15,972 15,977 15,960 15,983 16,014 16,063 16,113 16,106 16,068 16,046 8,333 52.0 7,172 8,369 52.2 7,216 8,329 51.9 7,264 8,411 52.6 7,412 8,229 51.5 7,130 8,430 52.8 7,237 8,308 52.0 7,238 8,317 52.1 7,265 8,376 52.4 7,289 8,381 52.3 7,280 8,337 48.1 6,601 8,243 48.2 6,655 8,195 48.2 6,680 8,050 47.1 6,563 7,802 47.6 6,627 ulation ratio2............ Agriculture.................. Nonagricultural industries.................. Unemployed................... Unemployment rate.... 44.7 234 45.4 235 45.3 46.4 45.3 233 45.3 242 45.5 274 45.6 257 41.1 220 205 41.3 143 41.5 191 40.8 229 41.3 222 44.6 218 45.5 220 6,938 1,162 13.9 7,041 1,093 13.1 7,044 1,065 6,912 1,099 13.4 7,004 1,193 14.2 6,996 1,070 12.9 6,991 1,052 13.1 6,983 1,149 13.8 6,980 1 2 .6 7,032 1,087 13.0 7,060 1 2 .8 7,190 999 11.9 13.6 6,876 1,127 13.8 6,678 1,143 14.2 6,541 1,060 13.6 173,085 174,428 174,197 174,316 174,443 174,587 174,745 174,899 175,034 175,145 175,246 175,362 175,416 175,533 175,653 116,509 67.3 112,235 117,574 67.4 113,475 117,329 67.4 113,240 117,477 67.4 113,493 117,298 67.2 113,201 117,554 67.3 113,378 117,553 67.3 113,464 117,603 67.2 113,584 117,640 67.2 113,509 117,945 67.3 113,811 117,622 67.1 112,768 117,883 67.2 113,029 118,166 67.4 113,445 117,572 67.0 113,162 117,491 66.9 113,261 64.8 4,273 3.7 65.1 4,099 3.5 65.0 4,089 3.5 65.1 3,984 3.4 64.9 4,097 3.5 64.9 4,176 3.6 64.9 4,089 3.5 64.9 64.8 4,131 3.5 65.0 4,134 3.5 64.3 4,854 4.1 64.5 4,853 4.1 64.7 64.5 64.5 4,019 3.4 4,721 4.0 4,410 3.8 4,230 3.6 24,855 25,218 25,161 25,191 25,221 25,258 25,299 25,339 25,376 25,408 25,382 25,412 25,441 25,472 22,501 16,365 65.8 15,056 16,603 65.8 15,334 16,577 65.9 15,264 16,573 65.8 15,277 16,501 65.4 15,232 16,540 65.5 15,239 16,489 65.2 15,304 16,627 65.6 15,401 16,732 65.9 15,485 16,742 65.9 15,470 16,577 65.3 15,372 16,511 65.0 15,440 16,699 65.6 15,348 16,576 65.1 15,299 16,608 65.1 15,311 60.6 1,309 60.8 1,269 7.6 60.7 1,313 7.9 60.6 1,296 7.8 60.4 1,269 7.7 60.3 1,301 7.9 60.5 1,185 7.2 60.8 1,226 7.4 61.0 1,247 7.5 60.9 1,272 7.6 60.6 1,407 8.5 60.8 1,319 60.3 1,435 8 .0 8 .6 60.1 1,242 7.5 60.0 1,294 7.8 ulation ratio2............ Agriculture.................. Nonagricultural industries................. Unemployed.................. Unemployment rate.... 2 ,1 2 1 2,280 Women, 20 years and over Civilian noninstitutional 2 ,2 1 2 1 0 1 ,1 1 1 2 ,1 1 1 822 Both sexes, 16 to 19 years Civilian noninstitutional 1 ,1 0 1 1 ,1 2 1 201 White Civilian noninstitutional Civilian labor force............ Participation rate........ Employed....................... Employment-popUnemployed................... Unemployment rate... Black Civilian noninstitutional Participation rate........ Employed....................... Employment-popUnemployed................. Unemployment rate... 8 .0 See footnotes at end of table. 74 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] E m p lo y m e n t s tatu s A n n u al a ve ra g e 2 000 2001 1999 2 000 M ay Ju n e J u ly A ug. Sept. O ct. Nov. Dec. Jan. Feb. M ar. A pr. M ay 21,650 22,393 22,292 22,355 22,422 22,488 22,555 22,618 22,687 22,749 22,769 22,830 22,889 22,957 23,021 14,665 67.7 13,720 15,368 15,294 15,243 15,312 15,513 14,492 14,411 14,384 14,439 14,647 15,626 68.9 14,686 15,671 68.9 14,772 15,653 6 8 .6 15,491 68.5 14,711 15,540 6 8 .6 15,320 68.5 14,456 14,612 15,770 69.1 14,782 15,712 68.4 14,747 15,592 67.7 14,634 63.4 64.7 64.6 64.7 64.2 64.2 64.9 65.0 64.7 64.9 63.8 64.1 64.4 64.3 63 9 945 6.4 876 5.7 883 5.8 864 5.6 859 5.6 873 5.7 866 780 5.0 940 899 5.7 989 6.4 1,034 1,083 951 6 .6 6 .8 6.1 885 5.7 Hispanic origin Civilian noninstitutional population 1.......................... Civilian labor force.............. Participation rate......... Employed........................ Employment-popUnemployed................... Unemployment rate.... 6 8 .0 6 8 .1 6 8 .8 5.6 The population figures are not seasonally adjusted. 2 6 .0 6 8 .1 6 8 .6 14,673 NOTE: Detail for the above race and Hlspanlc-orlgin groups will not sum to totals Civilian employment as a percent of the civilian nonlnstitutional population. becausedata for the "other races" groups are not presented and Híspanles are included in both the white and black population groups. ERRATUM: Due to a production error, table 46, instead of the first page of table 4, appeared on page 45 of the April Monthly Labor Review. The mistake has been corrected In the online version of the Review and a correct version appears on page 117 in this issue. 5. Selected employment indicators, monthly data seasonally adjusted [In thousands] 2000 2001 A n n u al a v e ra g e 1999 2 000 M ay Ju n e Ju ly A ug. S ept. O ct. Nov. Dec. Jan. Feb. M ar. A pr. M ay Employed, 16 years and over.. Men........................................ Women.................................. 133,488 71,446 62,042 135,208 72,293 62,915 134,843 72,049 62,794 135,183 72,240 62,943 134,898 72,141 62,757 134,939 72,379 62,560 135,310 72,398 62,912 135,464 72,427 63,037 135,478 72,354 63,124 135,836 72,534 63,302 135,999 72,589 63,410 135,815 72,359 63,456 135,780 72,201 63,578 135,354 72,245 63,109 135,103 71,978 63,125 Married men, spouse present................................ 43,254 43,368 43,306 43,364 43,308 43,375 43,321 43,345 43,251 43,293 43,134 43,340 43,385 43,516 43,733 Married women, spouse present................................ 33,450 33,708 33,723 33,745 33,621 33,507 33,491 33,622 33,633 33,635 34,249 34,059 34,080 33,662 33,686 Women who maintain families................................ 8,229 8,387 8,335 8,340 8,460 8,492 8,516 8,449 8,495 8,501 8,426 8,373 8,049 8,160 8,319 1,944 1,297 40 2,034 1,233 38 2,013 1,246 38 2,051 1,187 44 2,065 1,189 39 2,048 1,241 36 2,018 1,274 38 2,041 1,182 32 2,005 1,180 25 2,019 1,198 34 1,983 1,182 25 1,839 1,291 29 1,910 1,231 36 1,902 1,223 47 1 ,2 0 1 121,323 18,903 102,420 933 101,487 8,790 95 123,128 19,053 104,076 890 103,186 8,674 122,871 19,084 103,787 934 122,744 18,592 104,152 821 103,331 8,619 123,117 19,003 104,114 824 103,290 8,786 108 123,461 19,073 104,388 812 103,576 8,561 136 123,632 19,146 104,486 827 103,659 8,533 128 124,035 18,843 105,192 859 104,333 8,698 86 122,931 18,644 104,287 781 103,506 8,618 114 123,813 19,352 104,461 879 103,582 8,600 101 102,853 8,708 89 123,020 18,836 104,184 926 103,258 8,660 74 110 124,069 19,103 104,966 823 104,143 8,617 142 123,814 19,134 104,680 881 103,800 8,784 138 123,395 18,854 104,541 812 103,729 8,608 93 123,416 19,067 104,349 789 103,559 8,530 103 3,357 3,190 3,240 3,125 3,110 3,170 3,188 3,222 3,416 3,234 3,327 3,273 3,164 3,201 3,371 1,968 1,927 1,953 1,858 1,871 1,980 2,051 1,909 2,183 1,964 2,035 2,043 1,914 2,097 2,215 1,079 944 972 981 918 880 831 947 886 896 954 933 907 873 900 18,758 18,722 18,513 18,444 18,579 18,704 18,595 18,758 18,896 18,993 18,568 19,021 18,647 18,713 18,581 3,189 3,045 3,077 2,981 2,972 3,038 3,030 3,044 3,285 3,088 3,227 3,143 3,007 3,061 3,197 1,861 1,835 1,831 1,760 1,773 1,901 1,940 1,808 2,082 1,882 1,971 1,970 1,828 1,985 2,089 1,056 924 952 982 896 861 817 923 871 877 945 910 877 864 876 18,197 18,165 17,957 17,897 18,052 18,142 18,024 18,206 18,323 18,437 18,040 18,509 18,132 18,176 18,061 S e le c te d cate g o rie s Characteristic Class of worker A g ric u ltu re . Wage and salary workers..... Self-employed workers........ Unpaid family workers.......... Nonagricultural Industries: Wage and salary workers..... Government.......................... Private industries................. Private households........ Other............................... Self-employed workers....... Unpaid family workers........ 121 1,958 38 Persons at work part time' All Industries: Part time for economic reasons............................... Slack work or business conditions....................... Could only find part-time work................................ Part time for noneconomic reasons.............................. Nonagricultural Industries: Part time for economic reasons............................... Slack work or business conditions........................ Could only find part-time work................................ Part time for noneconomic reasons.............................. 1 Excludes persons "with a job but not at work" during the survey period for such reasons as vacation, illness, or industrial disputes. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 75 Current Labor Statistics: 6. Labor Force Data Selected unemployment indicators, monthly data seasonally adjusted [Unemployment rates] 2000 A n n u al a ve ra g e 2001 S e le c te d c a te g o rie s 1 99 9 2000 M ay June J u ly A ug. S e p t. O c t. N ov. 4.0 13.0 D ec . J an . Feb. M ar. A p r. M ay Characteristic Total, 16 years and over.............................. 4.2 4.0 4.1 4.0 4.0 4.1 3.9 3.9 Both sexes, 16 to 19 years..................... 13.1 3.3 1 2 .8 13.4 3.2 12.9 1 2 .6 3.3 11.9 3.2 14.2 Men, 20 years and over........................... 13.9 3.5 3.3 3.3 Women, 20 years and over..................... 3.8 3.6 3.8 3.7 3.7 3.7 3.5 3.3 3.4 White, total................................................ 3.7 3.5 3.6 3.5 3.4 11.5 3.5 3.6 3.7 3.7 4.0 3.8 1 2 .0 3.5 10.7 3.4 Both sexes, 16 to 19 years................ 3.5 11.4 9.9 11.5 1 2 .0 11.4 1 1 .2 11.7 11.5 11.7 10.9 1 1 .6 1 1 .8 1 1 .8 12.3 10.4 10.9 11.7 12.5 13.1 1 2 .2 1 1 .8 12.4 1 2 .2 13.3 1 2 .6 1 1 .8 1 2 .8 13.1 10.5 7.9 10.4 1 0 .8 1 0 .6 10.5 10.9 10.7 9.8 9.2 1 1 .2 1 0 .8 10.5 3.0 3.0 2.9 3.1 3.2 3.2 3.3 3.3 3.5 3.1 3.5 3.3 3.4 7.5 21.9 7.6 26.7 Men, 16 to 19 years......................... Women, 16 to 19 years................... Men, 20 years and over..................... Women, 20 years and over............... 1 2 .6 11.3 3.0 2 .8 2 .8 2 .8 2 .8 2 .8 2.9 2.9 3.3 3.1 3.3 3.2 3.2 3.3 3.1 3.0 Black, total................................................ 8 .0 27.9 7.6 24.7 7.9 24.4 7.8 Both sexes, 16 to 19 years................ 7.7 26.4 4.0 4.2 4.2 4.3 4.5 4.4 13.8 13.6 13.8 14.2 3.4 13.1 3.4 3.6 3.5 3.8 4.0 13.6 3.9 3.4 3.4 3.6 3.7 3.6 3.8 3.8 3.0 7.9 7.2 7.4 24.1 26.7 23.9 27.0 8.4 22.5 30.1 26.9 2 1 .2 21.3 23.4 28.9 7.5 28.8 8 .6 8 .2 8 .0 31.6 25.1 31.7 28.9 27.7 25.7 30.2 30.9 26.4 27.4 25.6 31.5 25.7 26.8 31.7 23.0 21.5 19.3 27.1 22.3 21.7 Men, 20 years and over..................... 25.1 6.7 7.1 6.7 6 .8 7.2 6.5 7.0 6.9 6 .6 8.5 8 .2 6.5 6.3 6 .2 5.8 5.8 6 .2 7.3 5.7 6.9 6 .8 7.0 6.3 6.9 Women, 20 years and over............... 7.3 5.8 6.3 5.5 20.3 7.6 6.4 6.4 5.7 5.8 5.6 5.6 5.7 5.6 5.0 6 .0 5.7 6 .0 6.3 6.3 6.5 6 .2 Married men, spouse' present............. 2 .2 2 .0 1.9 1.9 2 .0 2 .0 2 .1 2 .1 2 .2 2 .2 2.3 2.3 2.5 Married women, spouse present........ 2.7 2.7 2 .8 2 .6 2.7 2 .8 2.7 2.7 2.5 2.9 2.9 5.9 6.3 6 .0 7.7 6 .0 5.4 6 .1 6 .2 6.3 6 .2 Full-time workers................................... 3.9 3.9 3.8 3.8 3.9 4.1 4.0 4.2 4.3 4.3 5.0 3.8 4.9 3.8 Part-time workers................................... 3.9 4.8 5.1 3.9 2.5 6.4 2 .6 6.4 4.1 2.5 5.2 2 .6 Women who maintain families............ 2.5 5.4 5.1 5.0 4.6 4.5 4.5 4.6 4.9 4.8 4.8 5.5 4.6 4.1 4.1 4.0 4.1 4.1 4.0 3.5 4.0 3.6 2 .2 4.5 4.6 4.5 3.5 4.5 5.9 3.7 6 .0 6 .0 4.3 6.4 4.0 7.1 4.6 4.5 4.0 5.0 6.4 4.3 3.9 7.0 6 .2 6 .6 3.6 3.4 3.6 3.3 6.5 3.6 3.4 6 .8 3.4 6.9 3.6 5.1 7.1 4.2 4.2 4.5 4.2 4.6 43 5,1 4.8 49 47 Men, 16 to 19 years......................... Women, 16 to 19 years................... Hispanic origin, total............................. 5.1 27.9 34.9 28.6 30.0 2 .6 Industry Nonagricultural wage and salary workers......................................................... Mining........................................................ 4.3 5.7 Construction.............................................. Manufacturing........................................... 7.0 3.6 4.1 3.9 6.4 3.6 3.4 3.5 3.6 6.5 4.0 3.2 4.3 38 4.3 3.5 3.9 5.5 3.9 4.0 3.8 3.2 4.0 3.1 4.1 4.0 4.3 50 5.0 5.0 50 3.0 5.2 3.1 5.0 3.2 2.9 3.1 3.1 3.2 2 .8 2 .6 3.2 2 .8 2.9 3 1 4 1 3 4.8 4.7 4.8 5.0 2 .1 3.8 3.9 3.8 3.7 1.9 3.7 3.6 2.3 4.0 2.3 3.9 2.3 3.6 2 .1 3.8 4.1 5.3 2.7 4.1 5.3 Services..................................................... 5.1 2.5 4.2 5.3 2 .2 5.1 2.4 4.8 2.3 5.1 2.3 5.0 2.3 4.1 5.1 2.4 Government workers................................... 2 .2 2 .1 2 .0 2 .1 2.3 2 .1 2 .0 2.3 2 .2 2 .2 1.5 2 .1 2.3 2 .0 Agricultural wage and salary workers....... 8.9 7.5 7.4 2.5 7.2 7.2 8 .0 7.9 8 .8 9.4 8.9 9.0 9.2 11.3 9.2 8 .2 Less than a high school diplom a................ 6.7 6.4 6.9 6.4 6.4 6.3 6 .2 6.4 6 .6 7.7 6.9 6 .6 3.5 3.5 3.5 3.4 3.4 3.7 3.4 3.5 3.5 6.3 3.4 6 .8 High school graduates, no college............. 3.8 3.8 3.9 3.8 6.5 3.9 Some college, less than a bachelor's degree........................................................... 2 .8 2 .8 2 .6 2.4 2.7 2.7 3.0 2.7 2.7 3.0 3.0 1 .6 1 .6 2.7 1.7 2.7 1 .8 2.7 1.7 2 .6 College graduates......................................... 1.7 1.9 1 .6 1 .6 1 .6 1 .6 1 .6 2 .0 2.3 2 .1 3.5 Wholesale and retail trade..................... Finance, insurance, and real estate...... 2 .6 8 3.9 Educational attainm ent1 1 Data refer to persons 25 years and over. 76 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 7. Duration of unemployment, monthly data seasonally adjusted [Numbers in thousands] W e e ks of A n n u a l a v e ra g e u n e m p lo y m e n t 1 99 9 2000 2000 M ay June J u ly 2001 Aug. Sept O ct. N o v. D ec . Jan . F eb . M a r. A p r. M ay Less than 5 weeks............................ 2,568 2,543 2,536 2,572 2,493 2,567 2,498 2,510 2,531 2,440 2,613 2,797 2,674 2,958 2,679 5 to 14 weeks..................................... 1,832 1,803 1,901 1,776 1,811 1,832 1,750 1,755 1,796 1,852 1,977 1,669 1,992 1,977 2,028 15 weeks and over............................ 1,480 1,309 1,325 1,260 1,319 1,373 1,247 1,311 1,317 1,326 1,371 1,490 1,517 1,499 1,484 15 to 26 weeks............................... 755 665 670 609 650 673 618 702 713 675 731 793 814 759 852 27 weeks and over......................... 725 644 655 651 669 700 629 609 604 651 640 697 703 740 632 Mean duration, in weeks.................. 13.4 1 2 .6 1 2 .6 12.5 13.2 13.0 12.4 12.4 1 2 .6 1 2 .6 12.9 13.0 1 2 .6 1 2 .2 Median duration, in weeks............... 6.4 5.9 5.9 5.9 5.9 6 .1 6 .1 6 .1 5.9 6 .0 6.5 5.8 6.5 8. 1 2 .1 5.3 6 .1 Unemployed persons by reason for unemployment, monthly data seasonally adjusted [Numbers in thousands] R e a s o n fo r u n e m p lo y m e n t A n n u a l a v e ra g e 1 99 9 2000 2000 M ay June J u ly Aug. 2001 S e p t. O c t. N o v. D ec . J an . Feb. M a r. A p r. M ay 3,159 Job losers 1 ......................................... 2,622 2,492 2,460 2,439 2,450 2,585 2,502 2,446 2,501 2,514 2,742 2,853 2,963 3,199 On temporary layoff...................... 848 1,774 842 875 917 857 837 825 877 937 1,084 1,522 1,593 776 692 1,624 768 746 838 814 2,075 820 2,042 1,798 429 1 ,8 6 8 1,936 429 1,899 466 1,956 820 1,927 2,146 749 2,052 477 788 1,960 412 1,621 815 1,577 775 1,957 431 1,665 756 991 1,972 1,053 1,585 1,032 1,711 945 1,650 907 1,678 446 372 1,908 382 2,005 462 1,801 482 Not on temporary layoff................ Job leavers.......................................... Reentrants......................................... New entrants...................................... 783 2,005 469 416 780 1,930 503 398 1,908 Percent of unemployed Job losers 1 ......................................... On temporary layoff...................... 44.6 44.1 42.7 43.6 43.7 44.6 45.6 44.3 44.4 44.7 45.8 47.8 48.8 49.9 14.4 14.9 15.2 16.4 15.6 17.2 16.4 17.3 27.5 27.2 13.5 35 6 12.4 3fi 5 14.0 34 Q 13.8 14.7 14.0 13.7 32.5 13.4 33.5 13.7 34 6 28.0 13.3 28.6 13.3 34.1 28.8 13.6 15.8 32.0 16.3 29.2 14.9 29.3 16.7 30.2 15.3 30.4 15.6 Not on temporary layoff................. Job leavers......................................... 15.3 28.4 11.7 33.1 13.1 8 .0 7.6 8.3 7.4 7.3 8.7 7.8 7.2 7.6 8.3 7.4 6 .2 6.4 7.2 7.7 Job losers 1 .......................................... Job leavers......................................... 1.9 1 .8 1.7 1.7 1.7 1 .8 1 .8 1.7 1 .8 1 .8 1.9 2 .0 2 .1 2.3 2 .2 .6 .6 .6 .5 .6 .6 .5 .6 .5 .6 .6 .6 Reentrants.......................................... New entrants...................................... 1.4 1.4 .3 1.5 1.5 .3 1.4 .3 1.4 .4 1.3 .3 1.3 .5 1.4 1.3 .3 1.3 .3 1.4 .3 1.4 .3 1.3 .3 .5 1.4 .3 New entrants...................................... 28.9 13.5 50.4 Percent of civilian labor force 1 .3 .3 .3 .6 .3 Includes persons who completed temporary jobs. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 77 Current Labor Statistics: 9. Labor Force Data Unemployment rates by sex and age, monthly data seasonally adjusted [Civilian workers] A n n u al a v e ra g e 2000 S ex and age 1 99 9 55 years and over................... 2000 A p r. M ay June J u ly A ug. 2001 S e p t. 4.2 4.0 40 4.0 4 1 39 9.3 4.0 9.4 4.1 9.9 9.7 9.2 13.9 13.1 1 2 .8 1 2 .8 94 142 9 12 9 16.3 12.4 15.4 14.9 15.8 9.1 11 9 13.4 11.5 11.5 10 8 10 7 7.5 7.1 7.3 79 75 6 3.1 3.0 2.9 3.2 3.1 30 3.0 3 1 2 .8 2 .6 2.4 2.5 4.1 13.4 8 O c t. N ov. D ec . J an . 39 40 40 9 9 1 12 6 92 13 1 9 13 15 17 4 11 5 8 4*2 6 F eb . 4*2 95 13 M a r. A p r. 4*3 10 0 13 10 4 8 14 9 17 ? 11 n 18 0 19 3 18 7 7? 79 7 39 39 39 34 2 .8 2 .6 2 .8 16 3 11 5 16.9 15 7 15 2 12 6 11 1 11 1 13 0 15 4 11 4 9 6 6 6 6 6*8 6 8 30 31 30 3 1 3 1 32 30 3*0 30 29 3.0 70 30 3*0 30 3*2 3? 2.4 2.4 2.7 2.7 2 .8 2.9 2 .6 2.7 4*0 4.0 4*3 4*2 9.5 9.7 10.3 1 0 .8 10.9 10.9 13.6 14.1 15.0 15.5 13.8 8 11 6 8 8 8 19 Ç 8 3 34 35 3.9 9.7 39 9.7 3.9 39 3 8 40 39 39 1 0 .0 13.8 13.5 9.6 14.1 1 0 .2 14.0 9.6 14.2 9.4 13.4 17.0 13.1 16.8 16.8 11.4 15.9 17.5 17.5 18.4 20.5 18.5 15.6 15.1 18.7 13.0 1 2 .0 15.2 1 1 .2 17.6 10.7 17.5 1 2 .2 16.0 12.4 15.8 17.1 9.5 13.7 11.3 11.7 1 1 .8 13.1 12.7 1 2 .8 7.7 7.3 7.4 8 .1 7.0 7.1 6.9 7.1 7.3 7.3 7.2 7.6 8 .2 9.3 8.7 3.0 2 .8 2 .8 2 .8 2 .8 2 .8 2 .8 2 .8 3.0 3.0 3.1 3.0 3.2 3.5 25 to 54 years....................... 3.0 2 .8 2 .8 2.9 2 .8 2.9 2.9 2.9 2.9 2.7 2 .6 2.3 2.4 2.7 2 .6 2 .8 2.9 2 .8 3.0 2.9 3.5 2 .8 3.1 3.0 3.3 55 years and over................. 2.9 2.7 2.9 2.9 2.9 2.9 Women, 16 years and over............ 16 to 24 years.............................. 4.1 8.9 4.1 8.9 4.3 9.4 4.1 4.2 4.0 4.2 4.2 4.4 8 .2 4.0 8.7 4.1 8 .6 3.9 8.4 4.0 8 .8 8 .1 1 2 .1 1 1 .8 1 2 .1 8.9 13.7 15.5 14.0 14.8 18 to 19 years........................ 1 1 .6 1 0 .8 13.7 10.5 8.5 9.4 10.7 4.2 8.9 16 to 19 years........................... 16 to 17 years........................ 4.3 9.5 13.2 1 0 .2 8 .2 9.8 13.3 14.5 12.4 16 to 24 years.............................. 16 to 19 years........................... 16 to 17 years....................... 18 to 19 years....................... 20 to 24 years........................... 25 years and over....................... 10.3 14.7 8 .6 1 2 .6 12.4 1 2 .0 11.9 12.4 1 1 .6 16.8 13.8 1 2 .8 12.3 13.4 1 2 .1 15.0 10.9 13.2 14.1 15.7 9.8 1 1 .0 1 1 .6 11.5 1 1 .6 11.3 6.7 8.7 20 to 24 years........................... 7.2 7.0 7.2 7.8 8 .0 6.7 6.3 6 .0 6.3 6.3 6.7 25 years and over........................ 3.2 3.1 3.2 3.2 3.4 3.3 3.5 3.1 3.1 3.2 3.0 3.2 3.2 3.2 3.0 3.3 3.3 3.4 3.4 25 to 54 years....................... 3.3 3.4 55 years and over................. 2 .8 2 .6 2 .0 2.4 2.4 2.4 2 .6 2 .8 2 .8 2.7 78 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 16.4 11.9 6 .1 6.3 7.8 3.4 3.2 3.1 3.2 3.4 3.5 3.5 3.3 3.4 2.4 2.5 2.7 2 .2 2 .6 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 10. Unemployment rates by State, seasonally adjusted S ta te A p r. M a r. A p r. 2000 2001p 2001p S ta te A p r. M a r. A p r. 2000 2001p 2001p Alabama......................................................... 4.6 5.4 5.3 Alaska............................................................ 5.8 4.4 5.8 33 S0 Arizona.......................................................... 6.9 3.9 3.1 an 4.6 4.2 4.3 4.5 3 1 Arkansas........................................................ 39 4 6 California....................................................... 5.0 4.7 4.9 3 1 2 fi 49 2 Q 38 4J5 4.0 4J3 Colorado........................................................ 2 .8 3.7 3.8 4.2 2.3 2.9 1.9 2.7 Connecticut................................................... 2 .2 Delaware........................................................ 4.0 3.3 3.3 46 4,6 55 4.0 56 4J3 District of Columbia...................................... 5.6 6 .1 4.6 34 3.6 3.8 3.9 3 1 5 1 24 fi 4 Florida............................................................ 4 1 3.1 3 fi 3Q 3 1 2 sn 47 fi 2 2 fi Georgia.......................................................... 3.9 3.8 4.0 Hawaii............................................................ 4.4 Idaho.............................................................. 4.9 4.8 4.9 Illinois............................................................. 4.3 4.3 4.5 5.4 5.4 4 1 45 44 Indiana........................................................... 3.6 3.2 2.9 42 40 44 Iowa............................................................... 2 .6 2 .8 2.7 4.0 44 Kansas........................................................... 3.6 3.7 23 2 2 39 44 32 4 1 4.2 3.7 43 25 4.3 Kentucky....................................................... 4.1 4.2 3.5 4.4 Louisiana....................................................... 5.3 5.6 5.4 Maine............................................................. 3.8 2.4 3.1 Maryland....................................................... Massachusetts.............................................. 3.9 2 .8 3.6 3.2 3.6 3.2 Michigan........................................................ 3.4 4.7 4.6 Minnesota...................................................... 3.3 3.4 5.9 5.4 3.9 5.0 Utah............................ W yoming........................................................ Q 4.3 3q 3.0 3.0 3.1 2 2 25 2J 52 54 3 fi 8 fi 8 5 1 fi 1 3.9 3.4 5 4J2 3.4 p = preliminary 11. Employment of workers on nonfarm payrolls by State, seasonally adjusted [In thousands] S ta te Alabama... Alaska...... Arizona..... Arkansas.. California.. A p r. M a r. A p r. 2000 2001p 2001p 1,931.0 282.4 2,236.3 1,157.4 14,409.0 S ta te 1,931.2 288.0 2,276.1 1,926.2 287.5 2,276.4 1,166.6 14,798.9 1,164.2 14,818.3 2,270.4 Colorado................... Connecticut............... 2,200.4 Delaware................... District of C olum bia- 419.3 648.0 2,251.5 1,699.6 426.1 647.4 Florida........................ 7,032.3 7,246.0 649.9 7,264.1 GeorgiaHawaii.... 3,973.8 548.2 4,041.8 4,045.6 560.3 Idaho..... Illinois.... 558.1 6,040.6 563.1 6,077.1 560.0 564.8 6,058.2 Indiana... 3,010.0 2,999.9 2,995.8 Iowa.......... Kansas..... 1,474.9 1,489.3 1,346.1 1,358.5 1,482.0 1,363.7 Kentucky.. 1,819.4 Louisiana.. Maine....... 1,927.2 602.6 2,843.3 1,953.7 612.5 1,835.9 1,951.7 Maryland........... Massachusetts.. 2,444.4 2,477.8 3,361.7 2,473.3 3,362.8 4,698.1 4,693.1 2,689.2 Michigan........... . Minnesota......... Mississippi......... 1,690.2 3,308.1 4,676.7 2,670.3 1,157.3 2,685.9 1,145.6 1,700.8 425.4 611.9 1,145.5 Missouri.......................................... Montana.......................................... Nebraska......................................... Nevada............................................ New Jersey..................................... New Mexico................................... New York........................................ North Carolina............................... A p r. M ar. A p r. 2000 2001p 2001p 2,751.3 387.8 2,763.6 2,756.9 909.6 1,018.6 620.5 394.3 913.3 1,063.7 626.3 393.1 911.3 1,068.6 627 9 3,990.9 4,032.8 4,024.7 742.5 8,613.3 753.8 8,723.8 3,977.5 8,729.5 3,975.7 3,930.3 754.7 North Dakota................................. 328.3 329.6 328.6 5,657.5 1,494.8 1,604.7 5,652.1 Oklahoma....................................... Oregon............................................ 5,638.1 1,480.9 1,599.5 Pennsylvania................................. Rhode Island.................................. 5,682.9 475.4 5,748.1 79.6 South Carolina............................... 1,869.8 380.0 1,893.6 379.9 Tennessee...................................... Texas............................................... Utah................................................. 2,728.2 2,748.7 9,386.3 1,071.6 9,625.2 1,091.7 Vermont.......................................... 296.3 582.2 300.4 3,561.6 2,705.0 735.3 2,745.0 South Dakota................................. Virginia............................................ W ashington..................................... West Virginia.................................. W isconsin....................................... 2,838.3 742.0 2,852.4 Wyoming......................................... 239.8 244.9 1,499.0 1,600.5 5,736.6 478.8 1,893.0 378.7 2,759.7 2,626.4 1,092.5 299 9 3,560.6 2,744.2 739.7 2,848.8 245.1 p = preliminary NOTE: Some data In this table may differ from data published elsewhere because of the continual updating of the data base. Monthly Labor Review July 2001 79 Current Labor Statistics: Labor Force Data 12. E m p lo y m e n t o f w o r k e r s o n n o n f a r m p a y r o lls b y In d u s try , m o n th ly d a t a s e a s o n a lly a d ju s t e d [In thousands] 2001 2000 Annual average 2000 May June July Aug. Sept. Oct. Nov Dec. Jan. Feb. Mar. Apr.p May” TOTAL................................ 128,916 PRIVATE SECTOR................. 108,709 131,739 111,079 131,909 110,795 131,969 111,029 131,899 111,180 131,837 111,237 132,046 111,463 132,145 111,564 132,279 111,689 132,367 111,753 132,428 111,799 132,595 111,915 132,654 111,943 132,489 111,742 132,497 111,731 25,507 25,709 25,774 25,727 25,711 25,688 25,633 25,627 25,602 25,421 25,332 453 41 312 542 40 313 543 40 313 25,696 547 40 316 25,713 543 41 311 25,683 542 41 310 25,727 539 44 297 551 40 320 548 40 319 548 41 320 550 39 325 555 39 328 557 38 331 560 37 335 564 37 339 1999 GOODS-PRODUCING................. Mining ...................................... Metal mining............................. Oil and gas extraction............... Nonmetallic minerals, except fuels............................ 113 114 113 113 113 114 115 115 114 112 113 113 113 112 Construction............................. General building contractors..... Heavy construction, except building.................................. Special trades contractors........ 6,415 1,458 6,698 1,528 6,648 1,520 6,663 1,520 6,678 1,520 6,699 1,525 6,728 1,538 6,758 1,549 6,781 1,548 6,791 1,543 6,826 1,538 6,880 1,555 6,929 1,552 6,852 1,548 6 ,8 8 6 874 4,084 901 4,269 894 4,234 896 4,247 897 4,256 900 4,274 900 4,290 904 4,305 909 4,324 913 4,335 921 4,367 930 4,395 938 4,439 915 4,389 924 4,405 Manufacturing........................... Production workers............. 18,552 12,747 18,469 12,628 18,493 12,678 18,521 12,675 18,554 1 2 ,6 8 8 18,485 12,631 18,421 12,559 18,404 12,545 18,382 12,511 18,349 12,466 18,257 12,394 18,192 12,323 18,116 12,254 18,009 12,166 17,882 24,442 Durable goods......................... Production workers............. 1 1 ,1 1 1 11,138 7,591 11,136 7,606 11,168 7,617 11,207 7,635 11,172 7,608 11,129 7,568 11,126 7,560 1 1 ,1 2 0 1 1 ,1 0 2 7,596 7,544 7,517 11,031 7,462 10,997 7,415 10,941 7,358 10,870 7,308 10,778 7,236 834 548 832 558 838 558 837 559 836 565 831 559 826 560 821 559 817 557 811 555 806 552 799 549 799 548 800 543 797 539 566 699 1,521 579 698 1,537 579 699 1,537 579 700 1,543 581 700 1,546 580 700 1,541 579 695 1,540 577 695 1,536 577 691 1,537 577 1,536 579 681 1,526 578 679 1,514 578 671 1,509 577 667 1,503 574 660 1,489 2,136 2 ,1 2 0 2,113 2 ,1 2 0 2,137 2,133 2 ,1 2 1 2,123 2 ,1 2 2 2,119 2,117 2,105 2,084 2,072 2,054 368 361 355 354 362 365 Lumber and wood products.... Furniture and fixtures.............. Stone, clay, and glass products............................... Primary metal industries......... Fabricated metal products...... Industrial machinery and equipment............................ Computer and office equipment.......................... Electronic and other electrical equipment............................ Electronic components and accessories......................... Transportation equipment....... Motor vehicles and equipment........................... Aircraft and parts.................. Instruments and related products.............................. Miscellaneous manufacturing industries.............................. 364 686 111 1,557 365 365 366 369 370 369 367 366 1,738 1,735 1,726 1,715 1,684 1,656 686 1,672 1,719 1,707 1,719 1,735 1,740 1,736 1,738 1,737 641 669 678 1 ,8 8 8 682 1,849 1 ,8 6 6 1 ,8 6 8 689 1,855 695 1,836 698 1,822 704 1,822 708 1,822 710 1,817 714 1,772 711 1,786 702 1,775 1,768 671 1,757 1,018 496 1,013 465 1,025 467 1,025 466 1,027 465 1,015 464 1,005 464 994 463 995 462 990 464 952 462 967 464 956 465 950 464 939 464 855 852 847 849 856 856 858 861 865 867 870 871 871 866 865 391 394 392 394 396 396 392 394 395 396 393 390 391 390 387 Nondurable goods.................. Production workers............. 7,441 5,150 7,331 5,038 7,357 5,072 7,353 5,058 7,347 5,053 7,313 5,023 7,292 4,991 7,278 4,985 7,262 4,967 7,647 4,949 7,226 4,932 7,195 4,908 7,175 4,896 7,139 4,854 1,704 4,830 Food and kindred products..... Tobacco products................... Textile mill products................ Apparel and other textile products.............................. Paper and allied products...... Printing and publishing........... Chemicals and allied products Petroleum and coal products.. Rubber and miscellaneous plastics products.................. Leather and leather products.. 1,682 37 559 1,684 34 528 1 ,6 8 8 1,685 35 531 1 ,6 8 6 34 530 1,679 33 528 1,674 33 523 1,678 32 518 1,679 33 514 1,682 32 510 1,684 32 505 1 ,6 8 6 35 534 31 496 1,687 32 494 1,687 32 489 1,685 33 479 690 633 657 1,547 1,038 127 641 658 1,546 1,038 128 639 657 1,552 1,037 129 637 656 1,553 1,036 128 625 655 1,549 1,036 128 620 655 1,547 1,037 127 616 655 1,544 1,038 126 611 654 1,540 1,038 127 604 652 1,539 1,039 127 599 651 1,534 1,039 127 595 645 1,529 1,039 127 590 642 1,524 1,039 126 581 641 1,512 1,036 128 579 639 1,503 1,033 127 1 ,0 1 1 1,017 72 1,016 72 1,013 74 1,009 71 1,006 70 1 ,0 0 2 993 69 979 973 967 960 69 997 69 987 71 68 68 68 66 66 SERVICE-PRODUCING............... 