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MONTHLY LABOR REVIEW Volume 132, Number 8 August 2009 Using internal CPS data to reevaluate trends in labor-earnings gaps 3 New wherever-provided services and construction indexes for PPI 19 Measuring the impact of income imputation in the Consumer Expenditure Survey 25 A new Current Population Survey data series uses cell means to more accurately measure gaps and trends in earnings Richard V. Burkhauser and Jeff Larrimore A new set of producer price indexes enables the BLS to expand coverage of the services and construction sectors of the economy Jonathan C. Weinhagen and Bonnie H. Murphy The 2004 introduction of income imputation has brought CE estimates closer to estimates from the CPS, although differences remain between many of the smaller components Bill Passero Departments Labor month in review Book review Précis Current labor statistics 2 43 45 46 Editor-in-Chief: Michael D. Levi Executive Editor: William Parks II Managing Editor: Terry Schau Editors: Brian I. Baker, Casey P. Homan Book Review Editor: James Titkemeyer Design and Layout: Catherine D. Bowman, Edith W. Peters Cover Design: Bruce Boyd Contributor: Horst Brand Labor Month In Review The August Review Included in the multitude of information provided by the Bureau of Labor Statistics are data on earnings. One source of such data is the Current Population Survey (CPS), which is administered to a large, nationally representative sample of households and has been conducted each month since the 1940s. Over the years researchers and other interested parties have studied changes and trends in earnings over time by race, sex, and other demographic variables. In the first article of this issue, Professor Richard V. Burkhauser and Jeff Larrimore, both from Cornell University, look more deeply into CPS data to reevaluate trends in earnings gaps. The article analyzes internal, or non-public use, CPS data from 1975–2007, which, the authors find, show earnings gaps different from those calculated from public-use CPS data. The authors point out that public-use data, which are the data usually used by researchers, do not include suppressed—or topcoded— earnings. Topcoding is the replacement of a datum representing part or all of a person’s true income with a lower value and is done in order to protect the confidentiality of survey respondents. The article also finds that trends in and gaps between the earnings of men and women, Blacks and Whites, and people of various education levels are all sensitive to topcoding. Another widely watched indicator produced by BLS is the Producer Price Index (PPI). The PPI is produced in the Office of Prices and Living Conditions (OPLC), and it measures the average change over time in the selling prices received by domestic producers for their output. Historically, this information has been collected 2 Monthly Labor Review • August 2009 and presented on an industry basis. However, beginning with the release of July data in August 2009, BLS introduced a new set of construction price indexes for wherever-provided goods and services. In contrast to industry-based price indexes, commodity-based indexes measure price change for a (wherever-provided) service or (wherever-made) good, regardless of the producer’s industry of origin. In this issue’s second article, Jonathan C. Weinhagen and Bonnie H. Murphy, both OPLC economists, introduce this new measure and explain in detail how it differs from the more traditional approach. The benefit of commodity-based indexes, the authors suggest, is that they allow data users to examine price movements for a specific service or construction-related product within a single price index that combines prices from all industries producing that product or service. In addition, detailed price indexes can be aggregated into many higher level indexes not found in the industry-based PPI aggregation structure. These wherever-provided aggregations give data users additional indexes to follow and analyze. This month’s third article, by Bill Passero, a senior economist in the OPLC, discusses the impact that income imputations have had on the Consumer Expenditure (CE) Survey. Beginning in 2004, the CE Survey began imputing for missing responses to questions about income that survey respondents acknowledged receiving, but for which they had not provided values. The purpose of the article is to assess the impact and efficacy of imputation by comparing pre- and postimputation estimates of CE-reported income with estimates from the CPS, which has employed imputation for many years in the course of producing its income estimates. The conclusions are that, generally, imputation has brought CE estimates closer to CPS estimates and that further refinements to the CE income questions and imputation procedures are expected in the future. Silicon valley employment For those who followed the news or their investment portfolios for most of 2000, the seemingly daily reports of downturns in the stock market are an all-too-painful memory. The “dot-com bubble” is the appellation usually used to refer to the financial fallout following the boom of investment and growth in certain kinds of information technology companies. But what did this dramatic fall in stocks and market capitalizations mean for workers and jobs in an area characterized by industries and occupations strongly associated with high-tech? A Regional Report by BLS economists Amar Mann and Tony Nunes looks at this issue from a regional perspective by analyzing Silicon Valley high-tech employment from 2001 to 2008. Silicon Valley refers geographically to six counties in northern California. The report shows that high-tech employment in the area remained relatively stable throughout early 2001, in spite of the 2000 stock market crash and the 2001 recession. However, by the end of 2001 the Silicon Valley unemployment rate had more than doubled, and it wasn’t until 2004 that high-tech employment began to increase. It continued to increase through 2008, although 2008 employment was still 17 percent lower than in 2001. The report is available online at http://www.bls.gov/opub/ regional_reports/200908_silicon_ valley_high_tech.pdf. Trends in Earnings Gaps Using internal CPS data to reevaluate trends in labor-earnings gaps The Current Population Survey provides data that are used to compare gaps in the labor earnings of women and men, people of different races, and people of different levels of education; this article presents a data series that uses cell means and more accurately measures gaps and trends in earnings than do other publicly available series Richard V. Burkhauser and Jeff Larrimore The results and conclusions presented in this article are those of the authors and do not necessarily reflect the views of the U. S. Census Bureau. This article has been screened to ensure that no confidential data are disclosed. Richard V. Burkhauser is a professor in the Department of Policy Analysis and Management at Cornell University. Jeff Larrimore is a Ph.D. candidate in the Department of Economics at Cornell University. Email: rvb1@cornell.edu, jhl42@cornell.edu T he Current Population Survey (CPS) is a large, nationally representative sample of households collected each month since 1942 by the U.S. Census Bureau.1 This article focuses on data from the surveys conducted in March because the March survey includes an extensive income questionnaire. The data that are publicly available from the CPS are the primary tool used to investigate yearly trends in United States average labor earnings and their distribution. However, to protect the confidentiality of its respondents, the Census Bureau topcodes the highest values from each source of income that it collects when it reports the income in the public-use CPS data. Topcoding is the replacement of a datum representing part or all of a person’s true income with a lower value. One of the challenges that topcoding presents for those using the public-use data to examine labor-earnings levels and trends is that the topcodes vary over time, which leads to artificial increases or decreases in earnings (when the term “earnings” appears alone in this article, it still refers to “labor earnings”) at the top of the earnings distribution as different fractions of the population are subject to topcoding each year.2 Although the public-use data are used extensively to measure the earnings gaps between men and women and Blacks and Whites,3 until now little was known about how topcoding affects comparisons of labor earnings across these subsets of the population.4 This article finds that gaps between the earnings of men and women, Blacks and Whites, and people of various education levels are all sensitive to topcoding. Ratios of these earnings as well as trends in the gaps and ratios also are sensitive to topcoding. The article arrives at these findings by analyzing 1975–2007 CPS data and comparing the values of gaps and ratios obtained using the public-use CPS data with values found using the internal CPS data. This article presents an extended cell mean series that will be explained in more detail in a later section. The earnings gaps calculated using the extended cell mean series in conjunction with public-use CPS data are found to closely approximate those obtained with the Census Bureau’s internal CPS data. Additionally, this article finds that women, Blacks, and the less-educated are relatively worse off compared with men, Whites, and the more-educated, respectively, than previously reported using the public-use CPS data. Although the trends for all of the aforementioned earnings gaps are sensitive Monthly Labor Review • August 2009 Trends in Earnings Gaps to topcoding, the impact that attempting to correct for topcoding has on trends differs by year.5 Calculating earnings gaps To calculate gaps in earnings between men and women, between Blacks and Whites, and among people of various levels of education, this article examines the annual labor earnings from wages and salaries, self-employment, and farm earnings of full-time, full-year workers in the CPS.6 Prior to 1987 these “earnings sources” were reported as three separate values. Since then a fourth source—primary labor earnings (regardless of source)—has been added. The earnings sources and their names in the public and internal CPS data files are listed in table A–1 of the appendix. Much of the previous work exploring earnings gaps between men and women, between or among races, and among people of various levels of education focuses solely on wage and salary earnings and excludes self-employment and farm earnings, primarily because of concerns about the accuracy of self-employment earnings in the CPS. However, as Theresa J. Devine demonstrates, earnings gap data are sensitive to the inclusion or exclusion of selfemployment earnings since the earnings gap between men and women is larger among full-time self-employed workers than among full-time wage earners.7 Because the aim is to compare groups of people on the basis of all their labor market earnings, farm and self-employment earnings must be included along with wages. An additional detail to consider is whether to analyze annual earnings or to instead recalculate the statistics as weekly or hourly wages. For this article a choice has been made to use annual earnings. The results are similar no matter which of these three methods is used; however, since women tend to work fewer weeks per year, using a weekly or hourly measure does generate a slightly smaller earnings gap between men and women.8 Another question is how best to calculate group earnings when calculating earnings gaps. To limit the impact of outliers on the earnings gap between men and women, the Census Bureau uses median rather than mean earnings when reporting the earnings gap between men and women in its Income, Poverty, and Health Insurance Coverage in the United States series.9 The Census Bureau does not calculate earnings gaps between people of different races or levels of education in this report. The gap in median earnings between men and women that is presented by the Census Bureau is regularly reproduced in factsheets by policy institutes and has been widely used as background Monthly Labor Review • August 2009 information in the literature on the pay gap between men and women.10 However, using median earnings comes at the cost of focusing only on the midpoint of the earnings distribution. As a result of the use of median earnings, if women make substantial gains compared with men at either tail of the distribution, a simple comparison of the median over time will probably understate these gains. Additionally, since earnings distributions are positively skewed in all years, mean earnings give relatively more weight than median earnings to changes in the upper tail of the distribution. So for researchers interested in this portion of the distribution, the mean is better able to capture differences between groups and changes over time. Because this article focuses on the upper tail of the distribution, where most topcoding occurs, it evaluates mean earnings, which better reflect changes occurring throughout the entire earnings distribution and are better able to capture the impact of topcoding on earnings gaps. Despite these differences in calculating earnings gaps, the general trends in earnings gaps in the literature have generally been consistent. Most previous literature has found that the earnings gap between men and women was largely unchanged for much of the 20th Century. It was not until the 1980s that women made substantial gains. In the 1990s, however, these gains subsided and the gap remained stable for much of the decade.11 While the consensus among researchers is that the earnings gap between Blacks and Whites also has been shrinking, the timing of its decline differs greatly from the timing of the decline in the earnings gap between women and men. The earnings gap between Blacks and Whites declined rapidly from the mid-1960s until the middle of the 1970s before stagnating or increasing slightly through much of the 1980s.12 There is some disagreement on the direction of the earnings gap between Blacks and Whites during the 1990s, with David Card and John E. DiNardo finding the gap more or less constant and Kenneth Couch and Mary C. Daly and Chinhui Juhn reporting a decline.13 The next section of the article shows the sensitivity of such earnings trends to four methods of dealing with topcodes in the CPS data. Topcoding CPS data To protect the confidentiality of respondents, the Census Bureau topcodes each source of income that respondents report in the public-use CPS data. The full list of laborearnings topcoding thresholds over time is presented in tables A–2 and A–3 of the appendix. In addition to topcoding each income source in the March CPS, the Census Bureau topcodes earnings reported in CPSs from other months, such as the usual weekly earnings reported in the surveys filled out by outgoing rotation groups.14 The further topcoding prevents researchers from obtaining additional earnings information from other questions in the CPS. Because topcodes vary over time, they can affect both the sizes of earnings gaps and their trends over time. Prior to 1995, the Census Bureau simply replaced the value for each source of an individual’s income that was topcoded with the level of income at the threshold for topcoding. Starting with 1995 data, the Census Bureau instead began replacing the income figure with a cell mean—the mean value of all topcoded data from the source of income in question. For labor earnings, each cell contains earnings figures from workers who are all of the same sex and race and who all either work both full time and year round or do not. Because the Census Bureau has not provided cell means retroactively for years prior to 1995, using the public-use CPS data without taking this major change in reported earnings values into account results in a sizable increase in measured earnings in 1995 and beyond. Hence, while the use of cell means starting in 1995 causes the public-use CPS data to conform better to the internal CPS data, not taking the improvement in measurement into account will overestimate actual increases in labor earnings from any year before 1995 to 1995 or any year after.15 Topcoding also has important implications for measuring the relative labor earnings of subsamples of the population and measuring gaps in earnings among subsamples. For example, if the distributions of labor earnings of women and men were identical, individuals’ earnings in both groups would be topcoded at the same rate. So, topcoding would reduce the mean earnings of both men and women by the same percentage, leaving intergroup inequality unchanged. However, if individuals in the two groups have different probabilities of being topcoded or if the mean suppressed labor earnings of those who are topcoded differ between the two groups, topcoding will influence the earnings gap measure. Because a larger percentage of women than men are below the topcoding threshold, women are less likely to be topcoded; it can be expected that topcoding will artificially raise the ratio of women’s mean earnings to men’s mean earnings, because the women’s observed mean earnings will be less artificially depressed from the topcodes than those of men and hence will be closer to their true mean. Similar results will occur even if the probability of topcoding is the same across both groups, provided that the amount of suppressed earnings is higher for men than for women. The same holds for Blacks relative to Whites and those with less education relative to those with more education. Prevalence of topcoding Table 1 shows, for the trough year of each business cycle since 1975, the percentages of various groups of full-time, full-year workers who have had earnings from at least one source topcoded in the public-use CPS data.16 The groups of people are organized by sex (men and women), race (Blacks and Whites), and level of education attained (less than a high school degree, a high school degree but no higher education, and education beyond high school). The three business cycles run from 1975 to 1982, from 1982 to 1992, and from 1993 to 2004. The method for selecting the starting points and endpoints of business cycles in this article has been chosen somewhat arbitrarily. Rather than define business cycles directly by changes in macroeconomic growth, this article uses troughs in income, which in general lag behind macroeconomic growth. Choosing slightly different trough years would not have a significant effect on this article’s findings. Although it is not a trough year, 1992 is included in the table. As will be discussed in more detail later, Census Bureau data collection procedures were redesigned after 1992. This reduces the ability to compare 1992 data with 1993 data. So 1993 represents both the trough year of the 1993–2004 business cycle and the first year of the new procedures. Like 1992, the year 2007 is not a trough year, but it is included in the table because it is the most recent year for which data are available. The business cycles are measured from trough to trough. As can be seen in table 1, although the percentage of people whose earnings are topcoded varies by sex, race, and level of education, the overall incidence of topcoding has increased greatly over the past 30 years for every group of workers in the table. For example, virtually no women or black full-time, full-year workers had topcoded labor earnings in 1975, but close to 1 percent of each group had topcoded earnings in 2007. While topcoding has been rising among the earnings of men, women, Blacks, Whites, and people of all three levels of education, in any given year there are noticeable differences in topcoding rates among these groups. Because women’s earnings are less likely to be topcoded than those of men, one expects to find a larger difference between men’s observed labor earnings and their true mean labor earnings than one expects to find for women’s observed Monthly Labor Review • August 2009 Trends in Earnings Gaps Table 1. Percentages of various groups of full-time, full-year workers whose labor earnings are topcoded, and ratios of selected percentages; by year, selected years,1975–2007 Year Women Men Ratio Blacks Whites Ratio 1975................. 1982................. 1992................. 1993................. 2004................. 2007................. SOURCE: Education beyond high school Ratio Ratio (8)/(7) (9)/(8) (1) (2) (1)/(2) (3) (4) (3)/(4) (7) (8) (9) 0.02 .16 .39 .66 .57 .86 1.18 1.76 2.98 3.51 2.23 2.59 0.02 .09 .13 .19 .26 .33 0.00 .33 .37 .80 .61 .85 0.91 1.30 2.22 2.68 1.84 2.30 0.00 .26 .17 .30 .33 .37 0.09 .07 .22 .30 .31 .22 0.28 .34 .35 .56 .59 .64 1.73 2.18 3.24 3.78 2.23 2.66 3.14 6.24 4.70 6.44 1.59 9.39 1.91 6.70 1.88 3.80 2.84 4.18 Authors’ calculations made by use of public and internal CPS data. and true earnings. Correcting for topcoding should show that the gap between women’s and men’s earnings is wider than previously reported. For the same reasons, one can expect that correcting for topcoding will show that the gap between the earnings of Blacks and those of Whites is wider than previously reported and that the gap between the earnings of people with a high school degree or less and the earnings of those in higher education groups also is wider than previously reported. As can be seen in the table, topcoding ratios also have changed over time. In 2007, women were topcoded 33 percent as much as men, up from only 2 percent as much in 1975. In 2007, Blacks were topcoded 37 percent as much as Whites, compared with 1975 when no Blacks were topcoded. On the whole, from 1975 to 2007 the less-educated showed larger increases in topcoding than did the more-educated. Hence, trends in earnings gaps between the sexes, between Blacks and Whites, and among people of varying levels of education are expected to be affected by topcoding. Methods of managing topcoding problems The issue of topcoding can be handled in various ways. A first approach—referred to for the purposes of this article as “Unadjusted Public Use”—is to simply ignore topcoding issues and use the unadjusted public-use CPS data as released by the Census Bureau. However, as discussed earlier, doing so will result in a series whose labor-earnings levels are suppressed prior to 1995, because of topcoding, and are much higher thereafter, primarily because of the Census Bureau’s introduction of cell means in 1995. This shift to cell means in 1995 is further complicated by changes to Less than High a high school school degree degree Monthly Labor Review • August 2009 topcoding thresholds made by the Census Bureau at the same time. For instance, the topcode for primary earnings rose from $99,999 to $150,000, thus reducing the share of full-time male workers whose primary labor earnings were topcoded from 3.93 percent to 1.35 percent, but the use of cell means increases the average reported primary labor earnings of those men who were still topcoded to $305,989. A second approach—referred to as “No Cell Mean Public Use”—is to ignore the introduction of cell means into the public-use CPS data and to produce a labor-earnings series in which all topcoded values are assigned the value of the topcoding threshold, even those values which date from after the introduction of cell means in 1995. While this approach removes the large artificial jump in labor earnings due to the introduction of cell means in 1995, it does not address the problem of inconsistent changes in topcoding thresholds over time (such as the change in the primary labor earnings topcode from $99,999 in 1994 to $150,000 in 1995) or the variation in topcoding rates across groups within the U.S. population.17 A third approach, used by Richard V. Burkhauser, J. S. Butler, Shuaizhang Feng, and Andrew J. Houtenville for labor earnings and by Burkhauser, Couch, Houtenville, and Ludmila Rovba for household income, is to create a consistent topcode series—an approach referred to as “Consistent Topcode Public Use.”18 For each earnings source, this series finds the year in which the topcoding threshold cuts most deeply into the source’s earnings distribution and then for every other year applies whatever topcoding threshold cuts into the source’s earnings distribution by the same percentage. This approach is preferable to both the Unadjusted Public Use approach and the No Cell Mean Public Use approach in that it consistently measures a given percentage of the distribution of the earnings from the source in question in all years of the study. However, this consistency over time in topcoding rates comes at the cost of losing information by topcoding a larger fraction of the population in almost every year. In this article, which analyzes labor earnings for full-time, full-year workers, the Consistent Topcode Public use approach cuts into the data by anywhere from 2.5 to 3.8 percent. The public-use CPS data reflect a cut (due to topcoding) that ranges from 0.6 to 2.7 percent, depending on the year. Just as the existence of topcoding in the public-use CPS data can distort gaps in earnings and trends in earnings inequality across groups, increasing the fraction of the population that is topcoded can exacerbate the problem. Because more individuals are topcoded with the Consistent Topcode Public Use approach than they are in the public data, the observed mean labor earnings of each group within the population will be lower. But, because most of the people who are captured by the reduction in the topcodes are men, white, or more educated, using this approach will reduce the mean earnings of these groups more than it will reduce the mean labor earnings of women, Blacks or the less-educated. Hence, the Consistent Topcode Public Use method will consistently overestimate the mean earnings of workers with the former set of characteristics relative to workers with the latter characteristics by disproportionately excluding the top part of the labor-earnings distribution. Given the limitations of consistent topcoding in providing a consistent comparison of the economic wellbeing of subpopulations, a new method for controlling for topcoding in the public-use CPS data is needed. As mentioned earlier, the Census Bureau began using cell means in 1995. Cell means from before 1995 are what is necessary to create an unbroken series that is based on cell means. Jeff Larrimore, Burkhauser, Feng, and Laura Zayatz have employed approximately the same method the Census Bureau used to create its cell means from 1995 onward in order to generate cell means that date back to 1975.19 With these cell means, it is possible to create an unbroken cell-means-based data series that can be used with the public-use CPS data. The earnings distributions in this series better match those found in the internal CPS data for each of the population subgroups examined. To create the extended cell mean series for each source of labor earnings, the population is divided by sex, race, and employment status, the same categories the Census Bureau uses to produce its cell means. The topcoded earnings value is then replaced with the weighted mean earnings—from the source of earnings in question—of all individuals with the same set of demographic characteristics for whom the source of earnings in question is topcoded in the publicuse CPS data. To protect the confidentiality of respondents’ identities, when fewer than 5 individuals are topcoded from an earnings source, those individuals’ earnings are combined with the earnings of individuals from a similar earnings source in order to obtain a cell size of 5 or more and generate a cell mean. (This procedure for preserving confidentiality is the same as that used by the Census Bureau.) Although this new approach for correcting the effects of topcoding—an approach referred to as “Cell Mean Public Use”—has significant advantages over consistent topcoding because it allows one to better understand changes at the high end of the earnings distribution, it still does not capture the full distribution. In addition to topcoding income in the public-use CPS data, the Census Bureau censors high-income values for each source of income in the internal CPS data. The full list of points beyond which labor earnings are not released internally—termed “censoring points” in this article—is reported in tables A–2 and A–3 of the appendix. Since the internal CPS data are censored, values at the very top of the distribution for each source of income cannot be observed in these data.20 This poses a potential problem when creating a cell mean series for the public-use CPS data from the internal CPS data, because at best the trends in the series will match those found in the internal data from which the cell means are created. If changes in the censoring points in the internal CPS data affect earnings gaps, ratios, or trends in the Internal series, the same gaps, ratios, and trends will be affected in the Cell Mean Public Use Series. While this is a limitation of the cell mean series in measuring the “true” trends in labor earnings, the problem is not as serious as it could be because the censoring points in the internal CPS data are much higher than the topcodes in the public-use CPS data. As a result, the fraction of individuals who are affected by censoring points is lower than the fraction affected by the public-use CPS topcodes. Thus, although some censoring does occur in the internal CPS data, the results calculated using the extended cell mean series with the public-use CPS data (that is, using the Cell Mean Public Use approach) are much closer to the results that would be obtained using data that consistently captures the full earnings distribution. Additionally, the censoring points tend to be more stable than their counterparts used for the public-use CPS Monthly Labor Review • August 2009 Trends in Earnings Gaps data, the topcoding thresholds. Since the Census Bureau switched from reporting three sources of labor earnings to four sources in 1987, the only years in which changes were made to censoring points were 1992 and 1993. Problems with data from the years 1992 and 1993 are not limited to the internal data. In 1993 the Census Bureau also implemented a substantial redesign of its collection procedures, a redesign that included the implementation of computer-assisted data collection.21 The change in procedures increased the ability of the Census Bureau to observe earnings near the top of the distribution; since those high earnings are observed in the internal data but are topcoded in the public-use data, the use of internal data exacerbates the observed break in the series. Therefore, although the use of cell means with publicuse CPS data allows for consistent trends before and after these years—trends that closely match the internal CPS data—researchers should take caution when using the cell mean series, or any CPS-based earnings series, to compare the year 1992 or any year before with the year 1993 or any year after. Accuracy in capturing mean labor earnings As was explained in the previous section, men’s and women’s mean labor earnings were calculated using four methods of dealing with topcoding. Each cell in panel 1 of table 2 is the ratio of a datum from one of the four series to its corresponding figure from the internal CPS data. There are separate columns for men and women. A ratio of 1.000 indicates that the method perfectly captures the mean earnings observed in the Internal data series. The lower the ratio, the more earnings are missed as a result of topcoding. As can be seen when looking at the data for 2007, because of the cell means provided by the Census Bureau, the mean earnings of full-time, full-year male and female workers captured in the Unadjusted Public Use data since 1995 are very close to the mean earnings in the Internal data series. So, for people only interested in years since 1995 (the year cell means were first provided by the Census Bureau), the men’s and women’s earnings statistics in the Unadjusted Public Use data and the Cell Mean Public Use data come very close to matching the corresponding statistics in the Internal series. But for those also interested in years prior to 1995, the Unadjusted Public Use data series is flawed because it does not provide cell means for earnings that are above the threshold for topcoding. Hence, its mean values are smaller for both men’s and women’s earnings. In contrast, Monthly Labor Review • August 2009 the Cell Mean Public Use data provide yearly means very close to those from the Internal series for both men and women in all years back to 1975, coming within 0.2 percent of the internal mean values for both men and women in each of the trough years. Unlike the Unadjusted Public Use and Cell Mean Public Use series, the No Cell Mean Public Use and the Consistent Topcode Public Use series understate the mean earnings of both men and women in all years. Additionally, the amount by which earnings are understated through the use of these series has grown over time. For example, the mean earnings that are calculated using the Consistent Topcode Public Use series understate the results in the Internal series by 4.9 percent for men and 0.2 percent for women in 1975. By 2007 the gap between the Consistent Topcode Public Use series and Internal series rises to 9 percent for men’s earnings and 4 percent for women’s earnings. As is seen in panels 2 and 3 of table 2, the methods for managing topcoding have effects on the calculations of mean earnings of black and white workers and of workers with different levels of education that are similar to the methods’ effects on the calculation of men’s and women’s earnings. Mean earnings computed using the Cell Mean Public Use series in all years or the Unadjusted Public Use series after 1995 closely match the mean earnings calculated using the Internal series. Use of the Consistent Topcode Public Use or the No Cell Mean Public Use series understates mean earnings (in relation to the Internal series), doing so more for white than for black workers and more for more highly educated workers than for less-educated workers. Accuracy in capturing earnings gaps Having shown that mean earnings of men, women, Blacks, Whites, and people of three levels of education are influenced by the height of topcoding thresholds, the article now focuses in this section on differences among the No Cell Mean Public Use, Consistent Topcode Public Use, Cell Mean Public Use, and Internal series in order to explain how topcoding affects earnings gaps. The Unadjusted Public Use series is excluded from further discussions because its data from prior to 1995 are identical to the No Cell Mean Public Use series and its data from 1995 onward are nearly identical to the Cell Mean Public Use series. In addition, the Unadjusted Public Use series has a clear artificial jump in 1995 that makes it inferior to either the No Cell Mean Public Use series or the Cell Table 2. The ratio of mean labor earnings according to each of four publicly available data series to mean labor earnings according to internal CPS data, selected years, 1975–2007 Panel 1. Ratios involving the mean labor earnings of women and men Year 1975.................. 1982.................. 1992.................. 1993.................. 2004.................. 2007.................. No Cell Mean Public Use Women Unadjusted Public Use Men 1.000 .998 .992 .970 .973 .970 0.986 .988 .958 .914 .929 .935 Consistent Topcode Public Use Women Men Women 1.000 .998 .992 .970 1.001 1.000 0.986 .988 .958 .914 1.000 1.000 0.998 .993 .988 .966 .965 .960 Men Cell Mean Public Use Women 0.951 .955 .940 .901 .902 .910 Men 1.000 1.000 1.000 .999 1.001 1.000 1.000 .999 1.000 1.000 1.000 1.000 Panel 2. Ratios involving the mean labor earnings of Blacks and Whites Year 1975................ 1982................ 1992................ 1993................ 2004................ 2007................ No Cell Mean Public Use Blacks Unadjusted Public Use Whites 1.000 .997 .993 .961 .978 .961 0.988 .990 .966 .927 .939 .944 Consistent Topcode Public Use Blacks Whites Blacks 1.000 .997 .993 .961 1.003 1.001 0.988 .990 .966 .927 1.002 1.002 0.998 .989 .990 .957 .972 .953 Cell Mean Public Use Whites Blacks Whites 1.000 1.000 1.000 1.000 1.003 1.001 1.000 .999 1.000 1.000 1.002 1.002 0.957 .962 .951 .916 .915 .921 Panel 3. Ratios involving the mean labor earnings of people of each of three levels of education No Cell Mean Public Use Year 1975.................................. 1982.................................. 1992.................................. 1993.................................. 2004.................................. 2007.................................. Less than a High school high school degree degree 0.999 .999 .992 .966 .967 .987 Unadjusted Public Use Education beyond high school 0.994 .997 .993 .967 .970 .973 0.982 .986 .957 .915 .934 .937 Less than a high school degree High school degree Education beyond high school 0.999 .999 .992 .966 .982 .994 0.994 .997 .993 .967 .996 .996 0.982 .986 .957 .915 1.003 1.002 Consistent Topcode Public Use Cell Mean Public Use Year 1975.................................. 1982.................................. 1992.................................. 1993.................................. 2004.................................. 2007.................................. Less than a High school high school degree degree 0.991 .996 .989 .964 .964 .982 Education beyond high school 0.982 .987 .990 .963 .962 .967 0.935 .947 .938 .902 .908 .913 Less than a high school degree High school degree Education beyond high school 1.000 1.000 .999 .979 .982 .994 0.999 1.000 .999 .989 .996 .996 1.001 .999 1.000 1.006 1.003 1.002 SOURCE: Authors’ calculations made by use of public and internal CPS data. Monthly Labor Review • August 2009 Trends in Earnings Gaps Mean Public Use series alone. The gap in earnings between women and men. Because the No Cell Mean Public Use and Consistent Topcode Public Use series consistently understate the labor earnings of both men and women, the true ratio of women’s earnings to men’s earnings could in principal be greater or less than the ratio in the Cell Mean Public Use and Internal series. But as tables 1 and 2 have shown, men are more likely than women to be topcoded, and the average man who is topcoded has a higher wage or salary than the average woman who is topcoded. One therefore expects the ratio of women’s earnings to men’s earnings to be higher in the No Cell Mean Public Use and Consistent Topcode Public Use series than in the Cell Mean Public Use and Internal series, especially in the years for which cell means were not calculated. The expectation proves to be true, as can be seen in chart 1, which compares the ratio of mean women’s earnings to mean men’s earnings as calculated using each of the four data series. In all years, the ratio of women’s earnings to men’s earnings is larger according to the No Cell Mean Public Use series than according to the Internal series. This difference is relatively small in the first year of the sample, but grows over time. In 1975 it was under 1 percentage point—female workers earned 56.6 percent of what male workers earned according to the No Cell Mean Public Use series, and they earned 55.8 percent of what male workers earned according to the Internal series—in 1989 it was over 2 percent, and in 2007 it was 2.8 percent. Thus, using the public-use CPS data without cell means will cause researchers to overstate the decline in the earnings gap between men and women over these years. This overstatement is even greater when the Consistent Topcode Public Use method is used, since this approach further suppresses values at the top of the earnings distribution and topcodes even more men’s earnings relative to women’s earnings. Using consistent topcoding overstates the ratio of women’s earnings to men’s mean earnings by 2.8 percentage points in 1975, and the overstatement rises to 4.0 percentage points by 2007. In contrast, as can also be seen in chart 1, the Cell Mean Public Use series nicely approximates the women-to-men earnings ratios found using the internal CPS data. The chart shows that the gap between the earnings ratio calculated using the No Cell Mean Public Use series and Chart 1. Ratio of women’s mean labor earnings to men’s mean labor earnings, according to four data series, 1975–2007 Ratio Ratio 0.80 0.75 0.70 0.80 No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 0.70 0.65 0.65 0.60 0.60 0.55 0.55 0.50 1975 1977 1979 1981 1983 1985 1987 1989 1991 SOURCE: Authors’ calculations made by use of public and internal CPS data. 10 0.75 Monthly Labor Review • August 2009 1993 1995 1997 1999 2001 2003 0.50 2005 2007 that calculated using the Internal series widens over time. The same happens for the Consistent Topcode Public Use series relative to the Internal series. Because of the widening of the gaps between the ratio calculated using the Internal series and the ratios calculated using the other two series, it might be assumed that using either of the other two series will overstate the earnings gains made by female workers relative to male workers for each of the three business cycles occurring during the 1975– 2004 period. However, it will be shown that this is not the case. Panel 1 of table 3 shows the percentage change in the ratio of women’s mean earnings to men’s mean earnings over each of the three business cycles that have occurred since 1975. As was done previously, direct comparisons across 1992–93 are excluded from the analysis because of the Census redesign. When the years from 1975 to 2004 are grouped into the business cycles of 1975–82, 1982–92, and 1993–2004, one finds that in each of the three business cycles the percentage change calculated with the Cell Mean Public Use series closely matches that calculated with the Internal series. In contrast, both the Consistent Topcode Public Use and the No Cell Mean Public Use series understate the percentage change that occurred in the 1975–82 business cycle and, to a lesser extent, also understate the change that occurred during the 1993–2004 business cycle. However, for the 1982–92 business cycle, these two series overstate the relative earnings gains of women. Thus, while each of these two series slightly misstates the relative earnings gains of Table 3. Percentage change in four ratios during the 1975–82, 1982–92, and 1993–2004 periods, according to four CPS data series Panel 1. Percentage change in the ratio of women’s mean labor earnings to men’s mean labor earnings Timespan No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 1975–1982 .............................................. 7.76 7.12 8.29 8.16 1982–1992 .............................................. 13.65 12.20 10.77 10.92 1993–2004 .............................................. 4.17 5.28 5.60 5.47 Panel 2. Percentage change in the ratio of Blacks’ mean labor earnings to Whites’ mean labor earnings Timespan 1975–1982 .............................................. 1982–1992 .............................................. 1993–2004 .............................................. No Cell Mean Public Use Consistent Topcode Public Use 1.60 3.04 4.51 0.55 2.32 –3.50 Cell Mean Public Use Internal 2.20 .78 –4.87 2.14 .90 –5.00 Panel 3. Percentage change in the ratio of the mean labor earnings of workers with a high school degree but no higher education to the mean labor earnings of wokers without a high school degree Timespan No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 1975–1982 .............................................. 3.33 3.20 3.29 3.16 1982–1992 .............................................. 4.79 5.38 4.55 4.43 1993–2004 .............................................. 5.31 4.99 5.47 5.06 Panel 4. Percentage change in the ratio of the mean labor earnings of workers with education beyond high school to the mean labor earnings of workers with a high school degree but no higher education Timespan No Cell Mean Public Use Consistent Topcode Public Use 1975–1982 .............................................. 1.70 2.37 1982–1992 .............................................. 5.63 7.04 1993–2004 .............................................. 6.14 5.18 SOURCE: Cell Mean Public Use Internal 1.24 8.66 3.39 1.58 8.41 4.33 Authors’ calculations made by use of public and internal CPS data. Monthly Labor Review • August 2009 11 Trends in Earnings Gaps women in all three business cycles, the direction of the misstatement is specific to the time period analyzed. in the Internal series. Panel 2 of table 3 displays the percentage change in the ratio of Blacks’ mean earnings to Whites’ mean earnings The gap in earnings between Blacks and Whites. Chart for each of the three business cycles. For every business 2 shows the ratio of Blacks’ mean earnings to Whites’ cycle, the relationships among trends in the ratios of Blacks’ mean earnings during the 1975–2007 period, according mean earnings to Whites’ mean earnings are similar to to the Internal series and each of the three methods of the relationships among trends in the ratios of women’s correcting for topcoding. Similar to the case of the ratio mean earnings to men’s mean earnings. Again, the Cell of women’s mean earnings to men’s mean earnings, using Mean Public Use series closely matches the trends in the the No Cell Mean Public Use series overstates the relative Internal series for all three business cycles. Additionally, earnings of black workers; the extent of this overstatement one also can see that during the 1975–82 business cycle, grows over time from 0.9 percentage points in 1975 to the Consistent Topcode Public Use and No Cell Mean 2.9 percentage points in 2004 before falling back to 1.3 Public Use series both slightly understate the relative gain percentage points in 2007. In another parallel to the ratio in earnings made by black workers, as compared with of women’s earnings to men’s earnings, the Consistent the Internal series. For the 1993–2004 business cycle, Topcode Public Use series overstates the relative earnings the Consistent Topcode Public Use and No Cell Mean of black workers by even more than the No Cell Mean Public Use series understate the relative decline in Blacks’ Public Use series, as white workers are more likely to be earnings in relation to Whites’ earnings. For the 1982– near the top of the earnings distribution and thus have 92 business cycle the No Cell Mean Public Use and the additional earnings suppressed by consistent topcoding. Consistent Topcode Public Use series slightly overstate However, the earnings ratio calculated from year to the earnings gains made by black workers. As was the case year with the Cell Mean Public Use series again closely regarding men’s and women’s earnings, although these matches the ratio from the Internal series, and it is the two series slightly misstate the percentage change in the best available method of replicating the earnings gap seen ratio of Blacks’ mean earnings to Whites’ mean earnings, Chart 2. Ratio of Blacks’ mean labor earnings to White’s mean labor earnings, according to four data series, 1975–2007 Ratio Ratio 0.80 0.80 0.76 0.76 0.72 0.72 0.68 0.68 0.64 0.60 1975 1977 No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 1979 1981 1983 1985 1987 1989 1991 SOURCE: Authors’ calculations made by use of public and internal CPS data. 12 Monthly Labor Review • August 2009 0.64 1993 1995 1997 1999 2001 2003 0.60 2005 2007 the direction of this misstatement varies over the three business cycles. It may not come as a surprise that the Cell Mean Public Use series is nearly able to replicate the results from the Internal series in generating comparisons of women with men and Blacks with Whites, since sex and race were two of the conditioning criteria used when generating the cell means for each earnings source. Thus, a natural question is whether the Cell Mean Public Use approach is as successful at replicating the Internal series for subsets of the population that do not match the conditioning criteria. Education mean earnings gaps. Mean earnings were calculated for the three levels of education previously mentioned: no high school degree, a high school degree but no higher education, and education beyond high school. For the 1975–2007 period, chart 3 displays the ratio of the mean earnings of workers with a high school degree but no higher education to the mean earnings of those without a high school degree. Chart 4 shows the ratio of the mean earnings of workers with education beyond high school to those of workers with only a high school degree. Both the charts present their respective ratios as calculated using data from the Internal series and each of the three methods of correcting for topcoding. In the creation of cells, level of education was not controlled for like sex and race were; therefore, the cells contain earnings figures from people of various levels of education. Nevertheless, as was seen with the earnings gaps between men and women and between Whites and Blacks, the “education earnings gaps” that are calculated using the Cell Mean Public Use series very closely match those calculated with the Internal series. Thus, it does not seem that the benefits of using cell means are confined to data calculated using the conditioning criteria of sex, race, and employment status. Additionally, this article finds that the degree to which labor earnings are understated when one uses the No Cell Mean Public Use or Consistent Topcode Public Use series increases with education because those with education beyond high school are more likely to have higher labor earnings and thus are more likely to have earnings suppressed by topcoding. Among the lower two education groups, there actually are some years in which the workers without a high school degree have earnings suppressed at a slightly higher rate than those with a high school degree, which causes the ratio of the mean Chart 3. Ratio of the mean labor earnings of workers with a high school degree but no higher education to the mean labor earnings of workers without a high school degree, according to four data series, 1975–2007 Ratio Ratio 1.45 1.45 1.40 1.35 1.40 No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 1.35 1.30 1.30 1.25 1.25 1.20 1.20 1.15 1.15 1.10 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 1.10 2005 2007 SOURCE: Authors’ calculations made by use of public and internal CPS data. Monthly Labor Review • August 2009 13 Trends in Earnings Gaps Chart 4. Ratio of the mean labor earnings of workers with education beyond high school to the mean labor earnings of workers with a high school degree but no higher education, according to four data series, 1975–2007 Ratio Ratio 1.80 1.80 1.70 1.60 1.70 No Cell Mean Public Use Consistent Topcode Public Use Cell Mean Public Use Internal 1.60 1.50 1.50 1.40 1.40 1.30 1.30 1.20 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 1.20 2005 2007 SOURCE: Authors’ calculations made by use of public and internal CPS data. earnings of the group with more education to the mean earnings of the group with less education to be higher in the No Cell Mean Public Use Series and the Consistent Topcode Public Use series than in the Internal series. In contrast, among the higher two education groups, in all years earnings are suppressed at a higher rate among those with some higher education than those with just a high school degree; therefore, not appropriately correcting for topcoding will lead to an understatement of the returns to higher education. Panels 3 and 4 of table 3 present percentage changes in ratios of mean earnings for the business cycles of 1975– 82, 1982–92, and 1993–2004, as calculated using data from the Internal series and the three other data series. The subject of panel 3 is the ratio of the mean earnings of workers with a high school degree but no higher education to the mean earnings of workers without a high school degree; the subject of panel 4 is the ratio of the mean earnings of workers with education beyond high school to those of workers with a high school degree but no higher education. Panels 3 and 4 take the same approach as panels 1 and 2 except that in panels 3 and 4, the ratio is of the group with the higher earnings to the group with 14 Monthly Labor Review • August 2009 the lower earnings. (The ratio is the other way around in panels 1 and 2). In each of the first two business cycles, there is a similar pattern to that seen for the mean earnings ratios of women to men and Blacks to Whites: the percentage changes calculated using the Cell Mean Public Use series are quite similar to those calculated the Internal series. Considering all three business cycles, the No Cell Mean Public Use series and Consistent Topcode Public Use series are less accurate in capturing trends, but, as is the case in panels 1 and 2, the direction of the misstatement is not systematic; the percentage change is understated in some years and overstated in others. In contrast to the findings concerning the earnings ratios of women to men and Blacks to Whites, in panels 3 and 4 the trends in data calculated using the Cell Mean Public Use series do not closely match the trends in data calculated using the Internal series in all three business cycles. In the 1993–2004 period, the Cell Mean Public Use series somewhat overstates the relative increase in the earnings of workers with a high school diploma (but no higher education) in relation to the earnings of workers without a high school diploma. This misstatement of the trend occurs primarily because the cells do not control for education, thereby causing variations in how closely cell means represent the individual components of the cells. Nonetheless, in calculating the relative earnings of the lower two education groups, the Cell Mean Public Use series still approximates the Internal series better than do the other series. For the 1993–2004 period the Cell Mean Public Use series somewhat understates the relative increase in the earnings of workers with some higher education in relation to workers with a high school diploma but no further education. Upon closer inspection, however, it can be seen that this understatement results mainly from the choice of 1993 as the first year in the timespan in question. In 1993 the difference (of 0.026) between the Internal and the Cell Mean Public Use series values for the earnings gap between those with some higher education and those with only a high school diploma is at its second largest amount over the entire 1975–2007 period. When 1994 is used as the base year, the Cell Mean Public Use values are much closer to the Internal series values. Thus, it is not that the Cell Mean Public Use series is unable to capture the trends in the Internal series in recent years, but rather that it does a poor job when 1993 is the anchor year. TOPCODING IS A WELL-DOCUMENTED PROBLEM for the CPS, but until recently, the only available strategy for mitigating the problem has been to place further restrictions on the data, either by using consistent topcoding or by discarding the cell means provided by the Census Bureau from 1995 onward. As a result, calculations have tended to understate true mean earnings in the United States. When comparing earnings across two groups within the population that are topcoded at different rates, all previously available topcode correction schemes may lead to a misstatement of the earnings gap between the groups. The authors of this article were able to partially lift the constraints of topcoding by obtaining access to the internal CPS data files. Although these internal data also are topcoded, the topcoding thresholds (censoring points) are substantially higher and more stable over time than those in the public-use CPS data. The key to this article is the extension of the cell mean series provided by the Census Bureau. The extension of cell means back to 1975 allows researchers using the public-use CPS data to estimate the earnings of individuals above the topcode threshold. Using the Cell Mean Public Use series with the public-use CPS data makes it possible to closely match the results found using internal CPS values from 1975 to 2007. Although the Cell Mean Public Use series best approximates the earnings statistics in the internal CPS data for groups based on race, sex, or employment status—because these characteristics are controlled for in the creation of cells—the cell mean series also is very useful for approximating the internal data for groups formed on the basis of other criteria, such as education level. Since the Cell Mean Public Use series is now available to the general public, researchers who are interested in exploring not just trends in earnings gaps and ratios but also more detailed questions about the underlying causes of gaps in pay can use the series to answer their questions with a precision similar to that obtained with access to the internal CPS files. For this article, four data series were used to calculate earning gaps between women and men, between Blacks and Whites, and among people of three levels of education—all who worked full time year round. Using the Cell Mean Public Use series resulted in earnings gaps that, on the whole, were moderately larger than those calculated using the No Cell Mean Public Use series. According to the public-use data without cell means, in 2007 the mean earnings of women who worked full time year round were 75.1 percent of those of their male counterparts. The figure drops to 72.3 percent when topcoding is accounted for through the use of cell means. Similarly, in 2007 the mean earnings of Blacks were 74.0 percent of those of Whites without the use of cell means, compared with 72.6 percent with the use of cell means. The largest change, however, occurs for groups based on educational attainment. For the year 2007, the mean earnings of workers with some postsecondary education were 64 percent more than the mean earnings of those with only a high school degree as calculated with data from the Cell Mean Public Use series, compared with 57 percent as calculated using the No Cell Mean Public Use series. Thus, the returns to higher education are understated substantially if cell means are not used. Sizes of individual earnings gaps and trends in earnings gaps both are sensitive to the choice of method of correcting for topcoding. Ignoring cell means and the earnings of individuals above the topcoding thresholds will distort the measured trends in earnings ratios between women and men, between Blacks and Whites, and among groups of different levels of education. However, unlike the case of earnings gaps, the direction of the distortion is not consistent and is sensitive to the years chosen for calculating the trends. Using public-use data without cell means will overstate relative changes in the earnings of women, Blacks, and the less-educated in some years but will understate relative changes in their earnings in other years. Monthly Labor Review • August 2009 15 Trends in Earnings Gaps NOTES ACKNOWLEDGMENTS: Support for the research in this article came from the National Science Foundation and the National Institute for Disability and Rehabilitation Research. The authors thank Lisa Marie Dragoset, Ian Schmutte, Arnie Reznek, Laura Zayatz, the Cornell Census RDC Administrators, and all their U.S. Census Bureau colleagues who have helped with this project. Each year the U.S. Census Bureau uses March CPS data to calculate yearly average income and poverty rates, and it releases these rates to the public; see www.census.gov/prod/2008pubs/p60-235.pdf (visited July 27, 2009) for more details. The March CPS data that the Census Bureau uses in its calculations are not available, except under certain conditions, to researchers outside of the Census Bureau. 1 For an early review of this problem in the earnings-inequality literature, see Frank Levy and Richard J. Murnane, “U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations,” Journal of Economic Literature, September 1992, pp. 1333–81. For a more recent discussion see Shuaizhang Feng, Richard V. Burkhauser, and J.S. Butler, “Levels and Long-Term Trends in Earnings Inequality: Overcoming Current Population Survey Censoring Problems Using the GB2 Distribution,” Journal of Business and Economic Statistics, January 2006, pp. 57–62. 2 See, among other sources, Chinhui Juhn, Kevin M. Murphy, and Brooks Pierce, “Accounting for the Slowdown in Black-White Wage Convergence,” in Marvin Kosters, ed., Workers and their Wages (Washington, DC, AEI Press, 1991); David Card and John E. DiNardo, “SkillBiased Technological Change and Rising Wage Inequality: Some Problems and Puzzles,” Journal of Labor Economics, October 2002, pp. 733–83; Kenneth Couch and Mary C. Daly, “Black-White Wage Inequality in the 1990s: a Decade of Progress,” Economic Inquiry, January 2002, pp. 31–42; and Chinhui Juhn, “Labor Market Dropouts and Trends in the Wages of Black and White Men,” Industrial and Labor Relations Review, July 2003, pp. 643–62. 3 For a discussion of the impact of topcoding on the income gap between men with and without disabilities, see Richard V. Burkhauser and Jeff Larrimore, “Trends in the Relative Household Income of Working-Age Men with Work Limitations: Correcting the Record using Internal Current Population Survey Data,” Journal of Disability Policy Studies, forthcoming article, see http://dps.sagepub.com (visited July 27, 2009). 4 The research in this article was conducted while the authors were Special Sworn Status researchers of the U.S. Census Bureau at the New York Census Research Data Center at Cornell University. The article was completed while Richard V. Burkhauser was a Visiting Scholar at the American Enterprise Institute. 5 In order to reduce the impact of changes in hours worked on the analysis of labor earnings, the sample used in this analysis is restricted to individuals over the age of 15 who work full time (35 hours or more per week) and year round (50 or more weeks per year). The Census Bureau uses the same restrictions for their annual analysis of earnings. (See page 10 of www.census.gov/prod/2008pubs/p60-235.pdf.) For this article, the sample is restricted also to individuals who are not in the military and do not reside in group quarters. These additional restrictions do not substantially affect the results. 6 Theresa J. Devine, “Characteristics of self-employed women in the United States,” Monthly Labor Review, March 1994, pp. 20–34. 7 8 Francine D. Blau, and Lawrence M. Kahn, “Gender Differences in 16 Monthly Labor Review • August 2009 Pay,” Journal of Economic Perspectives, Fall 2000, pp. 75–99. Carmen DeNavas-Walt, Bernadette D. Proctor, and Jessica Smith, Income, Poverty, and Health Insurance Coverage in the United States: 2006, Current Population Reports P60-233 (U.S. Census Bureau, 2007). 9 See “The Paycheck Fairness Act: Helping to Close the Gap for Women,” National Women’s Law Center, 2006, on the Internet at www.pay-equity.org/PDFs/PaycheckFairnessActApr06.pdf (visited July 27, 2009); and “The Gender Wage Ratio: Women’s and Men’s Earnings,” Institute for Women’s Policy Research, IWPR # C350, 2008, on the Internet at www.iwpr.org/pdf/C350.pdf (visited July 27, 2009) for examples of policy factsheets that use data from the Census Bureau. See Blau and Kahn, “Gender Differences in Pay”; and June O’Neill, “The Gender Wage Gap, circa 2000,” American Economic Review: AEA Papers and Proceedings, May 2003, pp. 309–14, for examples of using Census data for background information on the pay gap between men and women. 10 11 Francine D. Blau and Lawrence M. Kahn, “Swimming Upstream: Trends in the Gender Wage Differential in the 1980s,” Journal of Labor Economics, January 1997, pp. 1–42; Card and DiNardo, “Skill-Biased Technological Change and Rising Wage Inequality”; and O’Neill, “The Gender Wage Gap, circa 2000.” 12 Juhn and others, “Accounting for the Slowdown in Black-White Wage Convergence”; John Bound and Richard B. Freeman, “What Went Wrong? The Erosion of Relative Earnings and Employment Among Young Black Men in the 1980s,” Quarterly Journal of Economics, February 1992, pp. 201–32. Card and DiNardo, “Skill-Biased Technological Change and Rising Wage Inequality”; Couch and Daly, “Black-White Wage Inequality in the 1990s”; and Juhn, “Labor Market Dropouts and Trends in the Wages of Black and White Men.” 13 14 Outgoing rotation groups are groups of people who are in their fourth or sixteenth month as part of the sample. The survey of outgoing rotation groups contains questions on usual weekly and hourly earnings. However, unlike the income supplement in the March CPS, this survey does not contain detailed income questions asking about sources of income other than earnings. 15 Feng and others, “Levels and Long-Term Trends in Earnings Inequality.” 16 Complete annual statistics on topcoding rates and income by group as well as earnings ratios for all years from 1975 to 2007 for both the public use and internal use are available on request from the authors. A common refinement to the No Cell Mean Public Use approach is to assign topcoded individuals earnings that are a fixed multiple of the topcoding threshold—usually between 1.3 and 1.5. (See, for example, Blau and Kahn, “Gender Differences in Pay.”). While the addition of this refinement comes closer to capturing levels of earnings gaps, the trends are nearly identical to those seen in the No Cell Mean Public Use series, and the refinement does not account for changes in the distribution of earnings above the topcoding thresholds over time. For the sake of brevity, the results that were calculated through the use of this method are not included in this article, but they are available from the authors upon request. 17 18 Richard V. Burkhauser, J.S. Butler, Shuaizhang Feng, and Andrew J. Houtenville, “Long term trends in earnings inequality: what the CPS can tell us,” Economics Letters, February 2004, pp. 295–99; and Richard V. Burkhauser, Kenneth A. Couch, Andrew J. Houtenville, and Ludmila Rovba, “Income Inequality in the 1990s: Re-Forging a Lost Relationship,” Journal of Income Distribution, Winter 2004, pp. 8–35. 19 Jeff Larrimore, Richard V. Burkhauser, Shuaizhang Feng, and Laura Zayatz, “Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1975-2007),” Journal of Economic and Social Measurement, 2008, pp. 89–128. 20 For a more detailed discussion of internal censoring, see Edward J. Welniak, “Measuring Household Income Inequality Using the CPS,” in James Dalton and Beth Kilss, eds., Special Studies in Federal Tax Statis- Appendix A–1. tics 2003 (Statistics of Income Directorate, Internal Revenue Service, 2003); and Richard V. Burkhauser, Shuaizhang Feng, and Stephen Jenkins, “Using the P90/P10 ratio to measure U.S. inequality trends with the Current Population Survey: a view from inside the Census Bureau vaults,” The Review of Income and Wealth, February 2009, pp. 166–85. 21 For details on the redesign of the Census Bureau’s collection procedures, see Paul Ryscavage, “A surge in growing income inequality?” Monthly Labor Review, August 1995, pp. 51–61; and Arthur F. Jones and Daniel H. Weinberg, The Changing Shape of the Nation’s Income Distribution, Current Population Reports P60-204 (U.S. Census Bureau, 2000). Sources of labor earnings that are reported in the Current Population Survey Name Name in public files Name in internal files Definition 1975–86 Wages and salaries............................................ Self-employment............................................... Farm........................................................................ I51A I51B I51C Primary earnings................................................ ERN_VAL Wages and salaries............................................ WS_VAL Self-employment............................................... SE_VAL Farm........................................................................ FRM_VAL WSAL_VAL SEMP_VAL FRSE_VAL Wages and salaries Earnings from self-employment Farm earnings 1987–2007 ERN_VAL WS_VAL SE_VAL FRM_VAL Primary earnings Wages and salaries—second source Self-employment earnings—second source Farm earnings—second source SOURCES : Current Population Survey Annual Demographic File Technical Documentation, 1976–2002; Current Population Survey Annual Social and Economic Supplement Technical Documentation, 2003–08. Appendix A–2. Topcoding thresholds used for public CPS data and those used for internal data, by earnings source, selected years, 1975–86 Topcoding thresholds used for public data Topcoding thresholds used for internal data Year or years Wages SelfFarm Wages Self and salaries employment earnings and salaries employment 1975–80................................ 50,000 50,000 50,000 99,999 99,999 1981–83................................ 75,000 75,000 75,000 99,999 99,999 1984....................................... 99,999 99,999 99,999 99,999 99,999 1985–86................................ 99,999 99,999 99,999 250,000 250,000 Farm earnings 99,999 99,999 99,999 250,000 SOURCES: The topcoding thresholds used for public data come from Current Population Survey Annual Demographic File Technical Documentation. The topcoding thresholds used for internal data come from the authors’ calculations, which were made by use of internal CPS data. Monthly Labor Review • August 2009 17 Trends in Earnings Gaps Appendix A–3. Topcoding thresholds used for public CPS data and those used for internal data, by income source, selected years, 1987–2007 Topcoding thresholds used for public data Year or years Primary Wages earnings and salaries 1987–92............... 1993...................... 1994...................... 1995–2001.......... 2002–07............... 99,999 99,999 99,999 150,000 200,000 Topcoding thresholds used for internal data Self- Farm Primary earnings earnings employment 99,999 99,999 99,999 99,999 99,999 99,999 25,000 40,000 35,000 50,000 Wages and salaries Selfemployment Farm earnings 99,999 999,999 999,999 999,999 999,999 99,999 999,999 999,999 999,999 999,999 99,999 99,999 99,999 25,000 25,000 299,999 999,999 1,099,999 1,099,999 1,099,999 99,999 999,999 1,099,999 1,099,999 1,099,999 SOURCES: The topcoding thresholds used for public data come from the Current Population Survey Annual Demographic File Technical Documentation, 1987–2002, and from the Current Population Survey Annual Social and Economic Supplement Technical Documentation, 2003–08. The topcoding thresholds used for internal data come from the authors’ calculations, which were made by use of internal CPS data. 18 Monthly Labor Review • August 2009 Wherever-Provided Producer Price Indexes New wherever-provided services and construction indexes for PPI A new set of wherever-provided services and construction price indexes expands the BLS products covering the services and construction sectors of the economy; these indexes combine prices from all industries producing a specific service or construction product into a single price index for that service or product Jonathan C. Weinhagen and Bonnie H. Murphy E ffective with the release of July data on August 18, 2009, the Bureau of Labor Statistics (BLS) introduced a new set of wherever-provided (that is, commodity-based) services and construction price indexes. The new indexes measure price change for specific services and construction products, regardless of the provider’s industry of origin. Background and definitions Jonathan C. Weinhagen is an economist, and Bonnie H. Murphy is a supervisory economist, in the Office of Prices and Living Conditions, Bureau of Labor Statistics. E-mail: weinhagen.jonathan@bls. gov or murphy.bonnie@ bls.gov Prior to the mid-1980s, the BLS published industry and commodity-based price indexes for only the goods sector of the economy (mining, manufacturing, agriculture, and utilities). Due to the rapid growth of the U.S. services sector, the BLS undertook an effort to expand its coverage to include services and construction price indexes. This effort resulted in the publication of the first BLS industry-based service price index, the PPI for rail transportation, in January 1985. Through the mid-1990s, the services expansion effort continued, with the development of price indexes for many industries in the transportation sector that had relatively straightforward pricing methodologies. Over the past two decades, expansion efforts have moved forward to include indexes for more complex industries in the information, health care, real estate, professional services, administrative services, finance and insurance, and wholesale and retail trade sectors. Measuring price changes for industries in these sectors required the development of new, innovative pricing concepts, diverse sampling strategies, and unique data collection techniques. The BLS currently calculates and publishes price indexes representing approximately 77.4 percent of services1 and 28.6 percent of total nonresidential construction.2 Still, gaps in the coverage of services exist; for example, education services, computer systems design and related services, and scientific research and development services are not covered. As the BLS has expanded its coverage to include both the services and construction sectors of the economy, the expansion effort has focused primarily on the development of industry-based price indexes—indexes that measure price change for the output of an industry, including its primary, secondary, and miscellaneous production. Primary production is considered the industry’s main revenue-generating activity, whereas secondary and miscellaneous production encompasses additional activities from which the industry generates revenue. Secondary production is the production of nonprimary goods, while Monthly Labor Review • August 2009 19 Wherever-Provided Producer Price Indexes miscellaneous production is the provision of nonprimary services. For instance, the primary output of the wired telecommunications industry (NAICS 517110) is telephone-line provision services, such as local services, toll services, and private-line services. Miscellaneous production of this industry would include wired telecommunications services. In contrast to industry-based indexes, commoditybased price indexes measure price change for a (wherever-provided) service or (wherever-made) good, regardless of the producer’s industry of origin. For example, a wherever-provided index for air transportation of freight would measure price change for air transportation of freight from all industries which provide that service. Price changes from industries in which air transportation of freight is classified as either primary production or miscellaneous production would be included in the price index. In 2006, the BLS began an effort to develop a set of wherever-provided services and construction indexes. This effort included the creation of wherever-provided index weights, the development of an index construction methodology, the identification of the set of detailed whereverprovided indexes whose calculation and publication the BLS could support, and the development of an aggregation and publication structure for the detailed indexes. Aggregation and publication structure Instead of using an established product classification structure, the BLS developed its own publication structure for the new, wherever-provided indexes. Doing so allowed the Agency to build on and remain consistent with its already existing commodity-based structure for goods. The newly developed publication structure includes detailed product-level indexes, as well aggregate indexes that combine detailed price indexes for related services into higher level indexes. In developing the index publication structure, the BLS employed a set of six main principles. This section discusses each of these principles in detail and gives an overview of the publication structure. Coding structure. Indexes were grouped in accordance with a coding methodology similar to the current PPI commodity structure for goods indexes. Major groupings are coded at the two-digit level, and within these two-digit groupings are more detailed commodity groupings that descend in order of aggregation to the detailed-product level (typically, the eight-digit level). 20 Monthly Labor Review • August 2009 In order to remain consistent with current practice within the BLS goods-based aggregation structure, in some cases identical indexes are included at various levels of aggregation. For example, PPI 301401 and PPI 30140101 are identical indexes for air transportation of freight. Weight and price data do not support breaking out additional detail under 301401; therefore, no further eight-digit products could be added beneath the six-digit index. Instead, an eight-digit index denoting the same service was added. Although the current goods indexes encompass the two-digit groupings 01 through 15, the services groupings were numbered beginning with code 30. This choice permits a degree of flexibility that otherwise would be unavailable if the services structures began at two-digit group 16, directly following the last goods groupings. There may, for example, come a time when the numbering system for traditional commodities needs to be expanded or reorganized. The final services code in the structure is 60. Following the same line of reasoning, the BLS numbered the construction groupings beginning with twodigit group code 80. Similarity of product. Detailed indexes were grouped into higher level aggregates according to similarity of product. Data users often find this type of grouping useful, and the methodology is consistent with the current BLS organizational structure for goods-based commodity indexes, which also groups commodities according to similarity of product. For example, the two-digit index 30 encompasses all transportation services, the two-digit index 40 all investment services. Avoidance of multiple counting. In organizing the wherever-provided services indexes into two-digit groupings, the BLS attempted to avoid aggregations that would result in substantial multiple counting of price changes. Multiple counting, which can lead to inaccurate and distorted measures of price change, occurs when an aggregate index includes not only the price for a product, but also prices for one or more inputs to the product. The wherever-provided structure, for example, includes separate two-digit aggregations, one for transportation services and the other for services related to transportation, because services related to transportation are most often inputs to transportation services. Avoiding multiple counting will permit two-digit services commodity PPIs to provide meaningful information on price changes. Wherever-provided structure and PPI industry structure. In developing the index publication structure, an effort was made to develop alternative index aggregations not found in the industry structure. Within transportation services, for example, transportation of freight and mail were separated from passenger transportation. Then, separate aggregate indexes for total passenger transportation services, as well as total freight and rail transportation services, were created. By contrast, within the PPI industry structure, aggregations are based on mode of transportation. The industry structure includes, for instance, an aggregate index for air transportation that combines detailed indexes for air passenger and air freight transportation into a single index. In a second example, for book, periodical, and newspaper publishing, sales and subscriptions were separated from advertising space sales, and the latter category was combined into a two-digit grouping with advertising from all other media—for instance, television, Web sites, and radio. The industry structure, in contrast, aggregates indexes according to medium. Thus, the industry structure contains an aggregate index for all periodical publishers, and that index combines indexes for sales and advertising from all types of periodicals. A third example is that the wherever-provided structure separates wired telecommunications into residential services and business services and creates separate aggregate indexes for each. These indexes combine detailed indexes for local and long-distance telecommunications services into either the aggregate residential or the business telecommunications services index. The industry structure, by contrast, aggregates indexes according to long-distance or local telecommunications services. Partial coverage. Although the PPI covers all industries in the mining and manufacturing sectors, that is not the case in the services or construction sectors. Consequently, higher level aggregate indexes within the wherever-provided structure may be missing products that would be included if the PPI covered all services and construction industries. In cases where the PPI does cover a service area, but not all products under the aggregate area, the index is still published and the term “partial” is added to the end of the index title if the coverage is less than 80 percent. Within the transportation grouping, for example, only about 75 percent coverage exists for passenger transportation services. The PPI covers passenger transportation from air and rail, but does not currently cover boat, bus, taxicab, or several other forms of passenger transportation.3 Index reassignment from goods to services structure. In a small number of cases, the traditional PPI goods structure contained indexes for services. With the arrival of wherever-provided services indexes, the affected services indexes were removed from the goods structure and added to the new services structure. The areas affected by this change were publishing, metal treatment services, and mining services. Exhibit 1 presents an overview of the publication structure for services and construction up to the threedigit level.4 Weights An important step in developing the wherever-provided services and construction indexes was to construct a set of weights. The primary data source for these weights was Census Bureau revenue data—specifically, data for “Product Lines by Kind of Business.” These data are organized according to the North American Industry Classification System (NAICS) and indicate specific products provided by industries and the revenue value for these products. The products are organized according to Census Product Codes (CPCs).5 Note that, with its 2007 Economic Census survey, to be published by 2011, the Census Bureau will have completed its classification of service product-line data according to the North American Product Classification System (NAPCS), and PPI commodity weights for services will then be based on revenue figures from that system. The transition to NAPCS-based weights may result in some structural changes to the wherever-provided services indexes.6 However, in order to minimize future structural changes, the BLS reviewed the NAPCS structure while developing both the individual wherever-provided services indexes and the publication structure for those indexes. Wherever-provided weights were created by aggregating Census Bureau revenue data for individual products, regardless of the providers’ industries of origin. For example, the wherever-provided weight for auditing services was constructed by summing the revenues from all the industries that provide auditing services into a single value representing the total revenue of auditing services. (See exhibit 2.) The 2002 Census of Services classifies auditing services into two product lines: financial auditing services (CPC 34060) and tax auditing services (CPC 35800). Exhibit 2 presents the revenue for both of these products on an industry-by-industry basis. The first and second columns indicate, respectively, the Census of Services product code and title of the service being provided. The third and Monthly Labor Review • August 2009 21 Wherever-Provided Producer Price Indexes Exhibit 1. Summary of wherever-provided structure 30 Transportation services 301 Transportation of freight and mail 302 Transportation of passengers (partial) 31 Services related to transportation activities 311 Services related to water transportation 312 Services related to air transportation 313 Other selected services related to transportation activities (partial) 32 Warehousing, storage, and related services 321 Warehousing, storage, and related services 33 Publishing sales, excluding software 331 Book, periodical, and newspaper publishing sales and subscriptions 332 Directory, mailing list, and related compilations publishing sales 333 Greeting card publishing sales 334 Calendars, yearbooks, and other miscellaneous publishing sales 34 Software publishing 341 System software publishing 342 Application software publishing 35 Network compensation from broadcast and cable television and radio 351 Network compensation from broadcast and cable television 352 Network compensation from radio 36 Advertising space and time sales 361 Advertising space sales in periodicals, newspapers, directories, and mailing lists 362 Television advertising time sales 363 Radio advertising time sales 364 Internet advertising space sales (partial) 37 Telecommunication, cable, and Internet user services 371 Wired telecommunication services 372 Wireless telecommunication services 373 Cable and satellite subscriber services 374 Internet access services 38 Data processing and related services 381 Data processing and related services 39 Credit intermediation services (partial) 391 Loan services (partial) 392 Deposit services (partial) 393 Other credit intermediation services, including trust services 40 Investment services 401 Securities brokerage, dealing, investment advice, and related services 402 Portfolio management 403 Investment banking 41 Insurance and annuities 411 Insurance 412 Annuities 42 Commissions from sales of insurance 421 Commissions from sales of insurance 43 Real estate services (partial) 431 Nonresidential real estate services 432 Residential real estate services (partial) 433 Real estate appraisal fees 44 Rental and leasing of goods (partial) 441 Passenger car rental 442 Truck, utility trailer, and RV rental and leasing 443 Construction, mining, and forestry machinery and equipment rental and leasing 22 Monthly Labor Review • August 2009 45 Professional services (partial) 451 Legal services 452 Accounting services (partial) 453 Architectural and engineering services 454 Management, scientific, and technical consulting services 455 Advertising and related services (partial) 456 Information technology (IT) technical support and consulting services (partial) 46 Employment services 461 Permanent placement services 462 Executive search services 463 Staffing services 47 Travel arrangement services (partial) 471 Arrangement of flights from travel agencies (partial) 472 Arrangement of vehicle rentals and lodging (partial) 473 Arrangement of cruises and tours (partial) 474 Other travel arrangements (partial) 48 Security services (partial) 481 Guard services 49 Cleaning and building maintenance services (partial) 491 Janitorial services 50 Waste collection and remediation services (partial) 501 Waste collection 51 Health care services 511 Outpatient care (partial) 512 Inpatient care 513 Sales of blood and blood products, organs, and tissues 52 Educational services (partial) 521 Computer training school services 53 Accommodation services 531 Travelers’ accommodation services 54 Food and beverage for immediate consumption services (partial) 541 Food and beverage for immediate consumption services (partial) 55 Repair and maintenance services (partial) 551 Commercial and industrial machinery and equipment repair and maintenance 552 Motor vehicle repair and maintenance (partial) 553 Ship repair and maintenance 554 Aircraft repair and maintenance 56 Entertainment services (partial) 561 Membership dues and admissions and recreation facility use fees (partial) 562 Recreational activity instruction fees (partial) 563 Gaming receipts (partial) 564 Amusement machine receipts (partial) 57 Wholesale trade services 571 Machinery and equipment and parts and supplies wholesaling 572 Furnishings wholesaling 573 Building materials and hardware wholesaling 574 Metals, minerals, and ores wholesaling 575 Chemicals and allied products wholesaling 576 Paper and plastics products wholesaling 577 Apparel wholesaling 578 Food and alcohol wholesaling 579 Other commodities wholesaling 58 Retail trade services 581 Food and alcohol retailing 582 Health and beauty care retailing, including optical goods Exhibit 1. Continued—Summary of wherever-provided structure 583 Apparel and jewelry retailing 584 Computer hardware, software, and supplies retailing 585 TV, video, and photographic equipment and supplies retailing 586 Automobiles and automobile parts retailing 587 Manufactured (mobile) homes retailing 588 RVs, trailers, and campers retailing 589 Sporting goods, including boats, retailing 58A Lawn, garden, and farm equipment and supplies retailing 58B Furniture retailing 58C Flooring and floor coverings retailing 58D Hardware and building materials and supplies retailing 58E Major household appliances retailing 58F Fuels and lubricants retailing fourth columns respectively designate the NAICS code and title of the industry or industry group providing the services. The last column shows the revenue for the specific service. Thus, the first row shows that industry group 541 (professional, scientific, and technical services) produced $11,243,910,000 of commodity financial auditing services (CPC 34060) in 2002. Exhibit 2 shows that the total revenue generated by all industries for financial auditing services in 2002 was $11,339,564,000 and that the total revenue generated by all industries for tax auditing services that same year was $700,415,000. Therefore, the total 2002 revenue and the wherever-provided weight for auditing services is $11,339,564,000 + $700,415,000 = $12,039,979,000. This figure represents the weight the BLS would assign auditing services within the wherever-provided structure. Index construction This section describes both how the wherever-provided weights are used to construct the commodity-based services indexes and some additional aspects of index construction. The wherever-provided services indexes are calculated by the same methodology that is used for calculating commodity PPIs for mining, manufacturing, agriculture, and utilities. Like other commodity PPIs, the wherever-provided services indexes are typically published at the eight-digit product level. However, additional detailed indexes are calculated below the eight-digit level, and these indexes are aggregated to create the published eight-digit index. The detailed indexes are created to increase accuracy by allowing for a more precise weighting structure than would exist if just the eight-digit index were calculated. For a specific commodity, unpublished detailed indexes measuring the average change in the selling price from every industry that is a primary producer of the com- 58G Cleaning supplies and paper products retailing 58H Book retailing 58I Other merchandise retailing (partial) 59 Metal treatment services 591 Metal treatment services 60 Mining services 601 Mining services 80 Construction 801 New nonresidential building construction 802 Nonresidential building maintenance and repair construction (partial) modity are calculated. In addition, a single index tracking price change in industries in which the commodity does not represent their primary production is calculated. The unpublished indexes are then aggregated into an eightdigit wherever-made index. Prior to the implementation of the updated PPI estimation system in 2008, the BLS was unable to calculate detailed indexes for nonprimary producers to use in wherever-provided index estimation. The new estimation system allowed for this improvement in index calculation methodology. The new system also resulted in additional improvements for commodity-based calculation, including more accurate monthly weights and the possibility of calculating detailed product indexes not found within the industry-based indexes. As stated earlier, the PPI does not cover all industries in the services or construction sector. In cases where the index covers some industries producing a specific product, but is missing more than 20 percent of the production of the service, the uncovered weight is removed from the wherever-provided index. As mentioned earlier, the suffix “partial” in the title of the index informs the data user that the index includes only a portion of the wherever-provided service. Conversely, the PPI includes the weight of the missing industry (or industries) within the whereverprovided index in cases where coverage of a specific commodity is at least 80 percent. These indexes are published without the “partial” designation, and the weight is imputed with the use of standard PPI imputation methodology. For the product index, either removing or imputing the weight will yield the same index calculation. For higher level aggregate indexes, however, removing or imputing a commodity index’s weight will yield a different result.7 Finally, note that the wherever-provided indexes for new construction are methodologically identical to the industry-based new-construction indexes. These two sets of indexes are built from identical weights and share the Monthly Labor Review • August 2009 23 Wherever-Provided Producer Price Indexes Exhibit 2. Example of construction of wherever-provided index weight: auditing services Census of Census of Services Services product product title code NAICS Revenue (thousands) industry NAICS industry title code 34060 Financial auditing services 541 Professional, scientific, and technical services 34060 Financial auditing services 541211 Offices of certified public accountants 34060 Financial auditing services 541611 Administration management and general management consulting services 34060 Financial auditing services 541612 Human resources and executive search consulting services 34060 Financial auditing services 541613 Marketing consulting services 34060 Financial auditing services 541614 Process, physical distribution, and logistics consulting services 34060 Financial auditing services 541620 Environmental consulting services 34060 34060 Financial auditing services Financial auditing services 561 Administrative and support services 561110 Office administrative services 34060 Financial auditing service 35800 35800 Tax auditing services Tax auditing services 541 Professional, scientific, and technical services 541211 Offices of certified public accountants $11,243,910 10,831,314 394,940 4,068 8,357 3,978 1,253 95,654 95,654 total 11,339,564 700,415 665,489 35800 Tax auditing services 541219 Other accounting services 34,926 35800 Tax auditing services total 700,415 total auditing services 12,039,979 SOURCES: U.S. Census Bureau, Census of Services, 2002; North American Industry Classification System (NAICS). same base dates and history. The wherever-provided newconstruction indexes and their respective industry-based indexes therefore will exhibit identical month-to-month percent changes. For construction, the industry and wherever-provided indexes are the same because the BLS defines all types of new construction as primary production in all new-construction industries. The wherever-provided construction indexes were developed simply to provide completeness within the commodity-based PPI structure. WITH THE RELEASE OF JULY 2009 DATA IN AUGUST, the BLS expanded its coverage of the services and construction sectors of the economy to include wherever- provided producer price indexes. These indexes track price change for services and construction products, regardless of their industry of origin. Wherever-provided price indexes add analytical value to the PPI by allowing data users to examine price movements for a specific service or construction product within a single price index that combines prices from all industries producing that product. In addition, detailed price indexes are aggregated into many higher level indexes not found in the industry-based PPI aggregation structure. These wherever-provided aggregations give data users a large number of additional aggregate indexes, thereby further increasing the analytical usefulness of the PPI. NOTES 1 Based on 1992 Bureau of Economic Analysis data from the Gross Product Originating Industry Accounts. 