103,409 106,050 106,226 106,242 106,125 106,110 106,350 106,432 106,568 106,679 106,795 106,968 107,052 107,068 107,165 6,834 4,411 235 7,019 4,529 236 6,997 4,511 235 7,015 4,520 233 7,034 4,536 235 6,963 4,548 236 7,062 4,553 235 7,076 4,559 234 7,093 4,573 235 7,108 4,583 232 7,106 4,580 229 7,123 4,591 231 7,127 4,591 230 7,119 4,576 230 7,127 4,581 230 478 1,810 186 1,227 13 463 476 1,856 196 1,281 14 471 476 1,852 195 1,270 14 469 472 1,854 197 1,278 14 472 477 1,860 195 1,282 14 473 478 1,860 198 1,288 14 474 478 1,861 199 1,291 14 475 477 1,861 478 1,864 478 479 1 ,8 6 6 1 ,8 6 8 480 1,870 480 1,872 477 1,864 200 200 200 1,298 14 475 1,306 14 476 1,316 14 477 1,312 14 477 1,318 14 478 1,316 13 479 1,313 14 476 483 1,865 203 1,314 14 472 2,423 1,560 2,490 1,639 2,486 1,635 2,495 1,644 2,498 1,647 2,415 1,565 2,509 1,660 2,517 2,520 1,672 2,525 1,678 2,526 1,679 2,532 1,685 2,536 1,690 2,543 1,696 2,546 1,699 Transportation and public utilities................................. Railroad transportation.......... Local and interurban Trucking and warehousing..... Water transportation.............. Pipelines, except natural gas.. Transportation services........ Communications and public Communications.................... Electric, gas, and sanitary Retail trade............................... Building materials and garden General merchandise stores.... Department stores................. 668 1,552 1,035 132 1,006 77 80 200 20 1 202 863 851 851 851 851 850 849 849 848 847 847 847 846 847 847 6,911 7,024 7,006 7,019 7,030 7,037 7,042 7,059 7,070 7,068 7,067 7,064 7,066 7,053 7,039 22,848 23,307 23,247 23,280 23,311 23,348 23,371 23,380 23,395 23,406 23,415 23,472 23,457 23,530 23,531 988 2,798 2,459 1,016 2,837 2,491 1,019 2,837 2,488 1,016 2,831 2,482 1,014 2,820 2,470 1,015 2,830 2,483 1 ,0 1 2 1 ,0 1 2 1 ,0 1 1 1 ,0 1 0 2,834 2,487 2,829 2,481 2,835 2,492 2,822 2,480 1,007 2,789 2,448 1,007 2,807 2,462 1,006 2,797 2,451 999 2,804 2,459 1,007 2,817 2,469 See footnotes at end of table. Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1 ,6 6 8 201 July 2001 12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Industry Annual average 1999 Food stores............................... Automotive dealers and service stations...................... New and used car dealers...... Apparel and accessory stores... Furniture and home furnishings stores.................................... Eating and drinking places....... Miscellaneous retail establishments....................... Finance, insurance, and real estate............................... Finance..................................... Depository institutions............ Commercial banks................ Savings institutions............... Nondepository institutions...... Security and commodity Holding and other investment offices................................... Insurance.................................. Insurance carriers................... Insurance agents, brokers, and service........................... Real estate................................ Services'.................................. Hotels and other lodging places Business services..................... Services to buildings............... Personnel supply services...... Help supply services............. Computer and data processing services.............. Auto repair services and parking............................ Miscellaneous repair services.... Motion pictures......................... Amusement and recreation 2000 2000 May. June July Aug. 2001 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr.p May" 3,497 3,521 3,521 3,522 3,523 3,526 3,520 3,528 3,527 3,532 3,538 3,548 3,550 3,562 3,552 2,368 1,080 1,171 2,412 1,114 1,193 2,407 2,412 1,116 1,196 2,418 1,118 1,195 2,420 2,426 1 ,1 2 2 1 ,2 0 2 1 ,2 0 2 2,425 1,123 1,214 1 ,2 2 1 2,424 1,124 1,227 2,420 1,124 1,228 2,421 1 ,1 2 0 2,426 1,123 1,208 2,424 1,124 1,187 2,410 1,114 1,190 1,226 2,427 1,126 1,228 1,087 7,961 1,134 8,114 1,130 8,080 1,136 8,098 1,135 8,123 1,138 8,132 1,138 8,138 1,142 8,137 1,144 8,142 1,148 8,149 1,147 8,157 1,146 8,171 1,147 8,158 1,140 8,213 1,135 1,206 2,978 3,080 3,066 3,077 3,088 3,094 3,098 3,105 3,103 3,106 3,132 3,142 3,151 3,165 3,159 7,555 3,688 2,056 1,468 254 709 7,560 3,710 2,029 1,430 253 681 7,550 3,697 2,029 1,432 253 679 7,541 3,699 2,028 1,430 253 676 7,546 3,701 2,024 1,425 252 675 7,549 3,707 2,024 1,425 253 674 7,556 3,718 2,024 1,524 253 677 7,569 3,725 2,023 1,421 253 678 7,575 3,729 2,023 1,420 253 678 7,582 3,735 2,025 1,420 253 677 7,594 3,738 2,024 1,418 253 678 7,609 3,748 2,025 1,417 254 683 7,618 3,755 2,028 1,418 254 7,626 3,761 ' 2,032 1,421 255 691 7,644 3,769 2,038 1,426 255 695 689 748 740 745 751 756 762 767 770 774 777 781 781 780 776 234 2,368 1,610 251 2,346 1,589 249 2,348 1,592 250 2,345 1,590 251 2,340 1,585 253 2,341 1,585 255 2,335 1,580 257 2,337 1,580 248 2,340 1,583 259 2,339 1,582 259 2,346 1,588 259 2,351 1,592 260 2,353 1,593 258 2,356 1,596 260 2,359 1,599 758 1,500 757 1,504 756 1,505 755 1,497 755 1,495 756 1,501 755 1,503 757 1,507 757 1,506 757 1,508 758 1,510 759 1,510 760 1,510 760 1,509 760 1,516 39,055 766 1,848 1,226 9,300 983 3,616 3,248 40,460 801 1,912 1,251 9,858 994 3,887 3,487 40,312 795 1,905 1,240 9,830 991 3,902 3,514 14,447 795 1,917 1,247 9,876 992 3,916 3,517 40,495 798 1,923 1,250 9,884 994 3,909 3,505 40,613 801 1,923 1 256 9,921 994 3,917 3,506 40,736 40,767 40,845 40,901 40,984 41,020 41,073 40,993 41,058 1,924 1,927 1,939 1,946 1,952 1,957 1,960 1,944 1,936 9,965 995 3,947 3,547 9,939 994 3,890 3,465 9,933 998 3,869 3,461 9,893 3,816 3,404 9,888 1,007 3,779 3,372 9,851 1,007 3,731 3,339 9,822 1,007 3,694 3,201 9,729 1,009 3,600 3,202 9,696 1,013 3,585 3,194 1,875 2,095 2,080 2,091 2,106 2,114 2,124 2,135 2,152 2,164 2,176 2,186 2,195 2,199 2 ,2 0 0 1,196 372 599 1,248 366 594 1,238 365 595 1,240 365 597 1,248 365 596 1,254 366 596 1,260 366 590 1,266 366 588 1,270 366 593 1,278 365 597 1,291 365 600 1,291 365 600 1,298 364 605 1,300 364 601 1,308 362 585 1 0 ,2 1 1 10,236 10,259 10,280 10,294 1 ,1 1 1 1 ,0 0 2 686 1 ,1 2 2 1,651 1,728 1,720 1 726 1 735 Health services......................... Offices and clinics of medical doctors.................................. Nursing and personal care facilities................................. Hospitals................................. Home health care services..... Legal services.......................... Educational services................. Social services.......................... Child day care services.......... Residential care...................... Museums and botanical and zoological gardens................. Membership organizations....... Engineering and management services................................. Engineering and architectural services................................ Management and public relations............................... 10,036 10,197 10,063 10,078 10,097 10,114 10,131 10,146 10,164 10,184 1,875 1,924 1,919 1,921 1,923 1,926 1,933 1,938 1,941 1,948 1,953 1,958 1,962 1,967 1,972 1,786 3,974 636 996 2,267 2,783 680 771 1,795 3,990 643 1,009 2,325 2,903 712 806 1,793 3,977 642 1,005 2,322 1,793 3,982 643 1,793 3,988 645 1,798 3,993 645 1,799 4,005 646 1,014 2,329 2,950 724 817 1,800 4,016 644 1,013 2,338 2,958 727 820 1,803 4,025 642 1,015 2,357 2,977 729 823 1,806 4,035 646 1,017 2,363 2,985 732 827 1,806 4,045 645 1,811 4,055 648 1,816 4,062 646 99 2,436 Government............................... Federal..................................... Federal, except Postal Service................................. State......................................... Education................................ Other State government......... Local......................................... Education................................ Other local government.......... 1 1 ,0 1 0 1 ,0 1 0 1 ,0 1 1 707 800 2,335 2,887 712 804 2,337 2,883 715 807 2,352 2,889 719 809 1,797 4,001 645 1,013 2,344 2,928 719 813 106 2,475 105 2,473 106 2,474 107 2,466 107 2,470 107 2,482 107 2,482 108 2,486 108 2,487 109 2,487 3,256 3,419 3,395 3,421 3,423 3,440 3,455 3,467 3,478 3,490 3,496 957 1,017 1 ,0 1 0 1,018 1 ,0 2 2 1,026 1,030 1,034 1,035 1,040 1,046 1,031 1,090 1,081 1,089 1,090 1,098 1 ,1 0 2 1,108 1,113 1,116 1,119 1,123 1,125 1,124 1 ,1 2 2 20,206 2,669 20,681 2,777 21,114 3,240 20,940 3,101 20,719 2,820 20,600 2,653 20,583 2,623 20,581 2,622 20,590 2,620 20,614 2,613 20,629 2,613 20,680 2,615 20,711 2,613 20,747 2,615 20,766 2,611 1,796 4,709 1,983 2,726 12,829 7,289 5,540 1,917 4,785 2,032 2,753 13,119 7,440 5,679 2,377 4,775 2,026 2,749 13,099 7,436 5,663 2,238 4,776 2,029 2,747 13,063 7,396 5,667 1,957 4,782 2,033 2,749 13,117 7,438 5,679 1,790 4,794 2,037 2,757 13,153 7,456 5,697 1,762 4,813 2,051 2,762 13,147 7,439 5,708 1,762 4,798 2,035 2,763 13,161 7,445 5,716 1,761 4,798 2,033 2,765 13,172 7,449 5,723 1,754 4,809 2,037 2,772 13,192 7,457 5,735 1,755 4,800 2,028 2,772 13,216 7,468 5,748 1,756 4,825 2,048 2,777 13,240 7,479 5,761 1,754 4,836 2,055 2,781 13,262 7,492 5,770 1,756 4,847 2,065 2,782 13,285 7,495 5,790 1,753 4,844 2,058 2,786 13,311 7,519 5,792 2 ,8 8 8 1 ,0 2 0 1 ,0 2 2 1 ,0 2 1 2,375 2,997 734 829 2,384 3,009 739 831 2,388 3,023 743 835 1,813 4,071 645 1,027 2,419 3,039 744 843 110 110 2,487 2,489 109 2,489 2,496 3,504 510 3,517 3,515 1,050 1,052 1,053 1,056 110 Includes other Industries not shown separately. p = preliminary. Note : See "Notes on the data" for a description of the most recent benchmark revision. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 81 Current Labor Statistics: Labor Force Data 13. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls, by industry, monthly data seasonally adjusted A n n u al a ve ra g e 2000 2 001 In d u s try 1 99 9 2000 M ay June J u ly Aug. S e p t. O c t. N o v. D ec . J an . F eb . M a r. A p r .p M a / PRIVATE SECTOR............. ...................... 34.5 34.5 34.4 34.5 34.4 34.3 34.4 34.4 34.3 34.2 34.4 34.3 34.3 34.2 34.3 GOODS-PRODUCING.................................... 41.0 41.0 41.0 41.0 41.1 40.8 40.7 40.8 40.6 40.1 40.5 40.3 40.5 40.6 40.6 MINING........................................................... 43.2 43.1 42.8 43.0 43.2 43.1 43.0 43.1 43.0 42.5 43.1 43.2 43.8 44.0 43.9 MANUFACTURING....................................... 41.7 41.6 41.8 47 41.4 45 41.4 44 41.2 4*3 40.6 41.0 40.9 41.0 41.0 41.0 4.6 41.7 4.6 41.4 4.6 41.6 4.6 Durable goods............................................ 42.2 42.1 4.7 42.1 42.2 48 42.4 4.8 41.9 4.6 41.8 41.0 41.3 41.1 41.3 41.3 41.0 4 .5 41.9 4.6 41.6 Lumber and wood products.................. 4.8 41.1 40.6 38.6 4.8 4 .5 41.0 41.0 41.0 41.0 40.7 40.8 40.9 40.8 40.2 39.8 40.1 40.3 40.1 40.0 40.4 40.2 40.1 39.6 39.7 39.7 39.4 38.8 39.2 43.1 43.0 44.7 43.2 43.0 43.2 44.7 44.4 43.0 44.4 42.3 44.9 43.2 45.2 42.9 44.5 42.8 45.1 39.1 43.7 Primary metal industries......................... 3.1 44.7 39.1 42.8 39.3 Stone, clay, and glass products........... 40.3 43.4 43.5 43.8 43.2 43.4 44.3 Blast furnaces and basic steel products............................................... 45.2 46.0 46.4 46.5 46.2 45.9 45.8 45.1 42.6 42.7 42.7 43.0 42 3 42 2 42 2 44.7 41 3 44.7 41 7 44.4 41 7 45.4 4P q 44.6 42.4 45.2 42 1 44.4 Fabricated metal products.................... Industrial machinery and equipment.... 42.1 42.2 42.1 42.3 42.5 42.1 41.9 42.0 41.7 41.1 41.5 41.0 41.2 41.3 40.6 41.2 41.1 41.2 41 2 41 5 40 5 40 7 40 7 40 fi 40 3 40 3 40 3 43.8 45.0 41.3 39.8 43.4 44.4 43.1 44.3 41.5 43.6 44.7 43.7 44.5 41.6 43.2 44.3 40.9 42.9 43.8 41.1 43.0 43.9 42.5 43.2 42.0 42.0 41.1 38.7 38.5 38.1 38.3 38.2 43.3 41.0 38.2 43.6 40.9 39.3 42.0 42.3 41.0 38.2 42.4 41.2 38.4 42.0 42.1 41.0 42.4 41.2 38.6 41.5 41.5 40.7 40.9 4.4 40.8 4.4 40.7 4.4 40.7 40.5 4.2 41 4 40 fi 40.1 4.1 40 0 40.6 4.3 41 3 40.4 40.4 4.0 41 1 40.5 4.1 41 2 40.5 3.9 4.0 41.8 40.9 41.0 4.5 41 8 37.5 43.4 37 6 42 2 37 2 41 7 37 6 41 Q 37 fi 41 7 37 fi 41 ft 3ft 0 37 Q 38.4 38.4 42.3 38.6 38.2 38.1 42.6 42.3 42.6 42.3 Furniture and fixtures............................. 44.3 44.3 Electronic and other electrical Transportation equipment..................... Motor vehicles and equipment........... Instruments and related products........ Miscellaneous manufacturing............... Nondurable goods.................................... Overtime hours...................................... Food and kindred products................... Apparel and other textile products....... 41.3 39.0 39.1 41.5 39.0 41.7 41.2 40.8 4.4 41.7 41.3 40.8 4.4 41.9 41 1 41 37.8 42.5 37.8 42.6 37.9 42 6 6 41.8 40 8 4.3 41 6 40 8 40.6 4.3 41 5 40 fi 38.1 42 6 37.7 42 5 37.6 42 4 37.5 42 3 38.0 Printing and publishing........................... 38.1 38.3 38.3 38.4 38.4 38.1 38.2 43.0 42.5 42.5 42.4 42 7 42.3 38.2 42 4 38.2 Chemicals and allied products.............. 42.3 42.1 37 .0 42.1 41.7 37.4 41.4 41.5 41 3 41 5 41 3 41 3 41 2 41 0 40 4 Leather and leather products................ 37.5 37.6 37.4 37.6 37.4 37.3 37.4 37.3 36.8 36.9 36.4 36.1 36.6 35.8 SERVICE-PRODUCING................................. 32.8 32.8 32.8 32.8 32.8 32.7 32.8 32.8 32.8 32.7 32.9 32.8 32.8 32.7 32.7 Rubber and miscellaneous 40 Q TRANSPORTATION AND PUBLIC UTILITIES................................... 38.7 38.6 38.5 38.5 38.5 38.4 38.5 38.6 38.6 38.7 38.7 38.5 38.3 38.1 38.2 WHOLESALE TRADE.................................. 38.3 38.5 38.3 38.5 38.5 38.3 38.4 38.4 38.4 38.3 38.3 38.1 38.3 38.2 38.2 RETAIL TRADE............................................. 29.0 28.9 28.9 28.9 28.9 28.9 28.8 28.9 28.9 28.7 29.1 28.9 28.8 28.8 28.8 p = preliminary. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. 82 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 14. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry, seasonally adjusted 2001 2000 A n n u a l a v e ra g e In d u s try 1 99 9 2000 M ay June J u ly A ug. S e p t. O ct. N o v. D ec. J an . Feb. M a r. A p r .p M ayp $13.24 $13.75 $13.67 $13.72 $13.75 $13.80 $13.84 $13.90 $13.97 $14.03 $14.03 $14.11 $14.17 $14.21 $14.25 14.83 15.40 15.29 15.35 15.38 15.45 15.47 15.57 15.63 15.65 15.67 15.74 15.79 15.78 15.86 17.05 17.24 17.27 17.29 17.29 17.25 17.24 17.30 17.38 17.43 17.49 17.52 17.55 17.53 17.53 Construction........................................... 17.19 17.88 17.76 17.80 17.86 17.93 17.97 18.02 18.16 18.17 18.28 18.30 18.33 18.15 18.22 Manufacturing........................................ 13.90 14.38 14.28 14.35 14.37 14.43 14.44 14.54 14.57 14.58 14.54 14.63 14.66 14.72 14.78 Excluding overtime............................. 13.17 13.62 13.53 13.60 13.62 13.69 13.73 13.80 13.84 13.88 13.83 13.94 13.96 13.96 14.04 Service-producing................................... 12.73 13.24 13.16 13.22 13.24 13.29 13.34 13.39 13.46 13.53 13.54 13.62 13.68 13.73 13.76 Transportation and public utilities....... 15.69 16.22 16.20 16.26 16.18 16.27 16.31 16.39 16.42 16.50 16.51 16.64 16.68 16.74 16.78 Wholesale trade..................................... 14.59 15.20 15.08 15.21 15.24 15.25 15.33 15.37 15.44 15.55 15.53 15.60 15.68 15.74 15.69 Retail trade............................................. 9.09 9.46 9.41 9.44 9.47 9.50 9.54 9.57 9.61 9.65 9.64 9.69 9.72 9.74 9.79 Finance, insurance, and real estate.... 14.62 15.07 15.00 15.04 15.07 15.13 15.19 15.20 15.28 15.35 15.44 15.55 15.61 15.64 15.72 13.37 13.91 13.82 13.87 13.92 13.97 14.01 14.07 14.16 14.23 14.25 14.35 14.40 14.48 14.50 7.86 7.89 7.89 7.87 7.87 7.90 7.88 7.90 7.92 7.94 7.90 7.92 7.95 7.94 7.93 PRIVATE SECTOR (In current dollars).. PRIVATE SECTOR (in constant (1982) dollars)........................................................ p = preliminary. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 83 Current Labor Statistics: Labor Force Data 15. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry A n n u al a ve ra g e 2000 2001 In d u s try P R IV A T E S E C T O R ............................................. 1 99 9 2000 M ay June J u ly Aug. S e p t. O c t. N ov. D ec. J an . F eb . M a r. A p r .p M a y .p $13.24 $13.75 $13.65 $13.63 $13.69 $13.68 $13.89 $13.97 $13.99 $14.04 $14.10 $14.16 $14.19 $14.27 $14.22 17.22 17.15 17.21 17.13 17.16 17.28 17.32 17.54 17.67 17.61 17.57 17.60 17.68 18.30 18.07 18.17 14.65 14.74 14.75 12 16 M I N I N G ...................................................................... 17.05 17.24 C O N S T R U C T I O N ................................................. 17.19 17.88 17.70 17.73 17.92 18.05 18.17 18.22 18.20 18.23 18.17 18.16 M A N U F A C T U R I N G ............................................. 13.90 14.38 14.26 14.33 14.35 14.36 14.51 14.53 14.60 14.67 14.59 14.61 14 36 14 82 14 69 14 76 14 74 1 4 61 14 96 14 99 16 05 1 6 11 1 4 Q8 16 03 11.51 11.93 11.85 11.93 11.99 12 01 12 07 12 09 12 07 12 12 12 15 12 0 6 12 06 12 1 3 11.29 13.97 11.73 11.64 11.70 11.76 11.83 1 1 .8 8 1 1 .8 6 12.03 12.04 12.07 12.09 14.40 16.30 14.47 16.46 14.58 16.67 14.65 16.49 14.77 14.75 11.93 14.72 11.92 14.53 16.42 11.90 14.76 14.65 14.68 14.79 16 54 16.48 16.58 16.65 16.66 16.58 16.63 14.96 16.90 15.09 16.80 Furniture and fixtures............................ Stone, clay, and glass products.......... 15.80 Blast furnaces and basic steel products.............................................. Fabricated metal products................... 18.84 19.82 13.87 19.72 2 0 .0 0 20.16 20.05 2 0 .0 0 20.37 20.23 13.85 19.84 14.01 19.88 13.82 19.83 13.99 19.71 13.78 20.35 13.83 19.97 13.50 14.03 14.09 13.99 14.03 14.08 14.11 14.22 Industrial machinery and equipment... Electronic and other electrical 15.03 15.55 15.45 15.49 15.57 15.61 15.69 15.66 15.67 15.81 15.73 15.74 15.77 15.74 15.78 equipment............................................ Transportation equipment.................... Motor vehicles and equipment.......... 13.43 13.80 13.64 13.91 18.77 19.12 14.07 18.88 19.26 19.05 19.43 19.00 19.31 18.57 18.77 14.16 18.68 18.91 14.26 18.76 19.02 14.39 18.77 19.13 14.40 18.83 19.19 14.43 14.25 14.30 14.58 14.62 14.64 11.26 11.63 11.51 11.55 14.46 11.57 13.76 18.37 18.68 14.44 14.17 18.23 18.62 13.77 18.02 18.22 14.04 18.45 18.79 13.66 18.40 18.81 14.00 17.79 18.10 14.08 11.56 1 1 .6 6 11.75 11.82 14.80 11.94 11 98 14.60 11 98 14.73 12 05 14.80 12 04 12 10 N o n d u r a b l e g o o d s .......................................... 13.21 13.59 12.42 21.67 13.65 12.51 22.52 13.75 12.54 13.68 12.49 13.80 12.59 13.89 12.69 13.97 12.71 12.97 12.70 13.97 13.97 14.12 14.08 1 2 .1 1 13.69 12.50 21.57 .13.81 Food and kindred products.................. 1 2 .6 8 22.60 22.13 11.13 1 1 .2 1 21.34 11.32 9.29 9.29 16.27 11.30 9.36 16.37 21.76 11.27 22 11.09 9.26 21.85 11.27 12.79 22 59 11.16 22.90 11.18 12.65 21.49 11.27 9.37 9.36 16.54 11.30 9.44 11.29 9.41 16.61 9.39 16.53 9.46 16.43 9.33 16.50 16.56 16.74 16.80 14.56 14.50 14.56 14.66 14.69 18.35 22.23 18.47 22.31 18.41 14.75 18.48 2 2 .1 0 2 2 .2 1 18.33 21.83 14.75 18.64 21.78 18.27 22.14 14.59 18.34 14.64 18.32 22.06 22.09 21.80 Instruments and related products....... 19.87 Textile mill products.............................. Apparel and other textile products...... Paper and allied products.................... 10.81 8.92 15.88 9.30 16.25 Printing and publishing......................... 13.96 17.42 12.59 22.47 11.23 9.37 14.64 22 63 11.31 14.75 12.82 80 16.16 9.33 16.21 14.40 18.15 14.30 17.99 14.33 18.10 21.43 2 2 .0 0 21.79 21.83 12.40 9.71 12.85 10.18 12.75 12.79 1 2 .8 8 12.98 13.10 13.20 13.24 13.31 13.19 1 0 .1 1 10.13 12.87 10.24 12.96 10.03 10.31 10.33 10.32 10.37 10.51 10.35 10.46 13.33 10.37 13.31 10.23 P U B L IC U T I L I T I E S ......................................... 15.69 16.22 16.13 16 18 16 19 16 22 16 61 16 66 16 46 16 56 16 56 16 66 16 65 16 76 16 72 W H O L E S A L E T R A D E ....................................... 14.59 15.20 15.05 15.12 15.27 15.19 15.33 15.45 15.45 15.58 15.56 15.62 15.58 15.86 15.66 R E T A IL T R A D E .................................................... 9.09 9.46 9 40 9.39 9.40 9.41 9.58 9.59 9.61 9.65 9.69 9.72 9.74 9.78 9.78 A N D R E A L E S T A T E ....................................... 14.62 15.07 15.02 14.93 15.01 14.99 15.11 15.24 15.25 15.32 15.45 15.63 15.67 15.81 15.74 S E R V I C E S ............................................................... 13.37 13.91 13.79 13.72 13.78 13.74 14.00 14.11 14.20 14.33 14.39 14.47 14.48 14.58 14.47 Chemicals and allied products............ Petroleum and coal products............... 16.36 14.41 18.33 21.93 14.39 18.21 Rubber and miscellaneous plastics products.................................. Leather and leather products............... T R A N S P O R T A T IO N A N D F IN A N C E , I N S U R A N C E , p = preliminary. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. 84 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 16. Average weekly earnings of production or nonsupervisory workers on private nonfarm payrolls, by industry 1999 2000 2001 2000 A nnual average May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. A pr.p M ayp $471.60 473.34 270.10 $477.78 473.00 273.33 $474.70 473.34 271.72 $479.21 476.10 272.43 $484.76 478.16 275.28 $479.86 479.17 272.03 $480.17 479.83 272.51 $477.99 482.63 269.74 $481.44 483.97 270.62 $482.46 486.03 270.89 $486.61 485.98 271.70 $486.32 488.78 270.18 P R IV A T E S E C T O R Current dollars............................ $456.78 Seasonally adjusted............... 271.25 Constant (1982) dollars............ $474.38 272.16 $468.20 470.25 269.70 M IN IN G .................................................... 736.56 743.04 738.74 742.60 748.64 746.87 751.61 756.86 743.03 747.20 750.98 751.95 757.27 765.60 769.12 C O N S T R U C T IO N ................................ 672.13 702.68 700.92 700.34 716.80 725.61 728.62 732.44 704.34 694.56 692.28 682.82 702.52 695.70 730.43 579.63 344.20 598.21 343.21 593.22 341.72 598.99 343.06 592.66 339.05 594.50 340.30 606.52 344.81 604.45 343.24 607.36 344.31 607.34 344.69 596.73 336.76 591.71 332.61 597.72 335.61 588.13 328.38 600.33 333.52 - M A N U F A C T U R IN G Current dollars........................... Constant (1982) dollars............. 605.99 623.92 619.92 625.82 614.66 620.54 632.81 631.08 633.61 630.09 615.68 613.22 620.20 607.11 624.31 473.06 454.99 489.13 469.20 489.41 464.44 495.10 472.68 489.19 466.87 494.02 473.20 496.08 481.14 499.32 474.40 494.87 474.81 486.01 476.01 477.92 464.88 473.54 461.95 483.20 467.15 483.99 457.45 497.34 461.84 606.30 703.10 626.24 737.26 626.40 728.61 623.66 742.35 634.23 741.82 641.67 733.81 742.65 647.53 731.71 637.63 //////#### 624.13 735.93 613.84 731.37 610.69 716.26 631.53 718.42 638.79 730.08 674.52 727.44 851.57 572.40 911.72 590.86 911.06 588.41 930.00 594.26 944.24 583.63 916.62 585.86 908.21 598.77 890.82 596.83 902.72 597.68 890.62 596.01 901.15 581.98 882.20 580.84 884.00 585.73 920.72 567.22 898.21 590.13 632.76 656.21 651.99 655.23 653.94 652.50 658.98 656.15 658.14 662.44 655.94 648.49 651.30 628.03 642.25 553.32 779.20 567.18 800.73 559.24 789.36 562.79 807.76 561.82 758.64 558.66 789.91 573.09 822.13 575.00 819.39 575.64 821.06 585.22 807.50 567.02 772.51 566.40 775.22 568.97 789.80 554.02 765.82 560.16 804.04 814.50 834.28 828.59 852.09 772.53 823.79 860.40 857.07 852.98 826.47 778.96 786.66 808.35 791.98 840.52 581.50 488.15 595.96 453.57 589.95 451.19 592.02 450.45 595.75 446.60 587.71 448.53 597.78 455.91 602.34 457.08 607.56 457.43 621.72 460.88 603.17 454.04 605.90 454.04 605.40 461.52 594.96 559.15 601.80 566.02 N o n d u ra b le g o o d s .......................... 540.29 558.55 553.11 556.92 559.63 556.78 567.18 564.83 569.49 569.98 565.79 560.20 561.59 510.32 521.77 Food and kindred products...... 506.20 763.01 442.13 521.25 877.90 459.79 514.19 892.80 456.91 522.92 939.08 459.67 524.17 964.09 458.38 525.83 942.42 458.49 535.08 927.25 465.56 528.78 878.12 457.06 534.25 895.85 460.94 528.74 892.16 462.07 520.70 832.26 459.59 509.80 831.66 449.67 513.54 893.89 458.06 885.53 885.53 444.09 884.64 884.64 456.12 334.50 689.19 351.54 690.63 350.95 683.57 356.41 687.30 349.30 693.66 351.16 352.87 699.00 352.31 699.92 352.67 706.20 353.25 705.93 349.31 697.57 352.87 683.10 355.70 687.24 346.45 6 8 8 .2 2 6 8 8 .0 1 357.58 705.60 531.88 749.06 908.63 551.52 771.38 932.80 543.40 762.78 913.00 547.41 767.44 910.31 550.46 775.36 925.45 549.70 766.64 886.45 562.02 776.77 930.93 558.25 772.82 952.02 564.93 778.04 955.89 564.41 788.67 952.64 555.88 781.28 987.87 557.78 778.74 957.25 565.57 773.53 936.51 554.60 790.34 965.33 557.55 779.86 906.88 517.08 363.15 531.99 381.75 529.13 379.13 530.79 383.17 525.50 375.82 528.96 389.12 540.43 390.75 537.37 389.44 539.72 390.10 543.84 382.65 544.16 384.67 543.05 373.64 538.15 375.51 529.20 369.17 540.39 368.28 607.20 626.09 617.78 622.93 634.65 627.71 631.20 638.82 632.56 638.06 632.59 637.18 362.70 641.00 635.36 597.92 593.28 596.71 589.72 590.44 592.04 607.44 598.21 D u ra b le g o o d s D u ra b le g o o d s Lumber and wood products...... Furniture and fixtures............... Stone, clay, and glass Primary metal industries.......... Blast furnaces and basic steel products....................... Fabricated metal products....... Industrial machinery and equipment............................. Electronic and other electrical equipment.............................. Transportation equipment........ Motor vehicles and equipment............................ Instruments and related products................................. Miscellaneous manufacturing... Textile mill products.................. Apparel and other textile products................................. Printing and publishing............ Chemicals and allied products.. Petroleum and coal products.... Rubber and miscellaneous Leather and leather products... T R A N S P O R T A T IO N A N D P U B L IC U T IL IT IE S ......................... W H O L E S A L E T R A D E ....................... 558.80 585.20 576.42 582.12 592.48 581.78 588.67 R E T A IL T R A D E ................................... 263.61 273.39 270.72 275.13 280.12 277.60 275.90 277.15 274.85 278.89 273.26 276.05 276.62 281.66 280.69 A N D R E A L E S T A T E ....................... 529.24 547.04 539.22 540.47 550.87 539.64 545.47 557.78 549.00 553.05 556.20 567.37 564.12 580.23 565.07 S E R V IC E S ............................................. 435.86 454.86 448.18 448.64 456.12 452.05 455.00 464.22 462.92 467.16 464.80 471.72 472.05 476.77 470.28 F IN A N C E , IN S U R A N C E , p = preliminary. Note: See "Notes on the data" for a description of the most recent benchmark revision. Dash indicates data not available https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 85 Current Labor Statistics: Labor Force Data 17. Diffusion indexes of employment change, seasonally adjusted [In percent] T im e s p a n a n d y e a r J an . F eb . M ar. A p r. M ay June J u ly Aug. S e p t. O c t. N ov D ec . P riv a te n o n fa rm p a y ro lls , 3 5 6 in d u s trie s Over 1-month span: 1998............................................................ 63.2 56.2 59.3 60.2 1999............................................................ 55.1 59.6 52.8 57.2 2000 ............................................................ 55.7 59.3 2001 ............................................................ 53.7 50.4 61.0 55.8 58.9 58.2 57.1 55.4 58.4 54.8 55.0 58.2 56.4 54.2 57.1 54.4 55.2 59.9 56.8 54.2 47.7 60.5 57.8 55.1 46.0 - - - 52.0 - 55.1 45.0 57.9 54.8 - - 54.2 - 59.2 Over 3-month span: 1998............................................................ 65.3 6 6 .1 1999............................................................ 60.8 2 0 0 0 .............................................................. 61.6 51.7 57.8 63.3 Over 6 -month span: 1998............................................................. 1999............................................................. 2000 .............................................................. 2001 ............................................................. 2001 .............................................................. 64.6 58.5 65.7 62.2 57.9 57.5 58.4 59.1 59.2 59.3 58.1 57.2 61.5 61.0 60.6 56.4 59.8 54.1 59.1 55.1 57.9 57.9 59.2 61.9 55.8 56.2 54.1 48.6 48.7 42.4 - - - - 53.3 - 55.7 - 53.3 - 70.4 67.4 60.6 59.8 65.0 58.2 62.5 59.8 59.9 64.9 63.5 60.6 52.0 50.3 63.6 56.7 60.5 59.2 59.2 61.8 58.6 60.8 57.9 62.2 59.6 61.2 62.6 60.3 63.7 61.5 55.5 56.1 58.6 54.2 48.2 - - - - - 54.8 - - 62.3 51.8 - 54.2 - 60.8 61.3 60.9 Over 12-month span: 1998............................................................. 69.7 67.6 67.4 6 6 .0 64.0 62.7 61.9 62.0 60.9 59.3 1999.............................................................. 61.2 60.2 58.2 60.8 60.8 61.6 62.2 61.3 63.9 .............................................................. 62.5 63.0 61.8 59.5 58.4 56.8 55.7 56.5 - - - - - - - - 54.2 - 63.0 53.4 2000 2 0 0 1 ............................................................. - 58.8 52.3 - 51.8 41.2 53.3 43.8 - 43.4 46.7 44.1 - 36.8 40.8 46.0 35.7 - M a n u fa c tu rin g p a y ro lls , 139 in d u s trie s Over 1-month span: 1998............................................................. 57.4 1999.............................................................. 2 0 0 0 .............................................................. 2 0 0 1 .............................................................. 46.9 44.9 37.9 Over 3-month span: 1998.............................................................. 1999.............................................................. 59.6 41.2 2000 .............................................................. 2001 .............................................................. 50.0 28.3 51.5 44.5 56.6 32.4 59.6 39.0 54.0 29.4 53.7 43.0 55.5 41.5 53.3 42.3 46.7 31.3 43.8 50.4 41.2 30.5 48.2 38.2 51.5 39.3 54.8 30.5 51.5 53.7 39.3 38.6 41.9 45.2 34.6 - - - 46.3 41.5 - 41.9 40.8 38.2 44.9 46.3 41.5 55.9 38.2 50.4 46.7 37.9 41.5 41.8 45.2 52.9 24.6 42.3 26.8 40.8 43.0 48.5 39.0 48.2 41.5 45.2 33.6 - - - 28.7 - 30.5 - 39.0 - 34.9 37.1 34.2 46.3 51.5 25.0 - 27.9 - 2 0 .2 Over 6 -month span: 1998.............................................................. 63.2 54.4 50.4 40.4 1999.............................................................. 36.0 38.2 37.5 41.2 44.5 36.8 40.1 39.7 37.5 43.0 36.4 41.5 46.0 40.1 40.4 44.5 25.4 48.5 19.5 55.1 43.8 34.9 33.5 34.6 30.1 29.4 - - - - - - - 51.8 32.4 46.7 40.4 37.9 40.1 38.2 34.6 35.7 34.2 39.0 40.1 37.5 40.4 36.4 36.0 44.5 41.2 37.9 33.8 31.3 31.3 31.3 27.6 46.0 25.4 44.9 23.2 44.5 46.3 52.2 34.6 45.2 - - - - - - - - - - 2000 ............................................................. 51.5 2001 .............................................................. 26.8 Over 12-month span: 1998............................................................. 54.8 1999............................................................. 2 0 0 0 ............................................................. 2 0 0 1 .............................................................. 38.6 Dash indicates data not available. 