2 Based on 2007 Census Bureau data from the Value of Construction Put in Place series. 3 For a list of all partial-coverage indexes and explanations of missing coverage, go to www.bls.gov/ppi/partialcoverage.pdf. For the entire publication structure, go to www.bls.gov/ppi/wep_rel_ imp_200906. 4 24 Monthly Labor Review • August 2009 5 A concordance between the wherever-provided services indexes and can be found at www.bls.gov/ppi/wep_cpc_concord.pdf. CPCs 6 NAPCS-based weights have not yet been implemented in the 2007 Economic Census for the goods-producing sector, so the weighting structure for goods will not be affected. 7 Again, the complete list of partial-coverage indexes, as well as explanations of missing coverage, can be found at www.bls.gov/ppi/partialcoverage.pdf. Income Imputation The impact of income imputation in the Consumer Expenditure Survey With the release of 2004 data from the Consumer Expenditure Survey, the Bureau of Labor Statistics began implementing imputation for missing responses to questions about income; imputation has brought CE estimates closer to CPS estimates, but significant disparities remain between the estimates for many of the smaller components Bill Passero Bill Passero is a senior economist in the Branch of Information and Analysis, Office of Prices and Living Conditions, Bureau of Labor Statistics. E-mail: passero.bill@ bls.gov F rom 1980, the year the Consumer Expenditure Survey (CE) became a continuous survey, until 2004, no procedures were employed to produce estimates for sources of income that respondents acknowledged receiving, but for which they did not provide values. However, the release of 2004 data marked the introduction of imputation for missing income responses. With a number of years of imputed income data now available, it is possible to evaluate how well BLS imputation routines are working. The purpose of this article is to assess the impact and efficacy of imputation by comparing pre- and postimputation estimates of CE-reported income with estimates from the Current Population Survey (CPS), a large-scale household survey that has employed imputation for many years in the course of producing its income estimates. In the next section, after a brief discussion of the background and history of income imputation in the CE, the methodology for comparing CE and CPS income estimates is presented. Then the timing of income data collection in the two surveys is examined. Timing is important because it affects the construction of matching periods for comparison. The discussion then proceeds to detail the structure and content of the income questions asked in each survey’s respective collection instrument. Following the latter discussion, the next section of the article is dedicated to a comparative analysis of aggregate income estimates from the CE and CPS. The common income categories that can be created from the two surveys are detailed, and three alternative estimates of CE income are described. These estimates are then measured against CPS estimates. The analytical portion of this section is devoted to examining both levels and ratios of CE and CPS aggregates, for total income and by income category. The final section of the article briefly summarizes the results of the analysis and notes the direction that future refinements in the collection and imputation of income in the CE are likely to take. Background The CE produces comprehensive expenditure data reflecting the buying habits of U.S. families. Because it is vital that the soundness and consistency of these data be maintained, the Monthly Labor Review • August 2009 25 Income Imputation conducts regular, thorough comparisons of CE data with expenditure data from other sources, such as the Personal Consumption Expenditures (PCE) component of the National Income and Product Accounts produced by the Bureau of Economic Analysis.1 But a unique feature of the CE which makes it particularly useful is that, as a household survey, it also collects demographic and socioeconomic characteristics of participants that can be associated with the expenditures they make. Among these characteristics is family income, one of the most important demographic determinants of consumer spending. Household surveys intent on collecting data on family income, either as their primary interest or as supplementary to their primary interest, often encounter the issue of nonresponse because of the sensitive nature of income data. Respondents frequently feel uncomfortable answering questions about their income or may believe that such questions are an invasion of their personal privacy. Survey managers have resorted to various methods developed by the statistics community for imputing values to substitute for missing responses. These methods make certain assumptions about the distribution of missing values and the relationship of nonresponse to socioeconomic characteristics of the sample population. To the extent that the procedures violate the mechanisms leading to nonresponse, the resulting imputed values will lead to biased and inconsistent results when used for analytical purposes. CE managers have become particularly sensitive to these concerns because sampled consumer units2 report expenditure data that are expected a priori to be highly correlated with income. Consequently, from 1972 to 2003 the CE did not impute for missing income, and CE data releases instead identified sample households as either “complete” or “incomplete” income respondents.3 Given the unique requirements that any income imputation procedure would have to satisfy, CE and Census Bureau staff began a systematic search for an appropriate method. Geoffrey Paulin and David Ferraro laid out theoretical and practical issues that would have to be resolved before a method could be selected.4 Two general methods for performing imputations merited evaluation. Hot-decking was the technique employed by large-scale surveys such as the CPS. This technique imputes missing income values in the sample with values reported by persons in families with a similar set of demographic and socioeconomic characteristics, predetermined to be relevant to the level of income. Paulin and Ferraro eliminated hot-decking as a method for the CE because of the small sample size of that survey. BLS 26 Monthly Labor Review • August 2009 The second class of methods examined was modelbased imputation, which draws on the work of Roderick Little and Donald Rubin.5 Each of these methods consists of two parts. The first part involves the creation of a statistical model to predict income values, while the second part is concerned with producing error terms to add to the predicted values, thereby preserving the variance of the distribution. To employ a model-based imputation method appropriately, the response mechanism by which the missing income responses came into being had to be determined first. Little and Rubin laid out three mechanisms. In the first, the missing income responses occur completely at random and are not correlated with any characteristics of the respondents. In the second, the missing responses are correlated with characteristics of the respondents, excluding income. In the final method, the missing responses are correlated with both characteristics of the respondents and the level of income. In addition, two operational modeling questions had to be answered: first, would income imputation be done at the consumer unit level or at the individual member level within each consumer unit? and second, would imputation be done for total income or for each of the component items of total income? After researching these questions, Paulin and Ferraro concluded that the second response mechanism, wherein nonresponse is correlated with respondent characteristics only, would be tested first. This testing would then be aimed toward (1) imputation at the consumer unit level, which would avoid complications introduced by interactions involving work decisions between members, and (2) individual components of income, which would provide more information for researchers and allow for differences in model specification and parameter estimates between items. Finally, Paulin and Ferraro addressed the question of whether expenditures were useful in predicting income and, therefore, should be included in modeling. Testing also would confirm retrospectively whether past reluctance to impute with methods that did not account for expenditures was justified. Paulin and Ferraro found that both total expenditures and expenditures for selected subaggregations of items demonstrated predictive power. While research continued into the appropriate method for imputing income in the CE, changes were made in the collection instruments in 2001 to improve the reporting of income. Bracketing questions were added to the survey to follow the initial questions. The bracketing questions asked for the amount received for each source of income a respondent indicated that the consumer unit had received. Thus, if a respondent initially refused to report his or her income or did not know the amount received, the bracketing questions probed to determine whether the respondent would select a range that best reflected the amount received. The responses to the bracketing questions added a layer of complexity to the task of choosing an imputation method. Once the research was completed, it was determined that the method chosen for the CE would be a regression-based procedure that would preserve both means and variances for each source of income. The process would produce five imputed values for each missing observation. The first step would be to run a regression to obtain coefficients to use in creating imputed values. Random noise would then be added to each coefficient, and the resulting “shocked” coefficient used to estimate an imputed value. Additional noise would be added to the estimated values to ensure that consumer units with similar demographic characteristics would not receive similar imputed incomes. After the five imputed values were created for each missing value, an estimate representing the mean of those five values would be calculated. Reported specific values would be retained as is. If a respondent reported a certain bracket within which his or her income fell, the imputed values would have to fall within the range defined for that bracket. In a small number of instances, a consumer unit might report not receiving income from any source. In such an extremely unlikely situation, the income imputation procedure would be run with an additional step: a logistic regression based on the characteristics of the consumer unit, such as whether he or she was retired or was a student, would be run first to impute a receipt status (yes or no) for each source of income. For those sources of income that a consumer unit was imputed to have received, the model would be run to produce imputed income values. Data collection The introduction of imputed income in data released from the 2004 CE permits the same kind of comparisons between the CE and other sources that have been made in the past for expenditure items. In fact, by comparing the CE income estimates with those from another established source of income data over a period covering pre- and postimputation years, one can measure both the impact of imputation on the relationship of aggregate CE income to the independent source and the efficacy and quality of the imputation method in producing those estimates. For this study, CE income data are compared with similar data from the CPS for the 2002–06 period. Comparisons of mean or aggregate pretax income between the CE and the CPS have been a staple feature of BLS publications for almost 20 years.6 Almost all these published comparisons were based on CE data before imputation and CPS data that included imputed values. Income estimates for the CE are from its Interview Survey component, while the Annual Social and Economic Supplement (ASEC) is the source of CPS income data for comparison in this study. The difference in timing of the collection of income data between the CE and the CPS poses challenges in constructing matching periods for comparison purposes. The Interview Survey is designed to collect one year’s worth of expenditure data from sample units. This is done through five interviews, the first interview for bounding purposes only and the remaining four interviews conducted at 3month intervals, thereby collecting expenditure data for 12 months. The Interview Survey uses a rotating design whereby sample units are introduced every month (replacing other units that have completed their participation in the survey.) Income data are collected during the second and fifth interviews, covering the 12 months prior to the month of the current interview. Thus, a consumer unit undergoing the second interview in June 2007 would report wage income received from June 2006 through May 2007. The ASEC is conducted annually in March, although a limited number of eligible households are interviewed in February and April. The survey collects data on the previous calendar year’s income from all sources. Thus, households completing the ASEC in March 2007 report income for the 2006 calendar year. Conducting the ASEC in March is believed to provide better income data, because most households would either be in the process of completing or have just completed preparing tax returns and therefore would be more likely to remember income sources and amounts. Although the structure and wording of income questions are similar in the CE and the CPS, there are major differences that can affect the estimates. In the CE, the respondent is asked to report the amount received from earned income, Social Security, Railroad Retirement, and Supplemental Security Income individually for each consumer unit member aged 14 years and older. For each of the remaining sources of income, the respondent reports the amount received by the consumer unit as a whole. In comparison, in the ASEC the respondent is directed to report individually the amount received for each source Monthly Labor Review • August 2009 27 Income Imputation of income by each household member 15 years or older. Regarding income reference periods, the CE respondent is asked about the amount received over the last 12 months for each source of income, with the exception of Social Security and Railroad Retirement income, for which the respondent reports the amount of the last payment received. If the respondent either refuses to answer or does not know the amount received for any of these sources, he or she is shown a card with ranges or brackets of income and then is asked to report which bracket best reflects the amount received. In the ASEC, respondents are asked to report the amount received over the calendar year. If they find that a year is too big a time span over which they can exercise recall, they are allowed to report for shorter periods. The periodicity of their response is asked if necessary. Sources of income With respect to the contents of the income questions, and using the CE questions as a basis for comparison, one readily sees that it is natural to consider earned income first, because it is by far the largest contributor to total income. The questionnaire in the Interview Survey asks the amount each eligible member of the consumer unit received in wages and salaries (including commissions, tips, allowances, Armed Forces pay, severance pay, teaching fellowships, and the like) for all jobs. The Interview Survey also collects data in a separate question on income or losses after expenses from each consumer unit member’s unincorporated nonfarm business, partnership, or professional practice, as well as income or losses from the consumer unit’s own farm. The ASEC asks for earnings, including tips, bonuses, overtime pay, and commissions, from the employer for whom the member worked longest during the calendar year. Such earnings can be wage and salary income, net income (or loss) from nonfarm self-employment, or net income (or loss) from farm self-employment. Three followup questions probe for earnings from other employers, other nonfarm businesses, and other farms. Severance pay and military allotments are included in earnings, and questions on these topics are asked in combination with questions on other miscellaneous sources of income after the questions for all other specific income categories have been asked. The CE probes for amounts of Social Security and Railroad Retirement income received. These amounts include survivor and disability insurance payments, as well as retirement benefits. The ASEC asks separate questions about Social Security income and Railroad Retirement income. Data on Social Security income are obtained 28 Monthly Labor Review • August 2009 from a question on payments received by the household member directly or on behalf of children under age 19 in the household. Data on Railroad Retirement income are collected in questions covering three broad categories of income for which an individual may be eligible under the program: pension or retirement income, survivor benefits, and income related to a health condition or disability. Supplemental Security Income (SSI) is one of the few sources of income for which the CE and ASEC questions are essentially the same. Both surveys ask for the amount of SSI received from all government sources. Questions collecting data on interest income in the CE and ASEC also are quite similar. The only difference is in the potential sources of interest income referenced in the questions. The Interview Survey probes for interest from bank accounts, money market funds, certificates of deposit, or bonds, whereas the ASEC uses three questions that specifically screen for whether any members of the household have received any interest from money market funds, interestearning checking accounts, savings accounts, cashed savings bonds, treasury notes, individual retirement accounts (IRAs), certificates of deposit, or other investments that pay interest. In one of its questions, the CE queries respondents for amounts of regular income from dividends, trusts, estates, or royalties. The types of income cited in this question also are found in a number of places in the ASEC questionnaire. One question is specifically directed toward dividends from stocks and mutual funds. Data on receipts from estates or trusts are collected in two places. The first is as a source of survivor benefits, the second as a class of property income. Data on net royalty income also are collected in the latter question. Data on pension and annuity income, whether due to retirement, due to disability, or as a survivor, are collected through one question in the CE Interview Survey. Sources specified for such income are private companies, the military, government, IRAs, and Keogh plans. As mentioned earlier with regard to Railroad Retirement income, the ASEC inquires about retirement and pension income, survivor benefits, and disability income in separate questions. The question about retirement and pension income refers to all such income from a previous employer or union, or any other type of retirement income from sources other than Social Security or veterans’ benefits. With the exception of retirement income from Railroad Retirement, the income data collected here conceptually match CE counterpart data. The ASEC query on survivor benefits also mentions widows’ pensions, insurance annuities, and other survivor benefits (other than Social Security or veterans’ benefits). Income from survivor pensions from private companies; unions; Federal, State, and local governments; and the military are reported here. The ASEC questions concerning income related to a health condition or disability identify many of the same sources that are listed for survivor benefits, such as companies, unions, government at all levels, and the military. Finally, though not explicitly stated in the question, income received from foreign government pensions is offered as an example of one of the types of income the miscellaneous income question at the end of the ASEC is designed to capture. Unemployment compensation and supplemental unemployment compensation are other sources of income cited in the CE Interview Survey questionnaire. The ASEC poses three separate questions on unemployment compensation. One asks for the amount of State or Federal unemployment compensation, the second probes for income from supplemental unemployment benefits, and the third focuses on union unemployment or strike benefits. The CE asks respondents to combine income received from worker’s compensation or veteran’s benefits, including the GI bill, but excluding military retirement benefits, in one report. Worker’s compensation is surveyed in a distinct question in the ASEC, but the question also covers any other payments made as a result of a job-related injury or illness. Worker’s compensation benefits, including benefits for black lung disease, also are reported in the aforementioned ASEC questions on survivor benefits and disability income. The receipt of veterans’ benefit payments warrants its own question in the ASEC, but not in the CE. Another question in the CE Interview instrument pertains to income received as public assistance or welfare. In 2002, the questionnaire used Aid to Families with Dependent Children and grants from Job Corps as examples of such assistance. In subsequent years, the questionnaire was revised to refer specifically to cash assistance from any State or local government welfare program, such as Temporary Assistance to Needy Families, or short-term emergency help. The main question that seeks this information in the ASEC probes for cash assistance received from a State or county welfare program (with the name of a representative State program added as an example), either directly or on behalf of children in the household. The miscellaneous-income question at the end of the ASEC lists welfare, emergency assistance, and other shortterm cash assistance as examples of the types of income to be reported. Two questions in the CE Interview Survey instrument cover any net income or loss from any type of rental of rooms or living units. The first question is directed toward collecting data on net income or loss from roomers or boarders; the second focuses on ascertaining data on net income or loss received from other rental units. The property income question in the ASEC, which was heretofore mentioned as a source for trust/estate and royalty income, also seeks information on net income or loss from rental property and receipts from roomers and boarders. Child support payments not received as a lump sum are an additional component of income found in the CE Interview Survey. A similar question appears in the ASEC. The CE Interview Survey questionnaire asks about regular income from alimony or other sources, such as income from persons outside the consumer unit. The ASEC splits these sources between two questions, the first referring to alimony payments, the second to regular financial assistance from friends or relatives not living in the household. Finally, the CE Interview Survey poses a catchall question seeking information about “other” money income. Among the sources from which this other money might have been received, the question lists cash scholarships and fellowships, stipends not based on working, and the care of foster children. All other income from a source not specified in previous questions is to be reported here. The ASEC contains a question requesting information on educational assistance for tuition, fees, books, or living expenses, including Pell Grants. Listed in this question as sources of educational assistance are scholarships and grants, as well as employers, friends, and relatives living outside the household. Assistance from any of these sources could be reported in a number of places in the CE. To the extent that a student is receiving regular payments, such payments would be reported as regular income from sources outside the consumer unit. If the assistance is earmarked for a particular educational expense, such as tuition, it could be reported in the educational expenses section of the CE as an expenditure for which reimbursement is received. The miscellaneous-income question at the end of the ASEC encompasses payment for caring for a foster child, as well as any other money income not already covered by earlier questions. The ASEC is designed to cover the civilian noninstitutional population, plus those military personnel who live with at least one other civilian adult, on or off base. The CE also is designed to represent the civilian noninstitutional population, plus a portion of the institutional population: residents of boarding houses; those living in student or worker housing facilities, such as college dormitories; Monthly Labor Review • August 2009 29 Income Imputation staff units in hospitals or in homes for the aged, infirm, or needy; and those residing in permanent living quarters in hotels, motels, or mobile home parks. Nursing home residents are excluded, as are military personnel living on base. Off-base military personnel are included. Comparison of CE and CPS income Sources and timeframes. ASEC income data used in this article are derived from an unpublished Census table titled “In-House Table 8. Income Allocation by Income Source,” which the CPS produces annually for its internal use. For each source of income, the table shows the number of persons 15 years and older (in thousands) who receive income from that source and the mean amount of income they receive. Both those directly reporting income and those for which allocation is done are covered. In Census parlance, allocation is the equivalent of imputation in the CE. The means and numbers of persons reporting each source of income are multiplied together to obtain aggregate income. The income categories shown here are the most detailed that can be constructed from the types of income provided in table 8 from the ASEC and the income Universal Classification Codes from the CE.7 Total aggregate income is composed of the following categories: wage and salary income; net nonfarm self-employment income; net farm self-employment income; unemployment compensation; workers’ compensation (including compensation for black lung disease) and veterans’ benefits; Social Security and Railroad Retirement income; Supplemental Security Income; public assistance; pensions and annuities; interest; dividends, rents, royalties, and estates and trusts; child support; and accident and temporary insurance, educational assistance, alimony, financial assistance, and other income not elsewhere classified. As noted earlier, annual estimates of income for the CPS match the calendar year, while the annual estimates of income for the CE Interview Survey cover the year prior to the month of interview. Thus, a major issue in comparing CE and CPS income estimates is determining how to select consumer units for inclusion in the analysis. After due consideration, three estimators of CE income were chosen. The first replicates the method used for producing income estimates in the CE-CPS income comparison tables (and the reference tables) that appear in CE publications.8 Recall that the CE Interview Survey collects expenditure data for the 3 months prior to the interview month; annual income reported by consumer units in their second 30 Monthly Labor Review • August 2009 or fifth interview is adjusted to fit the same period. In practice, this means dividing the annual amount by 12, thus creating a monthly amount, and then assigning that amount to each of the 3 months covered by the interview. For example, if a consumer unit reports $600 of interest income at its second interview in March 2006, this process will assign $50 ($600 ÷ 12) to each of the months from December 2005 through February 2006, the reference period for the interview. Second-interview income is carried forward through the third and fourth interviews before the income data are collected again at the fifth interview. Thus, at its third interview in June 2006, the aforementioned consumer unit would have $50 of interest income assigned to each of March, April, and May of 2006. The annual CE estimate for any calendar year will be calculated from all income assigned to that year. Compared with the CPS estimate, the estimate created by this method uses a significant amount of income reported from an earlier period. With 2006 as an example, the first month whose interviews would be used in the CE estimate is February. One-twelfth of the income reported in that interview would be assigned to January. However, the 12-month reference period for reporting would run from February 2005 through January 2006, meaning that 11 months of the reference period would have been outside the calendar year of interest. April 2006 would be the first month in which one-twelfth of the annual income reported would be allocated to a 3-month reference period in which each month would be in 2006 ( January–March). Yet the recall period for income in the April 2006 interviews is April 2005–March 2006, a full 9 months of which still are outside the year of interest. In fact, the only month whose interviews would span a recall period matching the ASEC calendar year is January of the next year. (For calendar-year 2006, interviews conducted in January 2007 would have an annual reference period from January 2006 to December 2006.) This fact forms the basis for the second method of creating CE estimates for comparison with CPS income estimates: only the second and fifth interviews conducted in January of the next year are used to construct the estimate. Although using such interviews would exactly match the period covered by the ASEC, the number of interviews is very small—about one-sixth of the number of interviews conducted in any one quarter. This small number of interviews would be detrimental to the statistical reliability of the estimate, potentially leading to wide annual swings in it, particularly for some of the more thinly reported categories of income. Because of the conceptual attractiveness of the sec- ond method in matching the ASEC timeframe, the third method for creating CE estimates essentially expands on the second method. Centering on January interviews, this method adds the second and fifth interviews conducted between October of the previous year and April of the current year, or 3 months before and after January, to expand the number of interviews used in creating the estimate. As a result, one-seventh of the interviews report income earned in the year matching the calendar year. The earliest 12-month period, reported by one-seventh of the interviews, would run from October 1 of the previous year to September 30 of the current year; similarly, another one-seventh of the interviews would cover the latest 12month period, from April 1 of the current year through March 31 of the next year. In all three methods, weighting adjustments are made to ensure that the aggregate estimates are representative of the entire population. The adjustments start with the fact that sample units in the CE Interview Survey are assigned population weights such that the sum of the weights for consumer units interviewed in a calendar quarter will equal one national population. Thus, for any month, the sum of the weights of interviewed units will be approximately one-third of the national population and the sum of the weights of units undergoing a particular interview—the second, third, fourth, or fifth—during that month will approximate one-twelfth of the national population. To obtain a population-weighted estimate of CE income by the first method is straightforward because of the way annual income is mapped to the reference months of each interview. For example, all income assigned to March 2006 would originate in interviews conducted from April through June of 2006. The weights assigned to consumer units interviewed during those 3 months would approximate one national population. Thus, one can calculate a nationally representative estimate of March 2006 income by applying the weights to the income reported. This procedure can be extended to each month of a calendar year, and then a weighted annual estimate for each year can be derived by summing the monthly estimates. The weighting adjustment for the second method of estimating CE income also is fairly simple and is expanded to apply to the third method. The second method uses the second and fifth interviews in January of a survey year. These interviews represent approximately one-sixth of the interviews conducted in the first quarter of the year; thus, their weights are multiplied by 6 to produce a weighted national estimate. In the third method, the weights for the second and fifth interviews taken over the 7 months from October to April would represent about one-and- one-sixth times the national population. Rather than deflate them all equally, it was decided that the weights for units undergoing their second and fifth interviews in the outlying months of October and April would be cut by one-half. This decision would be simple to implement and would assign greater weight to interviews conducted in months closer to the central month of January. Results. The impact of imputation in the CE can be seen in table 1, which shows aggregate incomes, total and by source, from the CE and CPS, along with the ratio of CEto-CPS estimates for the years 2002–06. The CE did not impute for income nonresponse in the first 2 years of this period, so the estimates are based on all reported income, regardless of whether the consumer unit was considered a complete or incomplete income respondent. Imputation significantly raises CE aggregate income, bringing it into near comparability with CPS estimates. On average, imputation adds about 20 percentage points to the CE/CPS ratio. For the preimputation period of 2002–03, the mean CE/CPS ratio for total aggregate income, taking into account each method for estimating CE income, is about 0.75. The average ratio for the postimputation period of 2004–06 rises to about 0.95. This increase in the ratio for aggregate income is driven largely by the increase in wage and salary income after imputation in the CE. Wage and salary income accounts for about 80 percent of total CE income and 77 percent of total CPS income over the 2002–06 period. Before imputation, CE aggregate income averages about $1,650 billion less than CPS aggregate income, with CE wage and salary income trailing CPS wage and salary income by about $1,123 billion. The CE/CPS ratio for wage and salary income averages about 0.78. After imputation, the gaps between aggregate income and wage and salary income in the CE and CPS narrow to an average of about $462 billion and $179 billion, respectively. Wage and salary income for the CE almost matches the CPS estimate, with an average ratio of about 0.97. Social Security and Railroad Retirement income is the next-largest component of total income in the CE and CPS. The story here is similar to the one for wage and salary income. The mean 2002–03 CE/CPS ratio is somewhat more than 0.80, while the 2004–06 ratio increases to slightly more than 0.95. Imputation in the CE has a larger impact on the CE/ CPS ratio for nonfarm self-employment income, the thirdlargest contributor to total income, than for any other component of income. In fact, the ratio almost doubles after imputation, going from about 0.63 to a bit more than Monthly Labor Review • August 2009 31 Income Imputation Table 1. Aggregate pretax income and ratios for Current Population Survey (CPS) and for three alternative measures for Consumer Expenditure Survey (CE), by total and source of income, 2002–06 [In billions of dollars] Nonfarm Farm Unemployment Total Wage and salary self-employment self-employment compensation Year and survey Aggregate 2002 CPS.......................................................... CE, reference year 2002................... CE, January 2003................................ CE, October 2002–April 2003........ CPS.......................................................... CE, reference year 2003................... CE, January 2004................................ CE, October 2003–April 2004........ CPS.......................................................... CE, reference year 2004................... CE, January 2005................................ CE, October 2004–April 2005........ CPS.......................................................... CE, reference year 2005................... CE, January 2006................................ CE, October 2005–April 2006........ CPS.......................................................... CE, reference year 2006................... CE, January 2007................................ CE, October 2006–April 2007........ 2003 2004 2005 CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS ratio $6,515.7 4,629.0 4,858.1 4,838.7 ... 71.0 74.6 74.3 $5,078.4 3,736.3 3,880.9 3,890.2 ... 73.6 76.4 76.6 $302.6 197.8 204.3 198.6 ... 65.4 67.5 65.6 $20.4 14.9 4.2 18.5 ... 72.8 20.3 90.7 $37.9 14.7 13.2 20.1 ... 38.7 34.8 53.0 6,707.2 5,007.9 5,328.2 5,109.5 ... 74.7 79.4 76.2 5,157.1 4,042.1 4,295.7 4,125.7 ... 78.4 83.3 80.0 331.6 194.6 210.7 194.3 ... 58.7 63.5 58.6 28.0 15.8 8.2 14.8 ... 56.3 29.1 53.0 36.9 18.8 20.6 20.0 ... 51.0 55.8 54.1 6,939.6 6,322.2 6,689.9 6,636.6 ... 91.1 96.4 95.6 5,346.6 5,021.3 5,119.7 5,206.3 ... 93.9 95.8 97.4 321.7 338.4 566.6 435.1 ... 105.2 176.1 135.2 29.0 22.6 15.7 11.3 ... 77.8 54.0 38.9 25.0 18.6 22.4 16.4 ... 74.3 89.5 65.4 7,352.4 6,872.5 6,872.1 6,940.3 ... 93.5 93.5 94.4 5,630.6 5,432.6 5,394.3 5,522.8 ... 96.5 95.8 98.1 366.5 430.1 558.5 423.4 ... 117.4 152.4 115.5 37.3 12.5 20.1 10.6 ... 33.7 53.9 28.5 22.3 13.1 9.9 11.6 ... 58.8 44.4 52.1 2006 7,800.6 ... 5,967.4 ... 407.7 ... 31.7 ... 20.7 ... 7,170.8 91.9 5,718.6 95.8 414.0 101.5 14.7 46.5 12.8 61.9 7,332.3 94.0 5,994.1 100.4 445.0 109.1 13.1 41.5 16.0 77.3 7,286.8 93.4 5,815.2 97.5 380.1 93.2 26.7 84.3 11.0 53.5 Workers’ compensation Supplemental Public Pensions and (including compensation Social Security and assistance annuities for black lung disease) Railroad Retirement Security Income and veterans’ benefits Aggregate 2002 CPS.......................................................... CE, reference year 2002................... CE, January 2003................................ CE, October 2002–April 2003........ CPS.......................................................... CE, reference year 2003................... CE, January 2004................................ CE, October 2003–April 2004........ CPS.......................................................... CE, reference year 2004................... CE, January 2005................................ CE, October 2004–April 2005........ CPS.......................................................... CE, reference year 2005................... CE, January 2006................................ CE, October 2005–April 2006........ 32 2003 2004 2005 Monthly Labor Review • August 2009 CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS Aggregate ratio CE/CPS ratio 36.4 7.7 6.5 7.1 ... 20.4 17.2 18.7 389.8 312.9 299.1 315.9 ... 80.3 76.7 81.0 25.9 23.3 19.5 20.8 ... 90.0 75.2 80.3 6.0 4.1 4.2 4.6 ... 67.8 69.6 76.6 262.5 178.7 217.4 203.4 ... 68.1 82.8 77.5 36.1 8.0 8.1 9.9 ... 22.2 22.5 27.3 410.1 325.4 343.8 334.7 ... 79.3 83.8 81.6 28.0 19.1 14.6 15.5 ... 68.2 52.0 55.4 7.1 4.1 2.6 3.9 ... 57.4 36.9 55.7 276.3 226.3 252.6 231.8 ... 81.9 91.5 83.9 39.9 8.9 11.6 8.9 ... 22.4 29.0 22.4 431.8 400.0 431.0 411.4 ... 92.6 99.8 95.3 30.6 20.8 13.4 18.9 ... 67.9 43.8 61.9 5.8 4.7 5.6 5.0 ... 82.1 97.5 87.4 291.9 280.1 300.0 316.3 ... 96.0 102.8 108.3 43.9 10.8 7.5 10.3 ... 24.5 17.1 23.4 449.2 431.0 441.1 441.9 ... 96.0 98.2 98.4 31.1 25.0 25.9 26.4 ... 80.4 83.3 84.7 6.6 5.2 4.9 5.5 ... 78.7 74.8 83.8 310.3 290.4 268.1 291.1 ... 93.6 86.4 93.8 Table 1. Continued—Aggregate pretax income and ratios for Current Population Survey (CPS) and for three alternative measures for Consumer Expenditure Survey (CE), by total and source of income, 2002–06 [In billions of dollars] Workers’ compensation Social Security and Supplemental Public Pensions and (including compensation Security Income assistance annuities for black lung disease) Railroad Retirement Year and survey and veterans’ benefits CE/CPS CE/CPS Aggregate Aggregate CE/CPS Aggregate CE/CPS Aggregate CE/CPS Aggregate ratio ratio ratio ratio ratio 2006 CPS.......................................................... CE, reference year 2006................... CE, January 2007............................... CE, October 2006–April 2007........ $41.6 11.8 8.4 13.5 ... 28.4 20.1 32.4 $471.5 446.0 409.1 452.2 ... 94.6 86.8 95.9 $31.6 23.6 26.6 25.9 ... 74.6 84.1 81.8 $5.6 5.2 4.9 5.0 ... 92.9 87.9 90.2 $314.9 283.5 213.6 302.6 ... 90.0 67.8 96.1 Accident and temporary insurance, Dividends, rents, royalties, educational assistance, Interest Child support alimony, financial assistance, and estates and trusts and other income not elsewhere classified CE/CPS CE/CPS CE/CPS CE/CPS Aggregate Aggregate Aggregate Aggregate ratio ratio ratio ratio 2002 CPS.......................................................... 145.4 ... 119.7 ... 24.0 ... 66.7 ... CE, reference year 2002................... 36.9 25.4 50.3 42.1 13.3 55.3 38.1 57.2 CE, January 2003................................ 39.8 27.4 48.9 40.9 13.3 55.3 107.0 160.5 CE, October 2002–April 2003........ 41.7 28.7 57.3 47.8 14.3 59.6 46.3 69.5 2003 CPS.......................................................... CE, reference year 2003................... CE, January 2004................................ CE, October 2003–April 2004........ CPS.......................................................... CE, reference year 2004................... CE, January 2005................................ CE, October 2004–April 2005........ CPS.......................................................... CE, reference year 2005................... CE, January 2006................................ CE, October 2005–April 2006........ CPS.......................................................... CE, reference year 2006................... CE, January 2007................................ CE, October 2006–April 2007........ 2004 2005 2006 148.3 47.9 38.2 43.4 ... 32.3 25.7 29.2 152.4 60.7 63.2 65.6 ... 39.8 41.5 43.0 25.1 17.1 21.5 16.9 ... 67.9 85.4 67.4 70.0 28.0 48.5 32.9 ... 40.0 69.2 47.0 163.2 59.0 59.0 49.8 ... 36.2 36.1 30.5 157.0 85.3 50.6 81.0 ... 54.3 32.2 51.6 27.0 19.2 21.7 21.0 ... 71.1 80.5 77.7 70.2 43.1 72.6 55.2 ... 61.4 103.5 78.6 186.9 61.9 37.6 61.3 ... 33.1 20.1 32.8 169.8 99.9 45.1 71.9 ... 58.8 26.6 42.3 26.0 19.2 17.0 19.6 ... 73.8 65.4 75.4 72.0 40.7 41.9 43.9 ... 56.5 58.1 60.9 229.2 69.7 66.8 85.7 ... 30.4 29.1 37.4 186.7 106.9 80.1 109.5 ... 57.3 42.9 58.6 25.4 22.6 18.1 21.3 ... 88.9 71.3 84.0 66.6 41.4 36.6 38.0 ... 62.1 55.0 57.0 1.22, making nonfarm self-employment income the only source of income for which the CE estimate is, on average, higher than the CPS estimate. At about 4 percent of the total, pension and annuity income is the next-largest component of total income. After imputation, the CE/CPS ratio for pension and annuity income rises by an amount that is almost equivalent to that for Social Security and Railroad Retirement income. For 2002–03, the ratio averages just under 0.81, increasing to slightly under 0.93 for 2004–06. None of the nine remaining income components represents as much as 2 percent of total income reported in the CE. For the CPS, however, two categories—interest income; and income from dividends, rents, royalties, and estates and trusts—each make up more than 2 percent of total income. Hence, the CE/CPS ratios for these items are Monthly Labor Review • August 2009 33 Income Imputation fairly low, and, historically, they have been among the lowest in the published tables. In addition, interest income is one of the few components whose CE/CPS ratio does not increase appreciably after imputation: on average, the aggregate preimputation interest income estimate in the CE is about 28 percent of the CPS estimate, while, after imputation, the estimate increases about 3.5 percentage points, to just under 32 percent of the CPS estimate. Imputation does not have a marked impact on the CE/CPS ratio for income from dividends, rents, royalties, and estates and trusts either, although the initial level of the ratio is higher than that for interest income. The ratio for 2002–03 averages midway between 0.42 and 0.43, and increases to an average of just over 0.47 after imputation. Each of the remaining seven sources of income accounts for less than 1 percent of total income in each of the CE and the CPS. Thus, any change in the CE/CPS ratio after imputation has a tiny impact on overall aggregate income between the two surveys. In addition, the number of consumer units in the CE reporting income from these sources is often very low, particularly for the method of creating CE estimates from the second and fifth interviews from January of the next year. Hence, outlying values have a disproportionate impact on the calculated estimates. Of the seven components still outstanding, two actually show a drop in the average ratio between 2002–03 and 2004–06. The first of these is farm self-employment income, for which the CE-CPS ratio drops almost 3 percentage points, from slightly under 54 percent to 51 percent. The other component is an amalgam of individual income sources from each survey that could be combined into the category of accident and temporary insurance, educational assistance, alimony, financial assistance, and other income not elsewhere classified. The CE/CPS ratio for this component shows an even larger change between pre- and postimputation periods, dropping from an average of about 0.74 to approximately 0.66. For both of these components, and more strikingly for the latter, the wide swings in the CE estimates across years in the second and third estimation methods are due to infrequent reports of such income, a factor that offers an explanation for the drop in the ratio. Examining the five remaining sources of income reveals, on the one hand, that the mean CE/CPS ratio for unemployment compensation rises significantly after imputation. The CE estimate for 2002–03 averages almost 48 percent of the CPS estimate. For the 3-year period after imputation is introduced, the CE estimate rises to an average of more than 64 percent of the CPS estimate. On the other hand, for income from workers’ compensa34 Monthly Labor Review • August 2009 tion (including compensation for black lung disease) and veterans’ benefits, the ratio of CE to CPS income changes very little after imputation, moving from about 0.22 to more than 0.24. SSI is another income component for which the average ratio remains relatively stable subsequent to imputation. At a mean of about 70 percent of the CPS estimate in 2002–03, the CE estimate for SSI is the fifth highest among the components with respect to the CPS. Adding imputed SSI income to that reported by consumer units increases the CE estimate only to an average of somewhat under 74 percent of the CPS estimate during 2004–06. By contrast, child support income, a marginally smaller component of total income than SSI, exhibits a large increase in the CE/CPS ratio after imputation: the ratio averages slightly more than 0.65 for 2002–03, after which it rises to an average of well over 0.76 over the 3-year period that followed. The final and smallest source of total income, public assistance, displays the largest rise in the CE/CPS ratio after imputation began. The CE estimate averages under 61 percent of the CPS estimate in the 2 years prior to imputation, rising over the next 3 years to an average of slightly more than 86 percent of the CPS estimate, a greater-than-25-percentage-point increase. The role of imputation The preceding examination of the change in the ratio of CE income to CPS income after CE income estimates are augmented by imputation shows only part of the picture with respect to the impact of imputation on the relationship between the two measures. This section investigates more closely the magnitude of imputation as it affects the final aggregate estimates for total income and for each source of income in the CE and the CPS over the 2004–06 period when imputation is done for both surveys. Table 2 shows the percentage of CE and CPS aggregate income, both total and by source, accounted for by imputation for the 3 years during which it has been used in the CE. An examination of total income shows that about 37 percent of the CE aggregate is attributable to imputation, compared with about 33 percent in the CPS. On average, the percentage of imputed income in the CE has risen each year since the inception of imputation, while the percentage has remained stable in the CPS. Even though the CPS aggregates are larger than the CE aggregates and the difference between the aggregates has risen from approximately $400 billion in 2004 to about $530 billion in 2006, the dollar amounts imputed in the CE are uniformly larger than the amounts imputed in the Table 2. Aggregate pretax income and percent distribution, total and by reported and allocated status, by source of income, Current Population Survey (CPS) and three alternative measures of Consumer Expenditure Survey (CE), 2004–06 [In billions of dollars] Percent Percent Allocated Year, category of income, and survey Total Reported allocated reported 2004 Total aggregate income: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005 . .............................................................. CE, October 2004–April 2005......................................... $6,939.6 6,322.2 6,689.9 6,636.6 $4,603.6 3,944.6 4,318.1 4,274.2 66.3 62.4 64.5 64.4 $2,336.0 2,377.5 2,371.7 2,362.3 33.7 37.6 35.5 35.6 Wage and salary: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 5,346.6 5,021.3 5,119.7 5,206.3 3,672.9 3,084.1 3,251.8 3,331.5 68.7 61.4 63.5 64.0 1,673.8 1,937.3 1,868.0 1,874.8 31.3 38.6 36.5 36.0 Nonfarm self-employment: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 321.7 338.4 566.6 435.1 183.5 145.2 261.2 179.9 57.0 42.9 46.1 41.3 138.3 193.3 305.4 255.2 43.0 57.1 53.9 58.7 Farm self-employment: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 29.0 22.6 15.7 11.3 12.7 8.1 7.5 4.1 43.9 35.9 48.1 36.7 16.3 14.5 8.1 7.2 56.1 64.1 51.9 63.3 Unemployment compensation: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 25.0 18.6 22.4 16.4 18.7 15.0 13.4 13.0 74.8 80.7 59.9 79.5 6.3 3.6 9.0 3.3 25.2 19.3 40.1 20.5 Workers’ compensation (including compensation for black lung disease) and veterans’ benefits: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 39.9 8.9 11.6 8.9 27.6 6.6 10.6 7.1 69.3 73.5 92.1 79.9 12.2 2.4 .9 1.8 30.6 26.5 7.9 20.1 Social Security and Railroad Retirement: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005 ........................................ 431.8 400.0 431.0 411.4 283.1 312.4 349.6 329.9 65.6 78.1 81.1 80.2 148.6 87.7 81.4 81.5 34.4 21.9 18.9 19.8 Supplemental Security Income: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 30.6 20.8 13.4 18.9 21.8 16.9 12.0 15.5 71.2 81.6 89.7 82.1 8.8 3.8 1.4 3.4 28.7 18.4 10.3 17.9 Public assistance: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 5.8 4.7 5.6 5.0 4.0 3.7 4.6 3.8 70.4 77.4 81.4 74.7 1.7 1.1 1.0 1.3 29.6 22.6 18.6 25.3 Monthly Labor Review • August 2009 35 Income Imputation Table 2. Continued—Aggregate pretax income and percent distribution, total and by reported and allocated status, by source of income, Current Population Survey (CPS) and three alternative measures of Consumer Expenditure Survey (CE), 2004–06 [In billions of dollars] Year, category of income, and survey Total Reported Percent Allocated reported Percent allocated Pensions and annuities: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... $291.9 280.1 300.0 316.3 $193.6 221.4 256.9 254.5 66.3 79.0 85.6 80.5 $98.4 58.7 43.1 61.8 33.7 21.0 14.4 19.5 Interest: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 163.2 59.0 59.0 49.8 41.3 27.8 38.8 24.7 25.3 47.0 65.9 49.7 121.8 31.3 20.1 25.0 74.7 53.0 34.1 50.3 Dividends, rents, royalties, and estates and trusts: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 157.0 85.3 50.6 81.0 81.8 53.7 34.4 48.6 52.1 62.9 67.9 60.0 75.3 31.6 16.3 32.4 47.9 37.1 32.1 40.0 Child support: CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005 . .............................................................. CE, October 2004–April 2005......................................... 27.0 19.2 21.7 21.0 19.5 16.7 19.1 18.9 72.3 86.8 87.9 89.9 7.5 2.5 2.6 2.1 27.7 13.2 12.1 10.1 Accident and temporary insurance, educational assistance, alimony, financial assistance, and other CPS........................................................................................... CE, reference year 2004.................................................... CE, January 2005................................................................. CE, October 2004–April 2005......................................... 70.2 43.1 72.6 55.2 43.0 33.3 58.1 42.6 61.3 77.3 80.0 77.1 27.1 9.8 14.5 12.6 38.7 22.7 20.0 22.9 2005 Total aggregate: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 7,352.2 6,872.5 6,872.1 6,940.3 5,026.8 4,322.3 4,332.7 4,405.6 68.4 62.9 63.0 63.5 2,325.7 2,550.1 2,539.4 2,534.6 31.6 37.1 37.0 36.5 Wage and salary: CPS............................................................................................ CE, reference year 2005.................................................... CE, January 2006 . .............................................................. CE, October 2005–April 2006 ........................................ 5,630.6 5,432.6 5,394.3 5,522.8 4,002.1 3,376.8 3,400.0 3,493.0 71.1 62.2 63.0 63.2 1,628.4 2,055.8 1,994.5 2,029.8 28.9 37.8 37.0 36.8 Nonfarm self-employment: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 366.5 430.1 558.5 423.4 216.4 187.7 229.6 181.0 59.1 43.6 41.1 42.8 150.1 242.4 328.9 242.3 41.0 56.4 58.9 57.2 Farm self-employment: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 37.3 12.5 20.1 10.6 13.7 2.2 12.1 6.2 36.7 17.7 60.1 57.9 23.6 10.3 8.0 4.5 63.3 82.3 39.9 42.1 Unemployment compensation: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 22.3 13.1 9.9 11.6 17.0 11.1 6.5 9.4 76.2 84.6 65.7 80.6 5.3 2.0 3.4 2.3 23.8 15.4 34.3 19.4 36 Monthly Labor Review • August 2009 Table 2. Continued—Aggregate pretax income and percent distribution, total and by reported and allocated status, by source of income, Current Population Survey (CPS) and three alternative measures of Consumer Expenditure Survey (CE), 2004–06 [In billions of dollars] Percent Percent Year, category of income, and survey Allocated Total Reported reported allocated Workers’ compensation (including compensation for black lung disease) and veterans’ benefits: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006 . .............................................................. CE, October 2005–April 2006 ........................................ $43.9 10.8 7.5 10.3 $30.3 8.4 7.5 7.6 69.0 77.8 99.4 74.2 $13.6 2.4 (1) 2.6 31.1 22.2 .6 25.8 Social Security and Railroad Retirement: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006 . .............................................................. CE, October 2005–April 2006 ........................................ 449.2 431.0 441.1 441.9 301.8 341.0 351.8 340.3 67.2 79.1 79.8 77.0 147.5 90.1 89.3 101.6 32.8 20.9 20.2 23.0 Supplemental Security Income: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 31.1 25.0 25.9 26.4 22.7 20.5 23.5 20.5 73.1 81.8 90.5 77.6 8.4 4.5 2.5 5.9 26.9 18.2 9.5 22.4 Public assistance: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006 . .............................................................. CE, October 2005–April 2006 ........................................ 6.6 5.2 4.9 5.5 5.0 4.2 4.2 4.5 76.4 80.4 84.1 81.7 1.6 1.0 .8 1.0 23.6 19.6 15.9 18.3 Pensions and annuities: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 310.3 290.4 268.1 291.1 211.4 229.5 223.2 224.9 68.1 79.0 83.2 77.3 98.8 60.9 44.9 66.2 31.9 21.0 16.8 22.7 Interest: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 186.9 61.9 37.6 61.3 54.8 29.6 12.7 26.1 29.3 47.8 33.6 42.7 132.1 32.4 25.0 35.1 70.7 52.2 66.4 57.3 Dividends, rents, royalties, and estates and trusts: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 169.8 99.9 45.1 71.9 87.3 63.7 22.3 45.7 51.4 63.8 49.5 63.6 82.5 36.2 22.8 26.2 48.6 36.2 50.5 36.4 Child support: CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006 . .............................................................. CE, October 2005–April 2006......................................... 26.0 19.2 17.0 19.6 19.5 17.7 14.8 17.7 75.0 92.0 87.0 90.4 6.5 1.5 2.2 1.9 25.0 8.0 13.0 9.6 Accident and temporary insurance, educational assistance, alimony, financial assistance, and other CPS........................................................................................... CE, reference year 2005.................................................... CE, January 2006................................................................. CE, October 2005–April 2006......................................... 72.0 40.7 41.9 43.9 44.7 30.0 24.8 28.7 62.0 73.9 59.2 65.3 27.3 10.6 17.1 15.3 38.0 26.1 40.8 34.7 See note at end of table. Monthly Labor Review • August 2009 37 Income Imputation Table 2. Continued—Aggregate pretax income and percent distribution, total and by reported and allocated status, by source of income, Current Population Survey (CPS) and three alternative measures of Consumer Expenditure Survey (CE), 2004–06 [In billions of dollars] Percent Percent Year, category of income, and survey Allocated Total Reported allocated reported 2006 Total aggregate income: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... $7,800.6 7,170.8 7,332.3 7,286.8 $5,226.9 4,354.7 4,435.1 4,492.4 67.0 60.7 60.5 61.7 $2,573.7 2,816.2 2,897.3 2,794.4 33.0 39.3 39.5 38.3 Wage and salary income: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 5,967.4 5,718.6 5,994.1 5,815.2 4,163.5 3,447.2 3,685.0 3,566.6 69.8 60.3 61.5 61.3 1,803.9 2,271.5 2,309.1 2,248.7 30.2 39.7 38.5 38.7 Nonfarm self-employment: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 407.7 414.0 445.0 380.1 227.3 144.9 109.7 132.8 55.7 35.0 24.7 34.9 180.4 269.1 335.3 247.3 44.2 65.0 75.3 65.1 Farm self-employment: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 31.7 14.7 13.1 26.7 15.6 5.1 2.8 17.5 49.1 34.3 21.4 65.6 16.2 9.7 10.3 9.2 51.0 65.7 78.6 34.4 Unemployment compensation: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 20.7 12.8 16.0 11.0 15.4 9.5 10.5 8.2 74.6 74.2 65.7 74.4 5.2 3.3 5.5 2.8 25.4 25.8 34.3 25.6 Workers’ compensation (including compensation for black lung disease) and veterans’ benefits: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 41.6 11.8 8.4 13.5 28.7 8.4 4.7 10.4 69.0 71.4 55.6 77.1 12.9 3.4 3.7 3.1 31.0 28.6 44.4 22.9 Social Security and Railroad Retirement: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 471.5 446.0 409.1 452.2 312.7 345.5 309.2 349.9 66.3 77.5 75.6 77.4 158.8 100.6 99.9 102.3 33.7 22.5 24.4 22.6 Supplemental Security Income: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 31.6 23.6 26.6 25.9 23.7 18.9 22.5 21.2 74.8 80.0 84.6 82.1 8.0 4.7 4.1 4.6 25.2 20.0 15.4 17.9 Public assistance: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007 . .............................................................. CE, October 2006–April 2007......................................... 5.6 5.2 4.9 5.0 4.1 4.1 2.8 3.8 74.5 78.9 56.7 75.4 1.4 1.1 2.1 1.2 25.5 21.1 43.3 24.6 Pensions and annuities: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... 314.9 283.5 213.6 302.6 212.0 221.1 160.8 228.1 67.3 78.0 75.3 75.4 102.9 62.4 52.9 74.5 32.7 22.0 24.7 24.6 38 Monthly Labor Review • August 2009 Table 2. Continued—Aggregate pretax income and percent distribution, total and by reported and allocated status, by source of income, Current Population Survey (CPS) and three alternative measures of Consumer Expenditure Survey (CE), 2004–06 [In billions of dollars] Percent Percent Year, category of income, and survey Total Reported Allocated reported allocated Interest: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007......................................... $229.2 69.7 66.8 85.7 $67.0 31.0 26.9 40.8 29.2 44.5 40.3 47.6 $162.1 38.7 39.9 44.9 70.7 55.5 59.7 52.4 Dividends, rents, royalties, and estates and trusts: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006– April 2007........................................ 186.7 106.9 80.1 109.5 94.8 71.1 57.3 67.6 50.8 66.5 71.6 61.7 91.9 35.8 22.8 41.9 49.2 33.5 28.4 38.3 Child support: CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007 ........................................ 25.4 22.6 18.1 21.3 18.2 20.4 15.7 19.3 71.6 90.6 86.6 90.6 7.2 2.1 2.4 2.0 28.5 9.4 13.4 9.4 Accident and temporary insurance, educational assistance, alimony, financial assistance and other CPS........................................................................................... CE, reference year 2006.................................................... CE, January 2007................................................................. CE, October 2006–April 2007 ........................................ 66.6 41.4 36.6 38.0 43.8 27.5 27.3 26.2 65.8 66.6 74.7 68.9 22.8 13.8 9.3 11.8 34.2 33.4 25.3 31.1 1 Less than 0.1. and the difference in imputed aggregate income has risen from about $35 billion in 2004 to around $260 billion in 2006. As noted earlier, wage and salary income is the predominant component of total income, so the contribution of imputation to aggregate wages and salaries essentially matched the contribution to total income. Imputation is a bigger factor in the CE estimates than the CPS estimates, in terms of both the percentage of the estimate and the actual dollar value. In 2004, 37.0 percent of CE wages and salaries are a result of imputation, and the percentage rises to 37.2 percent in 2005 and 39.0 percent in 2006. Over the same 3 years, imputation accounts for about 30.1 percent of CPS wages and salaries. Wages and salaries imputed in the CE exceed those imputed in the CPS by about $220 billion for 2004, rising to about $475 billion in 2006. The two components of total income representing retirement income show remarkably similar patterns with respect to the effect of imputation, both internally and in relation to the CPS. Though starting from a lower level, the average percentage of imputed income represented in the CE estimates for Social Security and Railroad Retirement income and for income from pensions and annuities CPS increases each year from 2004 to 2006. For the former component, the percentage goes from 20.2 percent to 23.2 percent; for the latter component, it rises from 18.3 percent to 23.8 percent. Nonresponse appears to have been less of an issue for the CE than for the CPS, because the CPS is seen to have imputed, on average, 33.6 percent of Social Security and Railroad Retirement income and 32.8 percent of pensions and annuities over the 3-year span. With one exception, the income directly reported by respondents is $30 billion to $55 billion more for Social Security and $10 billion to $60 billion more for pensions and annuities in the CE than in the CPS. More than one-half of the CE estimates for nonfarm self-employment income are derived from imputation. As with the sources of income mentioned in the previous two paragraphs, the average percentage of imputed income rises each year, but there is a sizable 11-percentage-point increase, from 57.5 percent to 68.5 percent, between 2005 and 2006. Imputation in the CPS averages 42.7 percent over the 3-year period. The amount imputed in the CE estimates is significantly greater than the amount imputed in the CPS each year, although, seemingly paradoxically, the average difference is smallest, at just over $103 billion, Monthly Labor Review • August 2009 39 Income Imputation in 2006, the year in which imputed income makes up the largest proportion of the CE estimate. Interest income and, to a lesser degree, income from dividends, rents, royalties, and estates and trusts show wildly different response patterns between the CE and the CPS. The percentage of imputed income incorporated into the CE estimates for interest income has varied from 45.8 percent in 2004, to 58.6 percent in 2005, to 55.9 percent in 2006. The change in the percentage from year to year is attributable to swings in the percentage of income imputed in the CE estimate that is derived from January interviews only. The CPS derives an average of 72.0 percent of its annual estimates from imputation, and the actual dollar amounts imputed dwarf the amounts of imputed interest income in the CE by $100 billion to $120 billion. The average percentage of imputed income for CE dividends, rents, royalties, and estates and trusts over the 2004–06 period peaks in 2005 at 41.0 percent and then drops the next year to 33.4 percent, the lowest of all 3 years. In 2004, imputed income makes up 36.4 percent of this category. CPS estimates for dividends, rents, royalties, and estates and trusts are composed of a higher percentage of imputed income—on average, about 48.6 percent—than is any CE estimate produced for the same period, with one exception: the 2005 CE estimate based on January 2006 interviews. In actual dollar amounts, the CPS uniformly imputes much higher amounts than does the CE, regardless of the way CE income is measured: on average, $83.2 billion dollars are imputed annually in the CPS, compared with $29.6 billion in the CE. Turning to the two components whose CE/CPS ratios fall after imputation is instituted reveals that the first—farm self-employment income—shows average percentages of CE imputed income rivaling the levels for nonfarm self-employment income. For both 2004 and 2006, almost 60 percent of CE farm self-employment income originates as a result of imputation, slightly more than the 54.8 percent of the farm self-employment income estimate imputed in 2005. The CPS imputes about $10 billion more of farm self-employment income than the CE imputes annually, although, as a percentage of the total, the CE and the CPS imputations differ by less than 2 percentage points (58.0 percent and 56.8 percent, respectively). Imputation constitutes a much smaller proportion of CE income for the second category: accident and temporary insurance, educational assistance, alimony, financial assistance, and other income not elsewhere classified. The average percentage of imputed income for this category ranges from 21.9 percent in 2004 to 33.9 percent in 2005. 40 Monthly Labor Review • August 2009 The amount of income imputed by the CPS for the same category averages twice as much ($25.7 billion compared with $12.8 billion) as the amount imputed in the CE across all of the years examined. As a proportion of the total, imputed income makes up 37 percent in the CPS and 28.6 percent in the CE. Over the 2004–06 period, the annual average percentages of income imputed for unemployment compensation in the CE are fairly low and stable: 26.6 percent in 2004, 23.0 percent in 2005, and 28.6 percent in 2006. However, a closer examination of the imputation percentages for each method of selecting CE observations shows that imputation is much more prevalent when January interviews alone are used, adding up to 6 percentage points to the average. Overall, the percentages imputed in the CE and the CPS are similar, differing from about 1 to 3 percentage points across the years studied. For the category of workers’ compensation (including compensation for black lung disease) and veterans’ benefits, tracking the average percentages imputed in the CE is somewhat misleading. In 2004 and 2005, the average percentages of income imputed are 18.2 percent and 16.2 percent, respectively. The average percentage almost doubles in 2006, to 32.0 percent. These results are due almost solely to the relative paucity of imputation in estimates based on January interviews. In 2005, barely any income from this source—0.6 percent—is imputed for January 2006 interviews. For the estimate based on interviews during the period from October 2005 to April 2006, the percentage imputed is 25.8 percent, and for the estimate based on the publication methodology, 22.2 percent results from imputation. In 2004, the situation is similar, though not so extreme. The respective percentages imputed are 26.5 percent (publication method), 20.1 percent (October 2004–April 2005), and 7.9 percent ( January 2005). A complete reversal of this pattern occurs in 2006, with the percentage imputed for January 2007 interviews leaping to 44.4 percent while the percentages for the publication method and the October 2006–April 2007 interviews are 28.6 percent and 22.9 percent, respectively, comparable to the rates posted in the earlier 2 years. Imputation in the CPS accounts for about 30.9 percent of such income, compared with 24.4 percent of income derived for the latter two methods in the CE. On average, the percentages of SSI imputed in the CE are the second lowest of any component of total income. Although imputed income makes up an increasing share of the total each year of the period examined, the overall rise is small, going from 15.5 percent in 2004 to 17.8 percent in 2006. CPS percentages of imputed income are about 10 points higher than those in the CE (26.9 percent, compared with 16.7 percent), with actual dollar values imputed running more than twice as high as the CE’s ($8.4 billion, compared with $3.9 billion). Imputation in the CE for income from public assistance shows the interyear variability exhibited by other components, such as accident and temporary insurance, educational assistance, alimony, financial assistance, and other income not elsewhere classified, as well as interest income. The average percentage imputed swings from 22.2 percent in 2004, down to 17.9 percent in 2005, and then up to 29.7 percent in 2006. As with these other sources, the variability in the case of income from public assistance can be traced to changes in percentages imputed for January interviews. The percentage of income resulting from imputation in the CPS is greater than that of the CE for the first 2 years of the period, but lower than the CE’s estimate for the final year. The final component of total income, child support, shows both the lowest and most consistent average percentages of imputed income as a share of the total of any component of income in the CE. In 2005, only 10.2 percent of child support income—the lowest average percentage of the three years examined—is obtained via imputation. The highest percentage, only about 1.6 percentage points greater than the lowest, is 11.8 percent of the total, registered in 2004. The CPS imputes a much higher percentage of child support over the period, an average of 27.1 percent, more than 3 times as much, on average, in dollar terms: $7.1 billion, as opposed to $2.1 billion. WITH THE RELEASE OF 2004 DATA from the Consumer Expenditure Survey (CE), the BLS began implementing imputation for missing responses to income questions. The multistage procedure produced multiple imputed values for each missing observation. To assess how well these imputation routines performed, estimates of aggregate income based on both reported and imputed values were compared with estimates calculated from the Current Population Survey (CPS) for the years 2002–06. This period covered the 2 years prior to the introduction of imputation and the 3 years following. Because of methodological differences between the CE and the CPS, three alternative measures of CE income were derived for comparison with the CPS. On average, prior to imputation CE estimates for total money income before taxes were about 75 percent of the CPS aggregate. After imputation, CE estimates rose to about 95 percent of the CPS estimate. An examination of individual sources of income reveals that, in general, imputation has brought CE estimates closer to CPS estimates, although significant disparities remain between the estimates for many of the smaller components. On the basis of these results, further refinements to the CE income questions and imputation procedures are expected. The analysis presented in this article has used the Annual Social and Economic Supplement (ASEC) of the CPS as a benchmark to which CE Interview Survey aggregates are compared. The Census Bureau, in its turn, evaluates the quality of ASEC estimates through comparison studies with other independent sources of income. In a similar vein, Daniel Weinberg has cited studies comparing CPS income data with national and State income data from the Bureau of Economic Analysis, with income data from the Census Bureau’s Survey of Income and Program Participation, and with earnings data from the Internal Revenue Service.9 Also, Bruce Webster has compared median household income and earnings estimates for 2004 and 2005 from the American Community Survey with CPS data.10 Comparing CE income estimates with these alternative sources, in addition to continuing work with the CPS, offers further avenues for analyzing the quality of CE income data. Notes ACKNOWLEDGMENT: Thanks go to Carmen DeNovas-Walt and Edward Welniak of the Income Surveys Branch of the U.S. Census Bureau for providing the CPS income data and reviewing the manuscript of this article. 1 For a comprehensive review and analysis of comparisons between CE and PCE expenditure estimates, see Thesia I. Garner, George Janini, William Passero, Laura Paszkiewicz, and Mark Vendemia, “The CE and the PCE: a comparison,” Monthly Labor Review, September 2006, pp. 20–46. 2 A consumer unit consists of (1) all members of a particular household who are related by blood, marriage, adoption, or some other legal arrangement; (2) a person living alone or sharing a household with others or living as a roomer in a private home or lodging house or in permanent living quarters in a hotel or motel, but who is financially independent; or (3) two or more persons living together who use their incomes to make joint expenditure decisions. Financial independence is determined by spending behavior with regard to the three major expense categories: housing, food, and other living expenses. To be considered financially independent, the respondent must be financially responsible for at least two of the three major expenditure categories, either entirely or in part. 3 See Thesia I. Garner and Laura Blanciforti, “Household Income Reporting: An Analysis of U. S. Consumer Expenditure Survey Data,” Journal of Official Statistics, March 1994, pp. 69–91, for more details. 4 Geoffrey D. Paulin and David L. Ferraro, “Imputing income in the Consumer Expenditure Survey,” Monthly Labor Review, December 1994, pp. 23–31. 5 Roderick J. A. Little and Donald B. Rubin, Statistical Analysis with Missing Data (New York, John Wiley and Sons, 1987), cited in Paulin and Monthly Labor Review • August 2009 41 Income Imputation Ferraro, “Imputing Income.” See Consumer Expenditure Survey, 1987, Bulletin 2354 (Bureau of Labor Statistics, June 1990), text tables 6 and 7; Consumer Expenditure Survey, 1990– 91, Bulletin 2425 (Bureau of Labor Statistics, September 1993), text tables 8 and 9; Consumer Expenditure Survey, 1992–93, Bulletin 2462 (Bureau of Labor Statistics, September 1995), text tables 6 and 7; Consumer Expenditure Survey, 1994–95, Bulletin 2492 (Bureau of Labor Statistics, December 1997), text tables 10 and 11; Consumer Expenditure Survey, 1996–97, Report 935 (Bureau of Labor Statistics, September 1999), text tables 8 and 9; Consumer Expenditure Survey, 1998–99, Report 955 (Bureau of Labor Statistics, November 2001), text tables 20 and 21; and Consumer Expenditure Survey, 2002–2003, Report 990 (Bureau of Labor Statistics, March 2006), text tables 3–6. 6 42 Monthly Labor Review • August 2009 7 Universal Classification Codes are six-digit codes that identify expenditure, income, and selected demographic variables at the most detailed level for use in CE data dissemination and CPI pricing activities. 8 Ibid. Daniel H. Weinberg, “Income data quality issues in the Labor Review, June 2006, pp. 38–45. 9 CPS,” Monthly 10 Bruce H. Webster, Jr., “Evaluation of Median Income and Earnings Estimates: A Comparison of the American Community Survey and the Current Population Survey” (U.S. Census Bureau), March 12, 2007, on the Internet at www. census.gov/acs/www/Downloads/Evaluation_of_Income_Estimates31207. doc (visited Mar. 9, 2009). Book Review ’Tis the season for learning The Race Between Education and Technology. By Claudia Goldin and Lawrence F. Katz. Cambridge, MA, Harvard University Press, 2008, 488 pp., $39.95/hardback; $19.95/paperback. This major work by two Harvard University economists argues that wealth creation in the United States was a direct result of the education of the masses of its citizens. They propose that the first 75 years of the 20th century could in fact be called a “human capital” period, in which most of today’s productive technologies were created and successfully applied, leading to progressively higher standards of living. During the last quarter of the century and stretching into the 21st century, however, the U.S. began to lag behind other countries in a number of measures of educational achievement. The authors contend that this lag, in combination with the ease of international transfer of technology to lower cost countries, challenges America’s ability to compete in the world market. The case for investing in human capital is well developed and persuasive in this book. The evolution and spread of high schools are what the authors term “the virtues” that led to economic success. The virtues are 1) ample funding of public education through high school 2) decentralization, with ever more numerous school districts 3) separation of church and state, promoting an educational experience common to all American youth 4) gender neutrality and 5) a measure of permissiveness in making up for failed grades or missed schooling opportunities. These virtues, the authors contend, contrasted posi- tively with the more elite systems of European countries, where tests were usually imposed at an early age that mandated placing youngsters on divergent and often inferior educational tracks. Known in the early 20th century as the High School Movement, “Americans pioneered the modern secondary school…(and) tailored it for the masses.” As early as 1920 a high school or college education was expected in 25 percent of all jobs, largely owing to the rapidly increasing need for whitecollar workers. Successive cohorts of students benefited from educational attainment exceeding that of their parents. Since 1980, however, the “human capital stock of the work force” has grown more slowly, reflecting “the slower rate of increase of educational attainment for post-1950 cohorts.” Some uncertainty about the continued viability of the “virtues” also colors the last parts of the authors’ relevant discussion, given such matters as the contentiousness over unequal financing of school districts, for example. But the authors’ chief concern remains the slowing of mass college education in relation to the need they postulate for a forward-racing technology. This concern is strongly motivated by worry about the widening inequality gap in the distribution of income since the 1970s and its regressive social and economic implications. During the 1947–1973 period family incomes rose rapidly; the distribution of income tended to favor those at the bottom while retarding growth at the top. After the mid-1970s, income generally grew more slowly for most Americans but at a much faster clip in the top quintiles (or deciles). Moreover, the link between the ad- vance in productivity—output per hour worked—and family income weakened; in fact, real median family incomes fell well behind gains in productivity. Thus, “the benefits of economic growth are now far less equally shared than in the past.” The authors trace the changes in the distribution of income to a growing inequality of earnings in the labor market. The labor market includes high-paid corporate executives, of course, but also middle- and low-income workers and unemployed persons looking for paid work. The authors present detailed analyses of the widening distribution of wage/salary incomes, not only between different skill groups but also within the same occupational, skill, and experience groups. This gap is truly an unprecedented phenomenon which requires much further research and explanation. The authors’ discussion of the rise in the college/high school premium is instructive. This premium more than doubled between the 1980s and the early 2000s, indicating strong rising returns to education. The four reasons thought to underlie this development are 1) intensified computerization, leading to a demand for highly-skilled and educated workers (although the authors disagree somewhat on the extent of the demand), 2) globalization and international trade, leading to outsourcing of labor-intensive jobs to lower wage countries and, simultaneously, putting downward pressure on the wages of lesser educated workers in the United States, 3) slowing growth in educational levels of post1950 cohorts, causing a demand-supply imbalance in favor of educated workers and, 4) the weakened bargaining power of trade unions. Monthly Labor Review • August 2009 43 The authors feel that these reasons are an implicit rejection of the widespread belief that the demand for more educated workers has been linked solely to the skill-biased technology associated with computerization—a topic they discuss at some length. They feel that the proponents of this explanation ignore the historical evidence. True, we still witness technological change today, but these changes are quite ordinary in comparison to those experienced during the first decades of the 20th century. As a result of the “electric motor spread,” for example, manufacturing horsepower in the form of purchased electricity rose from 9 percent in 1909 to 53 percent in 1929. Numerous new consumer goods—such as appliances, vacuum cleaners, radios, and automobiles—emerged in the market between 1900 and 1925, bearing witness to the productivity advances and the skill and education of the workers designing and fabricating them. In terms of today’s skill-based technological change, the authors contend 44 Monthly Labor Review • August 2009 that “the era of computerization has brought little that is new;” in fact, they allude to certain reductions in skill bias which they call “deskilling.” They cite “the substitution of office machinery for skill” as contributing to the “compression” of clerical workers’ wages. Many other examples might be mentioned in which computerization simplified tasks, requiring little skill from the worker performing it (retail checkout comes to mind). Task simplification has become a core characteristic of work organization; it has become a condition of economies of scale, which long ago spread from manufacturing to service industries. Good for productivity, perhaps, but not so good for stimulating new ideas and inventions. The case the authors make for improving the skill and education of the work force as key elements of economic growth, founded on a wealth of data, is well made. Their case for the need of a much enlarged college or university attendance, however, would have been stronger had they related it to the deeply unequal distribution of gains from advancing productivity. This is no small factor in depriving middle and lower class families of the means to finance their children’s tertiary education. The ability of the United States to further equalize educational opportunities can hardly be questioned; the United States still exceeds 19 other advanced countries in this measure, by 13 percent on average. The United States also ranks first among 24 countries in an index of business research and innovation, the adoption of new technology patents, and interaction between business and science. Notwithstanding the current recession, America possesses the wealth and accumulated knowledge to afford the advanced education urged by this valuable and informative work, and should pursue it. Horst Brand Former Economist with the Bureau of Labor Statistics Précis Productivity’s role in housing booms and busts Financial analysts and market observers across the globe have attributed the recent economic downturn to a housing bubble brought on by negligent lending standards and the belief that housing prices would continue to increase indefinitely. But in a recent study, “Productivity Swings and Housing Prices,” James A. Kahn of the Federal Reserve Bank of New York indicates that this view is incomplete and that it unjustly exaggerates the role that interest rate changes and credit market irregularities played in the growth and decline of housing prices. Kahn believes that a primary element of the housing boom and bust has been previously ignored by analysts: the role that changing economic fundamentals—specifically, swings in labor productivity, or output per hour of work—play in the movement of housing prices. The author explains that “productivity swings helped determine the price of housing through their effects on income growth and long-term income expectations—factors that directly influence what consumers are ready to pay for housing and what mortgage providers are willing to lend.” While not discounting the influence that other factors had on housing price movements, Kahn’s interpretation is one in which the scope of the effects of the credit condition in the United States is less far-reaching; he considers the credit market irregularities “to have exacerbated the situation caused in large measure by the decline in productivity growth.” In other words, it was primarily changing economic fundamentals that led to the financial distress which resulted in consumers being pummeled by higher interest rates and unable to pay their mortgages; that is, economic fundamentals affected the housing market more than the housing market affected economic fundamentals. Kahn’s data are derived from a model based on productivity data and on estimates of the relationships among income, housing prices, and demand from 1963 through 2008. In the recent housing boom of the late 1990s, there was a period of rebounding productivity growth and a return to a high growth rate, and there also was a noticeably sharp increase in housing prices during the period. The recent downturn in housing prices corresponds to a deceleration in productivity. This trend is observable throughout recent history. During the late 1960s and early 1970s when the productivity rate was trending up, there was a steady upswing in housing prices of 3 percent per year. Then, housing prices declined in the late 1970s as productivity slowed to less than 1.5 percent per year. How do productivity trends influence housing prices? Productivity growth is the most important determinant of long-term trends in household income. As productivity growth increases, so do income and the prospect of future income. As Kahn explains, “A sustained rise in income will significantly strengthen the current and future demand for housing. The increase in demand will drive up the price of land and hence…the market price of services that owners derive from living in this home.” Housing prices are determined by a number of factors, including current income and expectations of future income. If bor- rowers believe that productivity rates will remain strong, they have reason to suppose their income will continue to increase and are therefore willing to pay higher prices for a house. Similarly, lenders have increased confidence in the ability of the borrowers to pay for the higher expenditure and thus view mortgages as less of a risk. Further, housing demand is considered relatively inelastic; high prices usually are not enough to dissuade prospective house buyers from purchasing a home. Kahn explains that price-inelastic demand results in home prices growing faster than income during housing booms and declining more rapidly than income during housing busts. Many market analysts interpret these events as merely indicating a housing bubble, but Kahn believes that these price swings “can arise naturally from productivity shifts affecting the demand for housing.” Kahn places a strong emphasis on the importance of the public’s perception of productivity. Usually, there is a lag between an actual increase or decrease in productivity and the public recognition of a shift in productivity growth. For example, according to recent estimates productivity growth had begun to slow in 2004, yet there was little public recognition of such a decline until 2007. The recognition of a long-coming slowdown in productivity growth corresponds with a considerable drop in housing prices. The lax lending conditions of the 2000s resulted from an understandable— albeit false—confidence in continued productivity growth. When consumers realized that their faith in continued productivity growth was misplaced, there came a swift decline in economic conditions. Monthly Labor Review • August 2009 45 Current Labor Statistics Monthly Labor Review August 2009 NOTE: Many of the statistics in the following pages were subsequently revised. These pages have not been updated to reflect the revisions. To obtain BLS data that reflect all revisions, see http://www.bls.gov/data/home.htm For the latest set of "Current Labor Statistics," see http://www.bls.gov/opub/mlr/curlabst.htm Current Labor Statistics Notes on current labor statistics . .............. 