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 86 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 2 1 .0 decreasing employment. Data for the 2 most recent months shown in each span are preliminary. See the "Definitions" in this section. See "Notes on the data" for a description of the most recent benchmark revision. 18. Annual data: Employment status of the population [Numbers in thousands] 1 99 2 1 993 1 99 4 1 99 5 1 99 6 1997 1998 1999 2000 Civilian noninstitutional population........... 192,805 194,838 196,814 198,584 200,591 203,133 205,220 207,753 209,699 Civilian labor force................................... 128,105 129,200 131,056 132,304 133,943 136,297 137,673 139,368 140,863 Labor force participation rate............... 66.4 66.3 6 6 .6 6 6 .6 6 6 .8 67.1 67.1 67.1 67.2 Employed............................................. 118,492 120,259 123,060 124,900 126,708 129,558 131,463 133,488 135,208 Employment-population ratio.......... 61.5 61.7 62.5 62.9 63.2 63.8 64.1 64.3 64.5 Agriculture...................................... 3,247 3,115 3,409 3,440 3,443 3,399 3,378 3,281 3,305 Nonagricultural industries............ 115,245 117,144 119,651 121,460 123,264 126,159 128,085 130,207 131,903 5,655 E m p lo y m e n t s ta tu s 9,613 8,940 7,996 7,404 7,236 6,739 6 ,2 1 0 5,880 Unemployment rate.......................... 7.5 6.9 6 .1 5.6 5.4 4.9 4.5 4.2 4.0 Not in the labor force............................... 64,700 65,638 66,280 66,647 66,837 67,547 68,385 68,836 1996 1 99 7 1998 1 99 9 2000 19. 65,758 Annual data: Employment levels by industry [In thousands] 1 99 2 1 99 3 1 99 4 1 99 5 Total employment............................................ 108,601 110,713 114,163 117,191 119,608 122,690 125,865 128,916 131,759 Private sector................................................ 89,956 91,872 95,036 97,885 100,189 103,133 106,042 108,709 111,079 Goods-producing....................................... 23,231 23,352 23,908 24,265 24,493 24,962 25,414 25,507 25,709 Mining...................................................... 635 610 601 581 580 596 590 539 543 Construction........................................... 4,492 4,668 4,986 5,160 5,418 5,691 6 ,0 2 0 6,415 6,698 Manufacturing......................................... 18,104 18,075 18,321 18,524 18,495 18,675 18,805 18,552 18,469 Service-producing..................................... 85,370 87,361 90,256 92,925 95,115 97,727 100,451 103,409 106,050 Transportation and public utilities........ 5,718 5,811 5,984 6,132 6,253 6,408 6,611 6,834 7,019 Wholesale trade..................................... 5,997 5,981 6,162 6,378 6,482 6,648 6,800 6,911 7,024 Retail trade............................................. Finance, insurance, and real estate.... 19,356 19,773 20,507 21,187 21,597 21,966 22,295 22,848 23,307 6,602 6,757 6,896 6,806 6,911 7,109 7,389 7,555 7,560 29,052 30,197 31,579 33,117 34,454 36,040 37,533 39,055 40,460 18,645 18,841 19,128 19,305 19,419 19,557 19,823 20,206 20,681 2,969 2,915 2,870 2,822 2,757 2,699 2 ,6 8 6 2,669 2,777 4,408 4,488 4,576 4,635 4,606 4,582 4,612 4,709 4,785 11,267 11,438 11,682 11,849 12,056 12,276 12,525 12,829 13,119 In d u s try Federal................................................. Local..................................................... NOTE: See "Notes on the data" for a description of the most recent benchmark revision. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 87 Current Labor Statistics: 20. Labor Force Data Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm payrolls, by industry In d u s try 1 99 2 19 9 3 19 9 4 1 99 5 19 9 6 1997 1998 19 9 9 2000 Private sector: Average weekly hours.................................................. 34.4 34.5 34.4 34.6 34.6 10.57 34.5 10.83 34.7 Average hourly earnings (in dollars).......................... 1 1 .1 2 11.43 11.82 363.61 373.64 385.86 394.34 406.61 12.28 424.89 12.78 442.19 Average weekly hours................................................ 43.9 Average hourly earnings (in dollars)........................ 14.54 44.3 14.60 43.9 16.91 Average weekly earnings (in dollars)...................... 638.31 646.78 34.5 13.24 34.5 13.75 456.78 474.38 43.2 43.1 17.24 Mining: 44.8 44.7 45.3 45.4 14.88 666.62 15.30 683.91 15.62 707.59 16.15 733.21 742.35 17.05 736.56 743.04 Construction: Average weekly hours................................................ 38.0 38.5 38.9 38.9 39.0 39.0 38.9 Average hourly earnings (in dollars)........................ 14.15 14.38 537.70 553.63 14.73 573.00 15.09 587.00 15.47 603.33 16.04 625.56 16.61 646.13 39.1 17.19 672.13 39.3 17.88 702.68 Manufacturing: Average weekly hours................................................ 41.0 41.4 42.0 42.0 41.7 41.7 41.6 11.46 11.74 12.07 41.6 12.37 41.6 Average hourly earnings (in dollars)........................ Average weekly earnings (in dollars)...................... 12.77 13.17 13.49 469.86 486.04 506.94 514.59 531.23 553.14 562.53 13.90 579.63 14.38 598.21 Transportation and public utilities: Average weekly hours................................................ 38.3 39.3 39.7 39.4 39.6 39.7 39.5 38.7 38.6 Average hourly earnings (in dollars)........................ 13.43 514.37 13.55 532.52 13.78 547.07 14.13 556.72 14.45 14.92 592.32 15.69 607.20 16.22 572.22 15.31 604.75 626.09 Wholesale trade: Average weekly hours................................................ Average hourly earnings (in dollars)........................ 38.2 38.2 38.4 38.3 38.3 38.4 38.5 11.74 448.47 12.87 492.92 14.58 435.10 12.43 476.07 13.45 Average weekly earnings (in dollars)...................... 12.06 463.10 38.3 14.07 38.3 11.39 516.48 538.88 558.80 15.20 585.20 Retail trade: Average weekly hours................................................ 28.8 28.8 28.8 28.9 29.0 29.0 28.9 7.12 7.29 28.9 7.49 28.8 Average hourly earnings (in dollars)........................ 7.69 209.95 216.46 221.47 8.74 253.46 9.46 205.06 8.33 240.74 9.09 Average weekly earnings (in dollars)...................... 7.99 230.11 263.61 273.39 35.8 10.82 35.8 11.35 35.8 11.83 35.9 12.32 35.9 36.1 13.34 36.4 36.2 14.07 406.33 423.51 442.29 481.57 512.15 14.62 529.24 36.3 15.07 387.36 12.80 459.52 547.04 Average hourly earnings (in dollars)........................ 32.5 10.54 32.5 10.78 32.5 11.04 32.6 12.84 32.6 13.37 13.91 342.55 350.35 358.80 11.79 382.00 32.6 12.28 Average weekly earnings (in dollars)...................... 32.4 11.39 369.04 400.33 418.58 435.86 454.86 Finance, insurance, and real estate: Average weekly hours................................................ Average hourly earnings (in dollars)........................ Average weekly earnings (in dollars)...................... Services: Average weekly hours................................................ 88 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 32.4 32.7 21. Employment Cost Index, compensation,' by occupation and industry group [June 1989 = 100] 2001 2000 1999 Series Mar. June Sept. Dec. M ar. June Sept. Dec. M ar. P ercent change 3 12 m onths m onth s ended ended M ar. 2001 140.4 141.8 143.3 144.6 146.5 148.0 149.5 150.6 152.5 1.3 4.1 141.9 141.3 143.5 142.5 137.1 141.3 143.3 142.2 145.4 143.4 138.3 142.4 145.0 143.9 147.3 144.7 139.5 143.1 146.3 145.3 148.6 146.1 140.6 144.8 148.4 146.7 150.5 148.6 142.7 146.0 149.9 148.3 151.9 150.1 144.1 147.1 151.5 150.0 153.7 151.8 145.6 148.5 152.5 151.3 154.6 152.8 146.5 150.0 154.4 153.2 156.6 155.3 148.2 152.0 1.3 1.3 4.0 4.4 4.1 4.5 3.9 4.1 139.0 139.9 140.9 142.3 140.5 141.3 141.3 140.0 140.9 142.4 143.2 141.4 142.2 141.7 141.2 142.1 144.0 145.1 142.7 143.4 144.6 142.5 143.6 145.3 146.5 144.3 145.0 145.8 144.9 146.0 147.1 148.0 145.9 146.3 146.5 146.6 147.5 148.4 149.3 147.5 147.7 146.8 148.0 148.7 150.1 151.2 149.0 149.5 149.7 148.8 149.3 151.1 152.4 150.7 151.3 150.6 150.7 151.3 153.0 154.3 152.5 153.2 151.7 1.3 Public administration3 .................................................. Nonmanufacturing......................................................... 140.8 141.5 142.4 144.4 145.7 146.1 146.9 148.3 150.6 1.3 3.4 140.5 141.9 143.4 144.7 146.6 148.0 149.6 150.7 152.6 1.4 4.1 Private industry workers............................................... 140.4 140.5 142.0 141.9 143.3 143.2 144.6 144.5 146.8 146.5 148.5 148.2 149.9 149.8 150.9 150.9 153.0 153.0 1.4 1.4 4.2 4.4 142.4 143.0 142.9 143.7 139.6 142.6 136.9 137.2 137.3 131.6 141.0 144.1 144.5 144.1 145.8 142.6 143.7 138.2 138.4 138.4 133.6 142.3 145.6 146.0 145.2 147.7 144.1 145.0 139.4 139.6 139.9 134.4 143.2 146.9 147.3 146.7 149.1 145.3 146.2 140.5 140.6 141.4 135.2 144.4 149.3 149.4 148.4 151.1 148.9 149.0 142.6 142.3 144.0 137.5 146.4 151.1 151.3 150.7 152.7 150.3 150.6 144.1 144.1 145.0 138.6 148.1 152.6 152.9 152.2 154.4 151.2 152.3 145.5 145.8 146.0 139.9 149.4 153.6 154.1 153.7 155.3 151.4 153.4 146.4 146.7 146.8 141.1 150.4 155.7 156.5 156.3 157.3 152.3 156.1 148.2 148.3 142.6 152.2 150.0 1.4 1 .2 4.3 4.8 5.3 4.1 2.3 4.8 3.9 4.5 3.0 3.7 4.0 139.5 140.6 141.0 142.6 143.9 145.4 146.6 148.1 151.4 1.3 4.2 139.3 140.8 141.9 143.1 145.3 146.9 148.4 149.5 150.7 1.3 4.1 138.9 138.3 141.7 140.4 137.1 135.6 139.9 141.8 140.1 138.5 139.9 139.6 139.9 139.3 142.7 141.3 138.3 136.9 140.9 143.0 141.3 139.4 141.0 140.4 141.1 140.5 143.9 142.5 139.4 137.9 142.1 144.3 142.5 140.5 142.3 141.5 142.5 141.8 145.5 143.9 140.7 138.7 143.6 145.8 143.8 142.1 144.0 142.8 144.8 144.2 148.1 146.5 142.8 140.8 146.0 148.2 146.2 144.4 146.5 144.9 146.6 145.9 150.1 148.4 144.4 143.2 147.5 150.2 148.2 145.6 148.3 146.0 147.9 147.2 151.3 149.6 145.8 145.1 148.7 151.4 149.3 146.7 149.4 147.5 148.8 148.2 151.9 150.5 146.8 146.7 149.3 151.5 149.7 147.8 150.1 147.7 150.1 154.5 153.0 148.2 148.2 151.3 154.2 152.2 149.1 151.8 150.4 153.8 1.3 1.3 1.7 1.7 4.1 4.1 4.3 4.4 3.8 5.3 3.6 4.0 4.1 3.3 3.6 3.8 140.9 141.7 142.3 143.8 136.2 139.3 139.7 136.8 143.4 143.3 143.4 138.9 139.9 142.7 142.4 136.8 135.0 134.3 142.8 143.3 144.3 145.5 137.8 140.5 140.9 138.1 144.6 144.9 144.2 141.1 141.9 144.6 144.0 139.1 135.6 135.7 144.1 144.6 145.8 147.0 139.1 140.8 141.8 138.7 145.7 146.1 145.1 142.2 142.8 146.3 145.8 140.0 137.2 137.0 145.3 145.9 147.0 148.3 139.8 142.4 142.3 139.5 146.1 146.0 146.1 143.5 144.3 148.5 147.4 140.7 138.3 138.1 147.4 147.7 149.3 150.3 141.8 143.6 143.9 140.4 148.6 148.4 148.9 145.6 146.4 150.0 149.6 143.2 139.7 140.1 149.1 149.4 151.0 152.1 143.1 145.1 145.7 141.8 150.9 150.9 151.0 147.3 148.1 151.8 151.1 144.8 141.0 142.5 150.6 151.1 152.6 153.9 144.5 146.3 147.4 142.8 153.5 153.9 152.9 148.3 149.6 152.1 152.7 146.2 142.2 143.4 151.7 152.2 153.7 155.1 145.2 147.9 148.3 143.9 154.1 154.7 153.4 149.^ 150.6 154.4 154.9 146.6 144.4 144.5 154.6 155.8 157.5 147.7 149.6 150.5 145.4 157.3 158.3 156.0 151.0 1.4 Civilian workers2............................................................... Workers, by occupational group: White-collar workers...................................................... Professional specialty and technical........................... Executive, adminitrative, and managerial.................. Administrative support, including clerical................... Blue-collar workers........................................................ Service occupations...................................................... 1 .6 1 .2 1.3 1.3 Workers, by industry division: Goods-producing........................................................... Manufacturing.............................................................. Service-producing......................................................... Services........................................................................ Health services........................................................... Hospitals................................................................... Educational services................................................. Excluding sales occupations.................................... 1 .2 1 .2 1.3 .7 1 .6 .6 4.0 3.6 4.0 4.3 4.5 4.7 3.5 Workers, by occupational group: White-collar workers................................................... Excluding sales occupations.................................. Professional specialty and technical occupations... Executive, adminitrative, and managerial occupations.. Sales occupations..................................................... Administrative support occupations, including clerical... Precision production, craft, and repair occupations. Machine operators, assemblers, and inspectors.... Transportation and material moving occupations.... Handlers, equipment cleaners, helpers, and laborers.... Service occupations................................................... 4 Production and nonsupervisory occupations......... Workers, by industry division: Goods-producing......................................................... Blue-collar occupations.......................................... Manufacturing........................................................... Excluding sales occupations.............................. Durables................................................................... Excluding sales occupations.............................. Transportation........................................................ Electric, gas, and sanitary services.................... Food stores.......................................................... 1 .6 1.7 1.3 .6 1 .8 1 .2 1.4 1 .0 1.1 1 .0 1 .0 1.3 1 .8 1.7 .9 1.1 1 .8 1 .6 1.4 1.5 1.7 1.1 1.5 1 .0 2 .1 2.3 1.7 1 .1 4.3 4.7 4.4 4.8 4.2 4.6 4.6 3.6 5.9 6.7 4.8 3.7 _ 155.1 148.7 147.3 146.1 .5 1.3 1.4 2 .0 4.9 3.8 5.4 4.3 See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 89 Current Labor Statistics: Compensation & Industrial Relations 21. Continued—Employment Cost Index, compensation,1by occupation and industry group [June 1989 = 100] 1 99 9 2000 2001 P e rc e n t c h a n g e S e rie s M a r. June S e p t. D ec . M a r. June S e p t. D ec . 3 12 m o n th s m o n th s ended ended M a r. M a r. 2001 Finance, insurance, and real estate.................................. 141.5 145.8 147.6 148.3 152.0 153.1 155.2 155.7 157.9 1.4 3.9 Excluding sales occupations......................................... 145.6 148.8 151.0 151.6 154.2 155.5 157.4 158.4 161.0 1 .8 4.5 Banking, savings and loan, and other credit agencies. 148.8 141.7 155.4 159.3 159.8 162.7 164.2 165.8 166.5 170.8 2 .6 5.0 144.0 144.5 145.8 147.6 155.2 154.1 157.6 156.5 1 .6 Business services.............................................................. 146.1 150.7 154.8 152.9 5.1 144.6 148.7 151.3 151.2 1.5 143.5 147.5 149.9 149.4 140.5 141.4 142.6 151.9 144.2 154.2 Health services................................................................... 145.8 156.3 147.5 157.5 149.0 158.4 150.6 160.5 152.7 1.3 1.4 4.8 4.1 4.7 Hospitals........................................................................... Educational services......................................................... Colleges and universities............................................... 141.2 148.3 149.2 142.1 148.7 143.0 152.2 149.6 Nonmanufacturing................................................................ 140.3 142.0 White-collar workers.......................................................... 142.3 Insurance............................................................................. Services................................................................................. 144.6 145.8 147.5 149.2 151.1 153.5 1 .6 5.3 154.0 154.6 154.9 159.9 159.2 162.3 1.5 1.9 5.4 155.5 158.8 158.6 162.3 152.6 153.0 153.3 143.4 144.5 146.7 148.4 150.0 151.1 162.2 1.3 4.4 144.1 145.6 146.9 149.2 151.0 152.6 153.7 153.1 1.4 4.4 4.9 Excluding sales occupations........................................ 143.7 146.8 138.0 148.1 138.7 153.8 143.9 155.1 144.8 155.8 157.5 4.9 140.6 152.0 142.3 1.5 135.2 145.3 136.8 150.2 Blue-collar occupations..................................................... 1.5 Service occupations.......................................................... 139.2 140.4 140.7 142.3 143.5 145.1 146.3 147.8 146.9 1 .2 4.5 4.2 State and local government workers...................................... 140.5 141.0 143.1 144.6 145.5 145.9 147.8 148.9 - .9 3.3 White-collar workers................................................................. Professional specialty and technical................................... 139.8 140.2 142.6 .8 3.2 144.5 146.6 148.3 147.4 - 142.0 144.9 144.1 147.3 139.3 144.0 143.2 145.3 138.8 148.4 .7 3.0 Executive, administrative, and managerial......................... Administrative support, including clerical........................... Blue-collar workers.................................................................. 142.6 141.4 142.8 141.3 144.5 143.0 138.8 139.5 140.9 146.1 145.0 142.5 147.0 145.9 143.7 147.2 146.5 144.2 149.2 148.3 145.9 150.7 149.4 147.2 Workers, by occupational group: 152.4 - 1 .1 .9 1 .0 3.7 3.3 3.4 Workers, by industry division: 140.0 140.5 143.2 144.5 145.2 145.5 148.0 148.9 148.9 .7 3.2 Services excluding schools ................................................ Health services................................................................... 139.6 140.3 142.6 143.8 145.2 145.8 147.6 148.8 150.1 .9 3.4 141.2 145.8 147.3 147.9 152.1 .3 144.8 146.3 147.9 148.4 150.0 150.7 151.6 141.7 142.0 142.7 144.2 Hospitals........................................................................... 152.0 152.2 .1 3.3 2.9 144.4 144.7 Services.................................................................................... 5 Schools............................................................................. Elementary and secondary......................................... 1 139.9 140.2 Colleges and universities............................................ 139.6 141.7 Public administration 3 ............................................................. 140.8 140.3 143.1 140.6 140.0 143.5 142.9 142.1 144.8 141.5 142.4 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. 90 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 145.0 145.2 145.5 144.7 147.9 148.2 148.7 149.0 149.6 149.9 .6 3.2 3.2 147.3 150.5 148.5 153.7 2 .8 147.6 148.1 151.7 .3 146.5 145.3 144.5 147.4 1.3 4.3 144.4 145.7 146.1 146.9 148.3 150.6 1 .6 3.4 144.1 .6 3 Consists of legislative, judicial, administrative, and regulatory activities. 4 This series has the same industry and occupational coverage as the Hourly Earnings index, which was discontinued in January 1989. 5 Includes, for example, library, social, and health services. 22. Employment Cost Index, wages and salaries, by occupation and industry group [June 1989 = 100] 2000 1999 2001 S eries Mar. June Sept. Dec. M ar. June Sept. Dec. M ar. P ercen t change 3 12 m onth s m onths ended ended M ar. 2001 Civilian workers1..................................................................... 138.4 139.8 141.3 142.5 144.0 145.4 147.0 147.9 149.5 Workers, by occupational group: White-collar workers............................................................. Professional specialty and technical................................. Executive, adminitrative, and managerial......................... Workers, by industry division: Goods-producing.................................................................. Manufacturing..................................................................... Service-producing................................................................ Services.............................................................................. Health services................................................................. Hospitals......................................................................... Educational services........................................................ Public administration*......................................................... Nonmanufacturing................................................................ Private industry workers...................................................... Excluding sales occupations........................................... 1.1 3.8 1 .0 140.1 140.1 141.6 140.0 134.5 138.3 141.6 141.0 143.8 140.9 135.8 139.4 143.3 142.6 145.9 142.3 137.0 140.1 144.6 144.0 147.2 143.5 137.9 141.7 146.2 144.9 148.6 145.5 139.2 143.0 147.6 146.4 149.9 146.9 140.6 144.0 149.2 148.3 151.6 148.5 142.0 145.7 150.2 149.6 152.4 149.6 142.9 147.1 151.7 151.1 154.0 151.6 144.7 148.6 136.3 137.9 139.2 141.5 138.8 138.1 140.2 137.4 139.0 140.7 142.3 139.7 138.8 140.6 138.6 140.2 142.3 144.1 140.9 140.1 143.7 139.7 141.5 143.5 145.5 142.5 141.6 144.7 141.3 142.9 145.0 146.6 143.8 142.6 145.3 143.0 144.4 146.3 147.9 145.3 143.8 145.6 144.3 145.7 148.0 149.9 146.7 145.6 148.9 145.3 146.5 148.9 151.0 148.3 147.3 149.6 147.0 148.5 150.5 152.6 149.8 148.8 150.5 136.9 138.4 137.8 139.9 139.5 141.5 141.5 142.6 142.5 144.2 142.9 145.5 144.6 147.2 146.1 148.1 147.6 149.7 138.1 138.2 139.7 139.6 141.0 140.8 142.2 142.0 143.9 143.5 145.4 145.1 146.8 146.5 147.7 147.6 149.4 149.5 140.3 141.0 140.7 141.9 137.3 140.4 134.3 134.3 135.7 129.1 137.3 142.1 142.5 141.8 144.3 140.5 141.4 135.6 135.6 136.7 131.0 138.3 143.5 143.9 142.6 146.4 142.1 142.7 136.8 136.7 138.3 131.9 139.4 144.8 145.2 144.1 147.6 143.3 143.8 137.7 137.5 139.5 132.7 140.4 146.6 146.7 145.1 149.2 146.7 146.0 139.1 138.9 140.7 134.1 141.8 148.3 148.5 147.3 150.7 147.9 147.5 140.5 140.6 141.6 135.2 143.6 149.7 149.9 148.6 152.3 149.0 149.1 141.9 142.0 142.9 136.5 145.0 150.6 151.1 150.2 153.0 148.7 150.1 142.8 142.8 143.7 137.6 146.2 152.3 153.0 152.1 154.7 149.2 152.3 144.6 144.6 145.6 139.5 148.0 1 .0 1 .0 1 .0 1.3 1.3 1 .0 1 .2 1.4 1.1 1.1 1 .0 1 .0 .6 1 .0 1.1 1 .2 1.3 3.8 4.3 3.6 4.2 4.0 3.9 4.0 3.9 3.8 4.1 4.2 4.3 3.6 3.6 3.8 3.8 4.2 Workers, by occupational group: White-collar workers........................................................... Excluding sales occupations......................................... Professional specialty and technical occupations.......... Executive, adminitrative, and managerial occupations.. Sales occupations............................................................ Administrative support occupations, including clerical... Precision production, craft, and repair occupations...... Machine operators, assemblers, and inspectors........... Transportation and material moving occupations.......... Handlers, equipment cleaners, helpers, and laborers.... 1.1 1.3 1.3 1.1 .3 1.5 1.3 1.3 1.3 1.4 .5 3.9 4.3 4.8 3.7 1.7 4.3 4.0 4.1 3.5 4.0 4.4 Service occupations........................................................... 136.7 137.8 138.0 139.6 141.0 142.5 143.5 144.9 146.4 1 .0 3.8 Production and nonsupervisory occupations3 ................. 136.8 138.2 139.3 140.4 142.1 143.7 145.0 146.0 147.7 1 .2 3.9 136.3 135.5 139.4 137.8 134.3 130.7 137.9 140.1 138.3 136.3 137.9 138.0 137.3 136.6 140.5 138.8 135.4 131.9 139.0 141.4 139.6 137.2 139.1 138.7 138.5 137.8 141.7 140.1 136.6 133.0 140.2 142.7 140.8 138.4 140.4 139.7 139.7 138.9 143.0 141.3 137.6 133.6 141.5 144.0 142.0 139.7 141.8 140.9 141.3 140.5 145.0 143.2 139.0 136.0 142.9 145.8 143.7 140.8 143.0 142.7 143.0 142.1 146.8 144.9 140.5 138.0 144.4 147.7 145.6 142.0 144.7 143.9 144.3 143.4 147.9 146.0 142.0 139.4 145.7 148.7 146.6 143.4 146.1 145.0 145.2 144.6 148.7 147.2 143.1 140.7 146.5 149.2 147.5 144.6 147.3 145.4 147.0 146.3 150.5 148.9 144.7 142.1 148.5 151.1 149.9 146.4 149.0 147.5 1 .2 4.0 4.1 3.8 4.0 4.1 4.5 3.9 3.6 3.8 4.0 4.2 3.4 138.9 139.8 140.3 142.0 134.4 136.7 135.4 132.3 139.2 139.4 138.9 137.7 139.5 140.7 141.9 136.2 133.7 131.8 140.8 141.4 142.3 143.7 135.9 137.8 136.8 133.7 140.6 141.1 140.0 139.6 141.1 142.3 143.0 138.3 134.3 132.8 142.1 142.6 143.8 145.1 137.0 138.0 137.5 134.4 141.5 141.9 140.9 140.7 141.8 144.3 144.8 138.9 135.6 133.9 143.3 143.8 145.0 146.4 137.8 139.6 137.9 134.9 141.8 142.2 141.3 142.0 143.3 146.5 146.4 139.6 136.7 145.0 145.3 146.9 147.8 139.1 141.1 138.5 134.9 143.2 143.4 143.0 143.8 145.2 147.4 147.9 142.1 137.8 136.7 146.5 146.9 148.5 149.6 140.3 142.5 140.0 136.2 144.9 145.0 144.7 145.5 146.8 149.4 149.7 143.5 138.5 139.5 147.9 148.3 150.0 151.2 141.6 143.5 141.3 137.4 146.4 146.7 145.9 146.4 148.2 149.6 151.3 144.8 139.7 140.2 148.9 149.4 150.9 152.3 142.2 144.8 142.3 138.6 147.1 147.4 146.6 147.4 149.0 151.6 153.2 145.2 142.2 141.6 150.5 151.3 152.5 154.3 144.3 146.1 143.7 139.8 148.7 149.2 148.1 148.4 150.7 151.6 154.9 146.9 143.8 143.3 Workers, by industry division: Goods-producing................................................................ Excluding sales occupations...................................... Excluding sales occupations...................................... Blue-collar occupations................................................. Construction..................................................................... Manufacturing.................................................................. White-collar occupations............................................... Excluding sales occupations...................................... Durables........................................................................... Nondurables.................................................................... Service-producing............................................................... Excluding sales occupations...................................... Excluding sales occupations...................................... Transportation................................................................ Public utilities.................................................................. Communications.......................................................... Wholesale and retail trade.............................................. Wholesale trade............................................................. Retail trade.................................................................... General merchandise stores....................................... Food stores.................................................................. 134.9 1 .2 1 .2 1 .2 1.1 1 .0 1.4 1.3 1.1 1 .2 1 .2 1.4 1.1 1.3 1.1 1.3 1.5 .9 1 .0 .9 1.1 1 .2 1 .0 .7 1.1 3.8 4.1 3.8 4.4 3.7 3.5 3.8 3.6 3.8 4.0 3.6 3.2 3.8 .0 2 .8 1.1 4.7 3.4 4.4 4.8 1 .2 1.1 1 .2 See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 91 Current Labor Statistics: Compensation & Industrial Relations 22. Continued—Employment Cost Index, wages and salaries, by occupation and industry group [June 1989 = 100] 1Í)99 2000 2001 S e rie s M ar. June S e p t. D ec . M ar. June S e p t. D ec . M a r. P e rc e n t c h a n g e 3 12 m o n th s m o n th s ended ended M a r. 2001 Finance, insurance, and real estate.................................. Excluding sales occupations......................................... 137.2 141.0 142.4 144.8 154.5 Banking, savings and loan, and other credit agencies. Insurance............................................................................. 137.4 Services................................................................................. 142.2 139.8 143.2 Business services............................................................... Health services................................................................... 145.4 138.7 146.3 139.6 Hospitals........................................................................... 137.6 138.3 144.2 Educational services.......................................................... Colleges and universities............................................... Nonmanufacturing......................... White-collar workers................... Excluding sales occupations.. 146.1 143.9 144.1 144.5 147.5 145.2 148.7 148.0 150.2 159.2 159.6 140.2 141.5 149.5 151.5 151.7 151.7 3.5 154.1 153.9 156.6 1.5 153.3 1 .6 4.3 162.0 163.3 165.0 165.7 169.4 2 .2 4.6 145.5 146.6 150.7 150.8 152.4 1.1 4.7 149.1 154.1 150.6 151.8 1.4 145.3 143.3 156.0 148.1 153.8 158.2 1.3 155.3 146.6 149.8 1 .1 4.3 4.1 4.4 144.9 146.8 148.5 1 .2 4.7 .7 4.4 .8 3.5 144.5 146.0 147.4 148.5 149.8 142.2 152.0 143.5 140.9 141.8 148.9 148.9 149.6 153.4 154.3 140.6 139.3 147.5 144.4 147.2 148.2 147.9 149.4 152.5 152.9 155.4 154.1 137.9 139.7 141.0 142.1 143.9 145.5 146.9 147.9 149.5 1 .1 3.9 140.1 142.0 143.5 144.7 146.5 148.2 149.6 150.6 152.3 1.1 4.0 141.6 145.9 147.4 137.4 149.1 150.7 151.9 140.9 153.9 1.3 4.4 140.3 143.4 142.8 1 .2 3.9 144.7 146.0 .9 3.6 Blue-collar occupations.............. Service occupations.................... 132.4 143.2 134.0 144.6 135.1 136.5 137.7 State and lo cal gove rn m e n t w o rk e rs.............. 139.0 139.6 White-collar workers........................................ . 138.9 139.3 142.1 Professional specialty and technical............ 138.9 140.1 139.4 142.5 142.7 144.3 141.7 137.9 135.8 139.5 140.9 138.9 142.4 142.2 143.5 144.3 144.7 147.2 148.3 150.2 .7 3.5 143.4 144.1 147.1 147.4 148.2 149.0 149.1 .7 144.3 144.5 144.7 148.0 143.6 .6 3.4 3.3 144.9 * 145.1 142.4 143.0 141.5 142.1 147.3 145.0 Workers, by occupational group: Executive, administrative, and managerial. Administrative support, including clerical.... Blue-collar workers........................................... Workers, by industry division: Services................................. Services excluding schools 4 ........ Health services........................... Hospitals................................... 137.4 140.5 137.5 136.9 137.6 139.6 139.4 140.7 143.9 148.8 150.1 .9 146.2 145.1 147.0 .5 3.6 3.2 146.0 .6 3.2 139.5 139.9 142.9 144.0 144.6 144.9 147.9 148.7 149.5 .5 3.4 139.0 139.7 139.6 140.4 142.1 144.3 145.3 144.8 146.7 147.9 149.1 .8 145.7 147.7 139.7 139.5 140.6 143.2 144.2 144.1 145.6 144.8 147.7 .2 144.7 148.9 149.5 149.7 .5 3.5 3.5 144.1 144.4 144.5 144.9 144.9 144.6 148.0 148.1 149.3 149.2 148.7 149.9 149.5 144.0 144.2 145.3 144.5 3.3 3.2 2.9 147.9 148.5 145.6 148.3 149.5 149.0 151.4 .3 1.3 3.1 4.5 142.8 142.8 142.9 Educational services.................. Schools..................................... 139.6 139.8 140.0 Elementary and secondary.. 139.5 139.9 143.1 143.1 Colleges and universities.... 139.6 139.8 142.6 .4 .5 Public administration^..................... 136.9 137.8 139.5 141.5 142.5 142.9 144.6 146.1 147.6 1 .0 3.6 Consistsi iof private industry workers (excluding farm and household workers) and This series has the same industry and occupational coverage as the Hourly State and local government (excluding Federal Government) workers. Earnings index, which was discontinued in January 1989. 2 Consists of legislative, judicial, administrative, and regulatory activities. 