47 Comparative indicators 1. Labor market indicators..................................................... 59 2. Annual and quarterly percent changes in compensation, prices, and productivity........................... 60 3. Alternative measures of wages and compensation changes.................................................... 60 Labor force data 4. Employment status of the population, seasonally adjusted......................................................... 5. Selected employment indicators, seasonally adjusted......... 6. Selected unemployment indicators, seasonally adjusted..... 7. Duration of unemployment, seasonally adjusted................ 8. Unemployed persons by reason for unemployment, seasonally adjusted......................................................... 9. Unemployment rates by sex and age, seasonally adjusted ......................................................... 10. Unemployment rates by State, seasonally adjusted............. 11. Employment of workers by State, seasonally adjusted.......................................................... 12. Employment of workers by industry, seasonally adjusted.......................................................... 13. Average weekly hours by industry, seasonally adjusted....... 14. Average hourly earnings by industry, seasonally adjusted.......................................................... 15. Average hourly earnings by industry.................................. 16. Average weekly earnings by industry................................. 17. Diffusion indexes of employment change, seasonally adjusted ...................................................... 18. Job openings levels and rates by industry and region, seasonally adjusted........................................................ 19. Hires levels and rates by industry and region, seasonally adjusted........................................................ 20. Separations levels and rates by industry and region, seasonally adjusted......................................................... 21. Quits levels and rates by industry and region, seasonally adjusted........................................................ 61 62 63 63 Employment Cost Index, compensation .......................... Employment Cost Index, wages and salaries .................... Employment Cost Index, benefits, private industry .......... Employment Cost Index, private industry workers, by bargaining status, and region..................................... 34. National Compensation Survey, retirement benefits, private industry ............................................................. 35. National Compensation Survey, health insurance, private industry............................................................... 36. National Compensation Survey, selected benefits, private industry.............................................................. 37. Work stoppages involving 1,000 workers or more............. 88 89 92 93 94 97 99 99 Price data 70 71 72 73 Productivity data 74 47. Indexes of productivity, hourly compensation, and unit costs, data seasonally adjusted.......................... 109 48. Annual indexes of multifactor productivity........................ 110 49. Annual indexes of productivity, hourly compensation, unit costs, and prices...................................................... 111 50. Annual indexes of output per hour for select industries..... 112 64 65 65 66 69 74 75 75 24. Annual data: Quarterly Census of Employment and Wages, by ownership............................................... 79 25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, by supersector....... 80 26. Annual data: Quarterly Census of Employment and Wages, by metropolitan area ......................................... 81 27. Annual data: Employment status of the population.......... 86 28. Annual data: Employment levels by industry ................. 86 29. Annual data: Average hours and earnings level, by industry..................................................................... 87 Monthly Labor Review August 2009 30. 31. 32. 33. 38. Consumer Price Index: U.S. city average, by expenditure category and commodity and service groups.................. 100 39. Consumer Price Index: U.S. city average and local data, all items ........................................................ 103 40. Annual data: Consumer Price Index, all items and major groups........................................................... 104 41. Producer Price Indexes by stage of processing................... 105 42. Producer Price Indexes for the net output of major industry groups.............................................................. 106 43. Annual data: Producer Price Indexes by stage of processing..................................................... 107 44. U.S. export price indexes by end-use category................... 107 45. U.S. import price indexes by end-use category................... 108 46. U.S. international price indexes for selected categories of services...................................................... 108 64 22. Quarterly Census of Employment and Wages, 10 largest counties . ....................................................... 76 23. Quarterly Census of Employment and Wages, by State... 78 46 Labor compensation and collective bargaining data International comparisons data 51. Unemployment rates in 10 countries, seasonally adjusted......................................................... 115 52. Annual data: Employment status of the civilian working-age population, 10 countries........................... 116 53. Annual indexes of productivity and related measures, 17 economies................................................................ 117 Injury and Illness data 54. Annual data: Occupational injury and illness..................... 119 55. Fatal occupational injuries by event or exposure ................ 121 Notes on Current Labor Statistics This section of the Review presents the principal statistical series collected and calculated by the Bureau of Labor Statistics: series on labor force; employment; unemployment; labor compensation; consumer, producer, and international prices; productivity; international comparisons; and injury and illness statistics. In the notes that follow, the data in each group of tables are briefly described; key definitions are given; notes on the data are set forth; and sources of additional information are cited. General notes The following notes apply to several tables in this section: Seasonal adjustment. Certain monthly and quarterly data are adjusted to eliminate the effect on the data of such factors as climatic conditions, industry production schedules, opening and closing of schools, holiday buying periods, and vacation practices, which might prevent short-term evaluation of the statistical series. Tables containing data that have been adjusted are identified as “seasonally adjusted.” (All other data are not seasonally adjusted.) Seasonal effects are estimated on the basis of current and past experiences. When new seasonal factors are computed each year, revisions may affect seasonally adjusted data for several preceding years. Seasonally adjusted data appear in tables 1–14, 17–21, 48, and 52. Seasonally adjusted labor force data in tables 1 and 4–9 and seasonally adjusted establishment survey data shown in tables 1, 12–14, and 17 are revised in the March 2007 Review. A brief explanation of the seasonal adjustment methodology appears in “Notes on the data.” Revisions in the productivity data in table 54 are usually introduced in the September issue. Seasonally adjusted indexes and percent changes from month-to-month and quarter-to-quarter are published for numerous Consumer and Producer Price Index series. However, seasonally adjusted indexes are not published for the U.S. average AllItems CPI. Only seasonally adjusted percent changes are available for this series. Adjustments for price changes. Some data—such as the “real” earnings shown in table 14—are adjusted to eliminate the effect of changes in price. These adjustments are made by dividing current-dollar values by the Consumer Price Index or the appropriate component of the index, then multiplying by 100. For example, given a current hourly wage rate of $3 and a current price index number of 150, where 1982 = 100, the hourly rate expressed in 1982 dollars is $2 ($3/150 x 100 = $2). The $2 (or any other resulting values) are described as “real,” “constant,” or “1982” dollars. Sources of information Data that supplement the tables in this section are published by the Bureau in a variety of sources. Definitions of each series and notes on the data are contained in later sections of these Notes describing each set of data. For detailed descriptions of each data series, see BLS Handbook of Methods, Bulletin 2490. Users also may wish to consult Major Programs of the Bureau of Labor Statistics, Report 919. News releases provide the latest statistical information published by the Bureau; the major recurring releases are published according to the schedule appearing on the back cover of this issue. More information about labor force, employment, and unemployment data and the household and establishment surveys underlying the data are available in the Bureau’s monthly publication, Employment and Earnings. Historical unadjusted and seasonally adjusted data from the household survey are available on the Internet: www.bls.gov/cps/ Historically comparable unadjusted and seasonally adjusted data from the establishment survey also are available on the Internet: www.bls.gov/ces/ Additional information on labor force data for areas below the national level are provided in the BLS annual report, Geographic Profile of Employment and Unemployment. For a comprehensive discussion of the Employment Cost Index, see Employment Cost Indexes and Levels, 1975–95, BLS Bulletin 2466. The most recent data from the Employee Benefits Survey appear in the following Bureau of Labor Statistics bulletins: Employee Benefits in Medium and Large Firms; Employee Benefits in Small Private Establishments; and Employee Benefits in State and Local Governments. More detailed data on consumer and producer prices are published in the monthly periodicals, The CPI Detailed Report and Producer Price Indexes. For an overview of the 1998 revision of the CPI, see the December 1996 issue of the Monthly Labor Review. Additional data on international prices appear in monthly news releases. Listings of industries for which productivity indexes are available may be found on the Internet: www.bls.gov/lpc/ For additional information on international comparisons data, see International Comparisons of Unemployment, Bulletin 1979. Detailed data on the occupational injury and illness series are published in Occupational Injuries and Illnesses in the United States, by Industry, a BLS annual bulletin. Finally, the Monthly Labor Review carries analytical articles on annual and longer term developments in labor force, employment, and unemployment; employee compensation and collective bargaining; prices; productivity; international comparisons; and injury and illness data. Symbols n.e.c. = n.e.s. = p = r = not elsewhere classified. not elsewhere specified. preliminary. To increase the timeliness of some series, preliminary figures are issued based on representative but incomplete returns. revised. Generally, this revision reflects the availability of later data, but also may reflect other adjustments. Comparative Indicators (Tables 1–3) Comparative indicators tables provide an overview and comparison of major bls statistical series. Consequently, although many of the included series are available monthly, all measures in these comparative tables are presented quarterly and annually. Labor market indicators include employment measures from two major surveys and information on rates of change in compensation provided by the Employment Cost Index (ECI) program. The labor force participation rate, the employment-population ratio, and unemployment rates for major demographic groups based on the Current Population (“household”) Survey are presented, while measures of employment and average weekly hours by major industry sector are given using nonfarm payroll data. The Employment Cost Index (compensation), by major sector and by bargaining status, is chosen from a variety of BLS compensation and wage measures because it provides a comprehensive measure of employer costs for hiring labor, not just outlays for wages, and it is not affected by employment shifts among occupations and industries. Data on changes in compensation, prices, and productivity are presented in table 2. Measures of rates of change of compensation and wages from the Employment Cost Index Monthly Labor Review • August 2009 47 Current Labor Statistics program are provided for all civilian nonfarm workers (excluding Federal and household workers) and for all private nonfarm workers. Measures of changes in consumer prices for all urban consumers; producer prices by stage of processing; overall prices by stage of processing; and overall export and import price indexes are given. Measures of productivity (output per hour of all persons) are provided for major sectors. Alternative measures of wage and compensation rates of change, which reflect the overall trend in labor costs, are summarized in table 3. Differences in concepts and scope, related to the specific purposes of the series, contribute to the variation in changes among the individual measures. Employment and Unemployment Data because they were on layoff are also counted among the unemployed. The unemployment rate represents the number unemployed as a percent of the civilian labor force. The civilian labor force consists of all employed or unemployed persons in the civilian noninstitutional population. Persons not in the labor force are those not classified as employed or unemployed. This group includes discouraged workers, defined as persons who want and are available for a job and who have looked for work sometime in the past 12 months (or since the end of their last job if they held one within the past 12 months), but are not currently looking, because they believe there are no jobs available or there are none for which they would qualify. The civilian noninstitutional population comprises all persons 16 years of age and older who are not inmates of penal or mental institutions, sanitariums, or homes for the aged, infirm, or needy. The civilian labor force participation rate is the proportion of the civilian noninstitutional population that is in the labor force. The employment-population ratio is employment as a percent of the civilian noninstitutional population. (Tables 1; 4–29) Notes on the data Household survey data From time to time, and especially after a decennial census, adjustments are made in the Current Population Survey figures to correct for estimating errors during the intercensal years. These adjustments affect the comparability of historical data. A description of these adjustments and their effect on the various data series appears in the Explanatory Notes of Employment and Earnings. For a discussion of changes introduced in January 2003, see “Revisions to the Current Population Survey Effective in January 2003” in the February 2003 issue of Employment and Earnings (available on the BLS Web site at www.bls.gov/cps/rvcps03.pdf). Effective in January 2003, BLS began using the X-12 ARIMA seasonal adjustment program to seasonally adjust national labor force data. This program replaced the X-11 ARIMA program which had been used since January 1980. See “Revision of Seasonally Adjusted Labor Force Series in 2003,” in the February 2003 issue of Employment and Earnings (available on the BLS Web site at www.bls.gov/cps/cpsrs.pdf) for a discussion of the introduction of the use of X-12 ARIMA for seasonal adjustment of the labor force data and the effects that it had on the data. At the beginning of each calendar year, historical seasonally adjusted data usually are revised, and projected seasonal adjustment factors are calculated for use during the January–June period. The historical season- Notes on the data Definitions of each series and notes on the data are contained in later sections of these notes describing each set of data. Description of the series Employment data in this section are obtained from the Current Population Survey, a program of personal interviews conducted monthly by the Bureau of the Census for the Bureau of Labor Statistics. The sample consists of about 60,000 households selected to represent the U.S. population 16 years of age and older. Households are interviewed on a rotating basis, so that three-fourths of the sample is the same for any 2 consecutive months. Definitions Employed persons include (1) all those who worked for pay any time during the week which includes the 12th day of the month or who worked unpaid for 15 hours or more in a family-operated enterprise and (2) those who were temporarily absent from their regular jobs because of illness, vacation, industrial dispute, or similar reasons. A person working at more than one job is counted only in the job at which he or she worked the greatest number of hours. Unemployed persons are those who did not work during the survey week, but were available for work except for temporary illness and had looked for jobs within the preceding 4 weeks. Persons who did not look for work 48 Monthly Labor Review • August 2009 ally adjusted data usually are revised for only the most recent 5 years. In July, new seasonal adjustment factors, which incorporate the experience through June, are produced for the July–December period, but no revisions are made in the historical data. F OR ADDITIONAL INFORMATION on national household survey data, contact the Division of Labor Force Statistics: (202) 691–6378. Establishment survey data Description of the series Employment, hours, and earnings data in this section are compiled from payroll records reported monthly on a voluntary basis to the Bureau of Labor Statistics and its cooperating State agencies by about 160,000 businesses and government agencies, which represent approximately 400,000 individual worksites and represent all industries except agriculture. The active CES sample covers approximately one-third of all nonfarm payroll workers. Industries are classified in accordance with the 2002 North American Industry Classification System. In most industries, the sampling probabilities are based on the size of the establishment; most large establishments are therefore in the sample. (An establishment is not necessarily a firm; it may be a branch plant, for example, or warehouse.) Self-employed persons and others not on a regular civilian payroll are outside the scope of the survey because they are excluded from establishment records. This largely accounts for the difference in employment figures between the household and establishment surveys. Definitions An establishment is an economic unit which produces goods or services (such as a factory or store) at a single location and is engaged in one type of economic activity. Employed persons are all persons who received pay (including holiday and sick pay) for any part of the payroll period including the 12th day of the month. Persons holding more than one job (about 5 percent of all persons in the labor force) are counted in each establishment which reports them. Production workers in the goods-producing industries cover employees, up through the level of working supervisors, who engage directly in the manufacture or construction of the establishment’s product. In private service-providing industries, data are collected for nonsupervisory workers, which include most employees except those in executive, managerial, and supervisory positions. Those workers mentioned in tables 11–16 include production workers in manufacturing and natural resources and mining; construction workers in construction; and nonsupervisory workers in all private service-providing industries. Production and nonsupervisory workers account for about four-fifths of the total employment on private nonagricultural payrolls. Earnings are the payments production or nonsupervisory workers receive during the survey period, including premium pay for overtime or late-shift work but excluding irregular bonuses and other special payments. Real earnings are earnings adjusted to reflect the effects of changes in consumer prices. The deflator for this series is derived from the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Hours represent the average weekly hours of production or nonsupervisory workers for which pay was received, and are different from standard or scheduled hours. Overtime hours represent the portion of average weekly hours which was in excess of regular hours and for which overtime premiums were paid. The Diffusion Index represents the percent of industries in which employment was rising over the indicated period, plus one-half of the industries with unchanged employment; 50 percent indicates an equal balance between industries with increasing and decreasing employment. In line with Bureau practice, data for the 1-, 3-, and 6month spans are seasonally adjusted, while those for the 12-month span are unadjusted. Table 17 provides an index on private nonfarm employment based on 278 industries, and a manufacturing index based on 84 industries. These indexes are useful for measuring the dispersion of economic gains or losses and are also economic indicators. Notes on the data Establishment survey data are annually adjusted to comprehensive counts of employment (called “benchmarks”). The March 2003 benchmark was introduced in February 2004 with the release of data for January 2004, published in the March 2004 issue of the Review. With the release in June 2003, CES completed a conversion from the Standard Industrial Classification (SIC) system to the North American Industry Classification System (naics) and completed the transition from its original quota sample design to a probability-based sample design. The industry-coding update included reconstruction of historical estimates in order to preserve time series for data users. Normally 5 years of seasonally adjusted data are revised with each benchmark revision. However, with this release, the entire new time series history for all CES data series were re-seasonally adjusted due to the NAICS conversion, which resulted in the revision of all CES time series. Also in June 2003, the CES program introduced concurrent seasonal adjustment for the national establishment data. Under this methodology, the first preliminary estimates for the current reference month and the revised estimates for the 2 prior months will be updated with concurrent factors with each new release of data. Concurrent seasonal adjustment incorporates all available data, including first preliminary estimates for the most current month, in the adjustment process. For additional information on all of the changes introduced in June 2003, see the June 2003 issue of Employment and Earnings and “Recent changes in the national Current Employment Statistics survey,” Monthly Labor Review, June 2003, pp. 3–13. Revisions in State data (table 11) occurred with the publication of January 2003 data. For information on the revisions for the State data, see the March and May 2003 issues of Employment and Earnings, and “Recent changes in the State and Metropolitan Area CES survey,” Monthly Labor Review, June 2003, pp. 14–19. Beginning in June 1996, the BLS uses the X-12-ARIMA methodology to seasonally adjust establishment survey data. This procedure, developed by the Bureau of the Census, controls for the effect of varying survey intervals (also known as the 4- versus 5-week effect), thereby providing improved measurement of over-the-month changes and underlying economic trends. Revisions of data, usually for the most recent 5-year period, are made once a year coincident with the benchmark revisions. In the establishment survey, estimates for the most recent 2 months are based on incomplete returns and are published as preliminary in the tables (12–17 in the Review). When all returns have been received, the estimates are revised and published as “final” (prior to any benchmark revisions) in the third month of their appearance. Thus, December data are published as preliminary in January and February and as final in March. For the same reasons, quarterly establishment data (table 1) are preliminary for the first 2 months of publication and final in the third month. Fourth-quarter data are published as preliminary in January and February and as final in March. F OR ADDITIONAL INFORMATION on establishment survey data, contact the Division of Current Employment Statistics: (202) 691–6555. Unemployment data by State Description of the series Data presented in this section are obtained from the Local Area Unemployment Statistics (LAUS) program, which is conducted in cooperation with State employment security agencies. Monthly estimates of the labor force, employment, and unemployment for States and sub-State areas are a key indicator of local economic conditions, and form the basis for determining the eligibility of an area for benefits under Federal economic assistance programs such as the Job Training Partnership Act. Seasonally adjusted unemployment rates are presented in table 10. Insofar as possible, the concepts and definitions underlying these data are those used in the national estimates obtained from the CPS. Notes on the data Data refer to State of residence. Monthly data for all States and the District of Columbia are derived using standardized procedures established by BLS. Once a year, estimates are revised to new population controls, usually with publication of January estimates, and benchmarked to annual average CPS levels. FOR ADDITIONAL INFORMATION on data in this series, call (202) 691–6392 (table 10) or (202) 691–6559 (table 11). Quarterly Census of Employment and Wages Description of the series Employment, wage, and establishment data in this section are derived from the quarterly tax reports submitted to State employment security agencies by private and State and local government employers subject to State unemployment insurance (ui) laws and from Federal, agencies subject to the Unemployment Compensation for Federal Employees (ucfe) program. Each quarter, State agencies edit and process the data and send the information to the Bureau of Labor Statistics. The Quarterly Census of Employment and Wages (QCEW) data, also referred as ES202 data, are the most complete enumeration of employment and wage information by industry at the national, State, metropolitan area, and county levels. They have broad economic significance in evaluating labor Monthly Labor Review • August 2009 49 Current Labor Statistics market trends and major industry developments. Definitions In general, the Quarterly Census of Employment and Wages monthly employment data represent the number of covered workers who worked during, or received pay for, the pay period that included the 12th day of the month. Covered private industry employment includes most corporate officials, executives, supervisory personnel, professionals, clerical workers, wage earners, piece workers, and part-time workers. It excludes proprietors, the unincorporated self-employed, unpaid family members, and certain farm and domestic workers. Certain types of nonprofit employers, such as religious organizations, are given a choice of coverage or exclusion in a number of States. Workers in these organizations are, therefore, reported to a limited degree. Persons on paid sick leave, paid holiday, paid vacation, and the like, are included. Persons on the payroll of more than one firm during the period are counted by each ui-subject employer if they meet the employment definition noted earlier. The employment count excludes workers who earned no wages during the entire applicable pay period because of work stoppages, temporary layoffs, illness, or unpaid vacations. Federal employment data are based on reports of monthly employment and quarterly wages submitted each quarter to State agencies for all Federal installations with employees covered by the Unemployment Compensation for Federal Employees (ucfe) program, except for certain national security agencies, which are omitted for security reasons. Employment for all Federal agencies for any given month is based on the number of persons who worked during or received pay for the pay period that included the 12th of the month. An establishment is an economic unit, such as a farm, mine, factory, or store, that produces goods or provides services. It is typically at a single physical location and engaged in one, or predominantly one, type of economic activity for which a single industrial classification may be applied. Occasionally, a single physical location encompasses two or more distinct and significant activities. Each activity should be reported as a separate establishment if separate records are kept and the various activities are classified under different NAICS industries. Most employers have only one establishment; thus, the establishment is the predominant reporting unit or statistical entity for reporting employment and wages 50 Monthly Labor Review • August 2009 data. Most employers, including State and local governments who operate more than one establishment in a State, file a Multiple Worksite Report each quarter, in addition to their quarterly ui report. The Multiple Worksite Report is used to collect separate employment and wage data for each of the employer’s establishments, which are not detailed on the ui report. Some very small multi-establishment employers do not file a Multiple Worksite Report. When the total employment in an employer’s secondary establishments (all establishments other than the largest) is 10 or fewer, the employer generally will file a consolidated report for all establishments. Also, some employers either cannot or will not report at the establishment level and thus aggregate establishments into one consolidated unit, or possibly several units, though not at the establishment level. For the Federal Government, the reporting unit is the installation: a single location at which a department, agency, or other government body has civilian employees. Federal agencies follow slightly different criteria than do private employers when breaking down their reports by installation. They are permitted to combine as a single statewide unit: 1) all installations with 10 or fewer workers, and 2) all installations that have a combined total in the State of fewer than 50 workers. Also, when there are fewer than 25 workers in all secondary installations in a State, the secondary installations may be combined and reported with the major installation. Last, if a Federal agency has fewer than five employees in a State, the agency headquarters office (regional office, district office) serving each State may consolidate the employment and wages data for that State with the data reported to the State in which the headquarters is located. As a result of these reporting rules, the number of reporting units is always larger than the number of employers (or government agencies) but smaller than the number of actual establishments (or installations). Data reported for the first quarter are tabulated into size categories ranging from worksites of very small size to those with 1,000 employees or more. The size category is determined by the establishment’s March employment level. It is important to note that each establishment of a multi-establishment firm is tabulated separately into the appropriate size category. The total employment level of the reporting multi-establishment firm is not used in the size tabulation. Covered employers in most States report total wages paid during the calendar quarter, regardless of when the services were performed. A few State laws, however, specify that wages be reported for, or based on the period during which services are performed rather than the period during which compensation is paid. Under most State laws or regulations, wages include bonuses, stock options, the cash value of meals and lodging, tips and other gratuities, and, in some States, employer contributions to certain deferred compensation plans such as 401(k) plans. Covered employer contributions for old-age, survivors, and disability insurance (oasdi), health insurance, unemployment insurance, workers’ compensation, and private pension and welfare funds are not reported as wages. Employee contributions for the same purposes, however, as well as money withheld for income taxes, union dues, and so forth, are reported even though they are deducted from the worker’s gross pay. Wages of covered Federal workers represent the gross amount of all payrolls for all pay periods ending within the quarter. This includes cash allowances, the cash equivalent of any type of remuneration, severance pay, withholding taxes, and retirement deductions. Federal employee remuneration generally covers the same types of services as for workers in private industry. Average annual wage per employee for any given industry are computed by dividing total annual wages by annual average employment. A further division by 52 yields average weekly wages per employee. Annual pay data only approximate annual earnings because an individual may not be employed by the same employer all year or may work for more than one employer at a time. Average weekly or annual wage is affected by the ratio of full-time to part-time workers as well as the number of individuals in high-paying and low-paying occupations. When average pay levels between States and industries are compared, these factors should be taken into consideration. For example, industries characterized by high proportions of part-time workers will show average wage levels appreciably less than the weekly pay levels of regular full-time employees in these industries. The opposite effect characterizes industries with low proportions of part-time workers, or industries that typically schedule heavy weekend and overtime work. Average wage data also may be influenced by work stoppages, labor turnover rates, retroactive payments, seasonal factors, bonus payments, and so on. Notes on the data Beginning with the release of data for 2001, publications presenting data from the Covered Employment and Wages program have switched to the 2002 version of the North American Industry Classification System (NAICS) as the basis for the assignment and tabulation of economic data by industry. NAICS is the product of a cooperative effort on the part of the statistical agencies of the United States, Canada, and Mexico. Due to difference in NAICS and Standard Industrial Classification ( SIC) structures, industry data for 2001 is not comparable to the SIC-based data for earlier years. Effective January 2001, the program began assigning Indian Tribal Councils and related establishments to local government ownership. This BLS action was in response to a change in Federal law dealing with the way Indian Tribes are treated under the Federal Unemployment Tax Act. This law requires federally recognized Indian Tribes to be treated similarly to State and local governments. In the past, the Covered Employment and Wage (CEW) program coded Indian Tribal Councils and related establishments in the private sector. As a result of the new law, CEW data reflects significant shifts in employment and wages between the private sector and local government from 2000 to 2001. Data also reflect industry changes. Those accounts previously assigned to civic and social organizations were assigned to tribal governments. There were no required industry changes for related establishments owned by these Tribal Councils. These tribal business establishments continued to be coded according to the economic activity of that entity. To insure the highest possible quality of data, State employment security agencies verify with employers and update, if necessary, the industry, location, and ownership classification of all establishments on a 3-year cycle. Changes in establishment classification codes resulting from the verification process are introduced with the data reported for the first quarter of the year. Changes resulting from improved employer reporting also are introduced in the first quarter. For these reasons, some data, especially at more detailed geographic levels, may not be strictly comparable with earlier years. County definitions are assigned according to Federal Information Processing Standards Publications as issued by the National Institute of Standards and Technology. Areas shown as counties include those designated as independent cities in some jurisdictions and, in Alaska, those areas designated by the Census Bureau where counties have not been created. County data also are presented for the New England States for comparative purposes, even though townships are the more common designation used in New England (and New Jersey). The Office of Management and Budget (OMB) defines metropolitan areas for use in Federal statistical activities and updates these definitions as needed. Data in this table use metropolitan area criteria established by OMB in definitions issued June 30, 1999 (OMB Bulletin No. 99-04). These definitions reflect information obtained from the 1990 Decennial Census and the 1998 U.S. Census Bureau population estimate. A complete list of metropolitan area definitions is available from the National Technical Information Service (NTIS), Document Sales, 5205 Port Royal Road, Springfield, Va. 22161, telephone 1-800-553-6847. OMB defines metropolitan areas in terms of entire counties, except in the six New England States where they are defined in terms of cities and towns. New England data in this table, however, are based on a county concept defined by OMB as New England County Metropolitan Areas (NECMA) because county-level data are the most detailed available from the Quarterly Census of Employment and Wages. The NECMA is a county-based alternative to the city- and town-based metropolitan areas in New England. The NECMA for a Metropolitan Statistical Area (MSA) include: (1) the county containing the first-named city in that MSA title (this county may include the first-named cities of other MSA, and (2) each additional county having at least half its population in the MSA in which first-named cities are in the county identified in step 1. The NECMA is officially defined areas that are meant to be used by statistical programs that cannot use the regular metropolitan area definitions in New England. For additional information on the covered employment and wage data, contact the Division of Administrative Statistics and Labor Turnover at (202) 691–6567. Job Openings and Labor Turnover Survey Description of the series Data for the Job Openings and Labor Turnover Survey (JOLTS) are collected and compiled from a sample of 16,000 business establishments. Each month, data are collected for total employment, job openings, hires, quits, layoffs and discharges, and other separations. The JOLTS program covers all private nonfarm establishments such as factories, offices, and stores, as well as Federal, State, and local government entities in the 50 States and the District of Columbia. The JOLTS sample design is a random sample drawn from a universe of more than eight million establishments compiled as part of the operations of the Quarterly Census of Em- ployment and Wages, or QCEW, program. This program includes all employers subject to State unemployment insurance (UI) laws and Federal agencies subject to Unemployment Compensation for Federal Employees (UCFE). The sampling frame is stratified by ownership, region, industry sector, and size class. Large firms fall into the sample with virtual certainty. JOLTS total employment estimates are controlled to the employment estimates of the Current Employment Statistics (CES) survey. A ratio of CES to JOLTS employment is used to adjust the levels for all other JOLTS data elements. Rates then are computed from the adjusted levels. The monthly JOLTS data series begin with December 2000. Not seasonally adjusted data on job openings, hires, total separations, quits, layoffs and discharges, and other separations levels and rates are available for the total nonfarm sector, 16 private industry divisions and 2 government divisions based on the North American Industry Classification System (NAICS), and four geographic regions. Seasonally adjusted data on job openings, hires, total separations, and quits levels and rates are available for the total nonfarm sector, selected industry sectors, and four geographic regions. Definitions Establishments submit job openings infor-mation for the last business day of the reference month. A job opening requires that (1) a specific position exists and there is work available for that position; and (2) work could start within 30 days regardless of whether a suitable candidate is found; and (3) the employer is actively recruiting from outside the establishment to fill the position. Included are full-time, part-time, permanent, short-term, and seasonal openings. Active recruiting means that the establishment is taking steps to fill a position by advertising in newspapers or on the Internet, posting help-wanted signs, accepting applications, or using other similar methods. Jobs to be filled only by internal transfers, promotions, demotions, or recall from layoffs are excluded. Also excluded are jobs with start dates more than 30 days in the future, jobs for which employees have been hired but have not yet reported for work, and jobs to be filled by employees of temporary help agencies, employee leasing companies, outside contractors, or consultants. The job openings rate is computed by dividing the number of job openings by the sum of employment and job openings, and multiplying that quotient by 100. Hires are the total number of additions Monthly Labor Review • August 2009 51 Current Labor Statistics to the payroll occurring at any time during the reference month, including both new and rehired employees and full-time and parttime, permanent, short-term and seasonal employees, employees recalled to the location after a layoff lasting more than 7 days, on-call or intermittent employees who returned to work after having been formally separated, and transfers from other locations. The hires count does not include transfers or promotions within the reporting site, employees returning from strike, employees of temporary help agencies or employee leasing companies, outside contractors, or consultants. The hires rate is computed by dividing the number of hires by employment, and multiplying that quotient by 100. Separations are the total number of terminations of employment occurring at any time during the reference month, and are reported by type of separation—quits, layoffs and discharges, and other separations. Quits are voluntary separations by employees (except for retirements, which are reported as other separations). Layoffs and discharges are involuntary separations initiated by the employer and include layoffs with no intent to rehire, formal layoffs lasting or expected to last more than 7 days, discharges resulting from mergers, downsizing, or closings, firings or other discharges for cause, terminations of permanent or short-term employees, and terminations of seasonal employees. Other separations include retirements, transfers to other locations, deaths, and separations due to disability. Separations do not include transfers within the same location or employees on strike. The separations rate is computed by dividing the number of separations by employment, and multiplying that quotient by 100. The quits, layoffs and discharges, and other separations rates are computed similarly, dividing the number by employment and multiplying by 100. Notes on the data The JOLTS data series on job openings, hires, and separations are relatively new. The full sample is divided into panels, with one panel enrolled each month. A full complement of panels for the original data series based on the 1987 Standard Industrial Classification (SIC) system was not completely enrolled in the survey until January 2002. The supple-mental panels of establishments needed to create NAICS estimates were not completely