4 Includes, for example, library, social, and health services 23. Employment Cost Index, benefits, private industry workers by occupation and industry group [June 1989 = 100] 1 99 9 2000 2001 S e rie s M a r. June S e p t. D ec. M a r. June S e p t. D ec . M a r. P e rc e n t c h a n g e 3 12 m o n th s m o n th s ended ended M a r. 2 001 Private in d u s try w o rk e rs ................................... 145.8 147.3 148.6 150.2 153.8 155.7 147.9 142.2 149.4 143.6 151.0 144.8 152.5 146.2 156.3 150.0 144.3 146.1 145.2 147.9 146.3 149.4 148.2 150.7 152.3 154.0 154.2 155.7 156.0 Manufacturing......................................... 157.9 143.6 144.5 148.0 147.8 150.7 153.9 146.3 145.7 149.4 152.3 Nonmanufacturing......................................... 154.0 156.1 154.9 158.1 157.5 158.6 161.5 1 .8 158.5 160.4 165.2 155.7 5.7 153.1 161.5 154.1 2.3 151.6 1 .0 3.8 156.2 159.4 158.5 162.6 1.5 4 1 2 .0 154.8 157.1 1.5 5.6 3.2 159.7 162.9 2 .0 5.8 5.0 Workers, by occupational group: W hite-collar workers................................. Blue-collar workers............................. Workers, by industry division: Goods-producing................................... Service-producing....................................... 92 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 24. Employment Cost Index, private nonfarm workers by bargaining status, region, and area size [June 1989 = 100] 2001 2000 1 99 9 S e rie s M a r. June S e p t. D ec . M a r. June S e p t. D ec. M a r. P e rc e n t c h a n g e 3 12 m o n th s m o n th s ended ended M a r. 2001 COMPENSATION W orkers, by b argainin g s ta tu s 1 Union................................................................................................ 138.0 139.0 140.2 141.2 143.0 144.4 146.1 146.9 147.9 0.7 3.4 Goods-producing....................................................................... 136.8 138.2 139.2 143.3 142.5 144.8 146.8 147.3 147.9 .4 3.2 146.4 Service-producing...................................................................... 139.2 139.7 141.0 140.8 141.4 138.1 139.1 141.0 144.5 145.2 147.1 147.4 147.6 147.9 3.6 137.0 143.9 145.4 .8 Manufacturing............................................................................. .3 2.4 Nonmanufacturing..................................................................... 138.1 139.2 140.3 140.8 141.7 143.4 145.0 146.2 147.3 .8 4.0 Nonunion......................................................................................... 140.8 139.7 142.5 143.8 145.2 147.4 149.1 153.8 1.5 4.3 140.5 147.2 149.3 4.3 143.0 148.0 149.6 151.2 152.3 151.6 154.4 1.5 141.1 143.1 145.7 145.4 Service-producing...................................................................... 141.8 144.4 150.6 148.4 151.6 Goods-producing....................................................................... 1.4 4.3 Manufacturing............................................................................. 140.7 141.7 143.0 144.4 142.4 143.8 145.1 149.1 149.2 150.7 149.9 151.8 152.4 153.9 1.7 140.6 146.5 147.4 148.2 Nonmanufacturing..................................................................... 4.0 4.4 149.3 150.3 151.6 .9 3.6 147.6 152.2 148.6 153.3 151.1 154.8 1.7 4.2 148.9 147.6 146.7 150.7 1 .0 147.0 148.8 150.8 151.8 154.3 1 .6 4.0 5.0 146.9 146.0 148.6 150.1 1.4 148.8 151.0 150.3 153.1 147.7 152.1 1 .2 138.5 138.4 140.0 140.2 141.2 142.1 .6 3.6 141.3 142.4 .8 3.8 1.4 W orkers, by re g io n 1 Northeast........................................................................................ 140.5 141.5 143.2 144.3 South............................................................................................... 139.1 141.7 140.7 143.6 141.8 145.0 140.3 142.1 143.3 143.0 146.3 144.7 146.3 145.0 W orkers, by area size 1 Metropolitan areas................................................ ........................ 144.7 143.6 4.2 4.2 140.4 142.0 143.3 140.5 141.8 143.1 133.6 134.7 135.7 136.5 137.2 132.3 135.4 133.8 134.9 137.2 135.8 134.7 136.8 136.1 137.2 137.6 138.9 140.1 141.5 142.2 .5 3.3 135.8 137.5 138.8 136.4 139.7 141.4 142.6 143.9 .9 3.7 3.4 W AGES AND SALARIES W orkers, by bargainin g s ta tu s 1 Union................................................................................................ Goods-producing....................................................................... Service-producing...................................................................... Manufacturing............................................................................ 133.6 133.7 134.6 135.6 135.9 Nonunion......................................................................................... 139.0 140.7 142.0 Goods-producing...................................................................... Service-producing...................................................................... 137.8 139.3 139.4 140.0 142.6 138.6 138.8 141.3 140.5 140.5 143.3 141.1 143.9 141.7 141.8 142.9 143.0 Northeast....................................................................................... 137.1 138.2 139.9 South............................................................................................... 137.9 139.4 138.9 138.2 141.0 140.2 140.2 142.4 141.3 138.3 137.1 139.9 138.4 141.2 Manufacturing............................................................................ 137.8 139.2 140.4 141.1 .5 146.7 148.1 149.0 150.8 1 .2 145.8 148.7 146.8 149.6 148.8 151.4 1.4 147.2 148.0 148.0 148.9 150.1 150.7 1.4 3.9 4.1 3.8 3.9 145.0 144.7 147.3 146.1 146.6 1 .2 3.9 140.9 142.3 143.7 145.3 144.6 147.1 145.3 148.6 148.2 .9 1.4 3.5 3.7 142.6 143.0 145.3 144.7 146.0 146.3 147.3 141.5 143.6 149.6 149.2 151.3 .9 1.4 3.9 4.6 142.5 140.2 144.1 142.2 147.1 144.7 148.0 146.0 149.8 147.4 1 .2 1 .0 4.0 3.7 145.1 142.9 145.8 144.4 1 .2 W orkers, by re g io n 1 146.3 148.3 150.9 W orkers, by area size 1 Other areas.................................................................................... 1 139.8 145.7 143.7 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. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 93 Current Labor Statistics: Compensation & Industrial Relations 25. Percent of full-time employees participating in employer-provided benefit plans, and in selected features within plans, medium and large private establishments, selected years, 1980-97 Ite m 1980 Number of employees (in 000's): With medical care...................................................... With life insurance..................................................... With defined benefit plan.......................................... 1982 1984 1986 1988 1989 1991 1993 1997 1995 21,352 21,043 21,013 21,303 31,059 32,428 31,163 28,728 33,374 38,409 20,711 20,498 17,936 20,412 2 0 ,2 0 1 20,383 20,172 27,953 28,574 17,676 17,231 20,238 20,451 16,190 29,834 30,482 20,430 25,865 29,293 18,386 23,519 26,175 16,015 25,546 29,078 17,417 29,340 33,495 19,202 9 26 73 26 10 11 10 8 27 72 26 26 71 26 84 - - - 3.3 97 30 67 28 80 3.3 92 9 29 75 - 9 25 76 25 1 0 .2 80 3.3 89 9.1 81 3.7 89 9.2 26 83 3.0 91 9.4 22 21 21 22 20 31 33 31 3 .3 3 .5 19,567 Tim e-off plans Participants with: Paid lunch time............................................................ Average minutes per day......................................... Paid rest time.............................................................. Average minutes per day......................................... 10 - 99 9.8 1 0 .0 29 72 26 85 3.2 96 9.4 23 3.6 25 3.7 24 33 88 Average days per occurrence................................. Paid holidays............................................................... average uays per year............................................. 1 0 .1 1 0 .0 Paid personal leave.................................................... 20 24 99 99 3.8 Paid vacations............................................................. 3.2 99 68 9.3 100 99 99 100 98 97 96 97 96 95 62 67 67 70 69 33 16 68 67 37 26 65 60 53 58 56 Unpaid family le a ve ................................................... _ _ _ 97 97 97 58 62 46 62 - - 26 27 46 51 37 18 _ “ — 84 93 Insurance plans Participants in medical care plans............................... Percent of participants with coverage for: Home health care...................................................... Extended care facilities............................................. 95 90 92 83 82 77 76 66 76 79 28 75 80 28 81 80 30 86 82 42 78 73 56 85 78 63 61 $31.55 76 $107.42 67 $33.92 78 $118.33 69 $39.14 80 $130.07 8 70 18 36 $11.93 58 $35.93 43 $12.80 63 $41.40 44 $19.29 64 47 $25.31 $60.07 $72.10 51 $26.60 69 $96.97 96 96 96 92 94 94 91 87 87 72 74 72 78 6 76 5 77 7 74 8 71 7 71 10 Percent of participants with employee contribution required for: Average monthly contribution................................ average mommy comnuuiion................................ 96 Percent of participants with: Accidental death and dismemberment insurance.................................................................. 69 • Retiree protection available...................................... Participants in long-term disability 66 6 _ 64 64 59 49 42 44 41 37 33 40 43 47 48 42 45 40 41 42 43 54 51 51 49 46 43 45 44 53 55 Participants in sickness and accident Participants in short-term disability plans 1 ................. Retirement plans participants in detinea Denetit pension plans............ 84 84 82 76 63 63 59 56 52 50 Percent of participants with: Normal retirement prior to age 65........................... Early retirement available......................................... Ad hoc pension increase in last 5 years................ 55 98 - 58 97 - 64 98 35 59 98 26 62 97 52 95 52 96 4 52 95 22 55 98 7 Terminal earnings formula...................................... Benefit coordinated with Social Security................ 53 45 52 45 63 97 47 54 56 57 62 55 62 64 63 56 54 48 58 51 56 49 - - _ 60 45 48 48 49 55 57 - - - 33 36 41 44 43 54 55 - _ _ _ _ 38 5 32 7 Participants in defined contribution plans................... Participants in plans with tax-deferred savings arrangements............................................................. 6 61 10 Other benefits Employees eligible for: Reimbursement accounts 2........................................ Premium conversion plans......................................... The definitions for paid sick leave and short-term disability (previously sickness and accident insurance) were changed for the 1995 survey. Paid sick leave now includes only plans that specify either a maximum number of days per year or unlimited days. Short- terms disability now includes all insured, self-insured, and State-mandated plans available on a per-disability basis, as well as the unfunded per-disability plans previously reported as sick leave. Sickness and accident insurance, reported in years prior to this survey, included only insured, self-insured, and State-mandated plans providing per-disability bene- 94 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 2 5 g 10 12 5 12 23 36 52 _ _ _ _ _ Prior to 1995, reimbursement accounts included premium conversion plans, which specifically allow medical plan participants to pay required plan premiums with pretax 2 dollars. Also, reimbursement accounts that were part of flexible benefit plans were tabulated separately. Note: Dash indicates data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 26. Percent of full-tim e em p lo y e e s participating in e m p lo yer-p ro vid ed benefit plans, a n d in selec te d features within plans, small private establishments a n d State an d lo cal governm ents, 1 9 8 7 ,1 9 9 0 ,1 9 9 2 ,1 9 9 4 , a n d 1996 State and local governm ents Sm all private establishm ents Item 1992 1990 1994 1996 1987 1992 1990 1994 Scope of survey (in 000's)......................................... 32,466 34,360 35,910 39,816 10,321 12,972 12,466 12,907 Number of employees (in 000's): With medical care.................................................... With life insurance................................................... With defined benefit plan........................................ 22,402 20,778 6,493 24,396 21,990 7,559 23,536 21,955 5,480 25,599 24,635 5,883 9,599 8,773 9,599 12,064 11,415 11,675 11,219 11,095 10,845 11,192 11,194 11,708 8 9 37 49 26 50 3.0 82 - - 10 51 3.0 80 17 34 58 29 56 3.7 81 11 50 3.1 82 36 56 29 63 3.7 74 34 53 29 65 3.7 75 62 3.7 73 7.6 14 3.0 13.6 39 2.9 67 14.2 38 2.9 67 11.5 38 3.0 94 T im e -o ff p lan s Participants with: Paid lunch time......................................................... Average minutes per day....................................... Paid rest time........................................................... Average minutes per day....................................... Average days per occurrence................................ Paid holidays............................................................ Average days per year1......................................... Paid personal leave.................................................. Average days per year........................................... Paid vacations.......................................................... Unpaid leave............................................................. 37 48 27 47 2.9 84 11 12 7.5 13 2 .8 2 .6 2 .6 88 88 88 86 10.9 38 2.7 72 47 53 50 50 97 95 95 17 18 7 _ _ _ 57 30 51 33 59 44 47 48 9.5 8 9.2 Unpaid family leave.................................................. - 66 _ _ 93 In s u ra n c e p lan s 69 71 66 64 93 93 90 87 79 83 26 80 84 28 - - 76 78 36 82 79 36 87 84 47 84 81 55 Average monthly contribution.............................. Family coverage.................................................... 42 $25.13 67 47 $36.51 73 52 $40.97 76 52 $42.63 75 35 $15.74 71 38 $25.53 65 43 $28.97 72 47 $30.20 71 Average monthly contribution.............................. $109.34 $150.54 $159.63 $181.53 $71.89 $117.59 $139.23 $149.70 64 64 61 62 85 88 89 87 78 76 79 77 67 67 74 64 1 1 2 1 1 1 1 2 19 25 20 13 55 45 46 46 19 23 20 22 31 27 28 30 6 26 26 14 21 22 21 Participants in medical care plans............................. Percent of participants with coverage for: Home health care................................................... Extended care facilities.......................................... Percent of participants with employee contribution required for: Percent of participants with: Accidental death and dismemberment insurance............................................................... Survivor income benefits........................................ Retiree protection available..................................... Participants in long-term disability Participants in sickness and accident 29 Participants in short-term disability plans 2................ R e tire m e n t p lan s Participants in aetmea oenetit pension plans........... Percent of participants with: Normal retirement prior to age 65.......................... Early retirement available...................................... Terminal earnings formula.................................... Benefit coordinated with Social Security................ Participants in defined contribution plans.................. Participants in plans with tax-deferred savings arrangements.......................................................... 20 22 15 15 93 90 87 91 54 95 7 58 49 50 95 4 54 46 - 47 92 92 90 33 89 92 89 - 100 - 53 44 18 8 92 87 13 99 49 31 33 34 38 9 9 9 9 17 24 23 28 45 45 24 28 88 16 100 10 100 10 O th e r b e n e fits Employees eligible for: Reimbursement accounts 3...................................... Premium conversion plans .................................... 1 2 3 8 14 19 _ _ _ 4 12 7 5 5 5 5 5 31 50 64 _ _ _ _ ' Methods used to calculate the average number of paid holidays were revised in 1994 to count partial days more precisely. Average holidays for 1994 are not comparable with those reported in 1990 and 1992. sick leave. Sickness and accident insurance, reported in years prior to this survey, included only insured, self-insured, and State-mandated plans The definitions for paid sick leave and short-term disability (previously sickness and accident insurance) were changed for the 1996 survey. Paid sick leave now includes only plans that specify either a maximum number of days per year or unlimited days. Short-term disability now includes all insured, selfinsured, and State-mandated plans available on a per-disability basis, as well as the unfunded per-disability plans previously reported as 3 2 providing per-disability benefits at less than full pay. Prior to 1996, reimbursement accounts included premium conversion plans, which specifically allow medical plan participants to pay required plan premiums with pretax dollars. Also, reimbursement accounts that were part of flexible benefit plans were tabulated separately. Note: Dash indicates data not available. Monthly Labor Review July 2001 95 Current Labor Statistics: 27. Compensation & Industrial Relations W ork s to p p a g e s invo lvin g 1,000 w orkers or m o re A n n u al to tals 1999 1999 Dec. M e as u re 2000 2 000 J an .p Feb.p M a r.p A p r.p M ayp Junep Ju lyp A u g .p S e p t.p O c t.p N o v.p D ec.p Number of stoppages: Beginning in period.............................. 17 39 0 0 1 2 6 2 5 3 6 5 7 0 2 In effect during period......................... 21 40 1 1 2 4 7 4 8 6 8 10 12 3 3 Workers involved: Beginning in period (in thousands).... 73 394 .0 .0 17.0 5.7 26.7 136.9 11.4 7.2 99.2 17.8 60.3 .0 8.7 In effect during period (in thousands). 80 397 3.0 3.0 2 0 .0 25.7 29.7 141.3 150.8 146.9 237.2 167.8 2 1 1 .6 4.5 10.3 1,995 20,419 63.0 60.0 298.0 327.6 272.2 3,095.3 3,134.0 2,804.4 4,186.6 3,029.3 3,088.6 64.5 58.9 .06 Ô (2) .01 .1 0 .1 0 .1 0 .13 (2) Ô Days idle: Number (in thousands)....................... Percent of estimated working time1.... .01 .0 1 .0 1 .1 1 .1 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 worked Is found in " 'Total economy' measures of strike Idleness," Monthly Labor Review, October 1968, pp. 54-56. 1 2 Less than 0.005. p = preliminary. 96 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 28. 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] Series Annual average 1999 2000 2001 May June July Aug. 2001 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May C O NSUM ER PRICE INDEX FO R A LL URBAN CO NSUM ERS 166.6 499.0 164.6 164.1 164.2 185.0 147.9 172.2 515.8 168.4 167.8 167.9 188.3 154.5 171.5 513.6 167.8 167.3 167.5 188.6 153.9 172.4 516.5 167.9 167.3 167.3 187.7 154.9 517.5 168.7 168.1 168.3 189.6 155.8 517.6 169.2 168.7 168.9 189.9 156.8 520.3 169.4 168.9 169.0 188.6 156.9 521.2 169.6 169.1 169.1 190.1 156.8 521.5 169.5 168.9 168.8 189.0 155.5 521.1 170.5 170.0 170.2 190.7 156.6 524.5 171.4 170.9 171.3 191.1 158.0 526.7 171.8 171.3 171.8 191.9 159.5 528.0 172.2 171.7 172.0 191.9 160.1 529.9 172.4 171.9 172.2 192.5 160.7 532.2 172.9 172.5 172.8 193.2 159.6 203.1 160.7 204.6 159.6 204.3 159.5 199.9 160.5 201.0 161.0 202.5 161.6 204.6 161.9 206.2 161.4 207.3 161.5 215.1 163.6 212.6 163.6 211.5 163.2 211.5 163.4 213.3 164.7 213.1 134.3 153.5 152.3 148.3 168.9 137.8 155.6 154.0 147.4 172.2 137.3 155.4 153.7 147.0 172.1 137.5 156.2 154.0 146.6 173.4 138.5 156.6 154.1 148.1 173.5 138.2 156.9 154.6 148.9 173.7 138.0 156.7 154.6 148.7 173.4 137.4 155.8 153.9 149.7 172.0 137.9 156.0 153.0 146.5 173.3 136.7 156.3 153.5 150.2 172.7 139.4 157.8 155.7 153.0 173.8 139.9 157.9 155.8 152.6 174.0 139.5 158.6 155.7 153.1 175.1 138.9 157.6 154.0 151.5 138.1 159.6 155.8 154.7 176.4 104.9 165.1 105.2 169.7 163.9 187.3 107.5 169.0 109.0 174.7 169.6 193.4 106.4 168.3 108.1 173.8 168.1 192.4 108.4 168.6 108.1 174.4 169.6 193.3 108.8 169.1 108.7 175.2 170.6 194.1 109.5 169.5 109.3 175.6 170.9 194.7 107.7 170.0 110.0 175.5 171.4 194.6 185.3 106.8 170.3 110.5 175.9 171.7 195.2 186.1 110.0 170.4 111.0 176.4 171.6 195.2 186.8 108.9 170.8 111.1 176.5 171.9 195.1 187.6 109.0 171.4 111.3 177.2 174.1 196.4 108.7 171.8 111.4 177.7 174.7 197.6 188 0 108.4 172.3 111.6 177 8 175.4 198.9 180 C 108.5 172.7 111.8 108.8 173.1 112.4 175.4 199.2 100 ° 175.9 199.6 112.3 192.9 117.5 198.7 117.5 197.6 198.2 198.6 199.2 199.9 200.5 201.2 201.8 202.4 105.4 203.6 204.2 204.9 101.3 128.8 113.5 91.4 120.9 126.7 131.3 131.1 123.3 103.7 137.9 122.8 129.7 128.0 128.2 129.6 129.7 121.5 103.8 132.4 116.8 121.6 122.0 128.1 132.2 132.6 124.4 103.9 138.9 124.0 120.9 130.2 128.1 128.3 129.4 119.2 104.2 141.3 126.5 120.8 133.0 128.6 124.5 126.4 104.0 140.9 125.9 120.8 132.4 128.6 125.3 126.8 104.2 143.8 129.1 133.7 134.8 129.0 130.4 129.1 104.2 143.1 128.3 137.6 133.6 128.7 132.8 130.4 104.5 142.7 127.7 140.3 132.7 128.9 131.8 131.3 104.7 145.3 130.6 144.9 135.6 128.6 127.8 128.0 105.0 153.8 139.8 149.1 145.7 128.8 125.4 125.5 105.1 152.3 138.0 144.6 144.0 129.1 128.4 126.6 105.4 150.8 136.3 138.1 142.6 129.1 132.2 127.5 105.5 149.7 135.1 134.4 141.6 129.1 131.9 128.2 106.8 151.3 136.8 131.9 143.8 128.9 129.8 129.1 129.0 125.7 144.4 140.5 100.1 142.9 152.0 100.7 100.1 100.5 171.9 197.7 250.6 230.7 255.1 229.2 299.5 102.1 100.7 101.2 130.6 123.8 153.3 131.7 126.1 153.1 130.5 123.9 155.7 128.1 120.3 155.0 126.7 120.7 153.2 127.4 124.9 154.7 130.8 125.3 154.4 130.7 125.4 155.2 128.2 123.8 154.4 127.4 121.4 154.4 129.3 122.6 154.9 1316.0 125.2 153.9 131.4 124.9 156.1 130.6 124.4 159.2 100.8 101.0 100.8 100.6 100.4 100.4 100.8 101.5 102.1 102.3 102.2 101.9 101.8 101.4 155.8 129.3 128.6 101.5 177.3 209.6 260.8 238.1 266.0 137.7 317.3 103.3 101.0 102.5 155.4 128.3 127.6 101.1 176.3 210.4 259.4 237.5 264.4 237.1 313.5 103.1 101.3 101.8 155.7 139.0 138.3 101.2 176.8 212.6 260.5 238.2 265.6 237.9 315.6 103.4 101.5 101.5 155.3 136.1 135.4 101.5 177.2 213.7 261.4 238.6 266.7 238.3 318.1 103.7 101.3 102.0 155.2 128.4 127.7 101.5 178.2 215.7 262.6 239.2 268.0 238.9 321.3 103.9 101.6 102.8 156.2 135.2 134.3 101.7 178.7 213.0 263.1 239.4 268.7 239.3 322.5 103.8 101.5 102.9 157.9 133.1 132.3 101.7 179.4 208.0 263.7 239.6 269.4 239.7 323.6 103.8 101.0 103.6 159.3 133.0 132.2 102.5 179.9 209.1 264.1 240.0 269.8 239.8 324.7 103.7 100.9 103.2 160.2 127.8 127.0 103.1 179.9 209.5 264.8 241.1 270.4 240.3 325.3 103.7 100.7 103.6 160.4 126.6 125.8 103.6 180.6 210.2 267.1 242.3 273.0 242.6 328.5 104.1 101.2 103.9 160.4 127.5 126.8 104.0 181.5 212.1 268.9 243.8 274.9 244.1 331.0 104.3 101.6 104.0 159.9 124.1 123.3 104.7 181.7 210.0 270.0 244.9 275.9 244.8 332.8 104.3 101.6 104.3 159.7 133.6 132.8 104.2 181.9 208.3 270.8 245.7 276.8 245.6 333.6 105.0 101.7 104.1 159.1 146.8 146.0 104.4 182.5 209.3 271.4 246.6 277.3 245.8 335.1 105.0 101.6 104.0 107.0 261.7 308.4 96.0 112.5 279.9 324.0 93.6 110.9 276.8 319.2 93.7 111.5 277.5 320.9 92.6 111.8 278.1 321.7 93.3 113.0 280.2 325.4 93.7 114.9 284.8 330.8 92.1 115.3 285.2 332.1 93.1 115.4 284.8 332.5 92.3 115.5 285.4 332.7 93.0 115.8 289.2 333.3 93.3 116.0 290.4 333.7 93.2 116.1 290.8 334.0 93.7 116.1 290.8 334.1 93.3 116.4 590.7 335.0 92.9 95.5 100.1 92.8 98.5 93.0 98.5 91.8 97.2 92.5 98.2 93.0 98.9 91.3 97.0 92.3 98.3 91.5 97.5 92.2 98.4 92.4 98.8 92.2 98.7 92.7 99.4 92.3 99.0 91.8 98.7 other than telephone services1,4............ Personal computers and peripheral 30.5 25.9 26.6 26.0 25.7 25.2 25.0 24.7 24.2 23.8 23.2 22.9 22.5 22.1 21.7 equipment1,2.................................. Other goods and services............................... Tobacco and smoking products..................... 53.5 258.3 355.8 41.1 271.1 394.9 42.4 270.2 393.5 41.2 269.6 388.5 40.3 272.2 400.7 39.5 271.6 394.1 38.9 274.7 408.0 38.3 273.0 396.7 37.3 276.2 411.0 36.5 274.0 396.6 35.0 275.9 404.3 33.9 277.2 408.5 32.4 277.7 407.7 31.7 277.7 424.2 30.4 281.3 418.7 Personal care1............................................ Personal care products1............................. Personal care services1............................. 161.1 151.8 171.4 165.6 153.7 178.1 165.1 153.0 177.3 165.4 153.6 177.9 165.7 153.7 178.2 166.2 154.3 179.3 166.6 154.3 179.9 167.0 153.4 180.3 167.4 153.9 180.6 167.8 155.5 181.3 168.2 155.3 181.6 168.6 155.3 181.9 169.1 155.7 182.2 169.6 155.8 183.4 169.5 153.2 184.1 All items (1967 = 100)..................................... Food and beverages..................................... Fruits and vegetables................................ Nonalcoholic beverages and beverage materials............................................... Other foods at home................................. Fats and oils........................................... Other miscellaneous foods’ ’2................. Food away from home1................................ Other food away from home1'2................... Housing........................................................ Shelter...................................................... Owners' equivalent rent of primary residence3 Tenants' and household insurance1,2........... Fuels and utilities...................................... Fuels..................................................... Fuel oil and other fuels........................... Gas (piped) and electricity....................... Household furnishings and operations.......... Apparel....................................................... Men's and boys’ apparel............................ Infants1and toddlers' apparel’ ..................... Footwear................................................. Transportation............................................... 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..................... . Recreation2................................................. Video and audio1,2..................................... Education and communication2....................... Education2................................................ Educational books and supplies................. Tuition, other school fees, and child care..... Communication1,2...................................... Information and information processing1,2... Telephone services1,2............................ Information and information processing _ See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 97 Current Labor Statistics: Price Data 28. 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] 2000 Annual average 1999 2000 May June July Aug. 2001 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 243.0 252.3 251.7 252.0 252.9 253.6 254.0 255.1 255.7 255.7 257.3 258.6 259.5 260.2 261.0 144.4 164.6 132.5 137.5 131.3 149.2 168.4 137.7 147.4 129.6 149.2 167.8 138.0 147.6 132.2 149.7 167.9 138.6 149.1 128.3 149.3 169.4 137.7 147.5 124.5 148.6 169.2 136.4 145.6 125.3 150.3 169.4 138.8 149.9 130.4 150.4 169.6 138.9 149.9 132.8 150.6 169.5 139.3 150.2 131.8 150.0 170.5 137.8 147.2 127.8 150.0 171.4 137.4 146.4 125.4 150.6 171.8 138.1 147.7 128.4 150.7 172.2 138.0 147.9 132.2 151.9 172.4 139.7 151.0 131.9 152.9 172.9 140.8 153.5 129.8 146.0 126.0 188.8 162.5 125.4 161.5 125.8 165.8 125.4 165.4 125.2 163.2 125.9 197.6 198.0 200.2 161.9 125.5 201.8 172.0 124.9 196.3 163.7 125.9 201.0 167.0 125.4 195.3 164.7 125.0 197.6 163.1 125.9 193.8 165.9 124.8 197.2 165.7 125.5 195.3 162.0 124.7 197.0 201.9 202.5 Rent of shelter3........................................... Transporatation services.............................. Other services............................................ Special indexes: 195.0 190.7 223.1 201.3 196.1 229.9 200.3 195.7 228.4 201.2 196.1 228.7 202.1 196.5 229.9 202.7 197.4 231.3 202.6 197.2 231.5 203.3 197.0 232.6 203.2 198.0 232.4 203.1 198.3 233.0 204.5 199.1 234.1 205.7 200.3 234.8 207.2 200.2 235.4 207.4 200.1 236.2 207.8 200.4 236.4 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............................................... 167.0 160.2 162.0 134.0 139.4 147.5 151.2 173.0 165.7 167.3 139.2 149.1 162.9 158.2 172.2 165.1 166.6 139.4 149.3 161.9 158.0 173.3 166.0 167.6 140.1 150.7 166.0 158.8 173.6 166.2 167.9 139.2 149.3 165.7 158.4 173.5 166.0 167.9 138.0 147.5 162.6 157.6 174.6 167.4 168.8 140.3 151.5 166.2 160.0 174.9 167.5 169.1 140.4 151.6 165.1 160.1 175.0 167.7 169.2 140.8 151.8 166.0 160.2 174.7 167.5 169.0 139.3 149.0 163.6 159.1 175.9 168.6 170.1 139.0 148.3 163.9 159.1 176.6 169.1 170.8 139.7 149.6 164.3 160..0 177.1 169.2 171.2 139.6 149.8 162.7 160.3 177.8 170.1 171.8 141.2 152.8 167.4 162.0 178.6 170.9 172.6 142.4 155.1 172.0 163.6 Services less rent of shelter3........................ 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................................ 195.8 182.7 106.6 174.4 177.0 144.1 100.0 195.7 202.9 188.9 124.6 178.6 181.3 144.9 129.5 202.1 200.9 187.4 121.0 178.2 180.9 145.5 127.9 201.2 202.9 188.9 129.6 178.3 181.0 144.5 137.6 201.9 204.2 189.9 129.7 178.7 181.3 143.8 135.0 202.7 205.0 190.5 125.9 179.1 181.7 143.7 127.9 203.5 205.7 190.7 130.6 179.6 182.3 145.1 135.2 203.5 205.8 191.1 129.3 180.1 182.8 145.6 133.6 204.1 205.9 191.1 129.0 180.3 183.0 146.0 133.8 204.2 206.9 191.5 128.1 180.2 182.8 145.1 129.3 204.4 210.0 193.6 132.5 181.0 183.5 144.8 128.6 205.7 210.5 194.3 132.0 181.8 184.4 145.9 129.1 206.8 210.6 195.1 129.5 182.6 185.3 146.2 125.4 207.7 210.6 195.2 133.1 182.9 185.6 146.6 133.8 208.0 211.4 195.7 140.1 182.9 185.5 145.7 145.6 208.4 163.2 486.2 163.8 163.4 163.0 184.7 147.6 168.9 503.1 167.7 167.2 166.8 188.0 154.1 168.2 501.1 167.2 166.7 166.4 188.4 153.5 169.2 504.1 167.3 166.8 166.3 187.3 154.6 169.4 504.7 168.0 167.6 167.3 189.2 155.4 169.3 504.2 168.6 189.9 156.8 161.0 202.5 170.4 507.6 168.8 168.3 168.1 188.4 156.6 170.6 508.2 169.0 168.5 168.1 189.9 156.4 170.9 509.0 168.8 168.3 167.8 188.6 155.3 170.7 508.5 169.8 169.3 169.1 190.4 156.3 171.7 511.6 170.8 170.3 170.3 190.9 157.9 172.4 513.4 171.2 170.8 170.8 191.7 159.2 172.6 514.2 171.6 171.1 171.1 191.7 160.0 173.5 516.7 171.9 171.4 171.3 192.2 160.7 174.4 519.4 172.3 171.9 171.8 192.9 160.6 159.4 201.8 160.5 203.4 159.3 203.1 159.4 198.9 160.5 200.0 138.2 201.5 161.6 203.6 161.9 204.7 161.4 205.8 161.5 213.3 163.8 210.9 163.5 210.1 163.1 209.8 163.5 211.7 164.7 211.5 133.2 152.8 152.2 147.9 168.8 136.9 155.1 153.9 147.2 172.3 136.4 154.9 153.6 146.9 172.2 136.7 155.6 153.9 146.4 173.4 137.5 156.0 154.2 147.9 173.5 137.4 156.2 154.4 148.6 173.6 137.1 156.1 154.4 148.5 173.5 136.6 155.3 153.8 149.4 172.0 137.1 155.4 152.7 146.3 173.4 135.8 155.8 153.3 149.9 173.0 138.7 157.3 155.4 152.8 174.0 139.3 157.3 155.6 152.4 174.1 138.8 158.2 155.6 153.0 175.4 138.2 157.1 153.7 151.4 174.6 137.2 159.1 155.8 154.3 156.5 Other miscellaneous foods1,2................. Food away from home1................................. Other food away from home1,2................... 