enrolled until May 2003. The data collected up until those points are from less than a full sample. Therefore, estimates from earlier months should be used with caution, as fewer sampled 52 Monthly Labor Review • August 2009 units were reporting data at that time. In March 2002, BLS procedures for collecting hires and separations data were revised to address possible underreporting. As a result, JOLTS hires and separations estimates for months prior to March 2002 may not be comparable with estimates for March 2002 and later. The Federal Government reorganization that involved transferring approximately 180,000 employees to the new Department of Homeland Security is not reflected in the JOLTS hires and separations estimates for the Federal Government. The Office of Personnel Management’s record shows these transfers were completed in March 2003. The inclusion of transfers in the JOLTS definitions of hires and separations is intended to cover ongoing movements of workers between establishments. The Department of Homeland Security reorganization was a massive one-time event, and the inclusion of these intergovernmental transfers would distort the Federal Government time series. Data users should note that seasonal adjustment of the JOLTS series is conducted with fewer data observations than is customary. The historical data, therefore, may be subject to larger than normal revisions. Because the seasonal patterns in economic data series typically emerge over time, the standard use of moving averages as seasonal filters to capture these effects requires longer series than are currently available. As a result, the stable seasonal filter option is used in the seasonal adjustment of the JOLTS data. When calculating seasonal factors, this filter takes an average for each calendar month after detrending the series. The stable seasonal filter assumes that the seasonal factors are fixed; a necessary assumption until sufficient data are available. When the stable seasonal filter is no longer needed, other program features also may be introduced, such as outlier adjustment and extended diagnostic testing. Additionally, it is expected that more series, such as layoffs and discharges and additional industries, may be seasonally adjusted when more data are available. JOLTS hires and separations estimates cannot be used to exactly explain net changes in payroll employment. Some reasons why it is problematic to compare changes in payroll employment with JOLTS hires and separations, especially on a monthly basis, are: (1) the reference period for payroll employment is the pay period including the 12th of the month, while the reference period for hires and separations is the calendar month; and (2) payroll employment can vary from month to month simply because part-time and oncall workers may not always work during the pay period that includes the 12th of the month. Additionally, research has found that some reporters systematically underreport separations relative to hires due to a number of factors, including the nature of their payroll systems and practices. The shortfall appears to be about 2 percent or less over a 12-month period. F OR ADDITIONAL INFORMATION on the Job Openings and Labor Turnover Survey, contact the Division of Administrative Statistics and Labor Turnover at (202) 961–5870. Compensation and Wage Data (Tables 1–3; 30–37) The National Compensation Survey (NCS) produces a variety of compensation data. These include: The Employment Cost Index (ECI) and NCS benefit measures of the incidence and provisions of selected employee benefit plans. Selected samples of these measures appear in the following tables. NCS also compiles data on occupational wages and the Employer Costs for Employee Compensation (ECEC). Employment Cost Index Description of the series The Employment Cost Index (ECI) is a quarterly measure of the rate of change in compensation per hour worked and includes wages, salaries, and employer costs of employee benefits. It is a Laspeyres Index that uses fixed employment weights to measure change in labor costs free from the influence of employment shifts among occupations and industries. The ECI provides data for the civilian economy, which includes the total private nonfarm economy excluding private households, and the public sector excluding the Federal government. Data are collected each quarter for the pay period including the 12th day of March, June, September, and December. Sample establishments are classified by industry categories based on the 2002 North American Classification System (NAICS). Within a sample establishment, specific job categories are selected and classified into about 800 occupations according to the 2000 Standard Occupational Classification (SOC) System. Individual occupations are combined to represent one of ten intermediate aggregations, such as professional and related occupations, or one of five higher level aggre- gations, such as management, professional, and related occupations. Fixed employment weights are used each quarter to calculate the most aggregate series—civilian, private, and State and local government. These fixed weights are also used to derive all of the industry and occupational series indexes. Beginning with the March 2006 estimates, 2002 fixed employment weights from the Bureau’s Occupational Employment Statistics survey were introduced. From March 1995 to December 2005, 1990 employment counts were used. These fixed weights ensure that changes in these indexes reflect only changes in compensation, not employment shifts among industries or occupations with different levels of wages and compensation. For the series based on bargaining status, census region and division, and metropolitan area status, fixed employment data are not available. The employment weights are reallocated within these series each quarter based on the current eci sample. The indexes for these series, consequently, are not strictly comparable with those for aggregate, occupational, and industry series. Definitions Total compensation costs include wages, salaries, and the employer’s costs for employee benefits. Wages and salaries consist of earnings before payroll deductions, including production bonuses, incentive earnings, commissions, and cost-of-living adjustments. Benefits include the cost to employers for paid leave, supplemental pay (including nonproduction bonuses), insurance, retirement and savings plans, and legally required benefits (such as Social Security, workers’ compensation, and unemployment insurance). Excluded from wages and salaries and employee benefits are such items as paymentin-kind, free room and board, and tips. Notes on the data The ECI data in these tables reflect the con-version to the 2002 North American Industry Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. ECI series based on NAICS and SOC became the official BLS estimates starting in March 2006. The ECI for changes in wages and salaries in the private nonfarm economy was published beginning in 1975. Changes in total compensation cost—wages and salaries and benefits combined—were published beginning in 1980. The series of changes in wages and salaries and for total compensation in the State and local government sector and in the civilian nonfarm economy (excluding Federal employees) were published beginning in 1981. Historical indexes (December 2005=100) are available on the Internet: www.bls.gov/ect/ A DDITIONAL INFORMATION on the Employment Cost Index is available at www. bls.gov/ncs/ect/home.htm or by telephone at (202) 691–6199. National Compensation Survey Benefit Measures Description of the series benefit measures of employee benefits are published in two separate reports. The annual summary provides data on the incidence of (access to and participation in) selected benefits and provisions of paid holidays and vacations, life insurance plans, and other selected benefit programs. Data on percentages of establishments offering major employee benefits, and on the employer and employee shares of contributions to medical care premiums also are presented. Selected benefit data appear in the following tables. A second publication, published later, contains more detailed information about health and retirement plans. NCS Definitions Employer-provided benefits are benefits that are financed either wholly or partly by the employer. They may be sponsored by a union or other third party, as long as there is some employer financing. However, some benefits that are fully paid for by the employee also are included. For example, long-term care insurance paid entirely by the employee are included because the guarantee of insurability and availability at group premium rates are considered a benefit. Employees are considered as having access to a benefit plan if it is available for their use. For example, if an employee is permitted to participate in a medical care plan offered by the employer, but the employee declines to do so, he or she is placed in the category with those having access to medical care. Employees in contributory plans are considered as participating in an insurance or retirement plan if they have paid required contributions and fulfilled any applicable service requirement. Employees in noncontributory plans are counted as participating regardless of whether they have fulfilled the service requirements. Defined benefit pension plans use predetermined formulas to calculate a retirement benefit (if any), and obligate the employer to provide those benefits. Benefits are generally based on salary, years of service, or both. Defined contribution plans generally specify the level of employer and employee contributions to a plan, but not the formula for determining eventual benefits. Instead, individual accounts are set up for participants, and benefits are based on amounts credited to these accounts. Tax-deferred savings plans are a type of defined contribution plan that allow participants to contribute a portion of their salary to an employer-sponsored plan and defer income taxes until withdrawal. Flexible benefit plans allow employees to choose among several benefits, such as life insurance, medical care, and vacation days, and among several levels of coverage within a given benefit. Notes on the data ADDITIONAL INFORMATION ON THE NCS benefit measures is available at www.bls. gov/ncs/ebs/home.htm or by telephone at (202) 691–6199. Work stoppages Description of the series Data on work stoppages measure the number and duration of major strikes or lockouts (involving 1,000 workers or more) occurring during the month (or year), the number of workers involved, and the amount of work time lost because of stoppage. These data are presented in table 37. Data are largely from a variety of published sources and cover only establishments directly involved in a stoppage. They do not measure the indirect or secondary effect of stoppages on other establishments whose employees are idle owing to material shortages or lack of service. Definitions Number of stoppages: The number of strikes and lockouts involving 1,000 workers or more and lasting a full shift or longer. Workers involved: The number of workers directly involved in the stoppage. Number of days idle: The aggregate number of workdays lost by workers involved in the stoppages. Days of idleness as a percent of estiMonthly Labor Review • August 2009 53 Current Labor Statistics mated working time: Aggregate workdays lost as a percent of the aggregate number of standard workdays in the period multiplied by total employment in the period. Notes on the data This series is not comparable with the one terminated in 1981 that covered strikes involving six workers or more. A DDITIONAL INFORMATION on work stop-pages data is available at www. bls. gov/cba/home.htm or by telephone at (202) 691–6199. Price Data (Tables 2; 38–46) Price data are gathered by the Bureau of Labor Statistics from retail and primary markets in the United States. Price indexes are given in relation to a base period—December 2003 = 100 for many Producer Price Indexes (unless otherwise noted), 1982–84 = 100 for many Consumer Price Indexes (unless otherwise noted), and 1990 = 100 for International Price Indexes. Consumer Price Indexes Description of the series The Consumer Price Index (CPI) is a measure of the average change in the prices paid by urban consumers for a fixed market basket of goods and services. The CPI is calculated monthly for two population groups, one consisting only of urban households whose primary source of income is derived from the employment of wage earners and clerical workers, and the other consisting of all urban households. The wage earner index (CPI-W) is a continuation of the historic index that was introduced well over a half-century ago for use in wage negotiations. As new uses were developed for the CPI in recent years, the need for a broader and more representative index became apparent. The all-urban consumer index (CPI-U), introduced in 1978, is representative of the 1993–95 buying habits of about 87 percent of the noninstitutional population of the United States at that time, compared with 32 percent represented in the CPI-W. In addition to wage earners and clerical workers, the CPI-U covers professional, managerial, and technical workers, the self-employed, shortterm workers, the unemployed, retirees, and others not in the labor force. The CPI is based on prices of food, clothing, shelter, fuel, drugs, transportation fares, doctors’ 54 Monthly Labor Review • August 2009 and dentists’ fees, and other goods and services that people buy for day-to-day living. The quantity and quality of these items are kept essentially unchanged between major revisions so that only price changes will be measured. All taxes directly associated with the purchase and use of items are included in the index. Data collected from more than 23,000 retail establishments and 5,800 housing units in 87 urban areas across the country are used to develop the “U.S. city average.” Separate estimates for 14 major urban centers are presented in table 39.The areas listed are as indicated in footnote 1 to the table. The area indexes measure only the average change in prices for each area since the base period, and do not indicate differences in the level of prices among cities. Notes on the data In January 1983, the Bureau changed the way in which homeownership costs are meaured for the CPI-U. A rental equivalence method replaced the asset-price approach to homeownership costs for that series. In January 1985, the same change was made in the CPI-W. The central purpose of the change was to separate shelter costs from the investment component of homeownership so that the index would reflect only the cost of shelter services provided by owner-occupied homes. An updated CPI-U and CPI-W were introduced with release of the January 1987 and January 1998 data. FOR ADDITIONAL INFORMATION, contact the Division of Prices and Price Indexes: (202) 691–7000. Producer Price Indexes Description of the series Producer Price Indexes (PPI) measure average changes in prices received by domestic producers of commodities in all stages of processing. The sample used for calculating these indexes currently contains about 3,200 commodities and about 80,000 quotations per month, selected to represent the movement of prices of all commodities produced in the manufacturing; agriculture, forestry, and fishing; mining; and gas and electricity and public utilities sectors. The stage-of-processing structure of PPI organizes products by class of buyer and degree of fabrication (that is, finished goods, intermediate goods, and crude materials). The traditional commodity structure of PPI organizes products by similarity of end use or material composition. The industry and product structure of PPI organizes data in accordance with the 2002 North American Industry Classification System and product codes developed by the U.S. Census Bureau. To the extent possible, prices used in calculating Producer Price Indexes apply to the first significant commercial transaction in the United States from the production or central marketing point. Price data are generally collected monthly, primarily by mail questionnaire. Most prices are obtained directly from producing companies on a voluntary and confidential basis. Prices generally are reported for the Tuesday of the week containing the 13th day of the month. Since January 1992, price changes for the various commodities have been averaged together with implicit quantity weights representing their importance in the total net selling value of all commodities as of 1987. The detailed data are aggregated to obtain indexes for stage-of-processing groupings, commodity groupings, durability-of-product groupings, and a number of special composite groups. All Producer Price Index data are subject to revision 4 months after original publication. FOR ADDITIONAL INFORMATION, contact the Division of Industrial Prices and Price Indexes: (202) 691–7705. International Price Indexes Description of the series The International Price Program produces monthly and quarterly export and import price indexes for nonmilitary goods and services traded between the United States and the rest of the world. The export price index provides a measure of price change for all products sold by U.S. residents to foreign buyers. (“Residents” is defined as in the national income accounts; it includes corporations, businesses, and individuals, but does not require the organizations to be U.S. owned nor the individuals to have U.S. citizenship.) The import price index provides a measure of price change for goods purchased from other countries by U.S. residents. The product universe for both the import and export indexes includes raw materials, agricultural products, semifinished manufactures, and finished manufactures, including both capital and consumer goods. Price data for these items are collected primarily by mail questionnaire. In nearly all cases, the data are collected directly from the exporter or importer, although in a few cases, prices are obtained from other sources. To the extent possible, the data gathered refer to prices at the U.S. border for exports and at either the foreign border or the U.S. border for imports. For nearly all products, the prices refer to transactions completed during the first week of the month. Survey respondents are asked to indicate all discounts, allow- ances, and rebates applicable to the reported prices, so that the price used in the calculation of the indexes is the actual price for which the product was bought or sold. In addition to general indexes of prices for U.S. exports and imports, indexes are also published for detailed product categories of exports and imports. These categories are defined according to the five-digit level of detail for the Bureau of Economic Analysis End-use Classification, the three-digit level for the Standard International Trade Classification (SITC), and the four-digit level of detail for the Harmonized System. Aggregate import indexes by country or region of origin are also available. BLS publishes indexes for selected categories of internationally traded services, calculated on an international basis and on a balance-of-payments basis. Notes on the data The export and import price indexes are weighted indexes of the Laspeyres type. The trade weights currently used to compute both indexes relate to 2000. Because a price index depends on the same items being priced from period to period, it is necessary to recognize when a product’s specifications or terms of transaction have been modified. For this reason, the Bureau’s questionnaire requests detailed descriptions of the physical and functional characteristics of the products being priced, as well as information on the number of units bought or sold, discounts, credit terms, packaging, class of buyer or seller, and so forth. When there are changes in either the specifications or terms of transaction of a product, the dollar value of each change is deleted from the total price change to obtain the “pure” change. Once this value is determined, a linking procedure is employed which allows for the continued repricing of the item. FOR ADDITIONAL INFORMATION, contact the Division of International Prices: (202) 691–7155. Productivity Data (Tables 2; 47–50) Business and major sectors Description of the series The productivity measures relate real output to real input. As such, they encompass a family of measures which include single-factor input measures, such as output per hour, output per unit of labor input, or output per unit of capital input, as well as measures of multifactor productivity (output per unit of combined labor and capital inputs). The Bureau indexes show the change in output relative to changes in the various inputs. The measures cover the business, nonfarm business, manufacturing, and nonfinancial corporate sectors. Corresponding indexes of hourly compensation, unit labor costs, unit nonlabor payments, and prices are also provided. Definitions Output per hour of all persons (labor productivity) is the quantity of goods and services produced per hour of labor input. Output per unit of capital services (capital productivity) is the quantity of goods and services produced per unit of capital services input. Multifactor productivity is the quantity of goods and services produced per combined inputs. For private business and private nonfarm business, inputs include labor and capital units. For manufacturing, inputs include labor, capital, energy, nonenergy materials, and purchased business services. Compensation per hour is total compensation divided by hours at work. Total compensation equals the wages and salaries of employees plus employers’ contributions for social insurance and private benefit plans, plus an estimate of these payments for the self-employed (except for nonfinancial corporations in which there are no self-employed). Real compensation per hour is compensation per hour deflated by the change in the Consumer Price Index for All Urban Consumers. Unit labor costs are the labor compensation costs expended in the production of a unit of output and are derived by dividing compensation by output. Unit nonlabor payments include profits, depreciation, interest, and indirect taxes per unit of output. They are computed by subtracting compensation of all persons from current-dollar value of output and dividing by output. Unit nonlabor costs contain all the components of unit nonlabor payments except unit profits. Unit profits include corporate profits with inventory valuation and capital consumption adjustments per unit of output. Hours of all persons are the total hours at work of payroll workers, self-employed persons, and unpaid family workers. Labor inputs are hours of all persons adjusted for the effects of changes in the education and experience of the labor force. Capital services are the flow of services from the capital stock used in production. It is developed from measures of the net stock of physical assets—equipment, structures, land, and inventories—weighted by rental prices for each type of asset. Combined units of labor and capital inputs are derived by combining changes in labor and capital input with weights which represent each component’s share of total cost. Combined units of labor, capital, energy, materials, and purchased business services are similarly derived by combining changes in each input with weights that represent each input’s share of total costs. The indexes for each input and for combined units are based on changing weights which are averages of the shares in the current and preceding year (the Tornquist index-number formula). Notes on the data Business sector output is an annually-weighted index constructed by excluding from real gross domestic product (GDP) the following outputs: general government, nonprofit institutions, paid employees of private households, and the rental value of owner-occupied dwellings. Nonfarm business also excludes farming. Private business and private nonfarm business further exclude government enterprises. The measures are supplied by the U.S. Department of Commerce’s Bureau of Economic Analysis. Annual estimates of manufacturing sectoral output are produced by the Bureau of Labor Statistics. Quarterly manufacturing output indexes from the Federal Reserve Board are adjusted to these annual output measures by the BLS. Compensation data are developed from data of the Bureau of Economic Analysis and the Bureau of Labor Statistics. Hours data are developed from data of the Bureau of Labor Statistics. The productivity and associated cost measures in tables 47–50 describe the relationship between output in real terms and the labor and capital inputs involved in its production. They show the changes from period to period in the amount of goods and services produced per unit of input. Although these measures relate output to hours and capital services, they do not measure the contributions of labor, capital, or any other specific factor of production. Rather, they reflect the joint effect of many influences, including changes in technology; shifts in the composition of the labor force; capital investment; level of output; changes in the utilization of capacity, energy, material, and research and development; the organization of production; managerial skill; and characteristics and efforts of the work force. FOR ADDITIONAL INFORMATION on this productivity series, contact the Division of Productivity Research: (202) 691–5606. Monthly Labor Review • August 2009 55 Current Labor Statistics Industry productivity measures Description of the series The BLS industry productivity indexes measure the relationship between output and inputs for selected industries and industry groups, and thus reflect trends in industry efficiency over time. Industry measures include labor productivity, multifactor productivity, compensation, and unit labor costs. The industry measures differ in methodology and data sources from the productivity measures for the major sectors because the industry measures are developed independently of the National Income and Product Accounts framework used for the major sector measures. Definitions Output per hour is derived by dividing an index of industry output by an index of labor input. For most industries, output indexes are derived from data on the value of industry output adjusted for price change. For the remaining industries, output indexes are derived from data on the physical quantity of production. The labor input series is based on the hours of all workers or, in the case of some transportation industries, on the number of employees. For most industries, the series consists of the hours of all employees. For some trade and services industries, the series also includes the hours of partners, proprietors, and unpaid family workers. Unit labor costs represent the labor compensation costs per unit of output produced, and are derived by dividing an index of labor compensation by an index of output. Labor compensation includes payroll as well as supplemental payments, including both legally required expenditures and payments for voluntary programs. Multifactor productivity is derived by dividing an index of industry output by an index of combined inputs consumed in producing that output. Combined inputs include capital, labor, and intermediate purchases. The measure of capital input represents the flow of services from the capital stock used in production. It is developed from measures of the net stock of physical assets—equipment, structures, land, and inventories. The measure of intermediate purchases is a combination of purchased materials, services, fuels, and electricity. Notes on the data The industry measures are compiled from 56 Monthly Labor Review • August 2009 data produced by the Bureau of Labor Statistics and the Census Bureau, with additional data supplied by other government agencies, trade associations, and other sources. FOR ADDITIONAL INFORMATION on this series, contact the Division of Industry Productivity Studies: (202) 691–5618, or visit the Web site at: www.bls.gov/lpc/home.htm International Comparisons (Tables 51–53) Labor force and unemployment Description of the series Tables 51 and 52 present comparative measures of the labor force, employment, and unemployment approximating U.S. concepts for the United States, Canada, Australia, Japan, and six European countries. The Bureau adjusts the figures for these selected countries, for all known major definitional differences, to the extent that data to prepare adjustments are available. Although precise comparability may not be achieved, these adjusted figures provide a better basis for international comparisons than the figures regularly published by each country. For further information on adjustments and comparability issues, see Constance Sorrentino, “International unemployment rates: how comparable are they?” Monthly Labor Review, June 2000, pp. 3–20, available on the Internet at www. bls.gov/opub/mlr/2000/06/art1full.pdf. Definitions For the principal U.S. definitions of the labor force, employment, and unemployment, see the Notes section on Employment and Unemployment Data: Household survey data. Notes on the data Foreign country data are adjusted as closely as possible to the U.S. definitions. Primary areas of adjustment address conceptual differences in upper age limits and definitions of employment and unemployment, provided that reliable data are available to make these adjustments. Adjustments are made where applicable to include employed and unemployed persons above upper age limits; some European countries do not include persons older than age 64 in their labor force measures, because a large portion of this population has retired. Adjustments are made to exclude active duty military from employment figures, although a small number of career military may be included in some European countries. Adjustments are made to exclude unpaid family workers who worked fewer than 15 hours per week from employment figures; U.S. concepts do not include them in employment, whereas most foreign countries include all unpaid family workers regardless of the number of hours worked. Adjustments are made to include full-time students seeking work and available for work as unemployed when they are classified as not in the labor force. Where possible, lower age limits are based on the age at which compulsory schooling ends in each country, rather than based on the U.S. standard of 16. Lower age limits have ranged between 13 and 16 over the years covered; currently, the lower age limits are either 15 or 16 in all 10 countries. Some adjustments for comparability are not made because data are unavailable for adjustment purposes. For example, no adjustments to unemployment are usually made for deviations from U.S. concepts in the treatment of persons waiting to start a new job or passive job seekers. These conceptual differences have little impact on the measures. Furthermore, BLS studies have concluded that no adjustments should be made for persons on layoff who are counted as employed in some countries because of their strong job attachment as evidenced by, for example, payment of salary or the existence of a recall date. In the United States, persons on layoff have weaker job attachment and are classified as unemployed. The annual labor force measures are obtained from monthly, quarterly, or continuous household surveys and may be calculated as averages of monthly or quarterly data. Quarterly and monthly unemployment rates are based on household surveys. For some countries, they are calculated by applying annual adjustment factors to current published data and, therefore, are less precise indicators of unemployment under U.S. concepts than the annual figures. The labor force measures may have breaks in series over time due to changes in surveys, sources, or estimation methods. Breaks are noted in data tables. For up-to-date information on adjustments and breaks in series, see the Technical Notes of Comparative Civilian Labor Force Statistics, 10 Countries, on the Internet at www.bls.gov/fls/flscomparelf.htm, and the Notes of Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted, on the Internet at www.bls.gov/fls/flsjec.pdf. F OR ADDITIONAL INFORMATION on this series, contact the Division of Foreign Labor Statistics: (202) 691–5654 or flshelp@ bls.gov. Manufacturing productivity and labor costs Description of the series Table 53 presents comparative indexes of manufacturing output per hour (labor productivity),output,total hours,compensation per hour, and unit labor costs for the United States, Australia, Canada, Japan, the Republic of Korea, Singapore, Taiwan, and 10 European countries. These measures are trend comparisons—that is, series that measure changes over time—rather than level comparisons. BLS does not recommend using these series for level comparisons because of technical problems. BLS constructs the comparative indexes from three basic aggregate measures—output, total labor hours, and total compensation. The hours and compensation measures refer to employees (wage and salary earners) in Belgium and Taiwan. For all other economies, the measures refer to all employed persons, including employees, self-employed persons, and unpaid family workers. The data for recent years are based on the United Nations System of National Accounts 1993 (SNA 93). Manufacturing is generally defined according to the International Standard Industrial Classification (ISIC). However, the measures for France include parts of mining as well. For the United States and Canada, manufacturing is defined according to the North American Industry Classification System (NAICS 97). Definitions Output. For most economies, the output measures are real value added in manufacturing from national accounts. However, output for Japan prior to 1970 and for the Netherlands prior to 1960 are indexes of industrial production. The manufacturing value added measures for the United Kingdom are essentially identical to their indexes of industrial production. For United States, the output measure for the manufacturing sector is a chain-weighted index of real gross product originating (deflated value added) produced by the Bureau of Economic Analysis of the U.S. Department of Commerce. Most of the other economies now also use chain-weighted as opposed to fixed-year weights that are periodically updated. To preserve the comparability of the U.S. measures with those of other economies, BLS uses gross product originating in manufacturing for the United States. The gross product originating series differs from the manufacturing output series that BLS pub- lishes in its quarterly news releases on U.S. productivity and costs (and that underlies the measures that appear in tables 48 and 50 in this section). The quarterly measures are on a “sectoral output” basis, rather than a valueadded basis. Sectoral output is gross output less intrasector transactions. Total hours refer to hours worked in all economies. The measures are developed from statistics of manufacturing employment and average hours. For most other economies, recent years’ aggregate hours series are obtained from national statistical offices, usually from national accounts. However, for some economies and for earlier years, BLS calculates the aggregate hours series using employment figures published with the national accounts, or other comprehensive employment series, and data on average hours worked. Hourly compensation is total compensation divided by total hours. Total compensation includes all payments in cash or in-kind made directly to employees plus employer expenditures for legally required insurance programs and contractual and private benefit plans. For Australia, Canada, France, Singapore, and Sweden, compensation is increased to account for important taxes on payroll or employment. For the United Kingdom, compensation is reduced between 1967 and 1991 to account for subsidies. Labor productivity is defined as real output per hour worked. Although the labor productivity measure presented in this release relates output to the hours worked of persons employed in manufacturing, it does not measure the specific contributions of labor as a single factor of production. Rather, it reflects the joint effects of many influences, including new technology, capital investment, capacity utilization, energy use, and managerial skills, as well as the skills and efforts of the workforce. Unit labor costs are defined as the cost of labor input required to produce one unit of output. They are computed as compensation in nominal terms divided by real output. Unit labor costs can also be computed by dividing hourly compensation by output per hour, that is, by labor productivity. Notes on the data The measures for recent years may be based on current indicators of manufacturing output (such as industrial production indexes), employment, average hours, and hourly compensation until national accounts and other statistics used for the long-term measures become available. F OR ADDITIONAL INFORMATION on this series, go to http://www.bls.gov/news. release/prod4.toc.htm or contact the Divi- sion of International Labor Comparison at (202) 691–5654. Occupational Injury and Illness Data (Tables 54–55) Survey of Occupational Injuries and Illnesses Description of the series The Survey of Occupational Injuries and Illnesses collects data from employers about their workers’ job-related nonfatal injuries and illnesses. The information that employers provide is based on records that they maintain under the Occupational Safety and Health Act of 1970. Self-employed individuals, farms with fewer than 11 employees, employers regulated by other Federal safety and health laws, and Federal, State, and local government agencies are excluded from the survey. The survey is a Federal-State cooperative program with an independent sample selected for each participating State. A stratified random sample with a Neyman allocation is selected to represent all private industries in the State. The survey is stratified by Standard Industrial Classification and size of employment. Definitions Under the Occupational Safety and Health Act, employers maintain records of nonfatal work-related injuries and illnesses that involve one or more of the following: loss of consciousness, restriction of work or motion, transfer to another job, or medical treatment other than first aid. Occupational injury is any injury such as a cut, fracture, sprain, or amputation that results from a work-related event or a single, instantaneous exposure in the work environment. Occupational illness is an abnormal condition or disorder, other than one resulting from an occupational injury, caused by exposure to factors associated with employment. It includes acute and chronic illnesses or disease which may be caused by inhalation, absorption, ingestion, or direct contact. Lost workday injuries and illnesses are cases that involve days away from work, or days of restricted work activity, or both. Lost workdays include the number of workdays (consecutive or not) on which the employee was either away from work or at work in some restricted capacity, or both, Monthly Labor Review • August 2009 57 Current Labor Statistics because of an occupational injury or illness. BLS measures of the number and incidence rate of lost workdays were discontinued beginning with the 1993 survey. The number of days away from work or days of restricted work activity does not include the day of injury or onset of illness or any days on which the employee would not have worked, such as a Federal holiday, even though able to work. Incidence rates are computed as the number of injuries and/or illnesses or lost work days per 100 full-time workers. Notes on the data The definitions of occupational injuries and illnesses are from Recordkeeping Guidelines for Occupational Injuries and Illnesses (U.S. Department of Labor, Bureau of Labor Statistics, September 1986). Estimates are made for industries and employment size classes for total recordable cases, lost workday cases, days away from work cases, and nonfatal cases without lost workdays. These data also are shown separately for injuries. Illness data are available for seven categories: occupational skin diseases or disorders, dust diseases of the lungs, respiratory conditions due to toxic agents, poisoning (systemic effects of toxic agents), disorders due to physical agents (other than toxic materials), disorders associated with repeated trauma, and all other occupational illnesses. The survey continues to measure the number of new work-related illness cases which are recognized, diagnosed, and reported during the year. Some conditions, for example, long-term latent illnesses caused by exposure to carcinogens, often are difficult to relate to the workplace and are not adequately recognized and reported. These long-term latent illnesses are believed to be understated in the survey’s illness measure. In contrast, the overwhelming majority of the reported new illnesses are those which are easier to directly relate to workplace activity (for example, contact dermatitis and carpal tunnel syndrome). Most of the estimates are in the form of incidence rates, defined as the number of injuries and illnesses per 100 equivalent 58 Monthly Labor Review • August 2009 full-time workers. For this purpose, 200,000 employee hours represent 100 employee years (2,000 hours per employee). Full detail on the available measures is presented in the annual bulletin, Occupational Injuries and Illnesses: Counts, Rates, and Characteristics. Comparable data for more than 40 States and territories are available from the bls Office of Safety, Health and Working Conditions. Many of these States publish data on State and local government employees in addition to private industry data. Mining and railroad data are furnished to BLS by the Mine Safety and Health Administration and the Federal Railroad Administration. Data from these organizations are included in both the national and State data published annually. With the 1992 survey, BLS began publishing details on serious, nonfatal incidents resulting in days away from work. Included are some major characteristics of the injured and ill workers, such as occupation, age, gender, race, and length of service, as well as the circumstances of their injuries and illnesses (nature of the disabling condition, part of body affected, event and exposure, and the source directly producing the condition). In general, these data are available nationwide for detailed industries and for individual States at more aggregated industry levels. FOR ADDITIONAL INFORMATION on occupational injuries and illnesses, contact the Office of Occupational Safety, Health and Working Conditions at (202) 691–6180, or access the Internet at: www.bls. gov/iif/ Census of Fatal Occupational Injuries The Census of Fatal Occupational Injuries compiles a complete roster of fatal job-related injuries, including detailed data about the fatally injured workers and the fatal events. The program collects and cross checks fatality information from multiple sources, including death certificates, State and Federal workers’ compensation reports, Occupational Safety and Health Administration and Mine Safety and Health Administration records, medical examiner and autopsy reports, media accounts, State motor vehicle fatality records, and follow-up questionnaires to employers. In addition to private wage and salary workers, the self-employed, family members, and Federal, State, and local government workers are covered by the program. To be included in the fatality census, the decedent must have been employed (that is working for pay, compensation, or profit) at the time of the event, engaged in a legal work activity, or present at the site of the incident as a requirement of his or her job. Definition A fatal work injury is any intentional or unintentional wound or damage to the body resulting in death from acute exposure to energy, such as heat or electricity, or kinetic energy from a crash, or from the absence of such essentials as heat or oxygen caused by a specific event or incident or series of events within a single workday or shift. Fatalities that occur during a person’s commute to or from work are excluded from the census, as well as work-related illnesses,which can be difficult to identify due to long latency periods. Notes on the data Twenty-eight data elements are collected, coded, and tabulated in the fatality program, including information about the fatally injured worker, the fatal incident, and the machinery or equipment involved. Summary worker demographic data and event characteristics are included in a national news release that is available about 8 months after the end of the reference year. The Census of Fatal Occupational Injuries was initiated in 1992 as a joint Federal-State effort. Most States issue summary information at the time of the national news release. F OR ADDITIONAL INFORMATION on the Census of Fatal Occupational Injuries contact the BLS Office of Safety, Health, and Working Conditions at (202) 691– 6175, or the Internet at: www.bls.gov/iif/ 1. Labor market indicators Selected indicators 2007 2007 2008 II III 2008 IV I II 2009 III IV I II Employment data Employment status of the civilian noninstitutional population (household survey): 1 Labor force participation rate........................................................ Employment-population ratio........................................................ Unemployment rate………………………………………………….… Men………………………………………………..…….….………… 16 to 24 years........................................................................... 25 years and older.................................................................... Women……………………………………………….….…………… 16 to 24 years........................................................................... 25 years and older.................................................................... Employment, nonfarm (payroll data), in thousands: 66.0 63.0 4.6 4.7 11.6 3.6 4.5 9.4 3.6 66.0 62.2 5.8 6.1 14.4 4.8 5.4 11.2 4.4 66.0 63.0 4.5 4.6 11.5 3.5 4.4 9.0 3.6 65.9 62.9 4.7 4.8 11.8 3.6 4.6 9.7 3.7 66.0 62.8 4.8 4.9 12.1 3.7 4.7 9.9 3.8 66.0 62.8 4.9 5.1 12.7 3.9 4.8 10.1 3.9 66.1 62.5 5.4 5.6 13.5 4.2 5.1 11.1 4.1 66.1 62.1 6.0 6.5 14.9 5.1 5.6 11.9 4.5 65.9 61.3 6.9 7.5 16.5 6.0 6.1 11.6 5.2 65.6 60.3 8.1 8.8 18.0 7.4 7.2 12.9 6.2 65.8 59.7 9.2 10.4 20.0 8.8 8.0 14.4 6.9 1 Total nonfarm…………………….................................................... 137,598 Total private....................................................................... 115,380 137,066 114,566 137,645 115,400 137,652 115,389 138,152 115,783 137,814 115,373 137,356 114,834 136,732 114,197 135,074 112,542 133,000 110,457 131,692 109,138 22,233 Manufacturing………….………………..………………………… 13,879 21,419 13,431 22,289 13,889 22,099 13,796 22,043 13,777 21,800 13,643 21,507 13,505 21,247 13,322 20,532 12,902 19,520 12,296 18,815 11,854 Service-providing ……………………………………………….………….. 115,366 115,646 115,356 115,553 116,109 116,014 115,849 115,485 114,542 113,480 112,877 Goods-producing ……………………………………………….………….. Average hours: Total private........................................………….......................... Manufacturing………...…………………………………………… Overtime……..………….………………...……………………… 33.9 41.2 4.2 33.6 40.8 3.7 33.9 41.3 4.3 33.8 41.3 4.1 33.8 41.2 4.1 33.8 41.2 4.0 33.6 40.9 3.8 33.6 40.5 3.5 33.3 39.9 2.9 33.1 39.4 2.6 33.0 39.5 2.8 Civilian nonfarm ……………………………….…………………………….…… 3.3 2.6 .8 1.0 .6 .8 .7 .8 .3 .4 .4 Private nonfarm……………...............………............................... 3.0 2.4 .9 .8 .6 .9 .7 .6 .2 .4 .3 2.4 2.4 1.0 .5 .6 1.0 .7 .4 .3 .4 .3 3.2 2.5 .9 .9 .6 .9 .7 .6 .3 .4 .3 4.1 3.0 .6 1.8 .7 .5 .5 1.7 .3 .6 .5 2.0 3.2 2.8 2.4 1.2 .9 .5 .8 .7 .6 .8 .9 .8 .7 .7 .6 .6 .2 1.0 .3 .6 .2 1, 2, 3 Employment Cost Index Total compensation: 4 5 Goods-producing ……………………………………………….………… 5 Service-providing ……………………………………………….………… State and local government ……………….……………………… Workers by bargaining status (private nonfarm): Union…………………………………………………………………… Nonunion………………………………………………………………… 1 Quarterly data seasonally adjusted. 2 Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter. 3 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 4 Excludes Federal and private household workers. 5 Goods-producing industries include mining, construction, and manufacturing. Serviceproviding industries include all other private sector industries. NOTE: Beginning in January 2003, household survey data reflect revised population controls. Nonfarm data reflect the conversion to the 2002 version of the North American Industry Classification System (NAICS), replacing the Standard Industrial Classification (SIC) system. NAICS-based data by industry are not comparable with SIC based data. Monthly Labor Review • August 2009 59 Current Labor Statistics: Comparative Indicators 2. Annual and quarterly percent changes in compensation, prices, and productivity Selected measures 2007 2007 2008 II 2008 III IV I II 2009 III IV I II 1, 2, 3 Compensation data Employment Cost Index—compensation: Civilian nonfarm................................................................... Private nonfarm............................................................... Employment Cost Index—wages and salaries: Civilian nonfarm………………………………………………. Private nonfarm............................................................... Price data 3.3 3.0 2.6 2.4 0.8 .9 1.0 .8 0.6 .6 0.8 .9 0.7 .7 0.8 .6 0.3 .2 0.4 .4 0.4 .3 3.4 3.3 2.7 2.6 .7 .8 1.0 .9 .7 .6 .8 .9 .7 .7 .8 .6 .3 .3 .4 .4 .4 .3 2.8 3.8 1.5 .1 .7 1.7 2.5 0 -3.9 1.2 1.4 3.9 4.5 1.8 4.1 12.1 6.3 7.4 2.8 10.5 21.5 1.9 2.5 -.1 3.2 3.8 .1 .2 -.1 .1 -2.4 1.8 1.9 1.2 2.0 11.9 2.8 3.4 .7 5.0 14.5 4.2 5.2 .6 6.9 14.9 -.1 -.4 1.0 .7 -15.6 -7.4 -10.0 1.9 -13.6 -32.1 .1 .1 -.1 -2.0 -7.4 3.1 4.3 .0 2.7 13.1 1.8 1.8 1.9 1.8 3.5 2.8 5.5 5.5 1.6 2.0 .2 -.1 3.1 3.1 .3 -.1 .8 .8 .2 .3 6.3 6.4 1.0 1.9 2.8 -1.1 5.3 -2.7 6.9 3.2 -1.4 -6.0 - 1 Consumer Price Index (All Urban Consumers): All Items...... Producer Price Index: Finished goods..................................................................... Finished consumer goods................................................. Capital equipment…………………………………………… Intermediate materials, supplies, and components………… Crude materials..................................................................... 4 Productivity data Output per hour of all persons: Business sector..................................................................... Nonfarm business sector....................................................... 5 Nonfinancial corporations ……………….…………...……………… 1 Annual changes are December-to-December changes. Quarterly changes are calculated using the last month of each quarter. Compensation and price data are not seasonally adjusted, and the price data are not compounded. 2 Excludes Federal and private household workers. 3 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 4 Annual rates of change are computed by comparing annual averages. Quarterly percent changes reflect annual rates of change in quarterly indexes. The data are seasonally adjusted. 5 Output per hour of all employees. 3. Alternative measures of wage and compensation changes Quarterly change Components 2008 II Four quarters ending— 2009 III IV I 2008 II II III 2009 IV I II 1 Average hourly compensation: All persons, business sector.......................................................... All persons, nonfarm business sector........................................... Employment Cost Index—compensation: 4.5 4.5 2.6 2.9 -2.5 -2.4 0.1 .2 2.6 2.7 2.9 3.1 2.5 2.6 1.5 1.5 1.1 1.3 .7 .7 .8 .7 .5 .8 .6 .7 .6 1.7 .3 .2 .6 .2 .3 .4 .4 1.0 .3 .6 .4 .3 .6 .2 .5 3.1 3.0 2.7 3.0 3.5 2.9 2.8 2.9 2.8 3.4 2.6 2.4 2.8 2.4 3.0 2.1 1.9 3.0 1.8 3.1 1.8 1.5 2.9 1.2 3.2 .7 .7 1.1 .7 .5 .8 .6 .7 .6 1.8 .3 .3 .7 .2 .3 .4 .4 .6 .4 .5 .4 .3 .7 .2 .5 3.2 3.1 2.9 3.2 3.4 3.1 2.9 2.9 3.0 3.5 2.7 2.6 3.2 2.5 3.1 2.2 2.0 3.1 1.9 3.0 1.8 1.6 2.7 1.4 3.0 2 3 Civilian nonfarm ……….………………………………………….…………..… Private nonfarm…....................................................................... Union………….......................................................................... Nonunion………….................................................................... State and local government…..................................................... Employment Cost Index—wages and salaries: 3 1.6 1.3 2 Civilian nonfarm ……….………………………………………….…………..… Private nonfarm…....................................................................... Union………….......................................................................... Nonunion………….................................................................... State and local government…..................................................... 1 Seasonally adjusted. "Quarterly average" is percent change from a quarter ago, at an annual rate. 2 The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard 60 Monthly Labor Review • August 2009 Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 3 Excludes Federal and private household workers. 4. Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] Employment status 2009 Annual average 2007 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June TOTAL Civilian noninstitutional 1 population ……………………. 231,867 Civilian labor force.............. 153,124 66.0 Participation rate........... Employed........................ 146,047 Employment-pop63.0 ulation ratio 2…………… 7,078 Unemployed................... 4.6 Unemployment rate..... Not in the labor force........ 78,743 233,788 233,627 233,864 234,107 234,360 234,612 234,828 235,035 234,739 234,913 235,086 235,271 235,452 235,655 154,287 154,400 154,506 154,823 154,621 154,878 154,620 154,447 153,716 154,214 154,048 154,731 155,081 154,926 66.0 66.1 66.1 66.1 66.0 66.0 65.8 65.7 65.5 65.6 65.5 65.8 65.9 65.7 145,362 145,738 145,596 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887 141,007 140,570 140,196 62.2 8,924 5.8 79,501 62.4 8,662 5.6 79,227 62.3 8,910 5.8 79,358 62.1 9,550 6.2 79,284 61.9 9,592 6.2 79,739 61.7 10,221 6.6 79,734 61.4 10,476 6.8 80,208 61.0 11,108 7.2 80,588 60.5 11,616 7.6 81,023 60.3 12,467 8.1 80,699 59.9 13,161 8.5 81,038 59.9 13,724 8.9 80,541 59.7 14,511 9.4 80,371 59.5 14,729 9.5 80,729 Men, 20 years and over Civilian noninstitutional 1 population ……………………. 103,555 Civilian labor force.............. 78,596 75.9 Participation rate........... Employed........................ 75,337 Employment-pop72.8 ulation ratio 2…………… 3,259 Unemployed................... 4.1 Unemployment rate..... Not in the labor force……… 24,959 104,453 104,371 104,490 104,613 104,741 104,869 104,978 105,083 104,902 104,999 105,095 105,196 105,299 105,412 79,047 79,055 79,286 79,308 79,392 79,380 79,335 78,998 78,585 78,687 78,578 79,081 79,395 79,291 75.7 75.7 75.9 75.8 75.8 75.7 75.6 75.2 74.9 74.9 74.8 75.2 75.4 75.2 74,750 74,949 74,973 74,737 74,503 74,292 74,045 73,285 72,613 72,293 71,655 71,678 71,593 71,387 71.6 4,297 5.4 25,406 71.8 4,106 5.2 25,315 71.8 4,313 5.4 25,204 71.4 4,572 5.8 25,305 71.1 4,889 6.2 25,349 70.8 5,088 6.4 25,489 70.5 5,290 6.7 25,643 69.7 5,714 7.2 26,085 69.2 5,972 7.6 26,318 68.9 6,394 8.1 26,312 68.2 6,923 8.8 26,516 68.1 7,403 9.4 26,115 68.0 7,802 9.8 25,904 67.7 7,904 10.0 26,121 Women, 20 years and over Civilian noninstitutional 1 population ……………………. 111,330 Civilian labor force.............. 67,516 60.6 Participation rate........... Employed........................ 64,799 Employment-pop58.2 ulation ratio 2…………… 2,718 Unemployed................... 4.0 Unemployment rate..... Not in the labor force……… 43,814 112,260 112,183 112,290 112,401 112,518 112,633 112,731 112,825 112,738 112,824 112,908 112,999 113,089 113,189 68,382 68,421 68,273 68,666 68,385 68,700 68,753 68,891 68,584 68,917 68,977 69,148 69,112 69,060 60.9 61.0 60.8 61.1 60.8 61.0 61.0 61.1 60.8 61.1 61.1 61.2 61.1 61.0 65,039 65,169 65,103 65,003 65,008 64,975 64,902 64,860 64,298 64,271 64,148 64,226 63,895 63,810 57.9 3,342 4.9 43,878 58.1 3,252 4.8 43,762 58.0 3,170 4.6 44,017 57.8 3,662 5.3 43,736 57.8 3,377 4.9 44,133 57.7 3,725 5.4 43,933 57.6 3,851 5.6 43,978 57.5 4,031 5.9 43,935 57.0 4,286 6.2 44,154 57.0 4,646 6.7 43,907 56.8 4,828 7.0 43,931 56.8 4,922 7.1 43,850 56.5 5,217 7.5 43,976 56.4 5,249 7.6 44,130 17,075 6,858 40.2 5,573 17,073 6,924 40.6 5,620 17,084 6,947 40.7 5,520 17,092 6,849 40.1 5,533 17,101 6,844 40.0 5,518 17,110 6,799 39.7 5,390 17,118 6,531 38.2 5,196 17,126 6,557 38.3 5,194 17,098 6,547 38.3 5,188 17,090 6,610 38.7 5,184 17,083 6,493 38.0 5,083 17,076 6,501 38.1 5,103 17,064 6,573 38.5 5,082 17,053 6,575 38.6 4,999 32.6 1,285 18.7 10,218 32.9 1,304 18.8 10,149 32.3 1,427 20.5 10,137 32.4 1,316 19.2 10,243 32.3 1,326 19.4 10,257 31.5 1,408 20.7 10,311 30.4 1,335 20.4 10,587 30.3 1,363 20.8 10,568 30.3 1,359 20.8 10,551 30.3 1,427 21.6 10,480 29.8 1,410 21.7 10,590 29.9 1,398 21.5 10,575 29.8 1,491 22.7 10,491 29.3 1,576 24.0 10,478 Both sexes, 16 to 19 years Civilian noninstitutional 1 population ……………………. 16,982 7,012 Civilian labor force.............. 41.3 Participation rate........... 5,911 Employed........................ Employment-pop34.8 ulation ratio 2…………… 1,101 Unemployed................... 15.7 Unemployment rate..... Not in the labor force……… 9,970 White3 Civilian noninstitutional 1 population ……………………. 188,253 Civilian labor force.............. 124,935 66.4 Participation rate........... Employed........................ 119,792 Employment-pop63.6 ulation ratio 2…………… 5,143 Unemployed................... 4.1 Unemployment rate..... Not in the labor force……… 63,319 189,540 189,428 189,587 189,747 189,916 190,085 190,221 190,351 190,225 190,331 190,436 190,552 190,667 190,801 125,635 125,712 125,979 125,987 125,844 126,298 126,029 125,634 125,312 125,703 125,599 126,110 126,423 126,199 66.3 66.4 66.4 66.4 66.3 66.4 66.3 66.0 65.9 66.0 66.0 66.2 66.3 66.1 119,126 119,417 119,432 119,082 118,964 118,722 118,226 117,357 116,692 116,481 115,693 115,977 115,561 115,202 62.8 6,509 5.2 63,905 63.0 6,295 5.0 63,716 63.0 6,547 5.2 63,608 62.8 6,904 5.5 63,761 62.6 6,880 5.5 64,072 62.5 7,577 6.0 63,787 62.2 7,803 6.2 64,193 61.7 8,277 6.6 64,718 61.3 8,621 6.9 64,913 61.2 9,222 7.3 64,628 60.8 9,906 7.9 64,837 60.9 10,133 8.0 64,441 60.6 10,862 8.6 64,244 60.4 10,997 8.7 64,601 27,843 17,740 63.7 15,953 27,816 17,708 63.7 16,041 27,854 17,744 63.7 15,989 27,896 17,949 64.3 16,026 27,939 17,733 63.5 15,709 27,982 17,768 63.5 15,762 28,021 17,708 63.2 15,703 28,059 17,796 63.4 15,674 28,052 17,791 63.4 15,546 28,085 17,703 63.0 15,336 28,118 17,542 62.4 15,212 28,153 17,816 63.3 15,142 28,184 17,737 62.9 15,095 28,217 17,700 62.7 15,103 57.3 1,788 10.1 10,103 57.7 1,667 9.4 10,109 57.4 1,755 9.9 10,111 57.4 1,923 10.7 9,947 56.2 2,024 11.4 10,206 56.3 2,006 11.3 10,214 56.0 2,005 11.3 10,313 55.9 2,122 11.9 10,263 55.4 2,245 12.6 10,261 54.6 2,368 13.4 10,382 54.1 2,330 13.3 10,576 53.8 2,673 15.0 10,337 53.6 2,642 14.9 10,446 53.5 2,597 14.7 10,517 Black or African American3 Civilian noninstitutional 1 population ……………………. 27,485 Civilian labor force.............. 17,496 63.7 Participation rate........... Employed........................ 16,051 Employment-pop58.4 ulation ratio 2…………… 1,445 Unemployed................... 8.3 Unemployment rate..... Not in the labor force……… 9,989 See footnotes at end of table. Monthly Labor Review • August 2009 61 Current Labor Statistics: Labor Force Data 4. Continued—Employment status of the population, by sex, age, race, and Hispanic origin, monthly data seasonally adjusted [Numbers in thousands] Employment status 2008 Annual average 2007 2008 June July Aug. 32,141 22,024 68.5 20,346 32,087 22,100 68.9 20,391 32,179 22,062 68.6 20,396 32,273 22,201 68.8 20,404 63.3 1,678 7.6 10,116 63.5 1,709 7.7 9,987 63.4 1,665 7.5 10,117 63.2 1,797 8.1 10,072 2009 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June 32,369 22,259 68.8 20,506 32,465 22,187 68.3 20,232 32,558 22,074 67.8 20,168 32,649 22,134 67.8 20,096 32,417 21,931 67.7 19,800 32,501 22,100 68.0 19,684 32,585 22,175 68.1 19,640 32,671 22,376 68.5 19,854 32,753 22,438 68.5 19,595 32,839 22,347 68.1 19,623 63.4 1,752 7.9 10,111 62.3 1,955 8.8 10,278 61.9 1,906 8.6 10,484 61.6 2,038 9.2 10,515 61.1 2,132 9.7 10,486 60.6 2,416 10.9 10,401 60.3 2,536 11.4 10,410 60.8 2,521 11.3 10,295 59.8 2,843 12.7 10,315 59.8 2,724 12.2 10,491 Hispanic or Latino ethnicity Civilian noninstitutional 1 population ……………………. 31,383 Civilian labor force.............. 21,602 68.8 Participation rate........... Employed........................ 20,382 Employment-pop64.9 ulation ratio 2…………… 1,220 Unemployed................... 5.6 Unemployment rate..... Not in the labor force ………… 9,781 1 The population figures are not seasonally adjusted. Civilian employment as a percent of the civilian noninstitutional population. Beginning in 2003, persons who selected this race group only; persons who selected more than one race group are not included. Prior to 2003, persons who reported more than one race were included in the group they identified as the main race. NOTE: Estimates for the above race groups (white and black or African American) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2003, data reflect revised population controls used in the household survey. 2 3 5. Selected employment indicators, monthly data seasonally adjusted [In thousands] Selected categories Annual average 2007 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Characteristic Employed, 16 years and older.. 146,047 145,362 145,738 145,596 145,273 145,029 144,657 144,144 143,338 142,099 141,748 140,887 141,007 140,570 140,196 Men....................................... 78,254 77,486 77,726 77,683 77,484 77,249 76,938 76,577 75,847 75,092 74,777 74,053 74,116 74,033 73,777 Women............................…… 67,792 67,876 68,012 67,913 67,789 67,780 67,720 67,567 67,491 67,007 66,970 66,834 66,890 66,537 66,419 Married men, spouse 46,314 45,860 45,902 46,093 45,804 45,887 45,787 45,610 45,182 44,712 44,502 44,470 44,469 44,255 44,294 35,832 35,869 36,189 36,110 35,994 35,864 35,590 35,649 35,632 35,375 35,563 35,481 35,444 35,391 35,464 4,401 5,875 5,495 5,813 5,879 6,292 6,848 7,323 8,038 7,839 8,626 9,049 8,910 9,084 8,989 2,877 4,169 3,905 4,220 4,240 4,418 4,953 5,399 6,020 5,766 6,443 6,857 6,699 6,794 6,783 1,210 1,389 1,359 1,300 1,412 1,514 1,514 1,585 1,617 1,667 1,764 1,839 1,810 1,922 1,980 reasons……………………… 19,756 19,343 19,428 19,348 19,690 19,275 19,083 18,886 18,922 18,864 18,855 18,833 19,065 18,872 18,718 4,317 5,773 5,390 5,693 5,802 6,167 6,742 7,209 7,932 7,705 8,543 8,942 8,826 8,928 8,845 2,827 4,097 3,839 4,160 4,171 4,279 4,889 5,304 5,938 5,660 6,390 6,773 6,650 6,681 6,699 1,199 1,380 1,340 1,287 1,385 1,541 1,499 1,579 1,619 1,658 1,760 1,850 1,802 1,909 1,969 reasons.................………… 19,419 19,005 19,036 18,992 19,269 18,930 18,808 18,635 18,642 18,567 18,562 18,493 18,661 18,502 18,358 present................................ Married women, spouse present................................ Persons at work part time1 All industries: Part time for economic reasons…………………….… Slack work or business conditions…………......... Could only find part-time work……………………… Part time for noneconomic Nonagricultural industries: Part time for economic reasons…………………….… Slack work or business conditions........................ Could only find part-time work……………………… Part time for noneconomic 1 Excludes persons "with a job but not at work" during the survey period for such reasons as vacation, illness, or industrial disputes. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. 62 Monthly Labor Review • August 2009 6. Selected unemployment indicators, monthly data seasonally adjusted [Unemployment rates] Annual average Selected categories 2007 2008 2008 2009 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Characteristic Total, 16 years and older............................ Both sexes, 16 to 19 years..................... Men, 20 years and older......................... Women, 20 years and older................... 4.6 15.7 4.1 4.0 5.8 18.7 5.4 4.9 5.6 18.8 5.2 4.8 5.8 20.5 5.4 4.6 6.2 19.2 5.8 5.3 6.2 19.4 6.2 4.9 6.6 20.7 6.4 5.4 6.8 20.4 6.7 5.6 7.2 20.8 7.2 5.9 7.6 20.8 7.6 6.2 8.1 21.6 8.1 6.7 8.5 21.7 8.8 7.0 8.9 21.5 9.4 7.1 9.4 22.7 9.8 7.5 9.5 24.0 10.0 7.6 White, total 1……………………………… 4.1 13.9 15.7 12.1 3.7 3.6 5.2 16.8 19.1 14.4 4.9 4.4 5.0 17.0 18.7 15.3 4.6 4.2 5.2 19.1 22.4 15.6 4.8 4.2 5.5 17.3 19.5 15.0 5.1 4.7 5.5 17.5 19.7 15.2 5.5 4.2 6.0 18.6 22.6 14.4 5.8 4.9 6.2 18.4 21.4 15.3 6.1 5.1 6.6 18.7 21.4 16.0 6.5 5.5 6.9 18.4 21.8 14.8 6.8 5.8 7.3 19.1 22.2 16.0 7.4 6.1 7.9 20.0 23.3 16.7 8.0 6.5 8.0 19.7 22.5 16.9 8.5 6.4 8.6 20.3 24.4 16.0 9.0 6.9 8.7 21.4 23.9 18.9 9.2 6.8 8.3 29.4 33.8 25.3 7.9 6.7 10.1 31.2 35.9 26.8 10.2 8.1 9.4 29.8 35.4 24.4 9.7 7.5 9.9 32.0 37.7 26.8 10.3 7.5 10.7 29.3 29.8 28.9 10.6 9.1 11.4 29.8 32.9 26.7 11.9 9.3 11.3 32.9 37.2 27.8 11.8 8.9 11.3 32.2 42.0 23.2 12.1 9.0 11.9 33.7 35.2 32.2 13.4 8.9 12.6 36.5 44.0 29.8 14.1 9.2 13.4 38.8 45.6 32.1 14.9 9.9 13.3 32.5 41.2 25.2 15.4 9.9 15.0 34.7 42.1 27.2 17.2 11.5 14.9 39.4 46.1 34.0 16.8 11.2 14.7 37.9 44.4 32.4 16.4 11.3 5.6 2.5 2.8 4.6 4.9 7.6 3.4 3.6 5.8 5.5 7.7 3.1 3.4 5.6 5.4 7.5 3.3 3.4 5.8 5.6 8.1 3.7 3.7 6.3 5.7 7.9 3.9 3.5 6.3 5.9 8.8 4.1 4.2 6.8 5.7 8.6 4.2 4.3 7.0 5.8 9.2 4.4 4.5 7.5 5.9 9.7 5.0 4.7 8.0 5.9 10.9 5.5 5.1 8.6 5.8 11.4 5.8 5.4 9.2 5.9 11.3 6.3 5.5 9.6 6.1 12.7 6.8 5.7 10.2 6.0 12.2 6.9 5.6 10.3 5.9 Both sexes, 16 to 19 years................ Men, 16 to 19 years........................ Women, 16 to 19 years.................. Men, 20 years and older.................... Women, 20 years and older.............. Black or African American, total 1……… Both sexes, 16 to 19 years................ Men, 16 to 19 years........................ Women, 16 to 19 years.................. Men, 20 years and older.................... Women, 20 years and older.............. Hispanic or Latino ethnicity……………… Married men, spouse present................ Married women, spouse present........... Full-time workers................................... Part-time workers.................................. Educational attainment2 Less than a high school diploma................ High school graduates, no college 3……… Some college or associate degree……….. 4 Bachelor's degree and higher ……………. 1 7.1 9.0 8.9 8.6 9.7 9.8 10.4 10.6 10.9 12.0 12.6 13.3 14.8 15.5 15.5 4.4 3.6 5.7 4.6 5.2 4.4 5.3 4.6 5.8 5.0 6.3 5.1 6.5 5.3 6.9 5.5 7.7 5.6 8.0 6.2 8.3 7.0 9.0 7.2 9.3 7.4 10.0 7.7 9.8 8.0 2.0 2.6 2.4 2.5 2.7 2.6 3.1 3.2 3.7 3.8 4.1 4.3 4.4 4.8 4.7 Feb. Mar. May June Beginning in 2003, persons who selected this race group only; persons who selected more than one race group are not included. Prior to 2003, persons who reported more than one race were included in the group they identified as the main race. 2 Data refer to persons 25 years and older. 7. Duration of unemployment, monthly data seasonally adjusted [Numbers in thousands] Weeks of unemployment Less than 5 weeks........................... 5 to 14 weeks.................................. 15 weeks and over.......................... 15 to 26 weeks............................. 27 weeks and over....................... Mean duration, in weeks................... Median duration, in weeks............... Annual average 2007 2,542 2,232 2,303 1,061 1,243 16.8 8.5 2008 2,932 2,804 3,188 1,427 1,761 17.9 9.4 2008 June 2,733 3,012 2,966 1,345 1,621 17.6 10.1 July 2,884 2,853 3,168 1,450 1,718 17.3 9.8 Aug. 3,242 2,874 3,447 1,568 1,878 17.6 9.3 Sept. 2,864 3,083 3,662 1,621 2,041 18.7 10.3 2009 Oct. 3,108 3,055 4,109 1,834 2,275 19.8 10.6 Nov. 3,255 3,141 3,964 1,757 2,207 18.9 10.0 Dec. 3,267 3,398 4,517 1,927 2,591 19.7 10.6 Jan. 3,658 3,519 4,634 1,987 2,647 19.8 10.3 3,404 3,969 5,264 2,347 2,917 19.8 11.0 3,371 4,041 5,715 2,534 3,182 20.1 11.2 Apr. 3,346 3,982 6,211 2,531 3,680 21.4 12.5 3,275 4,321 7,002 3,054 3,948 22.5 14.9 3,204 4,066 7,833 3,452 4,381 24.5 17.9 NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. Monthly Labor Review • August 2009 63 Current Labor Statistics: Labor Force Data 8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted [Numbers in thousands] Annual average Reason for unemployment 2007 1 Job losers …………………….… On temporary layoff.............. Not on temporary layoff........ Job leavers.............................. Reentrants............................... New entrants........................... 2008 2008 June July Aug. 2009 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June 3,515 976 2,539 793 2,142 627 4,789 1,176 3,614 896 2,472 766 4,465 1,106 3,358 847 2,562 761 4,595 1,041 3,554 875 2,668 818 4,994 1,279 3,715 999 2,678 829 5,348 1,396 3,952 982 2,587 822 5,811 1,367 4,443 946 2,650 825 6,156 1,413 4,744 940 2,655 760 6,471 1,524 4,946 1,007 2,777 829 6,980 1,441 5,539 917 2,751 780 7,696 1,488 6,208 820 2,834 1,005 8,243 1,557 6,686 887 2,974 868 8,814 1,625 7,189 890 3,087 900 9,546 1,832 7,714 910 3,180 956 9,649 1,762 7,886 822 3,335 947 49.7 13.8 35.9 11.2 30.3 8.9 53.7 13.2 40.5 10.0 27.7 8.6 51.7 12.8 38.9 9.8 29.7 8.8 51.3 11.6 39.7 9.8 29.8 9.1 52.6 13.5 39.1 10.5 28.2 8.7 54.9 14.3 40.6 10.1 26.6 8.4 56.8 13.4 43.4 9.2 25.9 8.1 58.6 13.4 45.1 8.9 25.3 7.2 58.4 13.8 44.6 9.1 25.1 7.5 61.1 12.6 48.5 8.0 24.1 6.8 62.3 12.0 50.2 6.6 22.9 8.1 63.5 12.0 51.5 6.8 22.9 6.7 64.4 11.9 52.5 6.5 22.5 6.6 65.4 12.6 52.9 6.2 21.8 6.6 65.4 11.9 53.5 5.6 22.6 6.4 2.9 .5 1.7 .5 3.0 .6 1.7 .5 3.2 .6 1.7 .5 3.5 .6 1.7 .5 3.8 .6 1.7 .5 4.0 .6 1.7 .5 4.2 .7 1.8 .5 4.5 .6 1.8 .5 5.0 .5 1.8 .7 5.4 .6 1.9 .6 5.7 .6 2.0 .6 6.2 .6 2.1 .6 6.2 .5 2.2 .6 Jan. Feb. Mar. Apr. May June Percent of unemployed Job losers 1…………………….… On temporary layoff............... Not on temporary layoff......... Job leavers............................... Reentrants................................ New entrants............................ Percent of civilian labor force 2.3 3.1 Job losers 1…………………….… .5 .6 Job leavers............................... 1.4 1.6 Reentrants................................ .4 .5 New entrants............................ 1 Includes persons who completed temporary jobs. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. 9. Unemployment rates by sex and age, monthly data seasonally adjusted [Civilian workers] Sex and age Annual average 2008 2007 2008 June Total, 16 years and older.................. 16 to 24 years............................... 16 to 19 years............................ 16 to 17 years......................... 18 to 19 years......................... 20 to 24 years............................ 25 years and older........................ 25 to 54 years......................... 55 years and older.................. 4.6 10.5 15.7 17.5 14.5 8.2 3.6 3.7 3.1 5.8 12.8 18.7 22.1 16.8 10.2 4.6 4.8 3.8 5.6 12.9 18.8 23.2 15.9 10.2 4.4 4.6 3.4 Men, 16 years and older................. 16 to 24 years............................. 16 to 19 years.......................... 16 to 17 years....................... 18 to 19 years....................... 20 to 24 years.......................... 25 years and older...................... 25 to 54 years....................... 55 years and older................ 4.7 11.6 17.6 19.4 16.5 8.9 3.6 3.7 3.2 6.1 14.4 21.2 25.2 19.0 11.4 4.8 5.0 3.9 Women, 16 years and older........... 16 to 24 years............................. 16 to 19 years.......................... 16 to 17 years………………… 18 t0 19 years………………… 20 to 24 years.......................... 25 years and older...................... 25 to 54 years....................... 55 years and older 1………… 4.5 9.4 13.8 15.7 12.5 7.3 3.6 3.8 3.0 1 July Aug. Sept. 5.8 13.5 20.5 24.9 17.6 10.4 4.5 4.7 3.7 6.2 13.3 19.2 22.2 17.4 10.7 5.0 5.2 4.1 6.2 13.4 19.4 21.7 17.8 10.8 5.0 5.3 4.2 5.9 14.1 20.8 26.1 17.5 11.2 4.5 4.7 3.5 6.2 15.3 23.5 29.3 20.1 11.7 4.8 5.0 3.8 6.4 14.6 21.1 24.5 19.0 11.7 5.1 5.3 4.3 5.4 11.2 16.2 19.1 14.3 8.8 4.4 4.6 5.3 11.5 16.8 20.4 14.1 8.9 4.2 4.5 5.3 11.6 17.4 20.5 14.9 8.9 4.2 4.4 3.7 3.4 4.3 2009 Oct. Nov. Dec. 6.6 13.8 20.7 23.1 18.4 10.6 5.3 5.5 4.6 6.8 13.9 20.4 24.1 18.3 11.1 5.6 5.8 4.8 7.2 14.7 20.8 24.1 19.1 12.1 6.0 6.3 4.9 7.6 14.8 20.8 21.4 20.2 12.1 6.4 6.7 5.2 8.1 15.5 21.6 22.9 21.0 12.9 6.9 7.2 5.6 8.5 16.3 21.7 23.7 20.9 14.0 7.2 7.6 6.2 8.9 16.7 21.5 23.0 21.3 14.7 7.5 7.8 6.4 9.4 17.3 22.7 23.4 22.9 15.0 8.1 8.4 6.7 9.5 17.8 24.0 25.1 23.7 15.2 8.2 8.5 7.0 6.8 14.8 21.4 23.2 20.4 11.9 5.5 5.8 4.5 7.2 16.5 24.7 27.3 21.7 12.9 5.6 5.8 4.7 7.4 16.1 24.0 28.8 21.2 12.9 5.9 6.1 5.1 7.9 16.9 23.3 27.0 21.5 14.2 6.4 6.7 5.1 8.3 17.1 24.4 26.5 22.8 14.1 6.9 7.3 5.3 8.8 17.6 24.9 26.5 24.7 14.6 7.5 7.9 6.0 9.5 19.3 25.7 28.2 24.6 16.7 7.9 8.3 6.3 10.0 19.8 25.6 26.3 25.3 17.5 8.3 8.8 6.7 10.5 20.2 26.7 26.1 27.8 17.5 9.0 9.5 7.0 10.6 19.8 26.2 25.8 26.9 17.2 9.2 9.5 7.7 5.9 12.0 17.3 20.1 15.6 9.5 4.9 5.1 5.5 11.9 17.3 20.3 14.9 9.4 4.4 4.6 5.9 10.7 16.5 19.2 14.7 8.1 5.1 5.2 6.1 11.5 16.7 19.7 15.1 9.2 5.2 5.4 6.4 12.4 18.2 21.2 16.6 9.8 5.4 5.7 6.7 12.2 17.1 16.2 17.5 10.0 5.8 6.0 7.3 13.3 18.3 19.8 17.0 10.9 6.2 6.4 7.5 13.1 17.8 19.4 17.2 11.0 6.5 6.7 7.6 13.3 17.4 19.9 17.1 11.5 6.6 6.7 8.0 14.2 18.6 20.7 17.5 12.2 7.0 7.2 8.3 15.7 21.8 24.4 20.4 12.8 7.0 7.2 4.5 3.9 4.3 4.3 4.3 5.4 5.3 5.8 5.4 5.8 6.4 Data are not seasonally adjusted. NOTE: Beginning in January 2003, data reflect revised population controls used in the household survey. 64 Monthly Labor Review • August 2009 10. Unemployment rates by State, seasonally adjusted May 2008 State Apr. 2009p May 2009p Apr. May 2008 State 2009p May 2009p Alabama............................………………… Alaska........................................................ Arizona............................…………………… Arkansas.................................................... California............................………………… 4.7 6.6 5.2 4.9 6.8 9.0 7.9 7.7 6.5 11.1 9.8 8.3 8.2 7.0 11.6 Missouri……………………………………… Montana..................................................... Nebraska............................………………… Nevada...................................................... New Hampshire............................………… 5.8 4.3 3.2 6.1 3.7 8.1 6.0 4.5 10.6 6.3 9.0 6.3 4.8 11.2 6.5 Colorado.................................................... Connecticut............................……………… Delaware................................................... District of Columbia............................…… Florida........................................................ 4.7 5.4 4.4 6.6 5.8 7.4 7.9 7.4 9.9 9.7 7.6 8.0 8.1 10.7 10.3 New Jersey................................................ New Mexico............................……………… New York................................................... North Carolina............................…………… North Dakota............................................. 5.1 4.0 5.2 5.9 3.1 8.4 5.8 7.7 10.7 4.1 8.8 6.5 8.2 11.1 4.3 Georgia............................………………… Hawaii........................................................ Idaho............................……………………… Illinois......................................................... Indiana............................…………………… 5.9 3.6 4.5 6.4 5.3 9.2 6.9 7.0 9.4 9.9 9.6 7.4 7.8 10.1 10.6 Ohio............................……………………… Oklahoma.................................................. Oregon............................…………………… Pennsylvania............................................. Rhode Island............................…………… 6.3 3.6 5.7 5.1 7.4 10.2 6.2 11.8 7.8 11.1 10.8 6.4 12.2 8.3 12.1 Iowa............................……………………… Kansas....................................................... Kentucky............................………………… Louisiana................................................... Maine............................…………………… 4.0 4.3 6.2 4.1 5.1 5.1 6.5 9.9 6.2 7.9 5.7 7.0 10.7 6.6 8.3 South Carolina............................………… South Dakota............................................. Tennessee............................……………… Texas......................................................... Utah............................……………………… 6.3 2.9 6.2 4.7 3.3 11.4 4.8 9.9 6.6 5.2 12.0 5.0 10.7 7.1 5.4 Maryland............................………………… Massachusetts........................................... Michigan............................………………… Minnesota.................................................. Mississippi............................……………… 4.1 4.9 8.2 5.3 6.8 6.8 8.0 12.9 8.0 9.1 7.2 8.2 14.1 8.1 9.7 Vermont............................………………… Virginia....................................................... Washington............................……………… West Virginia............................................. Wisconsin............................……………… Wyoming.................................................... 4.5 3.8 5.1 4.3 4.4 3.0 7.3 6.8 9.0 7.7 8.6 4.5 7.4 7.1 9.1 8.4 8.9 5.0 p = preliminary 11. Employment of workers on nonfarm payrolls by State, seasonally adjusted State May 2008 Apr. 2009p May 2009p State May 2008 Apr. 2009p May 2009p Alabama............................………… 2,165,770 2,131,372 2,128,625 Alaska............................................. 356,621 358,717 359,246 Arizona............................…………… 3,113,180 3,153,411 3,152,711 Arkansas........................................ 1,370,462 1,358,972 1,359,936 California............................………… 18,350,638 18,629,516 18,540,642 Missouri……………………………… 3,010,341 Montana......................................... 505,824 Nebraska............................………… 994,761 Nevada........................................... 1,363,718 New Hampshire............................… 738,886 3,008,361 502,680 990,513 1,400,452 744,003 3,010,398 500,764 986,374 1,405,644 741,954 Colorado......................................... 2,726,411 Connecticut............................……… 1,869,243 Delaware........................................ 441,836 District of Columbia........................ 332,437 Florida............................................ 9,182,221 2,737,359 1,887,180 438,347 326,180 9,247,899 2,721,183 1,886,515 437,897 328,977 9,243,663 New Jersey..................................... New Mexico............................…… New York........................................ North Carolina............................… North Dakota.................................. 4,491,277 957,148 9,667,195 4,523,232 368,799 4,572,378 955,478 9,771,997 4,579,637 369,837 4,560,364 958,824 9,771,413 4,567,108 368,264 Georgia............................………… 4,840,682 Hawaii............................................. 654,451 Idaho............................…………… 752,952 Illinois............................................. 6,721,065 Indiana............................…………… 3,224,739 4,784,070 646,671 750,167 6,611,172 3,205,269 4,771,449 649,217 750,801 6,667,033 3,217,452 Ohio............................……………… Oklahoma....................................... Oregon............................…………… Pennsylvania.................................. Rhode Island............................…… 5,974,256 1,743,609 1,948,331 6,392,041 567,555 5,968,531 1,771,688 2,003,610 6,430,784 563,408 5,979,690 1,771,775 1,997,653 6,472,104 566,044 Iowa............................……………… Kansas........................................... Kentucky............................………… Louisiana........................................ Maine............................…………… 1,676,096 1,494,100 2,037,985 2,063,640 706,045 1,674,828 1,521,980 2,076,540 2,074,281 703,855 1,678,902 1,528,417 2,077,485 2,068,540 702,616 South Carolina............................… 2,141,142 2,198,419 2,203,107 South Dakota.................................. 443,915 446,866 446,366 Tennessee............................……… 3,045,228 3,039,141 3,041,301 Texas.............................................. 11,657,814 11,924,810 11,955,424 Utah............................……………… 1,379,661 1,379,354 1,382,429 Maryland............................………… Massachusetts............................... Michigan............................………… Minnesota....................................... Mississippi............................……… 2,995,817 3,422,272 4,954,537 2,924,896 1,315,760 2,968,440 3,434,282 4,847,947 2,964,037 1,311,937 2,954,959 3,429,901 4,848,258 2,957,266 1,311,155 Vermont............................………… 354,952 Virginia........................................... 4,110,823 Washington............................……… 3,457,067 West Virginia.................................. 807,314 Wisconsin............................……… 3,075,254 Wyoming........................................ 291,844 360,992 4,170,518 3,539,901 795,041 3,110,840 290,793 360,927 4,170,047 3,560,990 793,448 3,105,412 291,608 NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database. p = preliminary Monthly Labor Review • August 2009 65 Current Labor Statistics: Labor Force Data 12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Industry Annual average 2007 TOTAL NONFARM................. 137,598 TOTAL PRIVATE........................ 115,380 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep 137,066 137,356 137,228 137,053 136,732 136,352 135,755 135,074 134,333 133,652 133,000 132,481 132,178 131,735 114,566 114,834 114,691 114,497 114,197 113,813 113,212 112,542 111,793 111,105 110,457 109,865 109,573 109,178 22,233 21,419 21,507 21,432 21,351 21,247 21,063 20,814 20,532 20,127 19,832 19,520 19,253 19,041 18,818 724 60.1 663.8 146.2 1 223.4 Mining, except oil and gas …… 77.2 Coal mining…………………… Support activities for mining…… 294.3 7,630 Construction................................ Construction of buildings........... 1,774.2 Heavy and civil engineering…… 1,005.4 Speciality trade contractors....... 4,850.2 Manufacturing.............................. 13,879 9,975 Production workers................ 8,808 Durable goods........................... 6,250 Production workers................ 515.3 Wood products.......................... 500.5 Nonmetallic mineral products 455.8 Primary metals.......................... 1,562.8 Fabricated metal products......... 1,187.1 Machinery………..................... Computer and electronic 774 57.0 717.0 161.6 227.7 80.6 327.7 7,215 1,659.3 970.2 4,585.3 13,431 9,649 8,476 5,986 459.6 468.1 443.3 1,528.3 1,185.6 770 56.0 713.8 160.7 226.9 79.6 326.2 7,232 1,660.6 972.2 4,598.7 13,505 9,723 8,533 6,040 462.9 469.7 446.6 1,534.8 1,190.8 777 55.8 721.3 162.7 227.6 79.5 331.0 7,201 1,655.5 970.9 4,574.6 13,454 9,672 8,502 6,006 458.4 466.4 444.8 1,528.4 1,191.1 787 56.1 730.6 164.7 230.0 81.7 335.9 7,177 1,647.5 966.1 4,563.1 13,387 9,608 8,439 5,948 451.9 464.5 440.8 1,530.6 1,187.5 794 56.5 737.7 166.3 230.2 82.5 341.2 7,131 1,625.0 960.2 4,545.4 13,322 9,543 8,392 5,898 446.4 460.2 441.1 1,519.4 1,183.1 794 56.6 737.7 166.5 230.5 83.1 340.7 7,066 1,609.9 952.6 4,503.9 13,203 9,425 8,300 5,805 438.8 458.2 438.6 1,505.0 1,179.3 793 56.6 736.8 167.4 230.7 84.3 338.7 6,939 1,588.4 942.5 4,408.5 13,082 9,322 8,216 5,741 429.8 450.1 429.8 1,486.3 1,162.7 789 55.7 733.3 169.4 229.2 84.5 334.7 6,841 1,572.9 933.2 4,335.2 12,902 9,174 8,085 5,633 416.2 441.2 419.6 1,461.5 1,150.2 781 55.2 725.3 167.7 227.9 84.9 329.7 6,706 1,536.9 926.6 4,242.2 12,640 8,946 7,881 5,458 403.9 434.3 409.3 1,425.3 1,126.0 771 54.5 716.4 167.8 225.7 84.1 322.9 6,593 1,509.5 919.0 4,164.4 12,468 8,804 7,753 5,352 390.4 425.8 395.2 1,399.0 1,100.8 754 51.9 701.9 166.9 222.8 83.3 312.2 6,470 1,481.5 907.2 4,081.4 12,296 8,654 7,620 5,239 388.4 417.0 386.4 1,370.3 1,070.5 740 51.4 689.0 167.0 220.4 82.4 301.6 6,367 1,461.7 885.5 4,019.6 12,146 8,532 7,490 5,130 382.4 415.5 376.2 1,344.1 1,051.4 731 51.3 679.6 168.1 219.4 81.4 292.1 6,310 1,451.2 876.1 3,983.1 12,000 8,409 7,372 5,034 373.5 410.7 367.8 1,325.9 1,032.0 725 51.1 673.8 169.1 217.7 80.3 287.0 6,224 1,428.3 860.3 3,935.3 11,869 8,304 7,267 4,952 366.1 405.5 359.8 1,308.5 1,015.1 products 1……………………… 1,272.5 Computer and peripheral 1,247.6 1,248.5 1,247.3 1,248.3 1,246.5 1,239.8 1,233.3 1,223.7 1,212.9 1,196.9 1,187.1 1,171.1 1,156.1 1,143.0 GOODS-PRODUCING……………… Natural resources and mining…………..……….......…… Logging.................................... Mining.......................................... Oil and gas extraction…………… equipment.............................. Communications equipment… 186.2 128.1 182.8 129.0 182.1 130.2 182.5 129.1 182.6 129.1 182.8 129.2 182.4 128.6 181.8 129.5 180.0 129.1 180.3 129.6 175.5 129.0 173.5 128.5 167.8 127.8 164.2 127.4 163.5 126.7 Semiconductors and electronic components.......... Electronic instruments………. 447.5 443.2 432.4 441.6 431.2 442.4 431.9 441.8 432.3 442.6 431.0 442.5 428.4 440.2 423.2 438.8 417.4 437.5 410.5 433.8 403.3 431.9 397.6 430.9 389.2 431.1 382.8 427.2 374.9 424.5 Electrical equipment and appliances............................... Transportation equipment......... 429.4 1,711.9 424.9 1,606.5 428.3 1,634.3 428.4 1,625.7 425.5 1,584.5 422.6 1,572.6 421.3 1,531.3 417.5 1,532.5 412.0 1,501.8 406.1 1,423.5 399.1 1,423.7 389.7 1,400.4 382.0 1,365.9 378.4 1,335.3 375.6 1,310.8 Furniture and related products.....……………………… 531.1 Miscellaneous manufacturing 641.7 Nondurable goods..................... 5,071 Production workers................ 3,725 Food manufacturing.................. 1,484.1 481.0 630.8 4,955 3,663 1,484.8 488.0 629.0 4,972 3,683 1,482.1 483.4 627.9 4,952 3,666 1,478.1 475.7 630.1 4,948 3,660 1,482.7 470.3 629.4 4,930 3,645 1,484.3 458.8 628.5 4,903 3,620 1,484.7 449.6 624.2 4,866 3,581 1,489.0 440.6 618.4 4,817 3,541 1,477.6 428.6 611.0 4,759 3,488 1,470.7 417.4 604.5 4,715 3,452 1,467.2 408.8 601.1 4,676 3,415 1,464.4 401.0 600.4 4,656 3,402 1,474.9 394.4 597.4 4,628 3,375 1,471.7 387.8 594.7 4,602 3,352 1,470.6 Beverages and tobacco products………………………… Textile mills……………………… Textile product mills................... Apparel…………………………. Leather and allied products....... Paper and paper products......... 198.2 169.7 157.7 214.6 33.8 458.2 199.0 151.0 147.5 198.4 33.6 445.8 200.6 150.7 147.1 200.0 34.2 448.2 200.0 149.0 146.2 199.5 33.0 447.1 199.2 149.5 145.2 200.4 34.5 444.7 199.3 147.5 145.5 197.3 34.3 441.9 197.2 145.6 144.5 192.8 33.9 439.7 196.4 140.6 143.5 187.1 32.6 437.1 195.8 136.8 141.2 183.5 32.6 433.4 194.2 133.6 137.4 178.9 32.4 427.3 191.3 130.0 134.2 176.3 31.9 422.5 191.6 128.2 129.3 173.8 31.7 418.3 190.9 127.3 127.5 169.9 31.7 415.1 190.5 126.1 127.0 170.2 31.5 410.5 189.9 123.9 126.5 165.8 31.0 409.0 Printing and related support activities………………………… Petroleum and coal products..... Chemicals.................................. Plastics and rubber products.. 622.1 114.5 860.9 757.2 594.1 117.1 849.8 734.2 594.8 117.6 852.8 743.4 591.5 118.1 850.0 739.3 591.5 118.0 847.3 734.7 587.6 117.9 844.3 729.7 582.3 117.8 843.4 721.1 574.1 117.2 842.6 705.9 567.0 116.9 837.1 694.9 558.1 114.2 832.7 679.7 549.2 114.6 828.2 669.3 541.5 114.5 823.4 659.0 534.4 114.6 818.9 651.1 529.6 114.5 814.9 641.4 523.2 114.2 811.8 636.4 SERVICE-PROVIDING................... 115,366 115,646 115,849 115,796 115,702 115,485 115,289 114,941 114,542 114,206 113,820 113,480 113,228 113,137 112,917 PRIVATE SERVICEPROVIDING……………………… 93,147 Trade, transportation, and utilities................................ Wholesale trade......................... Durable goods………………….. Nondurable goods…………… 26,630 6,015.2 3,121.5 2,062.2 93,146 93,327 93,259 93,146 92,950 92,750 92,398 92,010 91,666 91,273 90,937 90,612 90,532 90,360 26,385 5,963.7 3,060.7 2,053.0 26,467 5,983.1 3,071.7 2,061.5 26,425 5,966.9 3,062.5 2,053.2 26,354 5,954.3 3,052.4 2,049.0 26,257 5,947.2 3,047.2 2,044.1 26,157 5,920.1 3,026.1 2,040.5 26,005 5,890.3 3,004.9 2,033.6 25,843 5,850.7 2,978.6 2,025.1 25,735 5,819.3 2,959.6 2,013.9 25,605 5,773.7 2,926.2 2,006.6 25,479 5,741.3 2,899.4 2,002.5 25,371 5,710.8 2,875.5 1,997.7 25,308 5,695.7 2,861.8 1,996.6 25,263 5,681.7 2,846.6 1,995.6 Electronic markets and agents and brokers…………… 831.5 850.1 849.9 851.2 852.9 855.9 853.5 851.8 847.0 845.8 840.9 839.4 837.6 837.3 839.5 Retail trade................................. 15,520.0 15,356.3 15,404.4 15,380.2 15,334.5 15,278.2 15,216.8 15,126.0 15,037.9 14,991.5 14,934.3 14,872.4 14,839.7 14,811.6 14,791.0 Motor vehicles and parts dealers 1……………………… Automobile dealers.................. 1,908.3 1,242.2 1,844.5 1,186.0 1,866.2 1,204.7 1,851.4 1,191.5 1,832.6 1,176.2 1,818.4 1,164.8 1,792.7 1,141.7 1,770.5 1,121.2 1,745.6 1,099.9 1,730.1 1,088.6 1,716.8 1,078.7 1,701.8 1,067.7 1,690.2 1,057.1 1,681.6 1,050.2 1,673.5 1,043.0 Furniture and home furnishings stores.................... 574.6 542.8 546.5 545.8 542.3 538.4 532.4 522.6 514.2 508.3 499.7 497.7 492.4 486.3 484.6 Electronics and appliance stores....................................... 549.4 549.6 552.9 553.0 551.0 547.1 545.1 541.5 538.6 535.5 533.7 518.6 518.0 517.0 515.2 See notes at end of table. 66 Monthly Labor Review • August 2009 12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Annual average Industry 2008 2009 2007 2008 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep 1,309.3 2,843.6 1,253.1 2,858.4 1,252.2 2,863.2 1,244.1 2,863.4 1,245.9 2,853.8 1,248.4 2,846.5 1,245.9 2,851.9 1,235.8 2,843.5 1,227.8 2,835.1 1,214.9 2,835.3 1,207.1 2,826.0 1,193.5 2,827.6 1,189.3 2,828.9 1,186.3 2,828.0 1,182.0 2,830.4 993.1 861.5 1,002.4 843.4 1,003.6 845.8 1,005.4 843.0 999.0 840.9 998.9 834.8 995.9 836.1 989.4 836.9 991.2 834.4 985.7 833.0 986.9 832.1 985.0 830.4 984.2 831.1 984.7 829.0 984.7 829.4 Clothing and clothing accessories stores ………………… 1,500.0 1,484.2 1,487.2 1,483.6 1,483.3 1,478.5 1,471.5 1,462.2 1,448.5 1,445.0 1,443.8 1,433.4 1,432.7 1,426.8 1,422.7 Sporting goods, hobby, 656.3 book, and music stores…………… General merchandise stores1……… 3,020.6 Department stores………………… 1,591.5 Miscellaneous store retailers……… 865.4 Nonstore retailers…………………… 437.9 646.7 3,047.1 1,557.0 847.8 436.3 646.9 3,052.0 1,561.8 849.4 438.5 642.2 3,062.3 1,563.2 848.3 437.7 645.8 3,058.2 1,554.4 845.6 436.1 641.6 3,045.8 1,541.9 844.3 435.5 641.2 3,025.5 1,523.9 845.0 433.6 633.1 3,024.5 1,517.5 838.3 427.7 624.3 3,029.2 1,521.2 825.0 424.0 620.8 3,040.7 1,529.1 819.5 422.7 613.6 3,040.7 1,532.6 815.1 418.8 610.0 3,045.5 1,530.9 810.4 418.5 608.8 3,041.2 1,524.0 805.3 417.6 607.0 3,041.8 1,526.0 805.8 417.3 605.0 3,043.2 1,524.7 803.3 417.0 Transportation and warehousing................................. 4,540.9 Air transportation…………….……… 491.8 Rail transportation……...…………… 233.7 65.5 Water transportation………...……… Truck transportation………..……… 1,439.2 4,505.0 492.6 229.5 65.2 1,391.1 4,521.1 494.9 227.1 66.1 1,393.1 4,518.0 492.9 230.1 66.4 1,391.2 4,506.0 488.1 228.8 64.9 1,390.3 4,471.3 483.2 227.6 64.5 1,378.1 4,456.9 482.1 229.5 63.9 1,370.3 4,424.4 481.6 229.0 62.6 1,358.0 4,389.9 477.8 226.8 60.3 1,340.8 4,354.4 476.8 227.1 59.7 1,323.3 4,327.0 474.8 224.1 60.9 1,313.9 4,295.5 474.0 220.7 59.6 1,300.3 4,251.7 466.8 217.9 58.1 1,283.2 4,233.5 466.7 214.6 57.2 1,277.4 4,221.9 468.3 212.9 56.1 1,269.9 Building material and garden supply stores................................ Food and beverage stores............. Health and personal care stores……………………………… Gasoline stations…………………… Transit and ground passenger transportation………...…………… Pipeline transportation………...…… 412.1 39.9 418.1 42.0 421.9 42.3 420.8 42.7 422.7 42.5 414.4 43.1 413.8 43.3 411.7 43.2 410.1 43.3 408.1 43.1 406.4 43.1 406.2 43.0 401.8 43.0 405.4 42.5 412.6 42.1 Scenic and sightseeing transportation…….………………… 28.6 28.0 28.1 27.6 27.3 27.1 27.1 27.2 27.2 26.9 27.0 27.0 27.2 28.5 27.8 584.2 580.7 665.2 553.4 3,032 589.9 575.9 672.8 559.5 2,997 590.9 579.2 677.5 558.2 3,006 592.8 577.7 675.8 559.7 2,995 592.1 575.7 673.6 559.3 2,990 589.5 572.9 670.9 560.5 2,986 588.0 570.5 668.4 562.8 2,982 582.2 565.7 663.2 564.0 2,965 579.5 564.6 659.5 564.6 2,940 569.3 563.2 656.9 569.3 2,924 561.0 563.7 652.1 570.0 2,918 554.6 558.5 651.6 570.1 2,905 550.3 556.0 647.4 568.5 2,884 545.6 550.5 645.1 567.5 2,858 537.3 551.3 643.6 568.2 2,840 Publishing industries, except Internet…………………...………… 901.2 882.6 886.8 882.9 879.4 876.6 872.6 863.6 857.8 846.3 836.3 827.8 820.1 808.6 801.6 Motion picture and sound recording industries……...………… Broadcasting, except Internet.. 