104.6 165.0 107.1 169.0 106.1 168.3 109.6 170.5 108.4 172.7 110.9 174.8 111.2 175.6 108.5 171.4 111.5 176.5 108.5 172.3 110.4 174.4 160.0 181.6 177.1 122.2 175.7 165.5 187.2 182.7 120.9 180.4 166.6 188.4 184.1 122.5 181.3 167.3 188.7 184.8 118.3 181.9 167.5 189.3 167.6 189.5 111.8 177.2 171.0 192.6 112.0 177.6 171.0 192.9 185.6 118.6 182.4 186.2 113.9 183.0 187.7 113.8 184.1 111.6 177.0 170.5 191.5 188.3 118.5 184.5 108.7 173.1 112.5 178.0 Housing........................................................ Shelter........................................................ 108.6 170.8 111.4 175.8 168.1 189.6 187.0 108.7 183.5 108.5 171.8 108.5 172.9 163.9 186.5 182.2 117.8 179.9 109.0 169.5 109.6 174.7 106.3 170.3 109.2 173.8 165.4 187.4 183.4 117.3 180.8 108.4 169.1 108.8 174.4 166.4 187.9 183.4 123.1 180.8 107.5 170.0 105.1 168.8 108.0 168.6 108.4 173.6 189.0 123.8 185.2 189.6 121.2 185.7 101.6 128.7 113.0 91.7 120.4 124.7 130.1 131.2 121.3 103.9 137.4 121.8 128.8 127.5 125.5 128.3 129.7 119.3 104.0 131.9 116.0 120.9 121.6 125.5 130.9 132.7 122.1 104.1 138.7 123.3 120.2 129.9 125.3 127.3 129.5 117.4 104.4 141.0 125.7 120.1 132.5 125.7 123.6 126.6 112.2 132.3 124.2 152.8 150.1 133.4 126.6 152.5 149.7 132.0 124.6 155.5 152.8 129.8 120.9 154.4 151.6 104.4 143.4 128.2 133.1 134.4 126.1 128.7 128.8 121.5 129.0 124.8 154.2 151.4 104.4 142.5 127.2 136.7 133.0 125.8 131.3 130.3 125.5 132.6 125.5 154.0 151.3 104.7 142.0 126.5 139.3 132.1 126.0 130.5 131.3 122.6 132.7 125.7 154.9 152.2 104.9 144.6 129.3 144.1 134.8 125.6 126.6 128.0 117.5 130.0 124.0 153.9 151.2 105.2 153.2 138.6 150.1 144.8 125.7 124.1 125.8 113.2 129.0 121.5 154.0 151.2 105.3 151.5 136.6 145.0 143/0 125.9 127.0 126.9 118.4 131.0 122.4 154.5 151.7 105.6 149.9 134.8 138.0 141.5 125.9 130.6 127.6 125.2 133.3 125.2 153.3 150.5 105.8 148.8 133.6 133.9 140.4 126.0 130.5 128.3 124.7 130.3 126.2 143.4 140.7 104.2 140.4 125.0 120.1 131.8 125.7 124.0 126.8 113.2 128.4 121.5 152.3 149.3 133.2 125.2 155.8 153.2 106.9 150.8 135.7 131.5 142.9 125.7 128.5 129.2 120.2 132.0 124.5 159.2 156.6 100.4 101.4 101.5 101.4 101.1 100.9 101.0 101.4 102.2 102.8 102.9 102.8 102.5 102.4 102.0 Miscellaneous personal services................. Commodity and service group: Commodities................................................. Food and beverages..................................... Commodities less food and beverages............ Nondurables less food and beverages.......... Apparel.................................................. Nondurables less food, beverages, and apparel............................................ Durables................................................... Services........................................................ C O N S U M E R P R IC E IN D E X FO R URBAN W A G E E A R N E R S A N D C L E R IC A L W O R K ER S All items (1967 - 100)...................................... Food and beverages....................................... Cereals and bakery products....................... Meats, poultry, fish, and eggs...................... Dairy and related products1......................... Fruits and vegetables................................. Nonalcoholic beverages and beverage materials................................................ Sugar and sweets.................................... Fats and oils............................................ Other foods............................................. Owners' equivalent rent of primary residence3 Tenants' and household insurance1,2........... Fuels...................................................... Fuel oil and other fuels........................... Household furnishings and operations.......... Apparel........................................................ Men's and boys' apparel............................. New and used motor vehicles2.................... See footnotes at end of table. 98 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 170.2 190.6 171.7 193.5 190.4 119.9 186.3 28. 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 ave ra g e 2000 S eries 1999 2000 M ay June July Aug. 2001 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. M ay New vehicles................................................... 144.0 143.9 144.5 144.1 143.7 143.1 142.5 142.7 143.7 144.6 144.8 144.5 143.8 143.8 143.4 Used cars and trucks 1 .................................... 153.3 157.1 156.8 157.1 156.6 156.5 157.5 159.3 160.7 161.6 161.7 161.7 161.1 160.9 160.2 Motor fuel.......................................................... 1 0 0 .8 129.5 128.5 140.1 136.2 128.0 135.3 133.1 133.2 127.7 126.9 127.8 124.1 134.0 147.4 Gasoline (all types)........................................ 1 0 0 .2 128.8 127.9 139.4 135.5 127.3 134.6 132.3 132.4 126.9 126.2 127.1 123.4 133.3 146.7 Motor vehicle parts and equipment................. 1 0 0 .0 100.9 100.5 100.5 1 0 0 .8 100.7 100.9 1 0 1 .0 1 0 1 .8 102.3 103.0 103.4 104.0 103.5 103.6 Motor vehicle maintenance and repair............ 173.3 178.8 177.8 178.3 178.7 179.6 180.2 180.9 181.4 181.5 182.1 183.1 183.3 183.4 184.1 Public transportation........................................... 193.1 203.4 203.9 205.5 206.9 208.7 206.4 202.4 203.2 203.7 204.3 205.8 204.2 202.7 203.5 Medical care........................................................... 249.7 259.9 258.5 259.7 260.6 261.7 262.2 262.8 263.1 263.8 266.3 268.1 269.1 269.9 270.4 Medical care commodities................................. 226.8 233.6 232.9 233.7 234.2 234.6 235.0 235.2 235.5 236.5 237.8 239.1 240.2 241.0 241.7 Medical care services......................................... 254.9 265.9 264.4 265.6 266.6 267.9 268.5 269.2 269.4 270.1 272.8 274.7 275.7 276.5 277.0 Professional services....................................... 230.8 239.6 239.0 239.9 240.3 240.9 241.3 241.8 241.7 242.3 244.9 246.4 247.0 247.8 248.0 Hospital and related services........................... 295.5 313.2 309.5 311.7 314.2 317.1 318.2 319.2 320.3 320.9 323.9 326.6 328.3 329.1 330.6 Recreation2 ............................................................ 101.3 102.4 102.3 102.5 102.7 102.9 1 0 2 .8 1 0 2 .8 102.7 1 0 2 .6 103.0 103.1 103.0 103.7 103.7 Video and audio 1,2 ............................................. 100.5 100.7 1 0 1 .0 1 0 1 .2 100.9 101.3 1 0 1 .1 100.7 1 0 0 .6 100.3 1 0 0 .8 1 0 1 .2 1 0 1 .0 1 0 1 .2 1 0 1 .1 Education and communication2 ........................... 101.5 102.7 1 0 2 .1 101.7 1 0 2 .2 103.0 102.9 103.7 103.2 103.7 104.0 104.1 104.4 104.2 104.1 Education2 .......................................................... Educational books and supplies..................... 107.2 264.1 1 1 2 .8 1 1 1 .8 1 1 2 .1 283.3 111.3 280.0 280.9 281.5 113.2 283.6 115.1 288.6 115.4 289.0 115.6 288.6 115.7 289.2 116.0 292.9 116.2 294.1 116.3 294.7 116.4 294.7 294.5 Tuition, other school fees, and child care...... 302.8 318.2 316.2 326.5 94.1 327.0 94.4 328.2 329.1 94.2 326.3 93.3 327.9 94.3 324.7 93.1 327.4 93.6 319.2 94.8 325.7 94.6 313.8 94.7 315.4 96.9 94.4 94.8 94.4 94.0 Information and information processing 1,2 .... 96.5 94.1 94.3 93.0 93.9 94.4 92.6 93.8 92.8 93.6 93.8 93.7 94.1 93.8 93.4 Telephone services1,2 ................................. Information and information processing 1 0 0 .2 98.7 98.7 97.4 98.4 99.1 97.1 98.6 97.6 98.6 99.0 98.9 99.5 99.2 98.8 31.6 26.8 27.5 27.0 26.6 26.1 25.9 25.5 25.1 24.6 24.0 23.8 23.3 2 2 .8 22.4 other than telephone services1,4 ............... Personal computers and peripheral 116.7 equipment1,2 ......................................... Other goods and services...................................... 53.1 40.5 41.8 40.7 39.8 39.1 38.5 37.8 36.7 35.9 34.3 33.4 31.8 31.1 29.9 261.9 276.5 275.4 274.5 277.9 276.8 280.9 278.2 282.3 279.2 281.5 283.2 283.5 288.2 286.8 Tobacco and smoking products......................... 356.2 395.2 393.7 388.7 400.9 394.2 408.2 397.0 411.3 396.9 404.6 409.2 408.5 424.8 419.8 Personal care 1 .................................................... 161.3 165.5 164.9 165.3 165.5 166.1 166.5 166.8 167.1 167.7 168.1 168.5 169.0 169.4 169.3 Personal care products1................................... 152.5 154.2 153.4 154.0 154.1 155.0 155.1 153.9 154.2 155.8 155.7 155.7 155.9 156.0 153.8 171.7 178.6 177.7 178.3 178.6 179.7 180.3 180.8 181.1 181.7 182.1 182.4 182.8 183.9 184.7 Miscellaneous personal services..................... Commodity and service group: 243.1 251.9 251.2 251.4 252.2 253.0 253.4 254.5 255.1 255.3 257.0 258.4 258,3 260.0 260.7 Commodities......................................................... 144.7 149.8 149.9 150.6 150.1 149.3 151.0 151.0 151.4 150.6 150.8 151.4 151.4 152.8 153.9 Food and beverages.......................................... 163.8 167.7 167.2 167.3 168.0 168.6 168.8 169.0 168.8 169.8 170.8 171.6 171.9 Commodities less food and beverages............. 133.2 140.3 139.2 137.7 140.2 140.2 140.8 139.1 138.8 139.3 141.2 138.1 139.3 149.4 172.3 142.6 Nondurables less food and beverages............ 139.0 149.1 171.2 139.5 151.5 149.7 147.2 151.6 152.1 148.6 148.1 149.4 149.3 153.1 156.2 Apparel........................................................... Nonduraoies less tood, beverages, 130.1 128.3 130.9 127.3 123.6 124.0 151.8 128.7 131.3 130.5 126.6 124.1 127.0 130.6 130.5 128.5 and apparel................................................... 147.2 165.3 164.4 169.6 168.7 164.6 169.3 167.6 168.8 165.5 166.0 166.5 164.4 170.5 176.3 Durables............................................................ 126.0 125.8 126.2 125.9 125.6 125.2 125.3 125.6 126.2 126.6 126.6 126.6 126.2 126.0 125.5 Services.................................................................. 185.3 191.6 189.8 191.2 .192.2 193.0 193.4 193.9 194.0 194.5 196.6 197.2 197.8 198.0 198.7 Rent of shelter3 .................................................. Transporatation services................................... 174.9 187.9 180.5 192.9 179.6 192.4 180.3 192.6 181.0 193.0 181.5 193.8 181.7 193.7 182.3 193.9 182.5 195.0 182.6 195.2 183.6 196.0 184.4 197.2 185.5 197.2 185.8 197.2 186.3 197.6 Other services.................................................... 219.6 225.9 224.6 224.7 225.9 227.3 227.3 228.4 228.1 228.9 229.9 230.6 231.2 231.9 232.2 174.7 Special indexes: All items less food............................................... 163.1 169.1 168.3 169.5 169.6 169.4 170.7 170.9 171.3 170.9 171.9 172.5 172.8 173.8 All items less shelter.......................................... 158.1 163.8 163.1 164.3 164.3 163.9 165.4 165.5 165.7 165.5 166.5 167.0 167.0 168.0 169.1 All items less medical care................................ 159.2 164.7 164.0 165.0 165.1 165.0 166.2 166.4 166.6 166.4 167.4 168.0 168.2 169.1 170.0 Commodities less food...................................... 134.6 140.4 140.7 141.7 141.6 141.6 142.2 140.6 140.3 141.0 140.8 142.7 144.1 140.0 150.7 150.9 152.9 140.6 151.2 139.1 Nondurables less food....................................... 148.9 153.3 153.1 153.6 150.3 149.9 151.1 151.1 154.7 157.6 Nondurables less food and apparel.................. 148.4 165.4 164.5 169.4 168.7 164.9 169.2 167.7 168.8 165.8 166.3 166.8 164.9 170.5 175.9 Nondurables....................................................... 151.3 158.9 158.8 159.9 159.4 158.3 160.8 160.8 161.0 159.7 159.9 160.8 160.9 163.0 164.8 Services less rent of shelter3 ............................. Services less medical care services................. Energy................................................................. 174.1 180.1 178.2 180.2 181.3 181.9 182.5 182.7 182.8 183.7 186.6 186.9 187.0 187.0 187.8 179.5 106.1 185.4 124.8 183.7 121.5 185.1 130.9 186.0 130.1 186.6 125.7 187.2 130.9 187.6 129.3 187.7 129.0 188.3 127.6 190.3 131.8 190.8 131.3 191.4 128.6 191.6 132.9 192.3 140.6 All items less energy.......................................... 171.1 175.1 174.6 174.6 174.9 175.3 176.0 176.5 176.8 176.8 177.4 178.2 178.8 179.2 179.2 All items less food and energy........................ 173.1 177.1 176.7 176.6 176.8 177.2 178.0 178.6 179.0 178.7 179.3 180.1 180.9 181.3 181.2 Commodities less food and energy.............. 144.3 145.4 146.0 145.0 144.5 144.2 145.7 146.1 146.7 145.8 145.5 146.2 146.8 147.3 146.4 Energy commodities.................................... 100.3 129.7 128.3 139.1 135.4 127.7 135.4 133.5 133.8 128.9 128.5 129.1 125.1 134.2 146.6 Services less energy..................................... 192.6 198.7 197.5 198.0 198.8 199.5 2 0 0 .0 2 0 0 .6 2 0 0 .8 2 0 1 .1 2 0 2 .2 203.1 204.0 204.4 204.8 July 2001 99 Not seasonally adjusted. Indexes on a December 1997 = 100 base. 4 2 3 Indexes on a December 1982 = 100 base. N °TE: Index applied to a month as a whole, not to any specific date. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Indexes on a December 1988 » 100 base. Monthly Labor Review Current Labor Statistics: Price Data 29. Consumer Price Index: U.S. city average and available local area data: all items [1982-84 = 100, unless otherwise indicated] P ric in g sched- A re a u le 1 U.S. city average................................................................. M A ll U rb an C o n s u m e rs A p r. M ay 171.3 U rb a n W a a e E a rn e rs 2001 2000 M a r. F eb . 171.5 175.8 2000 A p r. 176.2 M ay 176.9 A p r. 177.7 2001 M ay 168.0 Feb. 168.2 M a r. 172.4 A p r. 172.6 M a y. 173.5 174.4 Region and area size2 Northeast urban.......................................................................... M 178.5 178.4 182.8 183.7 184.2 184.6 175.4 175.4 179.5 180.3 180.9 181.6 Size A— More than 1,500,000.............................................. M 179.2 179.1 183.7 184.6 185.0 185.6 175.1 175.1 179.4 180.2 180.7 181.6 Size B/C— 50,000 to 1.500.0003......................................... M 107.5 107.4 109.8 110.4 110.7 1 1 0 .8 107.0 107.0 109.4 109.8 1 1 0 .2 110.4 Midwest urban ........................................................................... Size A— More than 1,500,000.............................................. M 167.0 167.5 172.1 171.7 172.8 174.2 163.3 163.9 168.4 167.8 169.0 170.7 M 168.3 169.2 173.8 173.3 174.4 175.6 163.7 164.6 169.1 168.5 169.6 171.0 Size B/C— 50,000 to 1.500.0003......................................... Size D— Nonmetropolitan (less than 50,000).................... M 106.9 107.0 109.8 109.7 110.4 1 1 1 .6 106.9 107.0 109.9 109.6 1 1 0 .6 1 1 2 .0 M 161.4 161.4 166.3 165.9 166.7 167.9 159.9 160.0 165.0 164.3 165.1 166.4 South urban................................................................................ M 166.7 166.7 170.2 170.6 171.4 171.7 165.0 165.0 168.3 168.7 169.6 170.0 Size A— More than 1,500,000.............................................. M 166.1 166.0 170.4 170.9 171.6 171.9 163.8 163.8 167.9 168.4 169.3 169.7 Size B/C— 50,000 to 1,500,0003......................................... Size D— Nonmetropolitan (less than 50,000)..................... M 107.2 107.2 109.2 109.4 109.9 1 1 0 .1 107.0 107.0 109.0 109.1 109.7 109.9 M 166.8 167.2 169.1 169.5 170.6 171.0 167.7 168.0 170.0 170.4 171.8 172.0 West urban................................................................................. M 173.7 174.0 179.3 180.1 180.4 181.3 169.4 169.9 174.6 175.3 175.8 176.7 Size A— More than 1,500,000.............................................. M 175.2 175.5 181.3 182.0 182.5 183.4 169.0 169.4 174.8 175.4 176.0 177.0 Size B/C— 50,000 to 1,500,0003......................................... M 107.2 107.3 1 1 0 .1 110.7 1 1 0 .6 1 1 1 .1 107.1 107.1 109.8 110.4 110.4 110.9 M M M 155.3 107.0 155.5 107.2 159.9 109.6 160.3 109.8 160.9 161.6 110.7 153.8 154.1 107.0 158.6 109.5 1 1 0 .1 160.2 110.7 166.8 166.9 170.1 170.3 171.2 171.9 166.1 107.0 166.2 158.3 109.4 159.3 1 1 0 .2 169.4 169.5 170.5 171.1 C hicago-G ary-Kenosha, IL—IN—W l........................................ M 171.9 173.7 178.5 177.1 166.3 168.1 172.9 171.4 172.6 174.0 M 170.6 171.1 175.4 176.2 178.4 176.6 179.8 Los Angeles-R iverside-O range County, CA......................... 177.5 164.0 164.4 168.3 169.1 169.6 170.5 New York, NY-Northern N J-Long Island, N Y -N J -C T -P A .. M 181.4 181.4 185.3 186.4 186.6 187.3 181.8 181.9 180.8 181.8 181.9 4 Size classes: A5 .............................................................................................. B/C 3 .......................................................................................... Selected local areas6 181.7 1 190.9 190.9 189.3 180.6 183.0 190.1 Cleveland-Akron, O H ................................................................ 1 - 166.6 - 172.3 - 173.7 - 159.0 - 163.9 - 165.6 Dallas-Ft Worth, T X .................................................................. 1 - 163.2 - 168.9 - 169.4 - 163.1 - 168.5 - 169.1 W ashington-Baltimore, D C -M D -V A -W V 7 ............................ 1 - 106.7 - 109.7 - 1 1 0 .1 - 106.7 - 109.4 - 109.9 2 170.0 2 168.3 2 152.8 Detroit-Ann Arbor-Flint, M l....................................................... Philadelphia-W ilmington-Atlantic City, P A -N J-D E -M D .... Seattle-Tacom a-Brem erton, W A........................................... 1 2 166.9 2 175.8 2 178.7 2 177.8 175.3 - 173.2 179.0 184.0 1— January, March, May, July, September, and November. February, April, June, August, October, and December. 2 Regions defined as the four Census regions. 3 Indexes on a December 1996 = 100 base. 4 The "North Central" region has been renamed the "Midwest" region by the Census Bureau. It is composed of the same geographic entities. are published semiannually and appear in tables 34 and 39 of the January and July issues of the CPI Detailed Report: Anchorage, AK; Cincinnati-Ham ilton, O H -K Y -IN ; Denver-Boulder-G reeley, CO; Honolulu, HI; Kansas City, 100 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 - 181.2 184.2 - 175.8 173.3 - 178.2 179.2 _ 170.4 - 183.5 - 169.1 157.8 169.3 - 174.9 - 167.7 173.8 156.7 164.6 - 189.1 - 163.0 151.4 172.8 - 187.9 - 174.5 172.7 167.3 159.5 171.9 - Foods, fuels, and several other items priced every month in all areas; most other goods 5 Indexes on a December 1986 = 100 base. 6 In addition, the following metropolitan areas - 158.6 and services priced as indicated: M— Every month. 2— 176.0 180.7 - 184.9 - 179.4 - MO-KS; Milwaukee-Racine, Wl; Minneapolis-St. Paul, MN-WI; Pittsburgh, PA; Port-land-Salem, OR-WA; St Louis, MO-IL; San Diego, CA; Tampa-St. Petersburg-Clearwater, FL. 7 Indexes on a November 1996 = 100 base. Dash indicates data not available. 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. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 30. Annual data: Consumer Price Index, U.S. city average, all items and major groups [1982-84= 100] S e rie s 1 99 2 1 99 3 1 99 4 1 99 5 1 99 6 1997 1998 1999 2000 Consumer Price Index for All Urban Consumers: All items: Index............................................................................... 140.3 144.5 148.2 152.4 156.9 160.5 163.0 166.6 172.2 Percent change............................................................ 3.0 3.0 2 .6 2 .8 3.0 2.3 1 .6 2 .2 3.4 Food and beverages: Index............................................................................... 138.7 141.6 144.9 148.9 153.7 157.7 161.1 164.6 168.4 2.3 2 .8 3.2 2 .6 2 .2 2 .2 2.3 Percent change............................................................ Housing: 1.4 Index.............................................................................. Percent change............................................................ 137.5 141.2 144.8 148.5 152.8 156.8 160.4 163.9 169.6 2.9 2.7 2.5 2 .6 2.9 2 .6 2.3 2 .2 3.5 Apparel: Index............................................................................... 131.9 133.7 133.4 132.0 131.7 132.9 133.0 131.3 129.6 Percent change............................................................ 2.5 1.4 .9 .1 -1 .3 -1 .3 Index............................................................................... 126.5 130.4 134.3 139.1 143.0 144.3 153.3 2 .2 3.1 3.0 3.6 2 .8 0.9 141.6 -1 .9 144.4 Percent change............................................................. 2 .0 6 .2 2 .1 -.2 - 1 .0 -.2 Transportation: Medical care: Index............................................................................... 190.1 201.4 2 1 1 .0 220.5 228.2 234.6 242.1 250.6 260.8 Percent change............................................................. 7.4 5.9 4.8 4.5 3.5 2 .8 3.2 3.5 4.1 Other goods and services: Index............................................................................... 183.3 192.9 198.5 206.9 215.4 224.8 237.7 258.3 271.1 Percent change............................................................ 6 .8 5.2 2.9 4.2 4.1 4.4 5.7 8.7 5.0 and Clerical Workers: All items: Index............................................................................... 138.2 142.1 145.6 149.8 154.1 157.6 159.7 163.2 Percent change............................................................ 2.9 2 .8 2.5 2.9 2.9 2.3 1.3 2 .2 168.9 3.5 Consumer Price Index for Urban Wage Earners Monthly Labor Review July 2001 101 Current Labor Statistics: Price Data 31. Producer Price indexes, by stage of processing [1982 = 100] 2000 A n n u al a v e ra g e 2001 G ro u p in g 1999 2000 M ay Ju n e Ju ly A ug. Sept. Nov. Dec. Jan. Feb. M ar. A pr. M ay 138.0 140.0 140.5 138.2 139.7 140.1 137.9 141.2 141.9 138.4 141.5 142.5 139.5 141.0 141.9 140.9 141.7 142.7 141.6 O ct. 138.6 139.0 137.5 138.2 138.6 137.2 139.6 139.5 140.5 133.4 138.5 140.5 133.1 138.6 139.0 140.0 132.7 138.5 143.0 132.5 138.6 141.6 142.6 135.3 139.8 141.3 142.1 135.4 139.9 140.8 141.5 135.3 139.9 143.3 144.9 135.2 140.2 143.6 145.9 134.2 139.7 142.1 143.8 134.1 139.7 142.9 144.9 134.2 140.0 142.5 143.8 141.8 144.5 144.5 147.3 133.8 139.7 129.8 130.3 129.9 131.1 130.8 130.5 130.6 131.5 131.3 130.8 130.6 131.2 128.6 128.6 119.4 133.9 129.0 128.0 118.9 133.3 128.1 119.8 133.5 126.3 126.3 128.8 126.4 127.5 126.5 128.0 126.1 128.6 120.4 135.0 127.2 126.4 128.8 120.3 136.1 127.0 126.2 128.9 122.3 135.8 126.7 126.4 128.7 122.3 135.2 126.0 126.2 128.5 119.0 133.6 129.3 126.4 128.4 119.1 133.7 129.4 128.9 120.5 134.5 129.4 126.6 128.6 124.6 134.2 126.9 126.4 149.6 111.4 150.0 150.2 150.4 151.6 106.9 152.8 138.7 105.9 153.2 139.0 108.1 153.9 139.0 132.9 109.1 144.5 130.9 110.3 140.4 141.6 147.5 150.6 149.8 142.6 104.1 147.7 151.6 150.0 Finished goods............................................ 133.0 Finished consumer goods......................... Finished consumer foods........................ 132.0 135.1 138.0 138.2 137.2 137.3 137.4 138.2 138.6 139.1 137.6 Finshed consumer goods excluding foods...................................... Nondurable goods less food................. Durable goods........................................ Capital equipment................................... 130.5 127.9 133.0 137.6 138.4 138.7 133.9 138.8 136.9 136.5 133.8 138.6 123.2 129.2 128.3 124.6 128.1 119.2 132.6 129.0 126.2 128.5 120.5 133.3 129.6 126.0 139.4 140.1 137.4 141.1 140.1 140.7 Intermediate materials, supplies, and components...................... Materials and components for manufacturing....................................... Materials for food manufacturing.............. Materials for nondurable manufacturing.. Materials for durable manufacturing........ Components for manufacturing................ 1 2 0 .8 124.9 125.1 125.7 1 2 0 .6 133.7 Materials and components for construction........................................... 148.9 150.7 151.0 151.2 150.8 150.4 150.1 149.9 1 0 2 .0 Containers..................................................... 96.5 152.7 136.7 103.3 153.3 137.1 105.0 153.3 137.3 104.5 153.0 137.0 150.3 110.5 153.3 137.4 150.2 84.6 142.5 134.2 109.2 153.4 137.7 108.8 153.0 138.0 108.3 153.0 138.1 153.0 138.9 109.9 153.0 138.5 125.6 101.9 137.3 122.7 99.3 134.4 118.3 95.5 129.7 126.0 97.6 141.0 130.3 99.5 146.7 128.4 100.4 143.0 136.2 103.9 153.5 155.0 105.3 183.5 133.2 104.5 148.2 131.5 108.9 142.2 140.4 98.9 146.1 148.7 149.2 140.1 97.9 145.9 148.5 149.1 141.9 101.9 146.7 149.4 150.0 142.0 103.6 146.6 149.5 149.4 140.9 99.7 147.1 150.2 149.5 151.6 136.9 Crude materials for further 98.2 98.7 94.3 1 2 0 .6 130.4 115.9 104.9 119.3 goods, excluding foods................ energy goods................................ goods less energy........................ consumer goods less energy..... goods less food and energy........ 132.3 78.8 143.0 145.2 146.1 138.1 94.1 144.9 147.4 148.0 137.0 90.9 145.0 147.6 147.7 138.8 97.7 144.7 147.3 147.5 138.8 97.3 144.7 147.3 147.6 138.4 139.9 95.9 144.7 147.3 147.7 1 0 0 .6 144.8 147.5 147.8 140.6 99.6 146.0 148.6 149.2 Finished consumer goods less food and energy................................................. 151.7 154.0 153.7 153.6 153.5 153.8 154.0 155.5 155.4 155.3 156.5 155.9 156.1 156.4 156.9 Consumer nondurable goods less food and energy............................................... 166.3 169.8 169.3 169.4 169.6 170.4 170.9 171.3 171.2 171.0 173.2 173.2 173.5 174.0 175.4 123.9 129.2 113.4 96.3 135.3 130.7 113.4 103.0 135.5 131.2 112.7 104.6 135.7 131.0 132.2 1 1 0 .6 1 1 1 .1 104.2 135.3 135.4 131.9 111.5 108.8 135.4 131.5 111.7 107.6 135.2 131.5 113.5 107.9 135.3 132.4 115.1 110.9 135.8 132.3 113.6 109.5 135.8 131.7 114.1 106.4 136.0 131.6 114.0 105.5 136.0 132.1 114.9 107.6 136.1 processing................................................. Foodstuffs and feedstuffs............................ Crude nonfood materials............................. 1 0 0 .2 Special groupings: Finished Finished Finished Finished Finished 1 0 1 .2 Intermediate materials less foods Intermediate goods less energy................. 84.3 131.7 130.1 111.7 101.7 135.0 Intermediate materials less foods and energy................................................. 133.1 136.6 136.7 137.0 137.2 137.0 137.0 137.0 136.8 136.8 137.1 137.3 137.4 137.4 137.5 1 2 2 .1 106.5 116.1 148.8 130.6 113.4 146.7 127.6 122.4 107.4 141.9 136.7 109.2 142.9 144.8 111.7 145.2 1 1 0 .8 1 1 0 .1 Crude nonfood materials less energy........ 78.5 107.9 135.2 140.9 109.9 137.8 154.7 112.4 137.5 193.4 113.7 138.7 148.3 112.4 136.1 141.0 115.2 134.6 145.2 114.3 130.8 139.8 115.3 130.9 1 1 1 .1 102 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 144.3 1 1 0 .1 141.0 32. Producer Price Indexes for the net output of major industry groups [December 1984 = 100, unless otherwise indicated] 2001 2000 A nnu al average In dustry S IC 1999 _ 10 12 13 14 _ 2000 M ay June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. M ar. A pr. M ay 170.8 138.2 130.7 132.2 127.5 73.5 83.6 204.4 72.4 90.8 159.4 73.1 90.3 149.3 70.0 90.6 151.5 71.4 92.2 144.9 T o ta l m in in g in d u s tr ie s ............................................ 78.0 113.5 1 0 0 .6 118.4 118.1 113.8 124.7 131.8 128.9 139.6 Metal mining.................................................... Coal mining (12/85 = 100).............................. Oil and gas extraction (12/85 - 100).............. Mining and quarrying of nonmetallic minerals, except fuels.................................... 70.3 87.3 78.5 73.8 84.8 126.8 72.6 109.1 73.7 85.1 133.1 73.9 85.6 132.8 73.4 83.3 127.4 75.2 83.5 141.9 75.1 83.6 151.5 73.3 84.1 147.7 73.5 84.8 162.0 T o ta l m a n u fa c tu r in g in d u s trie s ............................ 8 6 .1 134.0 137.0 137.2 137.2 137.6 137.8 138.0 138.0 138.0 138.2 139.3 140.1 140.8 140.8 140.7 128.3 126.3 325.7 116.3 133.5 128.5 345.8 116.7 133.1 129.3 341.7 116.5 134.2 129.4 342.2 116.6 133.9 129.4 342.3 116.7 133.5 128.7 350.4 116.9 134.7 128.5 351.1 116.6 134.9 128.7 351.6 116.8 134.9 128.8 351.6 117.0 134.4 129.6 351.8 117.5 134.7 130.1 372.4 117.4 134.7 130.4 372.4 117.9 134.6 131.7 372.3 117.0 135.4 132.5 372.1 117.0 136.3 133.2 391.2 117.1 125.3 125.7 125.6 125.6 125.9 125.9 125.9 126.0 125.7 125.9 125.7 125.7 125.7 125.9 125.8 161.8 141.3 136.4 158.1 143.3 145.8 159.1 143.4 157.6 143.5 147.3 155.7 143.6 147.3 155.3 143.5 147.7 155.0 143.7 147.6 154.5 143.8 147.5 154.2 143.8 147.0 153.2 144.2 147.4 153.8 144.3 147.0 154.5 144.8 147.0 154.7 144.7 147.0 160.5 144.9 146.9 185.1 159.0 114.4 124.8 138.9 134.1 119.2 186.8 187.2 187.6 188.4 188.8 160.4 112.5 126.0 139.1 134.4 118.5 161.6 126.1 140.6 135.0 118.0 161.9 107.3 126.8 140.9 135.4 117.4 161.4 114.1 127.4 142.8 135.6 116.8 160.4 120.9 126.6 142.9 136.0 116.9 25 26 Food and kindred products............................. Tobacco manufactures.................................... Textile mill products......................................... Apparel and other finished products made from fabrics and similar materials...... ! Lumber and wood products, except furniture.............................................. Furniture and fixtures....................................... Paper and allied products............................... 146.9 158.7 143.5 147.3 27 Printing, publishing, and allied industries....... 177.6 182.9 182.0 183.1 183.2 183.6 183.6 184.9 28 29 30 31 32 33 34 Chemicals and allied products........................ Petroleum refining and related products......... Rubber and miscellaneous plastics products. Leather and leather products.......................... Stone, clay, glass, and concrete products..... 149.7 76.8 156.7 156.4 136.5 132.6 115.8 124.6 137.9 134.6 119.8 109.0 123.6 137.4 135.1 120.5 1 2 0 .2 124.7 137.8 134.5 120.4 158.3 125.1 125.4 138.4 134.8 120.5 158.6 1 1 2 .8 157.4 115.7 125.0 137.5 134.8 120.3 157.5 1 2 2 .2 156.5 119.9 124.4 137.2 135.1 1 2 0 .2 185.0 158.3 121.9 126.5 138.8 134.3 119.0 129.1 130.3 130.2 130.3 130.3 130.4 130.5 130.6 130.5 130.5 130.6 130.7 130.8 131.2 131.1 117.3 117.5 117.4 117.5 117.6 117.6 117.6 117.6 117.7 117.7 117.7 117.8 117.8 118.0 118.0 109.5 134.5 108.3 136.8 108.4 136.5 108.5 136.0 108.5 136.1 108.1 135.7 108.1 135.7 108.0 138.4 107.9 138.6 107.7 138.4 107.7 138.7 107.6 137.6 107.5 137.9 107.5 138.1 107.4 137.4 125.7 126.2 126.3 126.2 126.2 126.2 126.3 126.4 1 2 1 .8 126.4 126.9 127.1 126.9 126.9 127.3 130.3 130.9 130.5 130.7 130.9 131.0 131.0 131.0 131.2 131.3 131.7 131.9 132.3 132.2 132.5 114.8 135.3 113.0 130.8 98.3 119.4 135.2 118.6 135.2 123.8 146.0 119.0 135.2 124.1 147.2 1 2 0 .1 1 2 1 .2 1 0 2 .1 135.2 127.0 151.5 102.4 135.2 124.2 152.7 102.7 121.5 135.2 126.1 154.2 102.7 121.9 141.3 125.8 154.7 109.1 122.5 141.3 127.8 154.0 109.1 1 2 2 .6 135.2 126.1 147.9 102.5 121.4 135.2 126.5 152.5 102.7 1 2 1 .8 1 0 2 .0 118.9 135.2 125.2 147.6 102.5 141.3 126.8 155.4 108.9 122.7 141.3 125.9 155.4 108.9 123.0 141.3 125.6 156.4 109.0 20 21 22 23 24 Fabricated metal products, except machinery and transportation transportation equipment............................. 35 36 37 38 39 Electrical and electronic machinery, equipment, and supplies............................... Measuring and controlling Instruments; photographic, medical, and optical goods; watches and clocks........................... Miscellaneous manufacturing industries industries (12/85 = 100)................................. 1 1 2 .6 1 2 1 .8 125.3 138.4 134.5 1 1 2 .0 S e r v ic e in d u s trie s : 42 43 44 45 46 Motor freight transportation and warehousing (06/93 = 100)..................... Water transportation (12/92 = 100)................. Transportation by air (12/92 = 100)................. Pipelines, except natural qas (12/92 - 100).... https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1 2 2 .6 147.7 102.3 Monthly Labor Review July 2001 103 Current Labor Statistics: Price Data 33. Annual data: Producer Price Indexes, by stage of processing [1982 = 100] In d e x 1 99 2 1 99 3 19 9 4 199 5 19 9 6 1997 1998 1 99 9 2000 Finished goods 124.7 125.7 125.5 127.9 126.8 129.0 131.3 133.6 131.8 134.5 130.7 123.3 134.3 133.0 135.1 138.0 137.2 77.8 134.2 78.0 135.8 77.0 137.1 78.1 140.0 83.2 142.0 83.4 142.4 75.1 143.7 78.8 146.1 148.0 114.7 116.2 118.5 124.9 125.7 113.9 115.6 118.5 125.3 125.6 123.2 123.0 123.2 1 2 0 .8 84.3 83.0 127.1 135.2 89.8 134.0 89.0 134.2 80.8 133.5 84.3 133.1 101.7 1 2 2 .0 84.6 123.8 119.5 84.1 100.4 102.4 1 0 1 .8 102.7 113.8 1 1 1 .1 96.8 98.2 1 2 0 .6 105.1 106.5 72.1 105.8 69.4 121.5 1 1 2 .2 103.9 98.7 1 0 0 .2 78.8 108.4 76.7 87.3 6 8 .6 78.5 1 2 2 .1 94.2 94.1 97.0 105.8 85.0 105.7 103.5 84.5 91.1 118.0 123.2 94.1 Intermediate materials, supplies, and components Total....................................................................................... 123.2 129.2 119.2 136.6 Crude materials for further processing Monthly Labor Review Digitized for 104 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 34. U.S. export price indexes by Standard International Trade Classification [1995= 100] SITC 2001 2000 In d u stry Rev. 3 M ay June J u ly A ug. Sept. O ct. Nov. D ec. 88.5 107.6 74.0 89.8 105.9 75.8 88.9 Food and live animals..................................... .................... Meat and meat preparations............................................. 04 Cereals and cereal preparations....................................... Vegetables, fruit, and nuts, prepared fresh or dry........... 05 88.3 105.1 75.0 90.1 87.4 109.3 71.6 87.8 85.8 108.2 83.6 103.7 85.9 105.2 87.1 107.4 66.9 91.3 64.0 8 8 .6 67.8 91.9 70.8 88.7 85.2 82.9 89.7 80.3 24 Cork and wood................................................................... 86.5 89.1 86.7 99.0 69.0 93.0 79.6 84.4 86.7 86.3 86.7 97.6 69.6 93.3 78.2 83.7 22 Crude materials, inedible, except fuels........................... Hides, skins, and furskins, raw......................................... Oilseeds and oleaginous fruits.......................................... 83.5 104.7 81.3 87.2 142.3 94.5 163.0 0 01 2 21 25 26 27 28 3 Mineral fuels, lubricants, and related products............. 32 Petroleum, petroleum products, and related materials... 33 4 5 Chemicals and related products, n.e.s............................. 54 Medicinal and pharmaceutical products........................... 55 Essential oils; polishing and cleaning preparations........ 57 Plastics in primary fo rm s .................................................. 58 Plastics in nonprimary forms............................................. 59 Chemical materials and products, n.e.s........................... 86.5 95.9 67.7 93.3 78.0 82.9 95.4 78.0 88.4 91.7 70.7 93.1 78.7 100.5 83.8 86.9 90.7 72.2 91.5 78.7 144.9 93.8 168.2 151.2 93.8 178.3 147.6 93.1 172.3 70.1 67.1 64 6 63 2 95.8 95.5 99.7 94.7 100.5 103.3 97.0 99.4 99.3 94.9 100.3 103.3 95.4 99.4 99.2 1 0 0 .0 103.1 98.4 99.8 99.3 1 0 2 .8 98.1 99.3 99.1 82.2 1 0 2 .1 79.3 86.5 88.7 85.8 70.4 90.9 74.1 84.3 83.6 70.6 90.9 74.7 87.3 78.4 119.4 75.0 81.6 80.4 64.4 89.4 72.9 77.5 123.6 75.7 80.7 75.7 64.0 89.5 71.6 155.9 158.8 157.4 93.0 183.6 157.5 93.1 181.1 159.5 93.1 185.2 152.4 93.6 172.4 1 0 0 .0 1 0 0 .0 178.4 184.1 61.7 60 0 59 0 58 7 61 60 60 61 94.4 94.0 93.0 1 0 0 .2 1 0 0 .1 103.4 94.9 100.4 103.4 92.8 99.3 99.2 92.3 98.9 99.2 103.3 91.2 98.3 99.1 103.2 90.0 98.3 99.9 93.1 99.7 103.4 1 0 0 .2 97.3 97.3 97.3 97.4 97.3 97.4 97.4 1 1 2 .0 112.4 106.4 112.3 106.5 112.4 106.3 112.4 106.3 113.7 106.5 113.7 106.6 108.3 68.3 108.1 67.8 108.2 67.8 108.3 67.7 108.4 108.5 67.6 90.5 96.6 98.4 8 92.9 99.6 103.2 91.5 96.5 98.5 6 93.4 99.4 103.4 92.7 96.7 98.5 6 65 2 92.8 99.7 91.4 91.6 99.7 102.5 90.2 96.8 98.6 96.1 98.4 1 0 2 .6 1 0 0 .1 100.3 100.7 100.9 1 0 1 .1 1 0 0 .8 100.5 100.4 1 0 1 .0 1 0 0 .6 100.4 99.9 99.7 104.6 104.4 104.8 104.7 104.7 104.6 104.1 103.8 104.4 104.3 104.7 104.0 104.0 90.5 106.4 98.1 89.8 106.5 90.4 106.3 103.0 90.3 106.3 105.1 90.0 106.1 105.0 89.9 105.8 104.9 89.6 105.9 103.4 89.1 105.6 104.9 8 8 .6 106.2 109.1 88.4 106.2 108.1 87.8 106.0 106.5 87.7 106.5 103.1 87.6 106.6 101.5 97.5 97.6 97.9 97.8 97.7 115.2 106.8 115.2 107.1 14.7 106.8 115.0 106.9 115.0 106.9 108.6 67.1 108.8 67.1 109.2 109.5 66.7 109.5 6 6 .8 96.4 85.2 104.1 96.5 84.8 104.1 96.5 84.8 104.1 107.0 107.1 107.1 1 0 0 .1 106.2 106.5 108.2 108.2 68.5 6 8 .2 67.8 Road vehicles..................................................................... 97.0 86.3 103.9 96.9 85.7 103.9 96.7 85.7 103.9 96.8 85.8 103.9 96.8 85.8 104.1 96.6 85.4 104.0 96.5 85.3 103.9 96.3 85.4 104.0 96.5 85.2 104.1 96.4 85.2 104.1 87 Professional, scientific, and controlling instruments and apparatus.............................................. 105.7 105.8 106.4 106.4 106.5 106.9 106.9 106.6 107.0 107.0 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 89.5 162.1 93.1 193.4 0 82.3 67.6 89.9 72.5 87.6 108.8 74.7 157.2 93.3 189.0 1 1 2 .0 77 78 79.7 107.5 79.0 83.5 108.5 74.7 166.3 93.1 203.3 97.4 75 76 77.2 87.8 88.4 M ay 72.2 90.6 76.2 7 Machinery and transport equipment................................ General industrial machines and parts, n.e.s., and machine parts............................................................ Computer equipment and office machines...................... Telecommunications and sound recording and 80.9 106.5 78.1 89.1 107.2 A p r. 85.9 73.2 90.6 74.7 8 8 .6 Rubber manufactures, n.e.s.............................................. Paper, paperboard, and articles of paper, pulp, and paperboard................................................................ Nonmetallic mineral manufactures, n.e.s......................... Nonferrous metals.............................................................. Power generating machinery and equipment.................. 8 6 .2 M ar. 89.8 72.0 90.7 79.5 Manufactured goods classified chiefly by materials.... 71 72 74 78.8 86.9 8 8 .6 107.1 76.4 82.0 105.6 83.9 85.2 6 68 89.8 105.4 Feb. 82.6 103.3 85.0 85.9 62 64 66 Jan. Monthly Labor Review July 2001 6 6 .2 105 Current Labor Statistics: 35. Price Data U.S. import price indexes by Standard International Trade Classification [1995= 100] SITC Rev. 3 2 000 In d u stry M ay Ju n e Ju ly A ug. S ept. O ct. 2001 N ov. Dec. Jan. Feb. M ar. A pr. M ay 0 Food and live animals......................................................... 92.3 91.3 91.5 91.7 91.2 91.5 90.2 92.4 92.8 91.3 92.9 91.0 89.5 01 Meat and meat preparations............................................. Fish and crustaceans, mollusks, and other aquatic invertebrates....................................................... 1 0 0 .2 99.1 98.1 98.9 99.0 95.5 95.7 97.3 95.5 96., 1 99.3 101.5 103.3 109.6 96.8 109.1 95.7 110.7 97.2 113.5 97.6 1 1 2 .6 110.7 100.9 109.3 96.8 109.1 104.5 107.4 1 0 0 .1 106.1 105.6 101.7 1 0 2 .2 97.8 109.4 103.3 99.7 99.8 54.1 51.9 50.8 50.5 51.1 51.1 52.1 50.9 113.1 03 05 07 Vegetables, fruit, and nuts, prepared fresh or dry.......... Coffee, tea, cocoa, spices, and manufactures thereof............................................................................... 1 59.8 59.5 56.8 55.8 54.5 112 4 113 0 112 5 112 9 113 fi 1 1 0 .1 109.4 109.9 110.7 1 1 0 .6 110.7 1 1 0 .6 110.5 1 1 0 .8 1 1 1 .0 111.3 90.7 89.6 88.9 89.8 87.7 88.5 87.5 88.9 8 6 .1 8 6 .6 89.3 1 0 2 .2 99.7 82.0 1 0 1 .6 97.7 83 4 101.7 83 4 95.6 84 3 97.6 82 9 97.5 80 4 102.9 7fi 8 113.0 80.1 100.7 92.7 107.0 80.7 1 0 1 .2 1 0 2 .1 1 0 1 .6 1 0 0 .1 101.3 103.0 99.1 98.8 97.1 1 0 0 .8 1 0 1 .8 102.3 104.3 100.9 115.3 98.1 97.7 98.0 91.8 96.9 102.7 172.0 171.0 195.4 170 6 168.5 202.9 172 1 169.9 205.4 189 0 18fi 3 1RR 4 1 Rfi 2 17fi 9 187.6 218 1 181.8 242 6 183.3 249 3 163.9 331 8 151.7 401 2 154.1 322 1 144.6 244 0 142.7 150.9 95.5 92.5 87.6 97.5 89.9 95.5 81.5 95.9 92.6 94.7 93.7 86.9 95.7 87.2 95.9 79.5 100.4 95.0 94.2 86.9 95.7 86.9 95.8 78.6 96.3 98.9 89.6 94.9 96.6 97.9 89.1 94.6 96.3 95.0 88.4 94.0 8 8 .2 8 8 .6 8 8 .1 95.5 84.5 1 0 0 .6 1 0 1 .8 95.8 84.4 101.9 95.8 83.2 101.4 95.6 92.1 87.9 93.7 87.7 95.8 83.0 1 0 0 .0 95.1 93.1 87.0 96.0 87.6 96.0 80.0 100.4 95.8 98.5 97.3 89.4 95.4 80.9 95.4 92.5 87.9 96.7 1 0 0 .6 11 Beverages........................................................................... 109.4 2 Crude materials, inedible, except fuels........................... 91.9 24 25 28 29 Cork and wood................................................................... Metalliferous ores and metal scrap.................................. Crude animal and vegetable materials, n.e.s.................. 112.9 77.0 99.6 106.7 Petroleum, petroleum products, and related materials.... 154.3 154.2 3 33 34 167.5 90.7 1 1 0 .1 5 Chemicals and related products, n.e.s............................ 52 Inorganic chemicals........................................................... 53 Dying, tanning, and coloring materials............................. 54 Medicinal and pharmaceutical products........................... 55 Essential oils; polishing and cleaning preparations......... 57 Plastics in primary forms................................................... 58 Plastics in nonprimary forms............................................. 59 Chemical materials and products, n.e.s........................... 94.3 90.7 87.4 94.1 91.5 97.3 89.9 94.0 80.8 100.9 96.8 89.6 94.3 80.8 99.7 1 0 0 .2 8 6 .1 81 4 8 8 .6 8 8 .8 95.3 80.8 1 0 1 .1 113 3 83 4 1 0 2 .0 8 8 .8 95.1 87.1 95.5 80.3 1 0 1 .6 6 Manufactured goods classified chiefly by materials..... 97.1 97.6 98.0 98.8 97.9 97.6 97.2 97.3 98.2 98.8 97.2 96.4 95.4 62 64 Rubber manufactures, n.e.s.............................................. Paper, paperboard, and articles of paper, pulp, 92.5 91.8 92.1 91.9 91.7 91.6 91.5 91.8 91.8 91.9 91.8 91.6 91.5 89.1 100.5 110.7 95.7 89.5 100.9 112.5 95.8 91.4 6 91 9 92 2 92 1 92 Nonmetallic mineral manufactures, n.e.s......................... Nonferrous metals.............................................................. Manufactures of metals, n.e.s........................................... 89.6 100.7 106.9 95.9 89.4 66 100.9 118.7 95.4 1 0 0 .8 1 0 0 .2 1 0 0 .2 1 0 0 .2 100.7 114.4 95.4 115.7 95.2 114.3 94.9 114.4 95.0 1 2 1 .0 100.5 124.0 95.0 68 69 7 Machinery and transport equipment................................ 72 74 91 95.3 6 8 93 7 100.5 116.4 94.9 92 100.3 1 0 0 .2 1 1 1 .0 106.9 95.7 95.7 92 8 89.8 89.6 89.6 89.5 89.3 89.2 89.1 89.0 88.9 8 8 .8 8 8 .8 88.4 8 8 .2 97.0 96.1 96.7 96 5 95 9 95.7 95.4 95.3 95.9 96.6 96.3 96.0 95.8 96.7 60.2 96.2 60.0 96.7 59.9 96.4 59.9 96.1 59.8 95.5 58.8 95.3 58.8 95.4 58.7 95.9 58.3 95.9 57.8 95.6 57.5 95.1 56.5 94.7 56.4 84.6 83.3 84 3 82.8 84 1 82.6 83 7 82.5 102.9 83 fi 83 0 82 82 82 82 82.2 102.9 82.1 102.9 75 76 General industrial machines and parts, n.e.s., and machine parts........................................................... Computer equipment and office machines..................... Telecommunications and sound recording and 77 78 Electrical machinery and equipment................................ Road vehicles..................................................................... 84.7 83.5 102.7 1 0 2 .8 1 0 2 .8 84 2 82.7 102.7 1 0 2 .6 83 9 82.7 102.9 1 0 2 .8 1 0 2 .8 1 0 2 .6 81.9 102.4 85 Footwear............................................................................. 100.7 100.3 100.9 1 0 1 .0 100.9 1 0 0 .8 100.7 1 0 0 .6 1 0 1 .0 1 0 1 .2 101.5 1 0 1 .1 1 0 1 .0 88 Photographic apparatus, equipment, and supplies, and optical goods, n.e.s.................................................. 91.9 91.6 92.5 92.1 91.4 91.4 91.0 90.7 91.2 91.3 91.4 106 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 8 81.8 8 82.5 2 82.1 90.6 1 90.6 36. U.S. export price indexes by end-use category [1995 = 100] 2001 2000 C a te g o ry M ay June J u ly A ug. S e p t. O c t. N ov. D ec . Jan. F eb . M a r. A p r. M ay ALL COMMODITIES.......................................................... 96.4 96.3 96.2 96.0 96.6 96.5 96.5 96.3 96.5 96.5 96.2 96.1 95.8 Foods, feeds, and beverages........................................ 88.3 87.7 87.1 85.1 86.7 87.4 88.2 86.6 84.6 85.7 86.7 87.3 85.7 87.3 86.5 86.4 85.7 85.9 96.6 98.1 84.0 97.9 85.3 84.3 85.8 86.2 82.8 81.3 99.7 97.9 99.5 98.2 96.3 98.6 97.0 97.6 95.3 91.0 93.1 Agricultural foods, feeds, and beverages................. Nonagricultural (fish, beverages) food products...... 85.5 Industrial supplies and materials................................... 95.2 95.2 95.5 95.4 96.6 96.2 95.8 95.0 95.0 94.9 93.9 93.8 Agricultural industrial supplies and materials........... 78.2 78.2 77.9 80.3 81.9 82.3 82.0 82.9 82.4 82.6 80.7 80.7 81.2 Fuels and lubricants..................................................... 132.9 135.6 141.1 137.9 155.0 146.9 150.7 146.2 145.2 147.1 139.8 144.7 147.5 91.9 89.9 91.7 91.7 91.4 91.6 90.7 90.1 90.4 90.1 89.6 90.5 89.4 89.8 89.0 89.0 88.8 88.2 89.8 86.7 89.2 86.7 96.1 96.1 96.2 96.1 96.2 96.3 96.4 96.5 96.7 96.6 96.6 99.1 99.7 99.9 99.6 99.7 100.0 100.5 100.1 100.5 100.9 Nonagricultural supplies and materials, 88.0 86.2 excluding fuel and building materials...................... 92.1 Selected building materials......................................... 90.0 Capital goods................................................................... 96.1 Electric and electrical generating equipment........... 98.9 Nonelectrical machinery............................................. 91.9 91.7 91.6 91.6 91.5 99.5 91.5 91.5 91.5 91.5 91.5 915.0 91.3 91.2 Automotive vehicles, parts, and engines..................... 104.2 104.1 104.4 104.4 104.5 104.5 104.4 104.4 104.6 104.5 104.6 104.7 104.7 Consumer goods, excluding automotive..................... 102.4 102.4 102.3 102.5 102.4 102.4 102.2 102.2 102.3 102.4 102.0 102.0 101.1 102.1 102.0 102.0 101.5 101.9 101.4 101.8 102.1 101.3 101.7 101.4 96.1 99.2 Durables, manufactured............................................. 101.3 101.3 101.5 102.4 101.4 Agricultural commodities................................................ 85.6 84.4 Nonagricultural commodities......................................... 97.7 97.6 82.6 97.8 80.9 97.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 101.3 101.2 102.2 102.2 101.2 101.3 101.5 101.5 101.2 101.0 83.5 83.9 84.7 85.7 86.1 84.9 85.1 98.0 97.9 97.8 97.5 97.7 97.7 97.5 84.5 97.4 84.4 97.1 Monthly Labor Review July 2001 107 Current Labor Statistics: 37. Price Data U.S. import price indexes by end-use category [1995 = 100] 2000 C a te g o ry M ay ALL COMMODITIES.......................................................... June J u ly Aug. 2001 S e p t. O c t. N o v. D ec. J an . Feb. M a r. A p r. M ay 98.3 99.6 99.7 99.9 1 0 1 .0 1 0 0 .6 1 0 0 .6 1 0 0 .0 1 0 0 .0 99.3 97.8 97.2 97.5 91.1 91.3 83.2 90.7 89.4 91.0 90.8 82.5 83.0 81.9 84.2 84.3 89.8 83.4 90.6 89.1 84.1 88.5 83.4 Nonagricultural (fish, beverages) food products..... 109.8 84.1 109.7 91.1 83.7 90.7 Agricultural foods, feeds, and beverages................. 91.9 85.2 110.5 112.9 112.5 1 1 1 .2 109.5 109.1 107.9 106.7 103.9 102.4 1 0 2 .0 Industrial supplies and materials................................... 115.9 1 2 1 .8 1 2 1 .8 1 2 2 .8 127.6 126.6 126.9 124.5 124.4 122.3 116.1 115.1 116.9 Fuels and lubricants..................................................... 153.3 170.6 169.2 170.9 187.4 184.5 186.8 178.7 176.7 169.3 153.3 154.0 170.4 168.0 169.5 187.1 181.9 183.6 165.6 155.7 156.1 145.9 151.5 143.4 158.6 Petroleum and petroleum products....................... Paper and paper base stocks.................................... 8 6 .8 87.0 87.5 87.6 89.8 90.4 90.6 91.0 91.0 91.2 90.8 91.0 88.9 Materials associated with nondurable supplies and materials............................................... 92.1 91.7 92.7 93.4 92.8 92.8 92.6 93.3 94.1 94.3 94.4 93.9 93.1 Selected building materials......................................... 109.1 105.0 103.4 1 0 0 .2 98.7 99.3 97.2 99.1 95.3 96.0 96.2 98.3 104.2 Unfinished metals associated with durable goods.. 1 0 2 .0 104.1 87.1 107.2 108.7 103.8 1 0 1 .0 97.5 87.2 105.6 87.3 103.7 87.7 109.5 87.6 105.9 87.8 105.0 87.0 106.5 Nonmetals associated with durable goods............... 87.2 87.8 88.7 8 8 .8 88.5 8 8 .2 79.1 Foods, feeds, and beverages....................................... Capital goods.......................................................... 85.6 151.3 80.6 80.2 80.1 80.0 79.9 79.7 79.3 79.3 93.7 92.9 95.1 94.5 94.6 77.1 77.1 77.0 76.3 93.1 76.1 93.1 77.5 93.4 76.4 93.1 Nonelectrical machinery.............................................. 93.5 76.8 76.0 75.8 75.6 75.0 74.8 Automotive vehicles, parts, and engines..................... 1 0 2 .6 102.7 1 0 2 .8 102.7 102.5 1 0 2 .6 102.7 102.7 102.7 1 0 2 .6 1 0 2 .6 102.5 102.3 Consumer goods, excluding automotive...................... 97.0 96.5 96.8 99.8 93.4 96.8 96.6 96.5 96.4 96.6 96.4 96.4 99.8 99.6 1 0 0 .0 93.0 99.6 92.9 92.9 99.5 1 0 0 .0 93.2 99.2 99.8 92.8 99.1 96.6 99.8 96.6 1 0 0 .0 96.6 99.8 92.5 98.0 92.3 99.4 Nondurables, manufactured....................................... Durables, m anufactured.............................................. Nonmanufactured consumer goods.......................... 38. 1 0 0 .1 93.4 99.7 99.5 93.2 98.0 99.5 CO 80.9 94.1 80.7 94.3 evi 80.9 94.2 O) 81.2 Electric and electrical generating equipment........... 99.8 92.8 98.8 92.8 101.5 1 0 0 .1 92.8 99.1 U.S. international price Indexes for selected categories of services [1995 = 100] 1 99 9 C a te g o ry M a r. June Air freight (inbound)................................................ 8 8 .0 8 6 .2 Air freight (outbound)..................................................... 92.7 92.8 104.5 98.9 112.3 106.3 1 0 2 .6 133.7 Air passenger fares (U.S. carriers)................................... Ocean liner freight (inbound)......................................... Monthly Labor Review Digitized108 for FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 2000 S e p t. 87.9 92.7 D ec . M a r. June 2001 S e p t. D ec. M a r. 90.7 88.9 88.4 88.5 87.4 86.5 91.7 91.7 92.8 92.6 92.6 92.6 114.2 106.8 107.3 1 0 2 .2 1 0 2 .6 113.3 107.9 115.5 108.6 109.1 111.9 103.2 106.4 148.0 139.4 136.3 143.0 142.8 142.8 145.1 114.2 39. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted [1992 = 100]__________________________________________________________________________________________ Q u a r te rly in d e x e s 19 9 8 Ite m I II IV I II 2001 2000 19 9 9 III III IV 1 II IV III I Business 1 2 0 .2 119.7 134.6 136.3 109.1 110.3 1 1 0 .8 1 1 2 .0 110.5 113.9 119.5 118.7 117.7 114.0 114.5 115.3 119.5 119.1 135.2 112.5 112.7 114.0 1 2 1 .6 105.7 123.0 106.4 124.3 106.8 125.9 107.4 107.6 107.5 108.6 109.3 115.1 110.4 109.5 116.9 1 1 0 .0 1 1 0 .0 114.2 110.5 114.4 118.2 1 2 0 .0 111.4 1 1 1 .8 111.9 1 1 2 .2 113.0 113.7 115.6 126.3 116.2 118.0 129.4 118.8 131.4 107.8 109.7 105.0 106.7 107.8 108.6 116.3 115.1 114.5 108.8 114.6 110.3 110.5 110.7 110.9 109.6 116.8 1 1 0 .1 110.5 111.4 111.9 1 1 2 .0 113.4 118.3 123.4 103.6 107.5 120.9 105.1 1 2 2 .1 1 0 2 .6 119.8 104.5 108.4 115.7 108.6 1 1 1 .0 116.6 128.2 119.3 132.2 1 1 1 .8 120.3 103.2 116.1 127.1 118.6 130.4 1 1 0 .8 110.3 118.9 104.1 1 1 0 .0 117.4 Nonfarm business 106.5 117.4 110.5 116.2 110.7 105.6 106.0 125.0 106.6 1 1 0 .2 1 1 0 .2 115.8 109.0 116.7 115.8 1 1 1 .2 1 1 1 .8 1 1 2 .2 127.6 108.5 133.5 109.4 109.6 1 1 0 .6 1 1 1 .8 113.5 107.0 107.0 109.8 116.1 109.3 118.6 1 2 0 .1 1 2 1 .8 121.4 1 2 0 .6 112.4 112.7 113.6 114.1 114.5 115.0 119.6 115.7 1 2 2 .2 Nonfinancial corporations 1 1 0 .6 111.7 113.1 113.7 114.6 115.3 116.6 118.3 119.2 1 2 0 .8 1 2 2 .1 1 2 2 .2 113.7 115.2 116.7 123.0 104.2 123.9 103.9 125.8 104.8 130.0 131.8 1 0 1 .8 120.3 103.3 127.7 100.9 119.0 103.0 1 2 1 .8 99.9 117.8 102.4 105.4 106.4 106.9 107.9 102.3 1 0 2 .6 102.5 103.2 103.2 103.7 1 0 2 .8 103.1 103.6 1 0 1 .2 103.9 101.3 104.3 100.7 103.2 100.7 1 0 2 .1 1 0 2 .2 103.9 104.0 103.9 104.0 104.3 104.8 106.8 104.5 102.9 104.0 103.4 104.0 104.2 104.5 106.3 107.9 104.2 104.9 105.5 107.9 107.8 129.7 150.8 147.7 152.0 145.3 150.6 148.6 144.4 147.0 152.2 156.3 153.0 135.5 113.5 106.4 113.0 113.8 113.9 114.0 113.5 114.5 116.4 118.0 117.6 115.0 113.4 106.4 106.7 113.1 106.8 107.2 107.5 107.5 107.5 108.1 108.8 108.9 109.2 109.7 121.7 115.4 123.2 116.8 125.7 126.8 119.0 128.9 119.9 130.2 131.9 1 2 1 .2 1 2 2 .8 135.0 124.1 101.4 94.9 1 0 2 .2 103.0 103.7 104.1 104.7 94.8 93.9 103.4 93.9 93.0 93.1 93.1 Manufacturing https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 118.0 105.2 91.9 137.7 139.8 142.1 144.0 140.8 125.7 105.4 127.0 105.7 129.1 106.6 131.8 108.0 91.2 90.8 90.9 91.5 133.3 108.0 94.7 Monthly Labor Review July 2001 109 Current Labor Statistics: 40. Productivity Data Annual indexes of multifactor productivity and related measures, selected years [1996 = 100, unless otherwise indicated] Item 19 6 0 19 7 0 198 0 199 0 1991 19 9 2 199 3 1 99 4 19 9 5 19 9 6 1 99 7 1998 Private business Productivity: Output per hour of all persons........................................ 45.6 Output per unit of capital services................................. 110.4 Multifactor productivity..................................................... 65.2 O utput.................................................................................... 27.5 63.0 1 1 1 .1 80.0 42.0 75.8 90.2 91.3 94.8 95.4 96.6 97.3 1 0 0 .0 1 0 2 .0 104.8 101.5 99.3 97.7 99.7 1 0 0 .0 100.5 1 0 0 .1 95.3 1 0 0 .0 1 0 1 .1 1 0 2 .6 82.6 98.1 92.8 98.4 83.6 96.6 85.7 98.5 97.1 100.3 88.3 59.4 96.1 94.4 95.8 1 0 0 .0 105.2 1 1 0 .6 88.5 Inputs: Labor input......................................................................... 61.0 71.9 89.4 88.3 89.3 91.8 95.6 98.0 1 0 0 .0 103.7 106.4 58.6 84.2 87.7 8 6 .0 87.7 89.8 92.6 96.0 1 0 0 .0 104.7 42.3 37.8 52.4 87.5 8 8 .8 91.1 97.3 1 0 0 .0 104.0 41.3 56.7 90.8 95.0 97.0 96.8 94.6 96.3 110.4 107.7 97.6 1 0 0 .0 101.5 104.7 90.3 1 0 0 .0 91.4 96.6 94.8 97.9 90.5 95.6 94.7 59.6 83.5 82.5 96.6 85.5 Capital services................................................................. 54.0 24.9 Combined units of labor and capital input.................... Capital per hour of all persons.......................................... 67.3 74.7 Private nonfarm business Productivity: Output per hour of all persons........................................ Output per unit of capital services................................. Muitifactor productivity..................................................... Output.................................................................................... 48.7 64.9 69.1 118.3 82.6 27.2 41.9 1 2 0 .1 77.3 105.7 95.3 98.8 97.1 96.5 100.3 97.5 1 0 0 .0 101.7 1 0 0 .0 1 0 0 .2 104.5 99.8 1 0 0 .0 100.9 105.1 1 1 0 .6 98.1 99.9 98.6 88.4 92.6 95.8 1 0 0 .0 91.8 89.5 95.4 97.8 95.9 1 0 0 .0 103.8 106.6 92.3 1 0 0 .0 104.9 1 1 0 .8 91.0 96.5 94.4 96.3 97.2 97.6 1 0 0 .0 1 0 0 .0 104.2 101.5 108.0 104.7 102.4 Inputs: Labor input......................................................................... 50.1 59.3 70.7 89.2 8 8 .0 89.0 Capital services................................................................. 2 2 .6 35.5 56.4 83.5 Combined units of labor and capital input.................... Capitai per hour of all persons.......................................... 39.3 40.5 50.7 54.8 65.9 73.1 87.3 90.3 85.4 87.1 94.7 87.3 88.4 96.8 Manufacturing (1992 = 100) Productivity: Output per hour of ail persons....................................... 41.8 54.2 70.1 92.8 95.0 1 0 0 .0 101.9 105.0 109.0 1 1 2 .8 117.1 124.3 Output per unit of capital services................................. Multifactor productivity..................................................... O utput.................................................................................... 124.3 72.7 116.5 84.4 100.9 1 0 1 .6 1 0 0 .0 1 0 1 .1 104.0 99.3 1 0 0 .0 100.4 1 0 2 .6 38.5 56.5 75.3 97.3 95.4 1 0 0 .0 103.3 108.7 105.0 105.0 113.4 104.5 8 6 .6 97.5 98.3 105.6 109.8 123.5 106.5 113.2 130.7 92.0 30.9 51.3 104.2 107.5 74.7 92.5 104.8 95.8 100.4 1 0 0 .0 101.4 97.9 1 0 0 .0 1 0 2 .2 105.5 116.9 44.8 48.8 75.0 73.7 111.3 1 1 2 .8 107.0 120.4 103.9 120.4 109.2 38.2 28.2 103.7 105.7 104.0 108.0 109.5 111.9 1 0 0 .0 103.6 104.5 107.3 105.2 48.5 85.4 108.9 114.2 67.0 87.0 105.1 106.0 1 1 0 .0 52.9 103.0 102.9 107.9 1 1 0 .2 112.5 Inputs: Hours of all persons.......................................................... Capital services................................................................. Energy................................................................................. Nonenergy materials........................................................ Purchased business services......................................... Combined units of all factor inputs................................. no Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 99.9 92.5 1 0 0 .1 93.6 92.1 1 0 0 .0 92.5 98.0 97.0 1 0 0 .0 1 0 0 .0 106.1 116.9 103.7 1 2 2 .8 127.2 116.8 115.5 41. A n n u a l in d e x e s o f p ro d u c tiv ity , h o u rly c o m p e n s a tio n , unit costs, a n d p ric e s, s e le c te d y e a rs [1992 = 100] Ite m 19 6 0 1 97 0 19 8 0 1 99 0 1991 199 3 19 9 4 19 9 5 199 6 1997 1998 1999 2000 Business Output per hour of all persons.......................................... Compensation per hour..................................................... Real compensation per hour............................................. Unit labor costs.................................................................... 48.8 13.7 67.0 80.4 95.2 96.3 100.5 101.9 1 0 2 .6 105.4 107.8 1 1 0 .8 113.8 23.5 54.2 89.4 90.7 95.0 102.5 106.7 1 1 0 .1 113.5 96.5 97.5 98.7 99.9 104.5 99.7 99.3 99.7 1 0 0 .6 119.6 104.6 125.1 107.1 101.9 1 0 2 .6 104.1 104.5 108.0 109.9 108.9 110.7 97.0 98.1 102.5 106.4 115.1 119.1 104.0 113.3 107.7 115.1 1 0 2 .2 109.4 106.0 105.3 117.1 109.7 1 1 0 .6 1 1 1 .8 113.8 60.0 78.9 28.0 25.2 35.1 31.6 27.0 33.9 61.5 65.2 Output per hour of all persons.......................................... 51.9 95.3 96.4 100.5 1 0 1 .8 1 0 2 .8 105.4 14.3 68.9 23.7 82.0 Compensation per hour..................................................... Real compensation per hour............................................. 54.6 90.5 95.0 1 0 2 .2 104.3 106.6 109.8 107.5 113.1 62.8 90.0 96.3 97.5 Unit labor costs.................................................................... Unit nonlabor payments..................................................... Implicit price deflator........................................................... 27.5 24.6 26.5 66.5 60.5 64.3 95.0 93.6 94.5 98.5 97.1 98.0 99.6 101.7 Unit nonlabor payments..................................................... Implicit price deflator........................................................... 67.4 95.3 93.9 94.8 118.6 131.4 Nonfarm business 79.5 34.4 31.3 33.3 103.0 1 0 2 .2 110.4 113.2 118.1 124.2 130.5 108.1 99.5 99.2 99.4 1 0 0 .2 119.0 104.0 102.5 106.9 104.1 103.7 110.4 104.2 113.5 105.2 118.0 107.7 116.3 109.7 116.8 110.5 106.1 107.6 109.8 1 1 0 .8 112.3 114.3 106.4 1 2 1 .0 Nonfinancial corporations 55.4 70.4 81.1 95.4 97.7 100.7 103.1 104.2 107.5 108.4 112.3 116.2 1 2 1 .1 Compensation per hour..................................................... 15.6 56.4 1 0 2 .0 104.2 106.2 115.9 1 2 1 .1 126.8 93.1 98.8 109.0 98.7 110.3 68.3 90.8 96.7 95.3 Real compensation per hour............................................. 25.3 84.7 97.8 101.3 34.8 68.4 95.9 98 8 101 0 1 0 1 .1 102 0 101 2 101.5 1 0 2 .6 103.7 103.7 105.1 26.8 Unit labor costs.................................................................. 28.1 35.9 69.6 95.2 97.5 101.3 1 0 1 .0 101.9 101.4 1 0 1 .8 103.2 104.2 104.8 Unit nonlabor costs........................................................... 23.3 50.2 31.9 65.1 1 0 0 .2 1 0 2 .2 1 0 0 .6 100.9 1 0 1 .2 102.5 105.6 147.6 149.2 30.2 44.4 35.1 6 8 .8 Unit nonlabor payments..................................................... 6 6 .0 98.0 94.3 97.1 Implicit price deflator.......................................................... 28.8 35.6 68.4 95.8 108.8 41.8 14.9 54.2 70.1 23.7 55.6 92.8 90.8 79.5 91.7 96.6 79.3 80.2 97.8 99.7 1 0 0 .6 99.0 100.9 79.8 99.0 99.6 100.9 97.8 99.5 99.4 105.0 93.0 99.7 113.2 101.3 131.7 139 0 152.2 103.5 109.0 1 1 1 .6 113.8 156.9 115.2 148.9 113.4 98.3 1 0 2 .1 103.7 105.1 105.5 106.2 106.6 114.0 107.4 95.0 101.9 102.7 105.0 109.0 1 1 2 .8 117.1 105.6 124.3 117.3 1 2 2 .0 138.5 127,4 1 0 0 .8 109.3 99.0 111.4 1 0 0 .2 107.9 100.4 100.7 96.9 109.9 94.4 104.4 104.5 94.1 106.4 12.7 1 0 2 .8 99.0 106.9 98.8 95.1 109.6 1 0 2 .6 1 0 0 .8 105.5 - 1 0 2 .0 103.9 104.9 104.0 100.5 1 0 1 .1 - 1 0 2 .1 116.8 Manufacturing Output per hour of all persons.......................................... Compensation per hour..................................................... Real compensation per hour............................................. 65.2 35.6 Unit labor costs..................................................... .............. Unit nonlabor payments..................................................... 26.8 43.8 29.3 Implicit price deflator............................................. ............. 30.2 34.9 95.6 98.1 129.6 Dash indicates data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review July 2001 111 Current Labor Statistics: 42. Productivity Data Annual indexes of output per hour for selected 3-digit sic industries [1987 = 100] In d u s try S IC 1990 1991 1992 1993 1994 1 995 1 996 1 997 1 99 8 1999 M in in g Copper ores................................................................. 102 102.7 100.5 115.2 118.1 126.0 117.2 116.5 118.9 118.3 105.5 Gold and silver ores................................................... Bituminous coal and lignite mining........................... 104 122.3 118.7 127.4 122.4 141.6 159.8 141.2 160.8 144.2 155.9 138.3 168.0 158.5 176.6 2 0 0 .0 Crude petroleum and natural gas............................. 131 142 97.0 97.9 99.8 119.4 105.4 123.9 125.2 187.6 188.0 127.4 107.2 1 1 2 .6 1 1 0 .2 104.8 97.4 102.5 119.3 110.7 118.2 99.1 102.3 119.3 117.8 126.2 1 0 2 .2 116.0 109.2 108.0 95.6 1 0 0 .8 130.4 107.5 123.0 137.3 136.4 130.0 156.1 132.4 112.7 152.2 116.3 135.8 Crushed and broken stone........................................ M a n u fa c tu rin g Meat products............................................................. Dairy products............................................................. Preserved fruits and vegetables............................... Grain mill products..................................................... Bakery products.......................................................... Sugar and confectionery products........................... Fats and oils................................................................ Beverages.................................................................... 122 201 202 203 204 205 206 207 208 209 Miscellaneous food and kindred products.............. Cigarettes..................................................................... 211 Broadwoven fabric mills, cotton................................ 221 Broadwoven fabric mills, manmade......................... Narrow fabric mills...................................................... Knitting mills................................................................. 222 Textile finishing, except wool.................................... 224 225 226 133.0 99.6 108.3 99.2 104.9 90.6 104.6 111.4 104.3 109.6 1 0 1 .2 100.5 107.8 93.8 106.8 109.2 94.4 107.6 108.4 96.4 109.1 115.4 103.2 1 0 2 .0 104.5 106.2 116.7 1 2 0 .1 1 1 2 .6 1 1 1 .8 108.3 120.3 113.8 118.1 117.0 99.2 113.2 99.8 114.1 1 1 0 .1 1 2 0 .2 1 2 0 .0 127.1 101.7 107.6 101.5 126.4 105.2 106.5 130.1 100.9 126.6 133.5 102.9 142.9 135.0 109.1 147.2 135.5 104.1 147.2 117.8 131.7 111.4 127.9 1 2 2 .1 134.0 137.3 131.2 136.2 138.7 142.5 134.1 168.6 117.7 135.9 99.1 171.9 122.4 144.8 81.2 147.6 126.3 150.3 79.2 162.2 79.3 145.3 118.9 138.3 78.5 97.1 93.3 130.7 1 0 0 .2 100.3 150.4 118.7 162.1 149.9 102.3 153.0 1 2 0 .1 208.9 87.1 101.4 216.4 99.5 107.7 105.6 115.6 119.2 116.9 117.2 118.7 105.8 129.2 125.4 91.3 106.6 99.2 131.2 125.8 90.7 105.0 96.8 141.3 128.7 113.1 207.6 125.6 121.9 8 6 .6 109.8 210.9 127.0 122.7 88.4 97.1 107.3 95.6 105.4 92.7 103.1 111.3 96.5 107.5 83.4 1 1 1 .2 89.2 111.4 227 93.2 228 229 232 233 1 1 0 .2 Women's and children's undergarments................. Hats, caps, and millinery............................................ Miscellaneous apparel and accessories.................. Miscellaneous fabricated textile products................ Sawmills and planing mills........................................ 234 235 238 239 242 1 0 2 .1 Millwork, plywood, and structural members............ Wood containers......................................................... Wood buildings and mobile homes.......................... Miscellaneous wood products................................... Household furniture.................................................... 243 244 1 1 1 .2 245 249 103.1 107.7 251 104.5 Office furniture............................................................ 252 Public building and related furniture......................... Partitions and fixtures................................................ Miscellaneous furniture and fixtures......................... Pulp mills..................................................................... 253 254 259 261 95.0 119.8 95.6 103.5 116.7 109.2 1 0 2 .1 104.1 89.2 90.6 99.9 99.8 98.0 116.2 99.6 114.0 79.9 104.6 108.4 104.3 113.7 91.1 91.8 100.7 1 0 2 .6 1 1 1 .6 110.3 126.2 112.9 119.3 78.6 96.1 119.6 106.5 109.1 109.4 117.4 93.6 91.3 107.5 108.1 94.0 108.5 101.9 105.5 107.8 103.3 97.0 161.3 84.3 116.8 109.2 1 1 0 .2 123.1 134.7 141.6 174.5 82.2 103.1 114.2 103.8 115.3 98.3 1 1 1 .8 97.0 115.4 110.5 1 1 0 .6 112.5 116.9 1 2 1 .6 89.1 106.2 100.3 123.4 121.3 94.1 102.5 103.2 161.0 107.4 103.6 122.5 173.3 106.4 181.5 118.3 214.9 128.3 140.6 102.7 99.5 137.3 100.5 157.4 1 0 1 .1 1 2 0 .2 97.5 113.2 132.6 110.7 82.3 99.2 101.4 103.4 103.3 104.4 105.2 102.4 108.4 105.3 85.8 105.5 81.5 107.9 107.9 79.4 89.5 92.9 97.7 89.5 103.5 104.5 106.9 91.1 91.4 93.0 1 0 2 .1 271 90.6 Periodicals.................................................................. Books............................................................................ Miscellaneous publishing.......................................... 272 273 274 93.9 96.6 92.2 102.5 93.0 1 0 2 .0 Manifold business forms........................................... 275 276 89.1 105.8 108.0 94.5 Greeting cards............................................................ 277 1 0 0 .6 Blankbooks and bookbinding................................... Printing trade services............................................... 278 279 281 282 99.4 99.3 106.8 100.9 92.7 96.1 96.7 103.6 1 0 0 .6 1 1 2 .0 109.7 109.7 107.5 283 284 285 286 287 103.8 103.8 106.3 101.4 July 2001 138.0 77.7 147.4 138.0 94.3 92.4 106.7 96.7 114.4 Newspapers................................................................ Monthly Labor Review Digitized for112 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 124.5 87.2 95.8 137.4 123.7 123.4 135.5 1 1 0 .8 92.7 106.1 1 0 0 .6 104.7 1 2 1 .8 118.5 111.7 127.4 97.3 94.5 100.9 102.3 Agricultural chemicals............................................... See footnotes at end of table. 1 2 0 .1 102.3 116.4 1 0 0 .1 263 265 267 Industrial organic chemicals...................................... 1 1 1 .8 99.9 109.4 262 101.3 101.4 126.6 110.4 108.4 108.7 98.0 113.1 103.0 110.5 107.1 Paperboard mills........................................................ Paperboard containers and boxes........................... Miscellaneous converted paper products................ Drugs............................................................................ 192.2 132.3 105.0 1 0 2 .2 Carpets and rugs........................................................ Yarn and thread mills.................................................. Miscellaneous textile goods...................................... Men's and boys' furnishings...................................... Women's and misses' outerwear.............................. Plastics materials and synthetics............................. 148.1 112.4 105.9 103.6 1 0 2 .1 1 0 0 .8 95.9 1 0 0 .0 104.5 105.3 104.3 95.8 99.5 98.7 115.3 105.6 1 1 2 .0 99.5 104.4 102.9 94.6 99.7 108.7 108.8 92.2 99.5 103.8 98.9 104.7 128.9 1 0 1 .2 1 1 0 .0 131.9 1 2 1 .1 1 2 0 .1 174.7 151.9 114.1 1 2 0 .0 1 0 1 .0 97.8 169.5 127.0 187.0 174.5 293.0 108.7 1 1 0 .2 118.6 1 1 1 .6 1 1 2 .0 114.9 108.4 118.0 106.3 126.7 109.7 114.9 127.8 113.5 122.7 131.0 113.5 1 1 0 .6 119.5 105.1 113.3 122.9 127.3 79.0 113.6 77.4 119.5 79.9 79.0 83.6 86.3 115.1 105.4 81.9 103.0 97.5 106.5 82.0 89.0 105.4 1 1 1 .0 102.3 125.3 104.6 87.8 1 0 1 .6 94.8 107.2 76.9 92.5 108.7 116.7 109.3 128.3 89.1 99.3 93.6 1 0 0 .1 115.0 1 0 2 .6 1 0 1 .0 114.5 119.5 108.3 75.2 108.8 77.9 109.9 76.7 92.2 104.2 116.4 90.8 114.5 126.2 1 1 0 .1 125.3 114.2 123.3 116.8 135.4 112.4 116.7 99.9 108.7 118.6 118.0 98.6 112.5 120.9 125.6 99.0 126.4 126.4 105.0 108.5 1 1 0 .0 119.8 1 1 1 .2 1 1 1 .2 128.3 115.2 73.6 126.7 145.8 142.2 103.9 123.3 120.5 170.7 145.7 104.3 122.7 126.8 104.8 116.8 125.6 105.7 117.5 111.3 106.9 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 42. Continued— Annual indexes of output per hour for selected 3-digit SIC industries [1987 = 100] Ind u stry S IC Miscellaneous chemical products............................ 289 291 97.3 109.2 96.1 106.6 1 0 1 .8 107.1 111.3 1 2 0 .1 105.7 123.8 107.8 132.3 Asphalt paving and roofing materials...................... Miscellaneous petroleum and coal products.......... Tires and inner tubes................................................ 295 299 301 98.0 94.8 103.0 94.1 90.6 102.4 100.4 101.5 107.8 108.0 104.2 116.5 104.9 96.3 124.1 1 1 1 .2 Hose and belting and gaskets and packing............ Fabricated rubber products, n.e.c............................ Miscellaneous plastics products, n.e.c.................... Footwear, except rubber.......................................... Flat glass.................................................................... 305 96.1 92.4 97.8 99.7 102.7 306 308 314 321 109.0 105.7 109.9 108.3 94.4 83.6 115.2 114.4 104.2 92.7 123.1 116.7 105.2 97.7 Glass and glassware, pressed or blown................. Products of purchased glass.................................... Cement, hydraulic..................................................... Structural clay products............................................ 104.8 92.6 112.4 109.6 98.6 102.3 97.7 108.3 109.8 108.9 101.5 115.1 111.4 Pottery and related products.................................... 322 323 324 325 326 95.8 99.5 108.7 106.2 119.9 106.8 100.3 112.9 105.9 125.6 114.0 108.4 Concrete, gypsum, and plaster products................ Miscellaneous nonmetallic mineral products.......... Blast furnace and basic steel products................... Iron and steel foundries............................................ Primary nonferrous metals....................................... 327 329 331 332 333 102.3 95.4 109.7 106.1 102.3 1 0 1 .2 102.5 104.3 117.0 107.2 101.9 104.6 104.5 133.6 Nonferrous rolling and drawing................................ Nonferrous foundries (castings).............................. Miscellaneous primary metal products.................... Metal cans and shipping containers........................ Cutlery, handtools, and hardware............................ 335 336 339 341 342 92.7 104.0 113.7 117.6 97.3 91.0 103.6 109.1 122.9 96.8 96.0 103.6 114.5 127.8 Plumbing and heating, except electric.................... Fabricated structural metal products....................... Metal forgings and stampings.................................. Metal services, n.e.c................................................. Ordnance and accessories, n.e.c............................ 343 344 346 347 348 1 0 2 .6 1 0 2 .0 98.8 95.6 104.7 82.1 1 0 0 .0 1 1 1 .6 1 2 0 .6 8 8 .6 84.6 Miscellaneous fabricated metal products............... Engines and turbines................................................ Farm and garden machinery.................................... Construction and related machinery........................ Metalworking machinery........................................... 349 351 352 353 354 97.5 106.5 116.5 107.0 97.4 Special industry machinery...................................... General industrial machinery.................................... Computer and office equipment.............................. Refrigeration and service machinery....................... Industrial machinery, n.e.c....................................... 355 356 357 358 359 107.5 101.5 138.1 103.6 107.3 Electric distribution equipment................................. Electrical industrial apparatus Household appliances............................................... Electric lighting and wiring equipment.................... Communications equipment..................................... 361 362 363 364 366 Electronic components and accessories................. Miscellaneous electrical equipment & supplies...... Motor vehicles and equipment................................. Aircraft and parts....................................................... Ship and boat building and repairing....................... 1990 1 0 1 .1 84.5 1 0 1 .1 1991 94.0 107.8 104.5 110.7 92.9 99.4 81.5 105.8 112.9 99.1 96.4 1992 1993 1994 1999 155.7 128.1 169.5 87.4 131.1 113.1 87.1 138.8 123.1 96.5 149.1 124.7 98.5 144.2 115.7 90.7 145.5 104.6 121.5 107.4 1 2 1 .0 1 2 0 .8 1 2 1 .0 113.0 97.6 117.1 99.6 113.5 125.3 129.9 121.4 107.6 112.7 119.1 132.3 133.8 110.9 114.0 114.0 140.8 141.2 131.6 127.7 1 1 0 .1 124.7 126.1 101.5 115.7 121.4 106.1 124.3 1 2 2 .0 128.3 125.1 133.1 111.9 123.2 135.2 1 2 2 .0 109.3 101.5 106.3 142.4 113.0 105.3 104.5 107.8 142.6 112.7 107.3 110.4 147.5 116.2 107.6 114.6 155.0 1 1 2 .8 1 2 0 .8 1 2 1 .1 1 1 1 .0 1 1 0 .8 1 1 2 .0 125.8 114.4 114.6 148.9 126.2 131.2 98.3 108.5 1 0 1 .2 111.3 132.3 104.0 134.5 140.9 109.2 99.2 117.8 152.2 144.2 111.3 104.0 122.3 149.6 155.2 118.2 111.3 127.0 136.2 160.3 114.6 115.2 131.5 140.0 163.8 115.7 122.7 130.8 150.4 160.3 123.9 98.4 1 0 2 .0 104.8 108.7 109.1 107.7 108.5 123.0 83.6 109.2 103.9 103.7 118.6 106.5 113.6 128.4 87.5 127.3 111.9 130.3 112.7 1 2 0 .2 124.4 93.7 125.9 127.3 96.6 126.9 112.7 130.3 127.9 92.2 108.3 136.6 137.2 123.3 114.9 107.7 136.9 141.2 132.5 119.2 111.5 145.9 148.5 137.5 119.8 110.3 151.2 125.5 137.2 123.5 1 0 0 .1 1 1 2 .1 107.9 1 1 2 .1 1 1 2 .6 105.8 109.3 127.7 87.6 1 0 1 .1 1 0 2 .0 103.3 113.9 109.2 118.6 108.2 107.4 103.2 122.3 125.0 117.7 109.9 106.6 122.7 134.7 113.6 104.8 258.6 108.6 118.5 1 2 1 .2 106.7 328.6 110.7 127.4 132.3 109.0 469.4 112.7 1 0 2 .0 104.3 149.6 100.7 109.0 195.7 104.9 117.0 106.3 107.7 105.8 99.9 123.8 106.5 107.1 106.5 97.5 129.1 119.6 117.1 115.0 105.7 154.9 1 2 2 .2 132.9 123.4 107.8 163.0 131.8 134.9 131.4 113.4 186.4 367 369 371 372 373 133.4 90.6 102.4 98.9 103.7 154.7 98.6 96.6 108.2 96.3 189.3 101.3 104.2 112.3 102.7 217.9 108.2 106.2 115.2 106.2 Railroad equipment................................................... Motorcycles, bicycles, and parts............................. Guided missiles, space vehicles, parts................... Search and navigation equipment........................... Measuring and controlling devices.......................... 374 375 376 381 382 141.1 93.8 116.5 112.7 106.4 146.9 99.8 110.5 118.9 113.1 147.9 108.4 151.0 130.9 Medical instruments and supplies............................ Ophthalmic goods...................................................... Photographic equipment & supplies........................ Jewelry, silverware, and plated ware....................... Musical instruments................................................... 384 385 386 391 393 116.9 118.7 125.1 1 2 2 .1 114.8 138.8 114.7 151.0 1 2 0 .8 131.7 125.1 1 1 0 .0 1 1 1 .2 960.2 115.0 129.3 1350.6 121.4 127.5 139.3 111.4 1840.2 123.2 134.3 142.8 164.2 142.9 147.5 162.3 150.3 129.2 276.0 146.6 162.9 150.2 132.4 327.1 107.0 140.7 2 0 0 .6 143.9 154.3 127.4 116.9 229.5 275.3 274.1 110.5 108.8 109.6 103.8 401.5 114.1 106.7 107.9 98.0 514.9 123.1 107.2 113.0 99.2 613.4 128.3 116.3 114.7 105.3 768.0 135.3 125.2 140.1 136.5 139.6 1 0 2 .0 1 1 2 .6 150.0 120.3 149.5 146.4 148.3 125.5 129.4 142.2 150.5 184.2 120.4 136.5 149.5 142.4 189.1 127.7 142.4 149.1 143.5 205.1 121.4 158.2 139.7 152.9 131.5 167.2 129.5 139.8 188.2 128.7 1 0 0 .2 1 0 2 .6 86.9 78.8 147.4 196.3 121.5 114.2 82.9 158.6 199.1 124.8 113.1 81.4 160.2 229.5 147.2 133.9 86.4 110.5 1 2 2 .1 1 2 2 .1 119.9 129.1 124.0 152.5 125.1 118.9 132.1 133.8 123.5 144.5 116.4 96.7 96.0 127.3 157.8 126.9 96.7 95.6 126.7 160.6 132.7 99.5 88.7 143.0 150.8 127.3 113.7 134.0 109.4 681.3 114.7 141.4 134.1 114.8 127.1 143.6 134.0 139.6 124.0 128.7 119.6 119.3 106.0 95.8 96.9 1998 1 2 0 .6 1 0 1 .6 1 1 0 .2 1997 120.3 149.2 108.3 107.8 99.3 97.1 1996 142.0 1 0 1 .6 1 2 1 .2 1995 1 2 1 .0 1 2 1 .8 See footnotes at end of table. Monthly Labor Review July 2001 113 Current Labor Statistics: Productivity Data 42. Continued—Annual indexes of output per hour for selected 3-digit SIC industries [1987 = 100] 1 99 0 1991 1 99 2 1 99 3 1 994 1 99 5 1 99 6 1 99 7 1998 1 99 9 In d u s try S IC Toys and sporting goods............................................ 394 108.1 109.7 104.9 114.2 109.7 Pens, pencils, office, and art supplies...................... 395 118.2 116.8 111.3 1 1 1 .6 129.9 Costume jewelry and notions..................................... 396 105.3 106.7 1 1 0 .8 115.8 129.0 Miscellaneous manufactures..................................... T ra n s p o r ta tio n 399 106.5 109.2 109.5 107.7 106.1 Railroad transportation................................................ 4011 118.5 127.8 139.6 145.4 150.3 156.2 167.0 169.8 173.3 182.3 Trucking, except lo c a l 1 .............................................. 4213 1 1 1 .1 116.9 123.4 126.6 129.5 125.4 130.9 132.4 129.9 131.6 U.S. postal se rvice 2 ................................................... 431 104.0 103.7 104.5 107.1 106.6 106.5 104.7 108.3 109.7 110.3 Air transportation ' ...................................................... 4512,13,22 (pts.) 92.9 92.5 96.9 1 0 0 .2 105.7 108.6 1 1 1 .1 1 1 1 .6 110.7 108.3 Telephone communications....................................... 481 113.3 119.8 127.7 135.5 142.2 148.1 159.5 160.9 170.3 189.1 Radio and television broadcasting............................ 104.9 106.1 108.3 106.7 1 1 0 .1 109.6 105.8 1 0 1 .1 100.7 1 0 1 .8 Cable and other pay TV services.............................. 483 484 92.6 87.6 88.5 85.3 83.4 84.5 Electric utilities............................................................. 491,3 (pt.) 1 1 0 .1 113.4 115.2 1 2 0 .6 150.5 81.5 162.7 492,3 (pt.) 105.8 109.6 1 1 1 .1 1 2 1 .8 135.0 137.1 83.5 160.1 Gas utilities.................................................................... T ra d e 126.8 125.6 81.9 146.5 145.9 158.6 144.4 145.0 Lumber and other building materials dealers......... 521 104.3 111.4 118.9 117.8 1 2 1 .6 1 2 1 .8 134.2 142.3 523 106.8 127.8 115.3 130.9 115.5 133.5 119.5 134.8 119.0 163.5 137.8 163.2 525 107.6 115.2 114.2 Hardware stores........................................................... 102.3 100.4 108.7 106.4 Paint, glass, and wallpaper stores............................ Retail nurseries, lawn and garden supply stores.... Department stores....................................................... 526 84.7 89.3 1 0 1 .2 133.7 151.2 531 96.8 1 0 2 .0 135.5 147.4 Variety stores................................................................ 533 539 154.4 158.8 118.6 541 542 96.6 98.9 319.5 195.2 95.4 546 Auto and home supply stores.................................... Gasoline service stations............................................ 551 553 554 Men's and boy's wear stores..................................... 119.9 125.7 131.6 124.0 144.1 127.5 132.5 129.3 143.7 142.2 150.2 1 1 2 .8 118.0 109.4 131.2 108.1 108.5 1 1 1 .2 113.6 135.2 U t ilit ie s 84.7 113.9 1 2 1 .2 117.0 113.4 117.4 136.4 105.4 107.1 110.4 115.9 123.5 127.5 128.8 173.7 140.4 191.5 164.2 197.4 211.3 238.4 257.7 268.7 124.8 167.3 96.0 97.7 170.3 91.7 86.4 90.8 92.2 95.7 91.2 96.5 99.2 96.5 167.6 92.1 185.7 96.3 90.8 96.7 164.8 95.4 6 8 .1 106.7 104.9 103.6 1 0 0 .2 561 103.0 115.6 104.8 121.9 562 106.6 Family clothing stores................................................. Shoe stores.................................................................. 565 566 Furniture and homefurnishings stores..................... 571 572 Miscellaneous general merchandise stores............ 149.3 95.7 93.9 94.4 86.5 85.3 83.0 75.9 67.6 107.4 108.6 109.7 108.1 108.7 1 0 0 .8 105.3 109.1 109.1 108.2 108.8 1 0 1 .6 108.1 113.0 111.9 116.0 1 1 0 .2 115.9 1 2 1 .1 126.1 119.5 1 2 1 .8 127.2 121.4 126.1 122.3 140.6 154.6 123.6 130.0 130.4 139.9 136.3 157.3 133.9 145.2 1 1 1 .2 129.8 154.2 176.1 190.5 107.8 107.9 111.5 107.8 118.6 115.5 121.5 117.3 127.7 141.8 146.9 150.2 153.1 156.5 139.2 145.0 105.4 106.7 113.9 115.5 113.3 118.0 124.2 1 2 1 .1 129.8 139.9 154.5 199.3 208.1 153.5 218.4 127.2 181.4 573 121.5 179.1 117.4 138.4 151.1 134.1 104.3 151.9 123.6 140.7 148.4 104.6 130.7 114.7 Eating and drinking places......................................... 581 104.5 103.8 103.4 103.8 1 0 2 .1 1 0 2 .0 1 0 0 .6 106.3 108.0 109.9 1 1 1 .1 113.9 1 0 0 .1 104.7 593 594 106.9 102.3 1 0 1 .8 Used merchandise stores........................................... Miscellaneous shopping goods stores..................... 105.9 103.0 107.6 109.6 115.7 109.5 Liquor stores................................................................. 591 592 116.8 119.5 107.2 109.0 107.5 111.5 Nonstore retailers....................................................... 596 1 1 1 .1 112.5 126.5 Fuel dealers................................................................. 598 84.5 85.3 84.2 599 114.5 104.0 602 107.7 1 1 0 .1 Laundry, cleaning, and garment services................ 701 721 Photographic studios, portrait.................................... Beauty shops................................................................ 722 723 96.2 102.3 98.2 99.3 99.9 92.1 97.5 Barber shops................................................................ 724 100.7 726 753 91.2 107.9 783 118.1 Grocery stores............................................................. Meat and fish (seafood) markets............................... Retail bakeries............................................................. New and used car dealers......................................... Household appliance stores....................................... Radio, television, computer, and music stores....... 99.3 83.8 260.3 183.9 314.6 1 0 1 .6 1 0 2 .0 104.3 119.7 125.6 129.8 1 2 0 .6 113.8 132.7 109.9 140.3 116.5 163.6 117.1 123.1 125.3 129.1 138.8 114.6 181.9 145.2 132.2 149.0 152.4 111.4 186.5 109.0 2 2 2 .2 99.0 173.3 112.4 208.0 91.8 105.8 115.1 112.5 118.1 125.8 127.0 140.2 147.8 157.3 161.0 1 1 1 .0 118.5 121.7 126.4 129.7 133.0 132.6 135.2 108.0 99.3 95.8 106.5 99.9 109.9 105.0 108.3 1 1 0 .0 108.2 1 1 1 .6 113.5 1 2 1 .8 97.0 109.0 114.1 108.5 1 2 1 .6 100.9 109.8 110.7 107.6 116.2 95.8 110.5 106.6 116.2 104.8 110.5 105.1 113.3 94.9 89.9 113.2 128.8 150.4 1 0 0 .2 1 0 0 .1 121.9 98.7 105.7 115.7 103.8 105.1 1 2 1 .6 97.6 116.1 101.9 117.2 157.4 104.2 124.9 138.0 99.7 127.6 118.2 114.8 113.8 105.0 104.1 103.4 106.1 110.5 F in a n c e a n d s e rv ic e s Motion picture theaters.............................................. ' Refers to output per employee 2 1 0 1 .1 118.8 104.3 114.3 110.4 n.e.c. = not elsewhere classified Refers to ouput per full-tim e equivalent employee year on fiscal basis. 114 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1 0 1 .8 July 2001 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 43. U n e m p lo y m e n t rates, a p p ro x im a tin g U.S. c o n c e p ts , in n in e c o u n trie s , q u a rte rly d a t a s e a s o n a lly a d ju s te d A n n u a l a v e ra g e C o u n try 1 99 9 1 99 9 2000 1 II 2000 III IV 1 II III IV United States........ 4.2 4.0 4.3 4.3 4.2 4.1 4.1 4.0 4.0 Canada.................. 6 .8 5.8 7.1 7.1 6 .8 6 .2 6 .0 5.8 5.8 5.7 Australia................ 7.2 6 .6 7.5 7.4 7.1 7.0 6 .8 6.7 6.3 6.5 4.7 4.7 11.4 4.8 11.3 4.7 4.8 1 1 .2 4.8 9.7 4.8 France 1 .................. 1 1 .2 1 0 .8 1 0 .2 4.7 9.7 4.7 9.6 4.8 9.2 8 .8 8 .8 8.7 8.4 8.3 8 .2 8 .1 11.5 8.3 10.7 8 .8 Italv 1 ,2 .................... 1 1 .8 11.7 11.5 1 1 .2 11.3 1 0 .8 1 0 .6 1 0 .1 Sweden 1 ................ 7.1 5.9 7.1 7.0 7.1 7.1 6.7 6 .0 5.6 5.2 United KingdomV, 6 .1 6 .2 6 .1 5.9 5.9 5.8 5.5 5.4 - 8.7 1 - Preliminary for 2000 for Japan, France, Germany (unified), Italy, and Sweden and for 1999 onward for the United Kingdom. 2 Quarterly rates are for the first month of the quarter. dicators of unemployment under U.S. concepts than the annual figures. See "Notes on the data" for information on breaks in series. For further qualifications Comparative NOTE: Quarterly figures for France and Germany are calculated by applying annual adjustment factors to current published data, and therefore should be viewed as less precise in- 4.0 Civilian Labor and Force historical Statistics, data, Ten see Coun- tries, 1959-2000 (Bureau of Labor Statistics, Mar. 16, 2001). Dash indicates data not available. Monthly Labor Review July 2001 115 Current Labor Statistics: 44. International Comparison Annual data: Employment status of the working-age population, approximating U.S. concepts, 10 countries [Numbers in thousands] E m p lo y m e n t s ta tu s a n d c o u n try 1991 1992 1993 1994 1995 1996 1997 1998 1999 126,346 128,105 129,200 131,056 132,304 133,943 136,297 137,673 139,368 14,128 8,490 14,168 8,562 14,299 8,619 14,387 8,776 14,500 9,001 14,650 9,127 14,936 9,221 15,216 9,347 15,513 9,470 2000 Civilian labor force United States1.......................................................... Canada..................................................................... Australia......................................................... Japan..................................................................... 64,280 65,040 65,470 65,780 65,990 66,450 67,200 67,240 67,090 France....................................................................... Germany2 ........................................................ 24,470 39,130 24,570 39,040 24,640 39,140 24,780 39,210 24,830 39,100 25,090 39,180 25,210 39,480 25,540 39,520 25,860 39,630 Italy............................................................................... Netherlands................................................. Sweden............................................................. United Kingdom......................................................... 22,940 6,780 4,591 28,610 22,910 6,940 4,520 28,410 22,570 7,050 4,443 28,310 22,450 7,200 4,418 28,280 22,460 7,230 4,460 28,480 22,570 7,440 4,459 28,620 22,680 7,510 4,418 28,760 22,960 7,670 4,402 28,870 23,130 7,750 4,430 66.3 65.5 63.6 63.3 55.6 58.0 47.9 58.2 64.5 62.8 6 6 .6 6 6 .6 6 6 .8 65.2 63.9 63.1 55.5 57.6 47.3 59.0 63.7 62.5 64.9 64.6 62.9 55.3 57.3 47.1 58.9 64.1 62.7 64.7 64.6 63.0 55.5 57.4 47.1 60.3 64.0 62.7 140,863 15,745 9,682 66,990p _ _ - 29,090p Participation rate3 I In ito H 6 6 .2 Canada.......................................................... Australia................................................. Japan...................................................... France................................................................. 66.7 64.1 63.2 55.9 58.9 47.7 56.8 67.0 63.7 ^ o rm a m /^ Italy............................................................. Netherlands.................................................................... Sweden.......................................................................... United Kingdom.............................................................. 66.4 65.9 63.9 63.4 55.8 58.3 47.5 57.7 65.7 63.1 67.1 65.0 64.3 63.2 55.3 57.7 47.2 60.6 63.3 62.8 67.1 65.4 64.4 62.8 55.7 57.7 47.6 61.4 62.8 62.7 67.1 65.8 64.2 62.4 56.0 67.2 65.9 64.7 62.0P _ 57.9P 47.8 61.5 _ _ _ 63 2P 62.9P _ Employed United States 1................................ Canada........................................................ Australia...................................................................... Japan.............................................................. France.................................................................. R firm a n u ^ Italy.................................................................... Netherlands................................................... Sweden................................................................ United Kingdom................................................ 117,718 118,492 120,259 123,060 124,900 126,708 129,558 131,463 133,488 135,208 12,747 7,676 62,920 12,672 7,637 63,620 12,770 7,680 63,810 13,027 7,921 63,860 13,271 8,235 63,890 13,300 8,344 64,200 13,705 8,429 64,900 14,068 8,597 64,450 14,456 8,785 63,920 14,827 9,043 63,790p 2 2 ,1 2 0 2 2 ,0 2 0 36,920 21,360 6,380 4,447 26,090 36,420 21,230 6,540 4,265 25,530 21,740 36,030 20,270 6,590 4,028 25,340 21,730 35,890 19,940 6,680 3,992 25,550 21,910 35,900 19,820 6,730 4,056 26,000 21,960 35,680 19,920 6,970 4,019 26,280 22,090 35,570 19,990 7,110 3,973 26,740 22,520 35,830 22,970 36,170 20,460 7,490 4,117 _ _ 27,330p - 2 0 ,2 1 0 7,360 4,034 27,050 _ _ Employment-population ratio 4 61.7 61.5 61.7 62.5 62.9 63.2 63.8 64.1 64.3 64.5 58.9 57.0 62.0 50.0 54.4 58.5 56.6 61.7 49.0 53.4 59.0 57.7 61.3 48.7 52.8 59.4 59.1 60.9 48.8 52.6 59.1 59.1 60.9 48.5 52.2 59.7 58.8 61.0 48.5 52.0 60.4 59.2 60.2 49.1 52.3 61.3 59.6 59.4 49.8 62.1 60.4 Germany2 .................................................. 60.2 57.9 61.8 50.6 55.5 Italy.................................................... Netherlands......................................... Sweden..................................................... United Kingdom.......................................... 44.5 53.4 64.9 58.0 44.0 54.4 62.0 56.7 43.0 54.4 58.5 56.2 42.0 54.8 57.6 56.5 41.5 54.9 58.3 57.2 41.6 56.5 57.7 57.6 41.6 57.4 56.9 58.3 41.9 58.9 57.6 58.7 United States1............................................ Canada.............................................................. Australia............................................................. Japan.......................................................... France........................................................... 59.0P - 52.8P 42.3 59.4 _ 58 7P 59.1p _ Unemployed United States1........................................................ Canada.......................................................... Australia...................................................... Japan............................................................ 8,628 9,613 8,940 7,996 7,404 7,236 6,739 6 ,2 1 0 5,880 5,665 1,381 814 1,360 1,496 925 1,420 1,530 939 1,660 1,359 856 1,920 1,229 766 1,230 791 2,300 1,148 750 2,790 1,058 685 3,170 918 638 2 ,1 0 0 1,271 783 2,250 France.......................................................................... 2,350 Germany2 ..................................................... 2 ,2 1 0 2,550 2,620 2,900 3,110 3,060 3,320 2,920 3,200 3,130 3,500 3,130 3,910 3,020 3,690 2,890 3,460 Netherlands.................................................. Sweden.................................................... United Kingdom.................................................... 1,580 400 144 2,520 1,680 390 255 2,880 2,300 460 415 2,970 2,510 520 426 2,730 2,640 510 404 2,480 2,650 470 440 2,340 2,690 400 445 2,750 310 368 1,820 2,670 260 313 2 ,0 2 0 1,760p 3,200p - _ _ - Unemployment rate United States1........................................ Canada............................................................. Australia............................................................... Japan............................................................ France............................................................. Germany2 ......................................................... Netherlands.................................................. Sweden....................................................... United Kingdom...................................................... 6 .8 7.5 6.9 9.8 9.6 1 0 .6 10.7 10.9 2.5 1 0 .8 6.1 5.6 5.4 4.9 4.5 4.2 4.0 9.4 9.7 2.9 12.3 8.5 8.5 8.5 3.2 8.7 8 .2 7.5 6 .8 5.8 2.1 2 .2 9.6 5.6 10.4 6.7 1 1 .8 6.9 5.9 3.1 7.3 5.6 5.6 1 0 .2 1 1 .2 1 1 .8 6.5 9.3 10.5 7.2 9.6 9.7 7.1 9.1 8.7 8 .8 10 .1 7.9 1 1 .8 8 .2 8 .6 8 .6 8 .0 3.4 12.5 8.9 3.4 12.4 9.9 4.1 7.2 4.7 1 1 .8 1 1 .2 11.7 6.3 9.9 11.9 5.3 10.11 8 .2 7.01 9.3 8.7 8.3P 1 2 .0 11.5 3.4 7.1 10 7P 4.0 8.4 6.3 ________ &AP Labor force as a percent of the workina-aae DODulation. additional information, see the box note under "Employment and Unemployment Data" in the notes to this section. 2 Data from 1991 onward refer to unified Germany. See Comparative Civilian Labor Force Statistics, Ten Countries, 1959-2000, Mar. 16, 2001, on the Internet at http://stats.bls.gov/flsdata.htm . 116 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 Employment as a percent of the workina-aae population. NOTE: See Notes on the data for information on breaks in series for the l States, France, Germany, Italy, the Netherlands, and Sweden. Dash indicates data are not available, p = preliminary. 6 .6 4.8P 9.7P 5 gp https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 45. A n n u a l in d e x e s o f m a n u fa c tu rin g p ro d u c tiv ity a n d r e la te d m e a s u re s , 12 c o u n trie s [1992 = 100] Item and coun try 1960 1970 1980 1988 1989 1990 1991 1993 1994 1995 1996 1997 1998 1999 Output per hour 38.7 14.0 18.0 29.9 21.8 29.2 20.2 18.6 36.7 27.3 31.2 56.6 38.0 32.9 52.7 43.0 52.0 37.9 38.1 57.8 52.2 44.7 70.5 75.1 63.9 65.4 90.3 66.5 77.2 65.9 69.2 76.7 73.1 56.1 96.9 90.9 84.8 92.0 94.1 87.5 91.5 86.7 93.7 92.1 90.5 82.3 95.7 93.7 89.5 96.9 99.6 91.9 94.6 89.4 97.1 94.6 93.2 86.2 96.9 95.7 95.4 96.8 99.1 93.5 99.0 92.5 98.6 96.6 94.6 88.3 97.8 95.3 99.4 99.1 99.6 96.9 99.0 95.2 99.6 97.5 95.5 92.2 102.1 104.5 100.5 102.5 104.5 100.6 101.6 102.9 101.4 100.6 107.3 104.0 107.3 109.9 101.8 108.4 113.8 111.0 109.3 113.2 117.0 109.5 115.8 115 5 121.1 112.8 121.4 127.0 112.5 120.4 134.8 115.2 124.1 108.5 110.1 105.6 112.7 101.4 119.4 106.8 114.5 113.2 109.3 117.7 102.0 121.9 104.8 115.0 116.8 109.5 119.7 102.0 124.5 103.2 122.6 122.4 111.5 125.7 103.0 133.0 104.0 124.0 126.7 111.1 127.8 103.9 135.6 104.6 128.9 128.5 112.9 103.9 139.5 109.2 34.2 10.7 30.7 40.8 31.0 41.5 21.9 31.7 56.5 45.9 67.7 60.6 38.8 57.6 68.0 64.1 70.9 45.8 59.5 89.1 80.7 90.3 75.8 86.0 59.9 78.2 91.3 88.7 85.3 80.4 77.4 103.6 90.7 87.2 103.2 110.1 84.6 102.4 112.6 90.2 101.6 108.6 96.3 98.3 99.0 101.4 103.5 104.6 96.0 111.1 113.2 95.4 118.4 118.1 100.6 121.3 119.8 106.7 127.7 128.1 111.1 133.5 133.1 103.6 139.3 141.3 103.9 100.8 92.2 90.9 94.5 92.8 105.3 109.8 101.4 104.3 97.2 94.0 98.1 96.9 101.3 110.9 105.4 102.7 99.1 99.1 99.6 100.1 100.2 110.1 105.3 101.7 99.8 102.3 99.2 100.6 98.3 104.1 100.0 99.0 95.7 92.5 96.4 98.2 102.7 101.9 101.4 109.3 114.7 109.7 112.6 115.3 111.5 95.2 102.2 104.2 106.7 117.1 106.1 95.3 107.2 107.8 109.0 128.4 107.8 93.5 105.6 108.4 110.1 131.1 108.2 96.3 108.3 114.1 115.7 138.6 109.6 100.9 110.3 116.6 117.6 144.6 109.9 102.2 111.4 114.0 150.7 109.7 92.1 88.3 76.3 170.7 136.5 142.3 142.3 108.7 170.6 154.0 168.3 217.3 104.4 107.1 102.3 174.7 129.0 149.0 136.3 120.9 156.2 107.5 114.6 93.8 119.7 101.1 133.3 110.5 122.0 111.8 106.6 121.2 99.8 101.5 107.2 105.4 99.3 108.9 99.0 107.1 120.2 100.8 102.3 104.7 105.8 99.3 109.7 99.8 104.8 113.5 100.9 104.3 103.7 105.9 100.1 107.7 100.4 103.9 102.0 101.5 102.1 103.0 103.3 104.2 101.4 100.1 95.6 94.7 94.8 95.1 91.0 93.6 103.6 103.0 93.7 93.6 92.4 86.5 96.7 104.0 106.4 92.0 92.0 105.5 113.5 91.5 89.8 89.5 78.7 97.1 105.2 118.3 86.1 90.5 91.6 84.2 98.0 103.7 109.4 92.2 91.0 91.0 80.1 96.5 89.9 79.6 99.3 103.3 122.7 83.8 91.5 88.6 79.5 98.6 154.7 202.1 124.0 155.3 121.4 123.2 119.0 122.3 116.4 119.2 109.0 108.5 94.9 97.5 98.1 99.4 105.3 102.9 105.3 104.8 104.2 105.4 106.6 105.0 108.0 100.5 United States................................................ Canada......................................................... Japan........................................................... Belgium......................................................... Denmark....................................................... France......................................................... Germany....................................................... Italy.............................................................. Netherlands.................................................. Norway......................................................... Sweden........................................................ United Kingdom............................................. 14.9 9.9 4.3 5.4 4.6 4.3 8.1 1.6 6.4 4.7 4.1 3.1 23.7 17.0 16.5 13.7 13.3 10.3 20.7 4.7 20.2 11.8 10.7 6.3 55.6 47.7 58.6 52.5 49.6 40.8 53.6 28.4 64.4 39.0 37.3 33.2 84.0 77.8 79.2 81.1 82.9 81.6 79.1 69.3 87.7 83.3 71.8 67.7 86.6 82.5 84.2 85.9 87.7 86.0 83.2 75.9 88.5 87.2 79.4 72.9 90.8 89.5 90.7 90.1 92.7 90.6 89.4 84.4 90.8 92.3 87.8 80.9 95.6 94.7 95.9 97.3 95.9 96.2 92.1 93.6 95.2 97.5 95.5 90.5 102.7 99.6 104.6 104.8 104.6 103.0 106.1 107.5 103.7 101.5 97.2 104.3 105.6 100.4 106.7 106.1 105.6 112.3 107.8 108.2 104.4 99.8 106.5 107.9 103.6 109.5 109.2 108.4 118.5 112.8 110.6 109.2 106.3 107.4 109.3 102.8 110.9 112.0 110.2 125.2 120.3 113.2 113.6 114.2 108.2 111.4 106.7 113.9 115.2 113.0 128.0 125.4 115.8 118.7 119.7 111.4 117.3 110.8 115.8 116.0 114.9 128.9 123.0 118.3 126.2 123.3 117.0 123.2 110.8 117.7 116.0 119.3 130.8 126.5 133.4 127.4 122.6 Unit labor costs: National currency basis United States................................................. Canada......................................................... Japan........................................................... Belgium......................................................... Denmark....................................................... France.......................................................... Germany....................................................... Italy.............................................................. Netherlands.................................................. Norway......................................................... Sweden........................................................ United Kingdom............................................. 25.6 30.9 30.1 15.4 19.5 27.8 7.9 34.4 12.9 15.0 9.8 30.1 43.3 41.7 25.2 24.0 39.8 12.4 52.9 20.4 20.6 14.1 78.8 63.2 91.7 80.3 55.0 61.3 69.4 43.1 93.0 50.8 51.0 59.1 86.7 85.2 93.4 88.1 88.2 93.3 86.5 79.9 93.6 90.4 79.4 82.2 90.5 88.0 94.0 38.7 88.1 93.6 87.9 84.9 91.1 92.2 85.1 84.6 93.7 92.3 95.0 93.0 93.6 96.8 90.3 91.3 92.1 95.6 92.8 91.6 97.7 99.7 96.5 98.1 96.3 99.3 93.1 98.4 95.5 100.0 100.0 98.2 100.6 97.6 104.1 102.3 100.1 102.4 104.5 104.4 102.3 100.9 90.6 100.3 98.5 94.3 104.9 97.9 93.0 97.3 102.0 102.1 96.0 102.9 83.6 99.7 94.8 95.5 100.1 96.4 93.8 94.7 104.7 103.2 94.0 107.1 87.2 102.5 93.5 95.9 95.8 95.6 100.9 95.9 107.2 109.9 94.6 111.4 91.7 104.8 92.0 95.9 93.8 93.3 102.0 92.2 104.6 112.4 92.2 115.2 90.0 107.1 92.4 98.8 96.2 93.7 102.8 92.7 101.8 110.8 92.5 121.5 90.9 111.9 91.4 98.1 94.9 93.4 108.9 92.6 101.8 112.0 128.5 91.3 112.3 Unit labor costs: U.S. dollar basis United States................................................. Canada......................................................... Japan........................................................... Belgium......................................................... Denmark....................................................... France.......................................................... Germany....................................................... Italy.............................................................. Netherlands................................................... Noway......................................................... Sweden........................................................ United Kingdom............................................. 32.0 10.9 19.4 13.5 21.1 10.4 15.6 16.0 11.3 16.9 15.6 34.8 15.3 27.0 20.3 23.0 17.1 24.4 25.7 17.8 23.1 19.2 78.8 65.3 51.3 88.3 58.9 76.8 59.6 62.0 82.3 63.9 70.3 77.8 86.7 83.6 92.4 77.0 79.0 82.9 76.9 75.6 83.2 86.1 75.4 82.9 90.5 89.8 86.3 72.3 72.6 77.6 73.0 76.2 75.5 82.9 76.8 78.5 93.7 95.6 83.1 89.5 91.3 94.1 87.3 93.8 88.9 95.0 91.3 92.5 97.7 105.1 90.9 92.3 90.8 93.1 87.5 97.6 89.8 95.7 96.3 98.2 100.6 91.4 118.8 95.1 93.2 95.6 98.6 81.8 96.8 88.3 67.7 85.3 98.5 83.4 130.1 94.2 88.3 92.9 98.2 78.1 92.8 90.7 63.1 86.5 94.8 84.1 135.1 105.2 101.1 100.6 114.1 78.0 103.0 105.0 71.2 91.6 93.5 85.0 111.7 99.3 105.0 99.2 111.3 87.8 98.6 107.1 79.7 92.6 92.0 83.6 98.3 83.7 93.1 83.6 94.1 81.3 83.0 101.1 68.6 99.3 92.4 80.5 93.1 83.0 92.6 83.2 90.3 78.6 82.0 100.0 66.6 105.0 91.4 79.8 105.7 79.3 94.1 79.6 86.6 75.9 102.2 64.3 102.8 United States................................................. Canada......................................................... Japan.......................................................... Denmark....................................................... France......................................................... Germany...................................................... Italy.............................................................. Netherlands.................................................. Norway......................................................... Sweden........................................................ United Kingdom............................................. - Output United States................................................. Canada......................................................... Japan........................................................... Denmark....................................................... Germany....................................................... Italy.............................................................. Netherlands................................................... Norway......................................................... Sweden........................................................ United Kingdom............................................. Total hours United States................................................. Canada........................................................ Japan........................................................... Belgium........................................................ Denmark....................................................... France......................................................... Germany....................................................... Italy.............................................................. Sweden........................................................ United Kingdom............................................. - - Compensation per hour NOTE: Data for Germany for years before f 992 are for the former West Germany. Data for 1992 onward are for unified Germany. Dash indicates data not available. Monthly Labor Review July 2001 117 Current Labor Statistics: 46. Injury and Illness O c c u p a tio n a l injury a n d illness rates b y industry,' U nited States Incidence rates per 100 full-tim e w orkers3 industry and type of case 1988 1989 1 1990 1991 1992 1993 4 1994 4 1995 4 1 9 9 6 4 1997 4 1998 4 1999 4 P R IV A T E S E C T O R 5 Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 8 .6 8 .6 8 .8 4.0 76.1 4.0 78.7 4.1 84.0 8.4 3.9 86.5 8.9 3.9 93.8 8.5 3.8 8.4 3.8 3.6 7.4 3.4 7.1 3.3 - - - - - 10.9 5.6 10.9 5.7 100.9 1 1 .6 1 0 .8 1 1 .6 1 1 .2 1 0 .0 5.9 5.4 126.9 5.0 4.7 9.7 4.3 8.7 3.9 8.4 4.1 1 1 2 .2 5.4 108.3 - - - - - 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 3.9 5.4 3.2 5.9 3.7 - - - - - 14.3 13.0 13.1 5.8 161.9 1 2 .2 1 1 .8 1 0 .6 4.9 - 9.5 4.4 - 8 .6 5.5 - 9.9 4.5 - 8 .8 5.5 - 4.0 148.1 - 4.2 - 3.7 - 8.1 6.7 3.1 - 6.3 3.0 - 7.9 3.9 - 7.3 3.4 - 4.9 2.9 - 4.4 2.7 - A g ric u ltu re , fo re s try , a n d fis h in g 5 Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 1 0 1 .8 M in in g Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 8 .8 5.1 152.1 6 .2 C o n s tru c tio n Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 6 .8 6 .8 142.2 14.6 143.3 14.2 6.7 147.9 General building contractors: Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 14.0 6.4 132.2 13.9 6.5 137.3 13.4 6.4 137.6 1 2 .0 1 2 .2 5.5 132.0 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 - Heavy construction, except building: Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 15.1 7.0 162.3 13.8 6.5 147.1 13.8 6.3 144.6 12.1 9.9 4.8 9.0 4.3 - 8.7 4.3 4.1 160.1 7.8 3.8 - Special trades contractors: Total cases.................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 14.7 7.0 141.1 14.6 6.9 144.9 14.7 6.9 153.1 13.5 6.3 151.3 10.4 4.8 1 0 .0 5.0 - 9.1 4.1 - 8.9 4.4 - 13.1 5.7 107.4 13.1 5.8 113.0 13.2 5.8 120.7 10.3 4.8 9.7 4.7 9.2 4.6 14.2 5.9 14.1 14.2 6 .0 11.3 5.1 10.7 5.0 10.1 6 .0 116.5 123.3 18.4 9.4 177.5 18.1 16.6 7.3 115.7 6.1 1 2 .8 8 .0 11.1 1 0 .2 5.4 165.8 5.1 - 5.0 - 13.8 1 2 .8 5.8 12.5 5.8 168.3 - - - - 12.7 5.6 121.5 12.5 5.4 124.6 12.1 1 2 .2 1 1 .6 1 0 .6 5.3 5.5 5.3 4.9 13.6 5.7 122.9 13.4 5.5 126.7 13.1 5.4 13.5 5.7 1 2 .8 1 1 .6 5.6 5.1 16.3 7.6 165.8 15.9 7.6 15.7 7.7 14.9 7.0 14.2 13.5 6.5 13.2 6 .8 6 .8 13.0 6.7 172.5 16.8 8.3 172.0 16.1 7.2 16.9 7.8 15.9 7.2 14.8 14.6 6.5 15.0 7.0 13.9 6.4 1 2 .2 1 2 .0 5.4 5.8 11.4 5.7 11.5 5.9 16.0 7.5 141.0 15.5 7.4 149.8 15.4 7.3 160.5 14.8 13.6 13.2 6.5 12.3 5.7 1 1 .8 1 1 .8 6.1 13.8 6.3 12.4 6 .8 6 .0 5.7 6 .0 10.7 5.4 19.4 18.7 19.0 8 .2 8.1 8.1 15.0 7.2 14.0 7.0 12.9 6.3 14.2 6.4 13.9 6.5 1 2 .6 9.5 4.0 8.5 3.7 2 .8 2 .8 6 .0 6.1 11.1 4.7 8 .2 M a n u fa c tu rin g Total cases.................................................................................. Durable goods: Total cases................................................................................. 1 1 1.1 4.8 Lumber and wood products: 19.5 Total cases............................................................................... 1 0 .0 189.1 Furniture and fixtures: Total cases............................................................................... Stone, clay, and glass products: Total cases............................................................................... Primary metal industries: Total cases............................................................................... 8 .8 128.4 156.0 152.2 17.5 7.1 175.5 17.0 7.3 16.8 7.2 16.5 7.2 15.0 16.8 16.2 6.7 16.4 6.7 15.8 6.9 14.4 9.9 4.0 1 0 .0 6 .8 6 .6 3.1 3.1 161.3 168.3 180.2 17.7 7.4 169.1 18.8 18.5 7.9 147.6 18.7 7.9 155.7 17.4 7.1 146.6 Fabricated metal products: Total cases.............................................................................. 8 .0 138.8 6 .6 6 .6 6 .8 6 .2 6 .0 144.0 Industrial machinery and equipment: Total cases.............................................................................. 11.1 1 1 .6 1 1 .2 4.2 87.7 4.2 4.4 4.4 3.7 83.0 8.4 3.6 81.2 8.3 3.5 8.3 3.6 7.6 3.3 12.1 12.1 1 2 .0 1 1 .2 4.7 82.8 4.8 8 6 .8 4.7 88.9 8 6 .6 9.1 3.9 77.5 9.1 3.8 79.4 17.7 4.4 11.1 4.1 Electronic and other electrical equipment: 8 .0 3.3 64.6 8 .6 Transportation equipment: 6 .8 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 6 .6 6 .6 6.4 138.6 17.8 6.9 153.7 15.4 6 .6 134.2 6.1 5.6 2.5 55.4 5.9 2.7 57.8 6 .0 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 2.7 64.4 11.3 5.1 113.1 11.3 5.1 104.0 10.7 5.0 108.2 10.C 4.6 9.9 4.5 9.1 4.3 9.5 4.4 8 .S 4.2 3 .9 40 17.7 Instruments and related products: Total cases.............................................................................. 2 .6 51.5 1 .8 Miscellaneous manufacturing Industries: Lost workdays........................................................................... See footnotes at end of table. 118 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 11.3 5.1 91.0 11.1 5.1 97.6 46. C o n tin u e d — O c c u p a tio n a l injury a n d illness rates b y in dus try,1 U nited States Incidence rates per 100 full-tim e w orkers3 inaustry ana type or case 1988 1989 1 1990 1991 1992 1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 Nondurable goods: Total cases................................................................................. Lost workday cases..................................................................... 11.4 5.4 101.7 5.5 '107.8 11.7 5.6 116.9 11.5 5.5 119.7 1 2 1 .8 18.5 9.2 169.7 18.5 9.3 174.7 2 0 .0 2 0 2 .6 19.5 9.9 207.2 9.3 2.9 53.0 8.7 3.4 64.2 7.7 3.2 62.3 52.0 9.6 40 78.8 10.3 42 81.4 9.6 40 85.1 88.3 87.1 9.2 4.2 99.9 1 1 .6 10.7 5.0 10.5 5.1 9.9 4.9 9.2 4.6 8 .8 8 .2 4.4 4.3 7.8 4.2 18.8 9.5 211.9 17.6 8.9 17.1 9.2 16.3 8.7 15.0 14.5 8 .0 8 .0 13.6 7.5 12.7 7.3 6.4 6 .0 5.3 2.4 6.7 24 42.9 5.8 2.3 5.6 2 .6 2 .8 5.9 2.7 6.4 3.4 5.5 2 8 9.7 8.7 8 .2 7.8 6.7 3.1 7.4 3.4 6.4 3.2 9.5 4.0 104.6 9.0 3.8 - 8.9 3.9 - 8 .2 7.4 3.3 - 7.0 3.1 6 .2 5.8 3.6 - 2 .6 2 .8 7.0 3.7 11.3 5.3 Food and kindred products: Total cases.............................................................................. Lost workday cases.................................................................. Tobacco products: Total cases.............................................................................. Textile mill products: Total cases.............................................................................. Lost workdays........................................................................... Apparel and other textile products: Total cases.............................................................................. Lost workday cases.................................................................. Lost workdays........................................................................... 8.1 9.9 10.1 9.9 2 .2 8 .6 8 .8 6 8 .2 3.8 80.5 3.9 92.1 Paper and allied products: Total cases.............................................................................. Lost workday cases.................................................................. Lost workdays........................................................................... 13.1 5.9 124.3 12.7 5.8 132.9 12.1 1 1 .2 1 1 .0 5.5 124.8 5.0 122.7 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 Printing and publishing: Total cases.............................................................................. Lost workday cases.................................................................. Lost workdays........................................................................... 6 .6 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 5.0 2 .8 5.7 2.7 5.4 3.2 59.8 2 .8 2 .6 Chemicals and allied products: Total cases............................................................................... Lost workday cases................................................................... Lost workdays........................................................................... 7.0 3.3 59.0 7.0 3.2 63.4 6.5 3.1 61.6 6.4 3.1 62.4 6 .0 4.8 2.4 - 4.8 2.3 2.1 4.4 2.3 - 5.5 2.7 - 4.2 2 .8 64.2 5.9 2.7 - 5.7 2 .8 Petroleum and coal products: Total cases............................................................................... Lost workday cases................................................................... Lost workdays........................................................................... 7.0 3.2 68.4 6 .6 6 .6 6 .2 5.9 3.3 3.1 77.3 2.9 2 .8 6 8 .2 71.2 5.2 2.5 - 4.7 2.3 - 4.8 2.4 - 4.6 2.5 - Rubber and miscellaneous plastics products: Total cases............................................................................... Lost workday cases................................................................... Lost workdays........................................................................... 147.2 16.2 7.8 151.3 15.1 7.2 150.9 14.5 142.9 153.3 13.9 6.5 - 14.0 6.7 - 12.9 6.5 - 12.3 6.3 - Leather and leather products: Total cases............................................................................... Lost workday cases................................................................... Lost workdays........................................................................... 11.4 5.6 128.2 13.6 6.5 130.4 12.1 12.5 5.9 140.8 12.1 12.1 1 2 .0 5.9 152.3 5.4 128.5 5.5 - 5.3 - 11.4 4.8 - 10.7 4.5 - Transportation and public utilities Total cases................................................................................. Lost workday cases...................................................................... Lost workdays.............................................................................. 8.9 5.1 118.6 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 - Wholesale and retail trade Total cases................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 7.8 3.5 60.9 8 .0 7.9 3.5 65.6 7.6 3.4 72.0 8.4 3.5 80.1 8.1 3.6 63.5 3.4 7.9 3.4 7.5 3.2 Wholesale trade: Total cases................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 7.6 3.8 69.2 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 - Retail trade: Total cases................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 7.9 3.4 57.6 8.1 8.1 3.4 63.2 7.7 3.3 69.1 8.7 3.4 79.2 8 .2 3.4 60.0 3.3 - 7.9 3.3 - 7.5 3.0 - 2.4 3.5 16.3 8.1 6 8 .1 16.2 8 .0 6 .8 - - - 4.3 3.9 4.1 2 .2 1 .8 1 .8 11.9 5.8 1 1 .2 10.1 5.8 5.5 1 0 .6 9.8 4.5 10.3 5.0 4.8 7.3 4.3 4.4 6.7 3.0 6.5 6.1 2 .8 2.7 6.5 3.2 6.5 3.3 6.3 3.3 6.9 6 .8 2 .8 2.9 6.5 2.7 2.5 6 .8 2.9 - - 6 .6 3.4 - 2 .0 2 .0 2.4 2.9 2.9 2.7 2 .6 .9 17.2 .9 17.6 1.1 1.1 1.2 1.2 1.1 1 .0 27.3 24.1 32.9 - - - Services Total cases................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 5.4 5.5 2.7 51.2 6.5 6.4 6 .0 2 .8 7.1 3.0 6.7 2 .8 2 .8 2 .8 2 .8 2 .6 47.7 56.4 60.0 6 8 .6 - - - - 6 .0 6 .2 8 .2 7.3 6.1 - Finance, insurance, and real estate Total cases................................................................................. Lost workday cases...................................................................... Lost workdays............................................................................... 2 .6 4.3 2.4 .9 - .9 .7 .5 5.6 2.5 5.2 2.4 2 .2 1 .8 .8 4.9 2 .2 Data for 1989 and subsequent years are based on the Standard Industrial Class ification 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. 1 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: https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Excludes farms with fewer than 11 employees since 1976. Dash indicates data not available. 5 Monthly Labor Review July 2001 119 Current Labor Statistics: Injury and Illness 47. Fatal occupational injuries by event or exposure, 1993-98 F a ta litie s Event o r exposure1 1993-97 19972 Average Number 1998 Number Percent Total............................................................................................... 6,335 6,238 6,026 100 Transportation incidents..................................................................... 2,605 2,630 44 Highway incident................................................................................... 2,611 1,334 1,393 1,431 24 Collision between vehicles, mobile equipment............................. 652 640 701 12 Moving in same direction.............................................................. 109 103 118 2 Moving in opposite directions, oncoming................................... 234 230 271 4 Moving in intersection................................................................... 132 249 142 282 142 2 306 5 360 387 373 6 Jackknifed or overturned— no collision...................................... 267 388 214 298 377 300 384 5 Nonhighway (farm, industrial premises) incident............................. O verturned.......................................................................................... Aircraft.................................................................................................... 216 216 4 261 367 223 4 413 7 109 112 2 Vehicle struck stationary object or equipment.............................. Noncollision incident......................................................................... 315 Worker struck by a vehicle.................................................................. 373 106 Water vehicle incident.......................................................................... Railway................................................................................................ 83 60 1 960 16 860 708 709 12 569 9 Self-inflicted injuries.............................................................................. 215 216 61 79 ¿23 1 110 73 79 4 Contact with objects and equipm ent................................................ Struck by object.................................................................................... Struck by falling object..................................................................... 1,005 1,035 579 941 16 517 9 5 Struck by flying object....................................................................... 65 290 54 317 58 266 129 140 4 153 124 320 189 118 Falls............................................................................................................ 668 716 702 12 591 94 653 116 154 623 10 Fall from ladder.................................................................................. Assaults and violent acts.................................................................... 1,241 Homicides.............................................................................................. Shooting............................................................................................. 995 810 Stabbing............................................................................................. Other, including bombing................................................................ 75 573 369 Caught in or compressed by equipment or objects........................ Caught in running equipment or machinery.................................. 139 83 93 6 1 ,1 1 1 384 87 1 1 2 2 111 2 156 97 2 3 Fall on same level................................................................................. 52 44 51 1 554 298 572 334 9 Contact with electric current................................................................ 586 320 6 128 43 138 40 153 3 120 46 104 2 48 87 1 80 123 59 90 72 199 196 Contact with overhead power lines................................................ Contact with temperature extremes................................................... 70 Oxygen deficiency................................................................................. 101 Other events or exposures3................................................................ 1 Based on the 1992 BLS Occupational Injury and Illness 26 3 21 75 205 1 1 1 3 16 Includes the category "Bodily reaction and exertion." Classification Structures. 2 The BLS news release Issued August 12. 1998, reported a total of 6,218 fatal work Injuries for calendar year 1997. Since N0TE: Totals ,or major categories may include sub cate9 ° ries not shown separately. Percentages may not add to then, an additional 20 job-related fatalities were identified, bringing the total job-related fatality count for 1997 to 6,238. l0tals because of roundin9percent. 120 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis July 2001 Dash indicates less 1han °-5 i O b ta in in g in fo rm a tio n fro m th e B u re a u o f L a b o r S ta tis tic s O ffice or Topic Bureau of Labor Statistics Information services In tern et address http://www.bls.gov http://www.bls.gov/opbinfo.htm E-m ail blsdata_staff@bls.gov Employment and unemployment Employment, hours, and earnings: National State and local Labor force statistics: National Local Ul-covered employment, wages Occupational employment Mass layoffs Longitudinal data http://www.bls.gov/ceshome.htm http://www.bls.gov/790home.htm cesinfo@bls.gov data_sa@bls.gov http://www.bls.gov/cpshome.htm http://www.bls.gov/lauhome.htm http://w ww.bls .gov/ce whome .htm http://www.bls.gov/oeshome,htm http://www.bls.gov/lauhome.htm http://www.bls.gov/nlshome.htm cpsinfo@bls.gov lausinfo@bls.gov 202_info@ bis .gov oesinfo@bls.gov mlsinfo@bls.gov nls_info@ bis .gov Prices and living conditions Consumer price indexes Producer price indexes) Import and export price indexes Consumer expenditures http://www.bls.gov/cpihome.htm http://www.bls.gov/ppihome.htm http://www.bls.gov/ipphome.htm http://www.bls.gov/csxhome.htm cpi_info@bls.gov ppi-info@bls.gov ippinfo_ipp@ bis .gov cexinfo@bls.gov Compensation and working conditions National Compensation Survey: Employee benefits Employment cost trends Occupational compensation Occupational illnesses, injuries Fatal Occupational injuries Collective bargaining http://www.bls.gov/comhome.htm http://www.bls.gov/ebshome.htm http://www.bls.gov/ecthome.htm http://www.bls.gov/ocshome.htm http://www.bls.gov/oshhome.htm http://stats.bls.gov/oshcfoi 1.htm http://www.bls.gov/cbahome.htm ocltinfo@bls.gov ocltinfo@ bis.gov ocltinfo@bls.gov ocltinfo@bls.gov oshstaff@bls.gov cfoistaff@bls.gov cbainfo@bls.gov Productivity Labor Industry Multifactor http://www.bls.gov/lprhome.htm http://www.bls.gov/iprhome.htm http://www.bls.gov/mprhome.gov dprweb@bls.gov dipsweb@bls.gov dprweb@bls.gov Projections Employment Occupation http://www.bls.gov/emphome.htm http://www.bls.gov/ocohome.htm oohinfo@bls.gov oohinfo@bls.gov International http://www.bls.gov/flshome.htm flshelp@bls.gov Regional centers Atlanta Boston Chicago Dallas Kansas City New York Philadelphia San Francisco http://www.bls.gov/ro4home.htm http://www.bls.gov/ro 1home.htm http://www.bls.gov/ro5home.htm http://www.bls.gov/ro6home.htm http://www.bls.gov/ro7home.htm http://www.bls.gov/ro2home.htm http://www.bls.gov/ro3home.htm http://www.bls.gov/ro9home.htm BLS infoAtlanta@ bis .gov BLS infoBoston@ bis .gov BLSinfoChicago@bls.gov BLSinfoDallas@bls.gov BLSinfoKansasCity@bls.gov BLSinfoNY@bls.gov BLSinfoPhiladelphia@bls.gov BLS infoSF@ bis .gov Other Federal statistical agencies https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis http://www.fedstats.gov Periodicals Postage and Fees Paid U.S. Department of Labor USPS 987-800 U.S. DEPARTMENT OF LABOR Bureau of Labor Statistics Postal Square Building, Rm. 2850 2 Massachusetts Ave., NE Washington, DC 20212-0001 Official Business Penalty for Private Use, $300 Address Service Requested ML R FEDER442F ISSDUE000R 1 F E D E R A L R E S E R V E B A N K OF S T L O U CAROL T HA XTO N L I B R A R Y U N I T PO B O X 4 4 2 SAINT LOUIS MO 63166 Schedule of release dates for BLS statistical series S e rie s E m p lo y m e n t s itu a tio n R e le a se P e rio d R e le a s e P e rio d R e le a se P e rio d d a te c o v e re d d a te c o v e re d d a te c o v e re d July 6 June August 3 July September 7 August August 7 2nd quarter September 5 P ro d u c tiv ity a n d c o s ts U .S . 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