380.6 325.2 381.6 315.9 383.5 315.7 380.1 315.9 380.0 313.8 381.7 313.0 388.7 312.9 385.0 313.1 377.2 308.1 376.7 306.5 389.8 302.5 393.7 299.0 389.5 296.3 381.3 294.2 379.0 292.0 Internet publishing and broadcasting………………...……… Telecommunications………….…… 1,030.6 1,021.4 1,025.5 1,022.8 1,023.1 1,021.6 1,014.5 1,010.2 1,004.0 1,001.6 999.5 996.7 989.3 986.4 980.9 261.6 133.6 8,146 6,015.2 261.8 132.2 8,162 6,026.1 260.5 133.0 8,154 6,019.9 259.8 133.6 8,141 6,010.6 259.6 133.6 8,115 5,994.3 258.9 134.1 8,088 5,978.7 257.5 135.1 8,043 5,948.7 256.4 136.5 8,010 5,924.0 257.0 135.7 7,954 5,890.4 254.6 134.8 7,898 5,853.9 253.9 134.1 7,857 5,829.5 255.5 133.7 7,811 5,799.6 253.8 133.2 7,784 5,781.6 254.1 132.8 7,755 5,762.0 21.6 22.2 22.3 22.3 22.3 22.3 22.1 21.5 21.3 21.0 20.9 20.8 20.5 20.3 20.2 related activities 1………………… 2,866.3 Depository credit 2,735.8 2,738.5 2,730.9 2,724.4 2,722.4 2,706.4 2,692.8 2,680.8 2,665.3 2,648.8 2,635.4 2,619.8 2,613.5 2,602.8 intermediation 1…………………… 1,823.5 Commercial banking..…………… 1,351.4 1,819.5 1,359.9 1,822.2 1,362.1 1,820.0 1,361.1 1,818.4 1,360.1 1,814.8 1,359.0 1,811.1 1,356.0 1,806.9 1,352.7 1,804.9 1,351.8 1,798.1 1,346.6 1,790.9 1,340.5 1,783.4 1,334.2 1,778.0 1,329.4 1,774.4 1,327.9 1,772.6 1,324.5 848.6 858.1 864.4 860.4 861.4 851.4 847.8 842.1 839.9 826.5 814.9 805.8 797.0 791.7 784.6 Insurance carriers and related activities………………...… 2,306.8 2,308.8 2,310.6 2,316.1 2,312.0 2,307.6 2,311.0 2,300.9 2,292.0 2,287.4 2,281.1 2,279.4 2,274.3 2,268.3 2,265.2 88.7 90.3 90.3 90.2 90.5 90.6 91.4 91.4 90.0 90.2 88.2 88.1 88.0 87.8 89.2 Real estate and rental and leasing………………………..… 2,169.1 Real estate……………………….… 1,500.4 Rental and leasing services……… 640.3 2,130.2 1,481.1 620.9 2,135.9 1,485.5 622.5 2,134.4 1,481.5 624.4 2,130.0 1,482.4 619.4 2,120.6 1,474.5 617.7 2,109.0 1,471.2 609.7 2,093.8 1,461.7 603.8 2,085.8 1,458.2 599.3 2,063.2 1,444.9 589.9 2,043.8 1,432.4 583.2 2,027.0 1,421.9 576.6 2,011.7 1,411.9 571.5 2,002.7 1,405.1 569.2 1,993.3 1,397.6 567.7 Support activities for transportation………………..…… Couriers and messengers……...…… Warehousing and storage………… Utilities………………………….………...... Information…………………...…. ISPs, search portals, and data processing………..………… Other information services………… 267.8 126.3 8,301 Financial activities………………..… Finance and insurance……………..… 6,132.0 Monetary authorities— central bank…………………..…… Credit intermediation and Securities, commodity contracts, investments…………… Funds, trusts, and other financial vehicles…………….…… Lessors of nonfinancial intangible assets………………..… 28.4 28.2 27.9 28.5 28.2 28.4 28.1 28.3 28.3 28.4 28.2 28.5 28.3 28.4 28.0 Professional and business services…………………………...… 17,942 17,778 17,824 17,788 17,727 17,675 17,612 17,488 17,356 17,205 17,029 16,910 16,783 16,756 16,650 services1…………………………… Legal services……………..……… 7,659.5 1,175.4 7,829.7 1,163.7 7,828.9 1,164.5 7,833.6 1,163.0 7,833.0 1,161.0 7,834.4 1,160.2 7,844.0 1,160.2 7,827.7 1,157.7 7,797.2 1,156.8 7,765.5 1,154.1 7,729.2 1,148.7 7,697.9 1,144.9 7,670.7 1,139.4 7,652.4 1,136.9 7,617.3 1,131.5 Accounting and bookkeeping services…………………………… 935.9 950.1 948.3 947.5 947.9 945.6 946.4 941.0 933.7 927.5 924.4 929.5 929.3 938.0 936.3 Architectural and engineering services…………………………… 1,432.2 1,444.8 1,450.5 1,449.2 1,447.2 1,441.4 1,437.1 1,428.6 1,419.4 1,411.1 1,394.2 1,377.9 1,364.1 1,350.3 1,336.4 Professional and technical . See notes at end of table Monthly Labor Review • August 2009 67 Current Labor Statistics: Labor Force Data 12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted [In thousands] Industry Annual average 2008 2009 2007 2008 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep 1,372.1 1,450.3 1,446.2 1,456.2 1,460.6 1,461.6 1,466.1 1,467.9 1,466.8 1,462.4 1,463.7 1,459.2 1,460.4 1,457.0 1,456.4 952.7 1,008.9 1,010.1 1,011.3 1,011.6 1,021.0 1,022.9 1,024.9 1,020.5 1,025.7 1,021.6 1,016.0 1,016.7 1,017.9 1,016.7 1,866.4 1,894.6 1,900.6 1,895.3 1,895.2 1,887.1 1,882.8 1,882.0 1,872.1 1,871.7 1,862.1 1,852.6 1,840.2 1,829.9 1,818.9 Administrative and waste services…………………………… 8,416.3 Administrative and support 8,053.7 8,094.9 8,058.6 7,998.6 7,953.2 7,884.8 7,778.3 7,686.3 7,567.5 7,437.8 7,359.4 7,272.3 7,274.0 7,213.6 services 1……………………… 8,061.3 Employment services 1……… 3,545.9 Temporary help services…… 2,597.4 817.4 Business support services…… Services to buildings 7,693.5 3,144.4 2,342.6 823.2 7,736.4 3,184.0 2,383.5 818.1 7,699.3 3,146.9 2,349.1 817.4 7,637.0 3,089.5 2,301.1 814.9 7,591.9 3,049.8 2,264.2 818.1 7,522.0 2,987.7 2,218.9 820.8 7,414.2 2,896.7 2,128.5 823.7 7,324.4 2,829.5 2,055.6 816.0 7,203.1 2,720.5 1,965.7 817.6 7,076.5 2,638.7 1,892.7 805.0 6,999.2 2,567.0 1,835.4 799.1 6,911.7 2,506.4 1,781.5 792.9 6,912.7 2,501.9 1,780.6 790.5 6,853.0 2,466.2 1,749.2 784.6 and dwellings………………… 1,849.5 1,847.0 1,851.4 1,848.6 1,847.0 1,843.3 1,837.4 1,829.4 1,818.1 1,812.5 1,796.8 1,791.5 1,778.7 1,786.1 1,773.5 Waste management and remediation services…………. 355.0 360.2 358.5 359.3 361.6 361.3 362.8 364.1 361.9 364.4 361.3 360.2 360.6 361.3 360.6 18,322 2,941.4 18,855 3,036.6 18,843 3,049.2 18,888 3,062.4 18,950 3,083.7 18,957 3,055.1 18,981 3,047.3 19,044 3,066.0 19,080 3,063.1 19,119 3,088.4 19,138 3,083.1 19,158 3,077.9 19,175 3,077.4 19,215 3,077.6 19,252 3,090.0 Computer systems design and related services………… Management and technical consulting services…………… Management of companies and enterprises……..………..... Educational and health services………………...………. Educational services…….……… Health care and social assistance……….……………… 15,380.2 15,818.5 15,794.1 15,825.9 15,865.9 15,901.9 15,934.1 15,977.8 16,017.0 16,030.3 16,054.7 16,080.1 16,097.8 16,137.7 16,162.1 Ambulatory health care services 1……………………… 5,473.5 Offices of physicians…………… 2,201.6 Outpatient care centers……… 512.0 913.8 Home health care services…… Hospitals………………………… 4,515.0 5,660.7 2,265.7 532.5 958.0 4,641.1 5,652.0 2,264.6 531.2 955.3 4,634.0 5,676.3 2,272.7 535.4 961.1 4,646.8 5,683.8 2,272.7 537.2 963.4 4,660.7 5,699.5 2,279.0 534.8 966.8 4,668.9 5,706.1 2,283.3 536.6 968.6 4,681.9 5,727.7 2,289.8 536.9 975.6 4,692.4 5,742.6 2,294.5 536.7 980.7 4,703.7 5,753.3 2,300.4 538.0 981.4 4,707.5 5,770.1 2,304.4 538.5 991.0 4,711.3 5,779.8 2,308.0 537.7 996.7 4,715.1 5,794.1 2,310.5 538.7 1,004.5 4,716.7 5,812.9 2,314.6 539.3 1,013.3 4,719.1 5,829.3 2,320.6 542.8 1,017.9 4,722.1 3,008.1 1,613.7 2,508.7 859.2 13,459 3,005.7 1,613.0 2,502.4 853.8 13,490 3,006.3 1,612.3 2,496.5 844.6 13,473 3,009.9 1,612.6 2,511.5 851.6 13,454 3,007.6 1,608.9 2,525.9 862.5 13,428 3,013.2 1,611.0 2,532.9 862.3 13,395 3,022.3 1,614.5 2,535.4 863.2 13,344 3,029.6 1,617.3 2,541.1 864.3 13,304 3,029.4 1,616.6 2,540.1 862.7 13,268 3,033.6 1,617.9 2,539.7 860.4 13,236 3,041.0 1,621.8 2,544.2 858.2 13,202 3,042.8 1,624.5 2,544.2 853.9 13,168 3,049.1 1,626.8 2,556.6 860.3 13,195 3,054.7 1,628.4 2,556.0 852.2 13,177 Nursing and residential care facilities 1………………… 2,958.3 Nursing care facilities………… 1,602.6 Social assistance 1……………… 2,433.4 Child day care services……… 850.4 Leisure and hospitality……….. 13,427 Arts, entertainment, and recreation……….…….…… 1,969.2 1,969.3 1,975.1 1,966.6 1,964.7 1,955.3 1,952.0 1,944.0 1,947.1 1,943.8 1,936.2 1,928.7 1,900.6 1,901.8 1,883.6 Performing arts and spectator sports………………… 405.0 406.3 409.7 406.9 406.2 402.9 402.5 398.8 401.4 405.7 398.6 400.5 392.9 396.8 392.2 Museums, historical sites, zoos, and parks………………… 130.3 131.8 132.2 132.1 132.1 130.6 129.6 130.6 130.8 130.3 130.9 130.6 130.5 130.9 130.5 1,433.9 1,431.2 1,433.2 1,427.6 1,426.4 1,421.8 1,419.9 1,414.6 1,414.9 1,407.8 1,406.7 1,397.6 1,377.2 1,374.1 1,360.9 Amusements, gambling, and recreation……………………… Accommodations and food services…………………… 11,457.4 11,489.3 11,515.3 11,506.3 11,489.3 11,472.4 11,442.7 11,399.6 11,356.5 11,323.7 11,299.7 11,273.2 11,267.0 11,293.6 11,293.6 Accommodations………………. 1,866.9 1,857.3 1,865.0 1,854.6 1,843.6 1,841.3 1,827.9 1,812.1 1,794.3 1,768.4 1,754.7 1,732.7 1,723.6 1,728.7 1,726.9 Food services and drinking places…………………………… 9,590.4 Other services……………………… 5,494 Repair and maintenance……… 1,253.4 Personal and laundry services 1,309.7 9,632.0 5,528 1,228.2 1,326.6 9,650.3 5,535 1,233.6 1,327.4 9,651.7 5,536 1,230.6 1,328.9 9,645.7 5,530 1,220.6 1,331.7 9,631.1 5,532 1,221.2 1,333.9 9,614.8 5,535 1,216.4 1,330.1 9,587.5 5,509 1,204.7 1,323.2 9,562.2 5,477 1,189.9 1,320.9 9,555.3 5,461 1,184.7 1,313.6 9,545.0 5,449 1,177.3 1,312.5 9,540.5 5,426 1,166.3 1,302.4 9,543.4 5,420 1,163.7 1,297.3 9,564.9 5,416 1,158.4 1,293.3 9,566.7 5,423 1,156.7 1,300.2 Membership associations and organizations…………………… 2,931.1 Government.................................. Federal........................................ Federal, except U.S. Postal Service.................................... U.S. Postal Service……………… State........................................... Education................................ Other State government.......... Local........................................... Education................................ Other local government........... 2,973.3 2,973.8 2,976.6 2,977.6 2,977.1 2,988.3 2,980.7 2,965.7 2,963.1 2,958.7 2,956.8 2,958.6 2,964.3 2,965.8 22,218 2,734 22,500 2,764 22,522 2,765 22,537 2,776 22,556 2,768 22,535 2,771 22,539 2,775 22,543 2,783 22,532 2,778 22,540 2,793 22,547 2,796 22,543 2,808 22,616 2,876 22,605 2,860 22,557 2,819 1,964.7 769.1 5,122 2,317.5 2,804.3 14,362 7,986.8 6,375.5 2,016.8 747.5 5,178 2,359.0 2,818.9 14,557 8,075.6 6,481.8 2,014.6 750.5 5,175 2,355.4 2,819.4 14,582 8,101.3 6,481.1 2,020.2 755.8 5,184 2,365.1 2,819.1 14,577 8,088.3 6,488.2 2,027.1 740.6 5,204 2,379.5 2,824.6 14,584 8,084.5 6,499.4 2,034.3 736.5 5,192 2,373.3 2,818.9 14,572 8,075.4 6,496.4 2,043.5 731.9 5,194 2,372.8 2,820.7 14,570 8,071.6 6,498.3 2,052.4 730.1 5,197 2,380.3 2,816.4 14,563 8,067.6 6,495.6 2,057.3 720.9 5,196 2,381.3 2,814.8 14,558 8,060.5 6,497.7 2,065.8 726.9 5,192 2,380.2 2,811.6 14,555 8,070.7 6,484.7 2,071.0 724.9 5,192 2,382.3 2,809.4 14,559 8,076.7 6,482.5 2,086.0 721.7 5,186 2,379.9 2,805.9 14,549 8,078.7 6,469.8 2,154.6 721.0 5,189 2,385.5 2,803.5 14,551 8,081.4 6,469.2 2,150.2 709.5 5,189 2,386.2 2,802.5 14,556 8,078.0 6,478.3 2,111.9 706.8 5,176 2,381.1 2,795.1 14,562 8,085.8 6,476.2 1 Includes other industries not shown separately. NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. 68 Monthly Labor Review • August 2009 13. Average weekly hours of production or nonsupervisory workers1 on private nonfarm payrolls, by industry, monthly data seasonally adjusted Industry Annual average 2007 2008 2008 2009 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep TOTAL PRIVATE………………………… 33.9 33.6 33.6 33.6 33.7 33.6 33.5 33.4 33.3 33.3 33.3 33.1 33.1 33.1 GOODS-PRODUCING……………………… 40.6 40.2 40.3 40.3 40.2 39.9 39.8 39.5 39.4 39.3 39.2 38.9 39.0 39.0 39.0 Natural resources and mining…………… 45.9 45.1 44.9 44.8 45.3 44.5 44.7 45.3 44.3 44.2 43.9 43.4 43.0 43.3 43.1 Construction………………………………… 39.0 38.5 38.7 38.7 38.6 38.3 38.3 37.7 38.0 37.9 38.0 37.7 37.5 37.6 37.6 Manufacturing…………………….............. Overtime hours.................................. 41.2 4.2 40.8 3.7 40.9 3.8 41.0 3.7 40.8 3.7 40.5 3.5 40.4 3.5 40.2 3.2 39.9 2.9 39.8 2.9 39.5 2.7 39.4 2.6 39.6 2.7 39.4 2.8 39.5 2.9 Durable goods..…………………............ Overtime hours.................................. Wood products..................................... Nonmetallic mineral products............... Primary metals..................................... Fabricated metal products................... Machinery………………………………… Computer and electronic products…… Electrical equipment and appliances… Transportation equipment.................... Furniture and related products……….. Miscellaneous manufacturing.............. 41.5 4.2 39.4 42.3 42.9 41.6 42.6 40.6 41.2 42.8 39.2 38.9 41.1 3.7 38.6 42.1 42.2 41.3 42.3 41.0 40.9 42.0 38.1 38.9 41.2 3.8 39.1 42.0 42.5 41.2 42.1 41.2 40.9 42.1 38.7 39.0 41.2 3.7 38.8 42.6 42.2 41.2 42.1 41.1 40.8 42.6 38.3 39.1 41.1 3.7 38.8 42.2 42.5 41.1 42.5 41.0 40.8 41.7 37.9 39.4 40.6 3.4 38.4 41.9 41.8 40.9 42.1 40.8 41.0 40.9 37.4 38.7 40.6 3.4 38.1 41.8 41.4 40.8 41.8 40.8 40.4 41.3 37.4 38.9 40.4 3.1 37.6 40.9 40.9 40.8 41.4 41.3 40.2 40.9 37.2 38.5 40.0 2.8 36.8 40.9 40.5 40.3 41.1 40.4 39.7 40.9 37.3 38.3 39.8 2.7 36.9 40.2 40.4 39.7 40.9 40.7 39.4 40.4 37.7 38.4 39.6 2.5 37.1 40.0 40.1 39.5 40.6 40.5 38.9 40.1 37.4 38.2 39.3 2.4 36.9 39.9 40.1 39.0 40.1 39.9 38.8 40.0 37.7 38.2 39.5 2.5 37.0 40.2 40.0 39.2 40.1 40.2 39.6 40.6 37.6 38.3 39.4 2.6 36.9 40.5 40.0 39.2 39.9 40.0 39.3 40.0 37.8 38.0 39.4 2.6 37.5 40.8 39.6 39.2 39.8 39.9 39.1 40.4 37.8 37.9 Nondurable goods.................................. Overtime hours.................................. Food manufacturing............................… Beverage and tobacco products.......... Textile mills……………………………… Textile product mills…………………… Apparel................................................. Leather and allied products.................. Paper and paper products……………… 40.8 4.1 40.7 40.7 40.3 39.7 37.2 38.2 43.1 40.4 3.7 40.5 38.8 38.7 38.6 36.4 37.5 42.9 40.4 3.8 40.6 38.8 38.8 38.9 36.4 38.4 42.7 40.6 3.7 40.6 38.7 39.2 39.1 37.0 38.2 42.6 40.4 3.8 40.5 38.2 39.5 38.7 36.5 37.5 42.9 40.2 3.6 40.3 38.2 38.9 38.1 35.9 37.5 42.4 40.2 3.6 40.3 38.1 38.4 37.9 36.3 36.9 42.2 39.9 3.4 39.9 37.9 37.7 37.9 36.2 34.4 42.1 39.7 3.1 39.8 36.7 37.0 37.1 36.0 34.7 41.9 39.7 3.2 40.1 37.0 37.1 37.0 36.0 34.0 41.6 39.5 3.0 39.9 37.0 36.4 37.1 35.6 33.3 41.5 39.4 3.0 40.1 36.2 36.3 37.0 36.1 32.8 41.1 39.6 3.1 40.1 35.8 36.9 37.5 36.1 32.4 41.4 39.6 3.2 40.0 36.5 36.8 38.3 36.1 32.0 41.2 39.6 3.3 39.9 35.4 37.9 37.7 35.5 31.9 41.9 Printing and related support activities............................................. Petroleum and coal products…………… Chemicals………………………………… Plastics and rubber products…………… 39.1 44.1 41.9 41.3 38.3 44.6 41.5 41.0 38.1 44.6 41.6 41.0 38.0 45.5 41.9 41.3 38.2 45.6 41.4 41.0 38.3 45.2 41.3 40.7 38.3 45.2 41.5 40.6 38.2 44.4 41.3 40.6 38.0 45.3 41.1 40.0 37.7 45.1 41.1 39.9 37.3 43.8 41.1 39.6 37.5 44.3 40.9 39.4 37.7 43.8 41.0 39.8 37.6 43.4 41.1 39.8 38.0 43.3 41.2 39.9 PRIVATE SERVICEPROVIDING……………………………… 32.4 32.3 32.3 32.3 32.4 32.3 32.3 32.2 32.2 32.2 32.1 32.1 32.0 32.0 31.9 Trade, transportation, and utilities.......………………....................... Wholesale trade........………………....... Retail trade………………………………… Transportation and warehousing………… Utilities……………………………………… Information………………………………… Financial activities………………………… 33.3 38.2 30.2 37.0 42.4 36.5 35.9 33.2 38.2 30.0 36.4 42.7 36.7 35.8 33.2 38.3 30.0 36.4 43.0 36.7 35.8 33.2 38.4 30.0 36.4 42.4 36.7 35.7 33.2 38.3 30.0 36.4 42.3 36.8 36.1 33.2 38.1 30.1 36.4 42.7 36.9 36.0 33.1 38.2 29.9 36.3 42.5 36.9 35.9 33.0 38.1 29.8 36.1 42.4 37.0 36.1 32.9 37.8 29.7 36.2 42.9 37.0 35.9 32.9 38.1 29.7 36.0 42.6 37.2 36.2 32.8 37.9 29.8 35.7 43.2 36.9 36.2 32.7 37.8 29.7 35.7 42.4 36.7 36.1 32.8 37.8 29.8 35.8 42.3 36.4 36.0 32.9 37.6 29.9 36.0 42.1 36.5 36.0 32.8 37.6 29.8 35.8 41.9 36.4 35.9 Professional and business services…………………………………… Education and health services…………… Leisure and hospitality…………………… Other services……………........................ 34.8 32.6 25.5 30.9 34.8 32.5 25.2 30.8 34.8 32.5 25.3 30.7 34.8 32.5 25.2 30.8 34.9 32.6 25.2 30.9 34.8 32.5 25.2 30.7 34.9 32.5 25.1 30.7 34.9 32.4 25.0 30.7 34.8 32.4 25.0 30.6 34.9 32.4 24.8 30.7 34.8 32.3 25.0 30.6 34.7 32.4 24.8 30.5 34.7 32.3 24.8 30.5 34.7 32.3 24.7 30.5 34.6 32.2 24.6 30.3 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 33.0 NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. Monthly Labor Review • August 2009 69 Current Labor Statistics: Labor Force Data 14. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry, monthly data seasonally adjusted Industry Annual average 2008 2009 2007 2008 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep TOTAL PRIVATE Current dollars……………………… Constant (1982) dollars…………… $17.43 8.33 $18.08 8.30 $18.04 8.20 $18.10 8.16 $18.18 8.20 $18.21 8.21 $18.28 8.33 $18.34 8.54 $18.40 8.65 $18.43 8.64 $18.46 8.61 $18.50 8.64 $18.50 8.65 $18.53 8.65 $18.53 8.65 GOODS-PRODUCING............................... 18.67 19.33 19.27 19.36 19.43 19.48 19.56 19.63 19.69 19.72 19.78 19.85 19.82 19.84 19.84 20.97 20.95 17.26 16.43 18.20 15.67 22.50 21.87 17.74 16.97 18.70 16.15 22.04 21.77 17.73 16.94 18.70 16.11 22.54 21.85 17.80 17.03 18.78 16.16 23.01 22.02 17.78 17.01 18.74 16.19 23.08 22.09 17.81 17.07 18.74 16.28 23.03 22.17 17.89 17.15 18.84 16.35 23.28 22.28 17.94 17.25 18.91 16.37 23.23 22.41 17.96 17.33 18.94 16.39 23.14 22.43 17.99 17.36 18.99 16.43 23.14 22.42 18.07 17.47 19.09 16.49 23.33 22.59 18.10 17.52 19.17 16.46 23.38 22.55 18.11 17.51 19.18 16.49 23.31 22.60 18.11 17.49 19.22 16.46 23.31 22.60 18.11 17.49 19.22 16.46 PRIVATE SERVICEPROVIDING..........……………….............. 17.11 17.77 17.74 17.79 17.87 17.90 17.97 18.03 18.10 18.14 18.17 18.20 18.21 18.24 18.24 Trade,transportation, and utilities………………………………….... Wholesale trade.................................... Retail trade........................................... Transportation and warehousing……… Utilities…………………………………… Information.............................................. Financial activities.................................. 15.78 19.59 12.75 17.72 27.88 23.96 19.64 16.16 20.14 12.87 18.41 28.84 24.77 20.27 16.16 20.11 12.87 18.41 29.12 24.78 20.24 16.17 20.15 12.88 18.42 28.67 24.87 20.26 16.23 20.28 12.92 18.48 28.89 24.95 20.37 16.20 20.20 12.91 18.47 28.86 24.90 20.43 16.23 20.22 12.89 18.58 28.91 24.99 20.43 16.29 20.29 12.93 18.66 28.91 24.94 20.41 16.31 20.31 12.94 18.66 29.16 24.91 20.53 16.36 20.41 12.97 18.72 29.22 24.98 20.53 16.38 20.52 12.96 18.67 29.67 25.09 20.55 16.38 20.59 12.97 18.68 29.31 25.31 20.62 16.38 20.70 12.96 18.62 29.29 25.28 20.64 16.41 20.87 12.96 18.61 29.40 25.44 20.74 16.41 20.87 12.96 18.61 29.40 25.44 20.74 Professional and business services................................................. 20.15 21.19 21.08 21.19 21.38 21.47 21.63 21.78 21.97 22.04 22.17 22.26 22.26 22.27 22.27 Education and health services................................................. Leisure and hospitality.......................... Other services......................................... 18.11 10.41 15.42 18.88 10.84 16.08 18.84 10.85 16.09 18.92 10.87 16.13 18.96 10.89 16.17 19.04 10.90 16.20 19.08 10.92 16.24 19.13 10.90 16.29 19.20 10.94 16.29 19.18 10.97 16.30 19.24 10.97 16.25 19.24 10.98 16.23 19.33 10.97 16.22 19.35 10.98 16.25 19.35 10.98 16.25 Natural resources and mining............... Construction........................................... Manufacturing......................................... Excluding overtime........................... Durable goods…………………………… Nondurable goods……………………… 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 70 Monthly Labor Review • August 2009 NOTE: See "Notes on the data" for a description of the most recent benchmark revision. p = preliminary. 15. Average hourly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry Industry Annual average 2007 TOTAL PRIVATE……………………………… $17.43 Seasonally adjusted……………………. – 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep $18.08 $18.00 $18.02 $18.10 $18.25 $18.27 $18.40 $18.40 $18.49 $18.57 $18.57 $18.52 $18.47 $18.42 – 18.04 18.10 18.18 18.21 18.28 18.34 18.40 18.43 18.46 18.50 18.50 18.53 18.53 GOODS-PRODUCING...................................... 18.67 19.33 19.26 19.39 19.53 19.63 19.61 19.65 19.75 19.64 19.64 19.74 19.78 19.83 19.84 Natural resources and mining…………….. 20.97 22.50 21.75 22.45 23.06 23.19 22.98 23.31 23.53 23.41 23.19 23.40 23.40 23.10 22.99 Construction.………….................................. 20.95 21.87 21.69 21.90 22.16 22.34 22.28 22.32 22.52 22.32 22.25 22.45 22.44 22.54 22.48 Manufacturing…………………………………… 17.26 17.74 17.73 17.73 17.75 17.84 17.86 17.94 18.06 18.03 18.07 18.09 18.13 18.09 18.13 Durable goods..………………….................. Wood products ......................................... Nonmetallic mineral products ……………… Primary metals ......................................... Fabricated metal products ….................... Machinery …………..……………………… Computer and electronic products ........... Electrical equipment and appliances ........ Transportation equipment ........................ Furniture and related products ................. Miscellaneous manufacturing ................... 18.20 13.68 16.93 19.66 16.53 17.72 19.94 15.93 23.04 14.32 14.66 18.70 14.20 16.90 20.18 16.99 17.97 21.03 15.78 23.83 14.54 15.19 18.70 14.16 16.97 20.26 16.93 17.90 21.02 15.72 23.86 14.58 15.15 18.66 14.25 16.93 20.43 16.94 17.96 21.11 15.85 23.75 14.52 15.35 18.72 14.25 16.85 20.28 17.08 17.97 21.21 15.94 23.88 14.59 15.33 18.80 14.37 16.94 20.36 17.14 18.08 21.23 15.99 24.05 14.54 15.31 18.81 14.44 16.92 20.01 17.18 18.11 21.42 15.83 24.10 14.55 15.33 18.92 14.58 16.85 19.98 17.21 18.18 21.37 15.74 24.37 14.77 15.42 19.06 14.66 16.73 20.05 17.36 18.15 21.44 15.88 24.58 14.92 15.60 18.99 14.69 16.82 19.80 17.24 18.16 21.46 15.81 24.66 14.95 15.66 19.09 14.77 17.03 19.75 17.30 18.17 21.42 15.93 24.69 14.85 15.97 19.17 14.67 17.19 19.69 17.29 18.26 21.71 15.95 24.80 15.02 16.02 19.20 14.72 17.37 19.98 17.41 18.20 21.73 15.99 24.76 15.00 16.07 19.20 14.91 17.25 19.80 17.38 18.36 21.70 16.15 24.85 15.02 16.18 19.22 14.85 17.30 19.96 17.43 18.24 21.70 16.18 25.00 15.13 16.06 Nondurable goods………………………...... Food manufacturing ...........................…… Beverages and tobacco products ............. 15.67 13.55 18.54 16.15 14.00 19.35 16.08 13.97 18.74 16.20 14.03 19.02 16.15 14.02 18.60 16.30 14.15 18.97 16.32 14.10 19.41 16.35 14.17 19.98 16.43 14.26 19.95 16.51 14.34 20.07 16.48 14.30 20.25 16.43 14.24 20.40 16.51 14.27 20.25 16.43 14.26 20.38 16.51 14.34 20.21 13.00 11.78 11.05 12.04 18.44 16.15 25.21 19.55 15.39 13.57 11.73 11.40 12.96 18.88 16.75 27.46 19.49 15.85 13.58 11.80 11.35 12.88 18.93 16.77 26.99 19.29 15.72 13.77 11.80 11.35 12.85 19.11 16.81 27.54 19.41 15.87 13.67 11.78 11.28 12.94 18.81 16.83 27.69 19.53 15.86 13.72 11.81 11.48 12.98 19.04 16.90 28.25 19.77 15.94 13.71 11.62 11.38 13.14 19.11 16.99 28.69 19.67 16.03 13.69 11.59 11.35 13.61 18.89 16.86 28.28 19.77 16.13 13.80 11.72 11.38 13.47 19.11 17.01 28.17 19.72 16.24 13.90 11.59 11.46 14.10 19.27 16.79 29.13 19.89 16.24 13.76 11.53 11.40 14.19 18.99 16.79 29.57 19.96 16.22 13.88 11.34 11.26 14.21 18.90 16.69 29.80 19.93 16.20 13.79 11.34 11.44 14.34 19.29 16.76 29.26 20.02 16.19 13.63 11.34 11.28 13.85 19.09 16.61 29.18 20.16 16.09 13.63 11.33 11.40 14.08 19.29 16.61 29.41 20.22 16.02 Textile mills .............................................. Textile product mills ................................. Apparel ..................................................... Leather and allied products ……………… Paper and paper products ………………… Printing and related support activities…... Petroleum and coal products ……………… Chemicals …………………………………… Plastics and rubber products .................... PRIVATE SERVICEPROVIDING ……………………………………. 17.11 17.77 17.68 17.68 17.73 17.90 17.94 18.10 18.09 18.23 18.33 18.31 18.24 18.18 18.10 Trade, transportation, and utilities…….…….......................................... Wholesale trade ……………………………… Retail trade …………………………………… Transportation and warehousing …………… Utilities ………..…..….………..……………… 15.78 19.59 12.75 17.72 27.88 16.16 20.14 12.87 18.41 28.84 16.17 20.05 12.90 18.46 29.02 16.18 20.12 12.92 18.54 28.49 16.21 20.23 12.93 18.52 28.64 16.27 20.20 13.01 18.53 28.95 16.24 20.21 12.89 18.55 29.00 16.26 20.41 12.85 18.69 28.96 16.14 20.36 12.74 18.62 29.28 16.37 20.44 12.96 18.68 29.27 16.47 20.65 12.99 18.73 29.70 16.45 20.64 13.02 18.64 29.42 16.42 20.69 13.01 18.58 29.50 16.40 20.78 12.99 18.54 29.50 16.34 20.66 12.96 18.54 29.20 Information…………………………………..... 23.96 24.77 24.78 24.75 24.87 25.03 25.06 25.03 24.86 25.03 25.12 25.40 25.24 25.41 25.30 Financial activities……..……….................... 19.64 20.27 20.26 20.19 20.29 20.42 20.41 20.54 20.50 20.48 20.68 20.67 20.65 20.72 20.67 20.15 21.19 21.09 21.06 21.12 21.31 21.45 21.97 22.01 22.16 22.52 22.52 22.28 22.15 22.09 services………………………………………… 18.11 Professional and business services………………………………………… Education and health 18.88 18.79 18.96 18.95 19.08 19.04 19.10 19.23 19.26 19.26 19.23 19.33 19.29 19.32 Leisure and hospitality ……………………… 10.41 10.84 10.78 10.73 10.79 10.89 10.93 10.93 11.05 11.03 11.06 11.00 10.99 10.99 10.90 Other services…………………...................... 15.42 16.08 16.10 16.06 16.10 16.22 16.17 16.24 16.27 16.34 16.34 16.33 16.27 16.29 16.16 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. Monthly Labor Review • August 2009 71 Current Labor Statistics: Labor Force Data 16. Average weekly earnings of production or nonsupervisory workers1 on private nonfarm payrolls, by industry Industry Annual average 2007 TOTAL PRIVATE………………… $590.04 Seasonally adjusted.......... – 2009 2008 2008 June $607.99 – $613.80 606.14 783.88 July Aug. $607.27 $613.59 608.16 612.67 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. Mayp Junep $613.20 611.86 $613.87 612.38 $620.08 612.56 $610.88 612.72 $608.32 613.72 $616.52 614.72 $614.67 612.35 $607.46 612.35 $609.51 613.34 $609.70 611.49 791.09 788.32 782.07 778.15 762.03 758.10 763.94 759.55 773.37 779.71 GOODS-PRODUCING……………… 757.34 776.60 Natural resources and mining……………………….. 962.64 1,013.78 985.28 1,005.76 1,051.54 1,041.23 1,038.70 1,072.26 1,040.03 1,020.68 1,008.77 1,003.86 994.50 990.99 1,002.36 816.66 842.36 854.59 858.48 875.32 869.03 866.69 845.93 840.00 828.07 823.25 837.39 830.28 856.52 858.74 Manufacturing……………………… 711.56 724.23 730.48 719.84 727.75 729.66 726.90 726.57 727.82 712.19 708.34 709.13 705.26 710.94 719.76 767.56 547.81 711.30 850.84 701.47 759.92 776.05 566.40 724.62 871.18 699.21 755.38 761.33 560.03 726.30 860.10 692.85 750.73 775.01 561.45 726.24 865.96 707.11 763.73 770.80 561.87 725.03 861.23 707.88 764.78 767.45 551.61 719.10 832.42 707.82 760.62 766.26 549.67 692.54 817.18 707.33 758.11 771.93 538.02 677.57 818.04 706.55 755.04 750.11 524.43 654.30 797.94 680.98 740.93 748.33 531.72 657.36 786.05 678.16 735.89 751.46 531.05 673.85 793.51 670.85 730.40 746.88 534.34 694.80 783.22 668.54 720.72 752.64 553.16 700.35 788.04 677.82 727.06 763.03 574.70 716.22 798.40 685.00 724.13 808.80 861.43 872.33 861.29 869.61 874.68 876.08 891.13 883.33 866.98 863.23 864.06 860.51 863.66 872.34 656.46 986.79 645.60 647.66 999.94 1,016.44 640.34 650.35 978.50 1,002.96 660.39 645.86 990.86 1,002.56 642.19 646.32 994.30 1,022.53 621.33 993.80 613.31 990.07 615.67 992.00 615.62 985.45 633.08 635.87 991.52 1,017.50 560.84 554.20 571.54 557.57 566.09 549.61 542.72 546.49 563.98 559.13 547.97 563.25 552.00 566.25 manufacturing.......................... 569.99 591.73 595.40 594.05 608.60 595.56 593.27 593.67 600.60 599.78 603.67 613.57 610.66 614.84 611.89 Nondurable goods....................... 639.99 551.32 652.20 566.91 652.85 568.58 652.86 568.22 654.08 572.02 663.41 581.57 659.33 575.28 658.91 572.47 657.20 573.25 650.49 569.30 644.37 561.99 644.06 563.90 642.24 555.10 647.34 570.40 655.45 573.60 755.22 524.40 467.77 411.39 459.50 795.58 750.18 524.93 453.12 415.17 486.49 809.21 738.36 529.62 468.46 415.41 501.03 806.42 741.78 535.65 462.56 416.55 485.73 808.35 716.10 542.70 460.60 410.59 481.37 806.95 720.86 544.68 452.32 409.84 486.75 818.72 729.82 525.09 438.07 411.96 484.87 812.18 767.23 520.22 441.58 414.28 462.74 802.83 726.18 514.74 441.84 410.82 476.84 814.09 728.54 510.13 423.04 407.98 470.94 797.78 741.15 493.98 426.61 403.56 465.43 780.49 730.32 502.46 419.58 407.61 470.35 769.23 706.73 496.44 417.31 409.55 457.45 792.82 754.06 497.50 432.05 408.34 445.97 780.78 721.50 520.67 435.07 406.98 450.56 806.32 632.02 642.50 633.91 630.38 644.59 655.72 659.21 652.48 654.89 627.95 622.91 627.54 625.15 617.89 626.20 CONSTRUCTION Durable goods…………………… 754.77 539.34 Wood products ......................... 716.78 Nonmetallic mineral products.... Primary metals…………………… 843.26 687.20 Fabricated metal products......... Machinery………………………… 754.19 781.42 794.87 Computer and electronic products.................................. Electrical equipment and appliances............................... Transportation equipment……… Furniture and related products………………………… 577.97 Miscellaneous Food manufacturing................... Beverages and tobacco products.................................. Textile mills……………………… Textile product mills……………… Apparel…………………………… Leather and allied products....... Paper and paper products……. Printing and related support activities……………… Petroleum and coal products………………………… 1,112.73 Chemicals………………………… 819.54 1,224.26 1,219.95 1,266.84 1,259.90 1,302.33 1,322.61 1,275.43 1,256.38 1,307.94 1,286.30 1,290.34 1,258.18 1,254.74 1,288.16 808.80 808.25 809.40 810.50 820.46 814.34 822.43 814.44 811.51 820.36 815.14 816.82 820.51 837.11 Plastics and rubber products………………………… PRIVATE SERVICEPROVIDING………….................... Trade, transportation, and utilities……………………… Wholesale trade......…………...... Retail trade………………………… 635.63 649.04 650.81 647.50 650.26 655.13 652.42 658.10 657.72 647.98 639.07 636.66 633.03 635.56 644.00 554.89 574.31 579.90 572.83 576.23 578.17 577.67 588.25 578.88 579.71 592.06 587.75 580.03 579.94 577.39 526.07 748.94 385.11 535.79 769.91 386.39 544.93 779.95 393.45 538.79 770.60 391.48 541.41 774.81 391.78 543.42 767.60 395.50 535.92 772.02 384.12 536.58 787.83 381.65 531.01 767.57 380.93 530.39 770.59 378.43 538.57 784.70 384.50 537.92 782.26 384.09 535.29 775.88 385.10 537.92 779.25 388.40 535.95 776.82 387.50 Transportation and warehousing……………………… 654.95 Utilities……………………………… 1,182.65 Information………………………… 670.33 681.17 674.86 679.68 676.35 671.51 680.32 679.63 663.14 663.04 665.45 655.87 661.88 663.73 1,231.19 1,250.76 1,205.13 1,205.74 1,244.85 1,238.30 1,236.59 1,256.11 1,243.98 1,286.01 1,241.52 1,250.80 1,241.95 1,223.48 874.65 908.44 919.34 910.80 917.70 926.11 924.71 936.12 917.33 921.10 931.95 934.72 911.16 914.76 913.33 Financial activities………………… 705.13 726.37 737.46 718.76 726.38 728.99 728.64 753.82 731.85 735.23 761.02 754.46 739.27 739.70 737.92 Professional and business services……………… 700.82 738.25 748.70 730.78 739.20 739.46 750.75 775.54 761.55 762.30 785.95 785.95 766.43 766.39 766.52 Education and……………………… health services…………………… 590.09 614.30 614.43 618.10 617.77 620.10 616.90 624.57 621.13 622.10 624.02 623.05 620.49 619.21 620.17 Leisure and hospitality…………… 265.52 273.27 280.28 276.83 278.38 272.25 273.25 273.25 270.73 264.72 275.39 272.80 270.35 271.45 271.41 Other services……………………… 477.06 494.99 500.71 496.25 500.71 497.95 496.42 501.82 496.24 498.37 501.64 498.07 494.61 495.22 489.65 1 Data relate to production workers in natural resources and mining and manufacturing, NOTE: See "Notes on the data" for a description of the most recent benchmark revision. construction workers in construction, and nonsupervisory workers in the service- Dash indicates data not available. providing industries. p = preliminary. septTAB16 72 Monthly Labor Review • August 2009 17. Diffusion indexes of employment change, seasonally adjusted [In percent] Timespan and year Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Private nonfarm payrolls, 278 industries Over 1-month span: 2005............................................... 52.6 60.1 54.1 58.1 56.8 58.3 58.5 59.2 54.2 55.9 62.7 57.6 2006.............................................. 64.9 62.2 63.8 59.8 49.1 51.8 59.2 55.4 55.7 56.3 59.4 60.7 2007.............................................. 53.5 55.5 52.4 49.4 55.9 48.3 50.7 46.5 55.9 57.2 59.4 57.9 2008………………………………… 42.1 40.6 44.1 41.1 42.6 36.9 37.6 39.1 34.7 33.0 27.1 20.5 2009………………………………… 22.1 20.8 19.6 21.8 29.3 28.6 2005............................................... 51.7 57.2 59.0 59.8 57.9 62.0 60.5 62.9 60.3 55.5 56.3 62.7 2006.............................................. 67.7 68.6 65.1 65.1 60.5 58.9 55.5 57.0 55.0 54.4 59.0 64.2 2007.............................................. 62.5 54.8 54.2 54.8 54.1 50.4 52.8 48.7 53.3 53.9 58.3 62.5 2008………………………………… 57.7 44.8 40.2 39.7 37.3 33.6 33.6 32.8 34.9 33.2 26.9 20.8 2009………………………………… 18.6 14.2 15.1 15.3 20.3 23.8 2005............................................... 55.4 57.9 58.1 57.0 58.3 60.9 63.1 63.3 61.6 59.6 61.4 62.5 2006.............................................. 64.6 63.8 67.5 66.2 65.5 66.6 60.3 61.1 57.9 57.9 62.4 59.0 2007.............................................. 60.3 57.2 60.5 58.3 55.5 56.5 52.8 52.4 56.6 54.4 56.8 59.0 2008………………………………… 56.6 53.0 50.7 47.4 40.2 33.4 31.0 33.4 30.6 29.0 26.0 24.4 2009………………………………… 21.6 17.2 15.1 15.3 15.9 16.4 2005............................................... 60.9 60.9 60.0 59.2 58.3 60.3 61.3 63.3 60.7 59.2 59.8 61.8 2006.............................................. 67.2 65.5 65.9 62.9 65.5 66.8 64.8 64.4 66.6 65.9 64.9 66.2 2007.............................................. 63.3 59.4 61.1 59.6 59.2 58.3 56.8 57.2 59.4 58.9 58.1 59.6 2008………………………………… 54.4 56.1 52.6 49.1 50.2 47.8 43.7 42.3 38.0 37.8 32.3 28.2 2009………………………………… 24.0 22.0 19.9 18.1 17.5 17.5 Over 3-month span: Over 6-month span: Over 12-month span: Manufacturing payrolls, 84 industries Over 1-month span: 2005............................................... 36.7 46.4 42.2 46.4 40.4 33.7 41.0 43.4 45.8 47.6 44.6 47.0 2006.............................................. 57.8 49.4 53.6 47.0 37.3 50.6 49.4 42.2 40.4 42.8 41.0 44.0 2007.............................................. 44.6 41.0 30.7 24.7 38.0 32.5 43.4 30.7 39.2 42.8 60.8 48.2 2008………………………………… 30.7 28.9 37.3 32.5 40.4 25.3 25.9 27.7 22.9 18.7 15.1 10.2 2009………………………………… 6.0 9.6 10.8 16.3 11.4 13.3 2005............................................... 36.7 43.4 41.0 41.6 35.5 36.1 34.9 36.7 42.2 44.0 38.6 48.8 2006.............................................. 56.6 57.2 48.2 48.2 44.6 50.0 43.4 45.2 36.7 33.1 35.5 39.2 2007.............................................. 40.4 33.1 33.1 28.9 29.5 30.1 31.9 28.9 30.7 30.7 39.2 51.2 2008………………………………… 48.8 33.7 28.3 29.5 26.5 22.9 19.9 16.9 22.3 21.1 15.1 11.4 2009………………………………… 6.0 3.6 3.6 7.8 8.4 10.2 2005............................................... 33.7 39.8 38.0 36.1 35.5 34.9 39.8 36.1 36.1 38.0 36.7 39.8 2006.............................................. 45.2 45.2 50.6 48.8 50.6 50.0 45.2 47.0 43.4 42.2 39.8 34.3 2007.............................................. 37.3 33.1 29.5 28.9 30.7 34.9 28.9 26.5 29.5 28.3 33.7 38.0 2008………………………………… 34.3 30.1 37.3 35.5 25.3 20.5 17.5 18.1 16.9 13.3 11.4 9.6 2009………………………………… 9.0 4.8 4.8 6.0 4.8 4.8 2005............................................... 45.2 44.0 42.2 41.0 36.7 35.5 32.5 34.3 33.1 33.7 33.7 38.0 2006.............................................. 44.0 41.0 41.0 39.8 39.8 45.2 42.2 42.8 47.0 48.8 45.8 44.6 2007.............................................. 39.8 36.7 37.3 30.7 28.9 29.5 30.7 28.9 33.1 28.9 34.3 35.5 2008………………………………… 27.7 28.9 25.9 25.3 30.7 27.1 24.7 19.3 21.7 21.7 16.9 15.1 2009………………………………… 8.4 4.8 4.8 4.8 6.0 6.0 Over 3-month span: Over 6-month span: Over 12-month span: NOTE: Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment. See the "Definitions" in this section. See "Notes on the data" for a description of the most recent benchmark revision. Data for the two most recent months are preliminary. Monthly Labor Review • August 2009 73 Current Labor Statistics: Labor Force Data 18. Job openings levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region 2008 Dec. 2 Total ……………………………………………… Percent 2009 Jan. Feb. Mar. 2008 Apr. p May June Dec. 2009 Jan. 2.3 Feb. 2.1 Mar. 2.2 Apr. 1.9 p May 1.9 June 3,224 2,920 2,973 2,633 2,513 2,523 2,558 1.9 1.9 Total private 2………………………………… 2,861 2,461 2,606 2,269 2,042 2,191 2,206 2.5 2.2 2.3 2.0 1.8 2.0 2.0 Construction……………………………… 66 55 58 51 29 39 67 0.9 0.8 0.9 0.8 0.5 0.6 1.1 Manufacturing…………………………… 188 115 141 115 95 105 101 1.4 0.9 1.1 0.9 0.8 0.9 0.8 Trade, transportation, and utilities……… 495 488 488 414 332 466 484 1.9 1.9 1.9 1.6 1.3 1.8 1.9 Professional and business services…… 562 501 482 428 461 451 412 3.1 2.8 2.8 2.5 2.7 2.6 2.4 Education and health services………… 685 636 589 537 515 530 528 3.5 3.2 3.0 2.7 2.6 2.7 2.7 Leisure and hospitality…………………… 315 272 332 289 322 265 304 2.3 2.0 2.4 2.1 2.4 2.0 2.3 345 417 367 353 461 310 321 1.5 1.8 1.6 1.5 2.0 1.4 1.4 2.4 Industry Government………………………………… Region3 Northeast………………………………… 633 560 607 583 520 554 610 2.4 2.2 2.4 2.3 2.0 2.2 South……………………………………… 1,245 1,109 1,109 1,000 942 888 880 2.5 2.2 2.2 2.0 1.9 1.8 1.8 Midwest…………………………………… 607 587 563 499 512 512 485 1.9 1.9 1.8 1.6 1.7 1.7 1.6 West……………………………………… 689 655 638 556 570 544 560 2.2 2.1 2.1 1.8 1.9 1.8 1.9 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. West Virginia; Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. NOTE: The job openings level is the number of job openings on the last business day of the month; the job openings rate is the number of job openings on the last business day of the month as a percent of total employment plus job openings. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, P = preliminary. 19. Hires levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region 2008 Dec. 2 Total ……………………………………………… Percent 2009 Jan. Feb. Mar. 2008 Apr. May p June Dec. 3.3 2009 Jan. 3.3 Feb. 3.2 Mar. 3.1 Apr. 3.1 May 3.0 Junep 4,508 4,460 4,339 4,099 4,117 3,942 3,776 2.9 Total private 2………………………………… 4,214 4,141 4,042 3,799 3,822 3,739 3,673 3.7 3.7 3.6 3.4 3.5 3.4 3.4 Construction……………………………… 366 381 370 343 341 365 289 5.3 5.7 5.6 5.3 5.4 5.8 4.6 Manufacturing…………………………… 252 237 257 244 236 206 209 2.0 1.9 2.1 2.0 1.9 1.7 1.8 Trade, transportation, and utilities……… 891 949 814 883 888 842 740 3.4 3.7 3.2 3.5 3.5 3.3 2.9 Professional and business services…… 786 762 730 668 733 721 680 4.5 4.4 4.3 4.0 4.4 4.3 4.1 Education and health services………… 528 539 527 483 475 473 530 2.8 2.8 2.8 2.5 2.5 2.5 2.8 Leisure and hospitality…………………… 711 743 704 693 691 695 708 5.3 5.6 5.3 5.3 5.3 5.3 5.4 271 306 275 271 340 273 254 1.2 1.4 1.2 1.2 1.5 1.2 1.1 3.1 Industry Government………………………………… Region3 Northeast………………………………… 726 753 837 696 729 712 766 2.9 3.0 3.3 2.8 2.9 2.9 South……………………………………… 1,659 1,663 1,566 1,458 1,619 1,423 1,331 3.4 3.4 3.2 3.0 3.4 3.0 2.8 Midwest…………………………………… 1,009 1,003 904 943 901 867 856 3.3 3.3 3.0 3.1 3.0 2.9 2.9 West……………………………………… 1,053 1,002 960 931 949 995 904 3.5 3.3 3.2 3.1 3.2 3.4 3.1 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; 74 Monthly Labor Review • August 2009 NOTE: The hires level is the number of hires during the entire month; the hires rate is the number of hires during the entire month as a percent of total employment. p = preliminary. 20. Total separations levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region 2008 Dec. Total 2……………………………………………… Percent 2009 Jan. Feb. Mar. 2008 Apr. p May 2009 Dec. June Jan. 3.7 Feb. 3.7 Mar. 3.6 Apr. 3.5 3.5 May p June 4,958 4,949 4,833 4,712 4,641 4,356 4,337 3.3 3.3 Total private 2………………………………… 4,673 4,686 4,555 4,434 4,362 4,066 3,985 4.1 4.2 4.1 4.0 4.0 3.7 3.7 Construction……………………………… 452 524 463 463 437 411 359 6.6 7.8 7.0 7.2 6.9 6.5 5.8 3.0 Industry Manufacturing…………………………… 419 476 424 401 390 367 359 3.2 3.8 3.4 3.3 3.2 3.1 Trade, transportation, and utilities……… 1,041 1,049 920 1,001 982 951 785 4.0 4.1 3.6 3.9 3.9 3.8 3.1 Professional and business services…… 898 866 951 778 839 771 727 5.2 5.0 5.6 4.6 5.0 4.6 4.4 Education and health services………… 498 494 498 466 462 419 485 2.6 2.6 2.6 2.4 2.4 2.2 2.5 Leisure and hospitality…………………… 755 763 731 751 716 684 711 5.7 5.7 5.5 5.7 5.4 5.2 5.4 278 277 271 265 255 288 324 1.2 1.2 1.2 1.2 1.1 1.3 1.4 3.2 Government………………………………… Region3 Northeast………………………………… 799 813 783 878 700 774 780 3.2 3.2 3.1 3.5 2.8 3.1 South……………………………………… 1,815 1,898 1,742 1,741 1,682 1,565 1,524 3.7 3.9 3.6 3.6 3.5 3.3 3.2 Midwest…………………………………… 1,088 1,120 1,121 1,085 1,065 1,016 998 3.5 3.7 3.7 3.6 3.5 3.4 3.3 West……………………………………… 1,227 1,180 1,188 978 1,188 980 1,060 4.0 3.9 4.0 3.3 4.0 3.3 3.6 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; NOTE: The total separations level is the number of total separations during the entire month; the total separations rate is the number of total separations during the entire month as a percent of total employment. p = preliminary 21. Quits levels and rates by industry and region, seasonally adjusted 1 Levels (in thousands) Industry and region 2008 Dec. 2 Total ……………………………………………… Percent 2009 Jan. Feb. Mar. 2008 Apr. May p June Dec. 1.6 2009 Jan. Feb. 1.5 1.4 Mar. 1.4 Apr. 1.3 May p June 2,114 2,063 1,911 1,856 1,777 1,788 1,808 1.4 1.4 Total private 2………………………………… 1,984 1,945 1,831 1,749 1,678 1,682 1,698 1.8 1.7 1.6 1.6 1.5 1.5 1.6 Construction……………………………… 92 85 87 102 74 84 75 1.3 1.3 1.3 1.6 1.2 1.3 1.2 Industry Manufacturing…………………………… 87 105 105 81 80 86 88 .7 .8 .8 .7 .7 .7 .7 Trade, transportation, and utilities……… 518 469 372 444 385 398 392 2.0 1.8 1.5 1.7 1.5 1.6 1.6 Professional and business services…… 297 326 310 278 272 281 267 1.7 1.9 1.8 1.6 1.6 1.7 1.6 Education and health services………… 256 248 258 249 228 249 263 1.3 1.3 1.3 1.3 1.2 1.3 1.4 Leisure and hospitality…………………… 461 443 431 433 430 396 434 3.5 3.3 3.3 3.3 3.3 3.0 3.3 130 105 115 107 99 107 110 .6 .5 .5 .5 .4 .5 .5 Northeast………………………………… 302 278 271 273 263 303 262 1.2 1.1 1.1 1.1 1.1 1.2 1.1 South……………………………………… 847 790 759 751 691 718 671 1.7 1.6 1.6 1.6 1.4 1.5 1.4 Midwest…………………………………… 452 491 468 431 410 397 419 1.5 1.6 1.5 1.4 1.4 1.3 1.4 West……………………………………… 498 492 453 408 453 398 450 1.6 1.6 1.5 1.4 1.5 1.3 1.5 Government………………………………… Region3 1 Detail will not necessarily add to totals because of the independent seasonal adjustment of the various series. 2 Includes natural resources and mining, information, financial activities, and other services, not shown separately. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin; West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming. 3 Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont; South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia; NOTE: The quits level is the number of quits during the entire month; the quits rate is the number of quits during the entire month as a percent of total employment. p = preliminary. Monthly Labor Review • August 2009 75 Current Labor Statistics: Labor Force Data 22. Quarterly Census of Employment and Wages: 10 largest counties, fourth quarter 2008. County by NAICS supersector Average weekly wage1 Employment December 2008 (thousands) Percent change, December 2007-082 Fourth quarter 2008 Percent change, fourth quarter 2007-082 United States3 .............................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 9,177.5 8,884.3 127.0 881.7 360.0 1,925.3 147.4 862.8 1,537.6 857.4 742.2 1,229.1 293.2 133,870.4 111,752.9 1,802.7 6,636.1 12,891.3 26,316.1 2,948.2 7,853.7 17,366.1 18,304.3 12,957.7 4,445.7 22,117.5 -2.3 -2.9 2.0 -10.2 -6.2 -3.5 -3.4 -3.2 -4.1 2.9 -1.7 -.7 .9 $918 919 996 1,052 1,094 766 1,360 1,390 1,201 872 390 581 914 2.2 2.0 5.1 4.9 1.8 1.1 .1 -.4 3.7 3.7 1.8 2.8 4.0 Los Angeles, CA .......................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 433.9 430.0 .5 14.0 14.5 53.6 8.8 24.1 42.6 28.1 27.2 201.1 4.0 4,152.9 3,552.8 10.5 136.7 417.6 802.4 207.5 231.8 574.2 500.0 396.1 258.8 600.1 -3.4 -3.8 -2.7 -12.3 -5.9 -5.4 ( 4) -5.7 ( 4) ( 4) -1.6 .5 ( 4) 1,075 1,064 1,261 1,138 1,107 833 1,889 1,462 1,306 979 927 454 1,141 1.8 1.1 5.4 4.8 3.8 -.8 (4) -3.8 (4) (4) 5.9 1.1 5.6 Cook, IL ........................................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 141.0 139.6 .1 12.4 7.0 27.6 2.6 15.7 29.1 14.0 11.7 14.6 1.4 2,480.0 2,169.2 1.1 82.8 219.9 467.7 56.1 203.7 423.4 386.1 227.5 96.1 310.8 -2.8 -3.3 -5.6 -10.5 -6.5 -4.9 -3.2 -4.3 -4.8 3.1 -2.2 -.1 .8 1,118 1,126 998 1,478 1,119 840 1,487 2,007 1,525 930 440 783 1,058 1.5 1.3 -5.0 6.9 3.0 -.4 -4.3 .7 3.5 1.3 .0 3.2 2.9 New York, NY ............................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 118.9 118.6 .0 2.4 3.0 22.0 4.6 19.2 25.5 8.9 11.8 18.0 .3 2,386.4 1,934.3 .2 36.3 33.7 255.2 134.5 369.0 489.1 297.7 224.3 90.2 452.1 -1.3 -1.6 -3.6 .6 -8.3 -3.3 -1.5 -3.9 -2.4 1.6 .8 .7 .0 1,856 2,041 1,594 1,939 1,565 1,294 2,055 4,085 2,173 1,133 889 1,102 1,062 -.6 -.7 4.7 .6 .7 -1.5 -.3 -1.3 .6 6.0 -.7 ( 4) 1.6 Harris, TX ..................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 98.1 97.6 1.6 6.7 4.6 22.5 1.4 10.6 19.6 10.4 7.6 11.9 .5 2,078.1 1,820.6 85.8 156.9 187.7 443.1 32.0 117.9 336.9 224.3 175.2 59.6 257.5 1.0 .9 7.1 .5 2.4 .6 -2.4 -2.7 -.2 3.1 -.6 .4 1.8 1,187 1,215 2,872 1,217 1,468 1,035 1,393 1,517 1,448 958 404 673 988 2.6 2.3 -7.6 7.1 -3.4 4.0 8.2 4.7 3.7 3.2 4.7 3.2 5.2 Maricopa, AZ ................................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 103.6 102.9 .5 11.0 3.6 22.9 1.7 12.9 23.2 10.3 7.4 7.4 .7 1,741.0 1,512.8 9.0 115.5 120.8 365.7 29.4 140.1 289.2 216.8 176.8 48.4 228.2 -5.8 -6.9 -4.9 -25.3 -8.0 -6.8 -4.1 -4.8 -8.5 5.7 -5.3 -4.9 2.0 892 893 1,026 986 1,217 796 1,098 1,066 989 999 420 613 881 2.1 2.2 20.6 3.4 3.6 .9 3.4 -.4 5.0 2.3 -1.4 2.7 .1 See footnotes at end of table. 76 Establishments, fourth quarter 2008 (thousands) Monthly Labor Review • August 2009 22. Continued—Quarterly Census of Employment and Wages: 10 largest counties, fourth quarter 2008. County by NAICS supersector Establishments, fourth quarter 2008 (thousands) Average weekly wage1 Employment December 2008 (thousands) Percent change, December 2007-082 Fourth quarter 2008 Percent change, fourth quarter 2007-082 Orange, CA .................................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 102.7 101.3 .2 6.9 5.3 17.2 1.3 10.7 19.1 10.0 7.1 18.0 1.4 1,451.2 1,301.1 4.2 83.3 166.4 272.3 29.0 110.0 258.3 150.8 171.7 49.0 150.1 -4.8 -5.3 -9.0 -14.9 -5.7 -6.9 -3.8 -7.5 -7.6 3.2 -2.2 -.3 -.8 $1,043 1,043 665 1,234 1,226 947 1,423 1,582 1,259 960 406 569 1,044 1.4 1.2 -2.8 4.5 -.2 1.4 4.0 -2.6 6.0 2.3 1.5 -4.2 3.2 Dallas, TX ..................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 68.6 68.1 .6 4.4 3.1 15.2 1.7 8.8 15.1 6.7 5.4 6.6 .5 1,484.4 1,314.7 8.5 80.1 129.8 308.2 47.3 142.9 275.6 153.9 128.5 39.0 169.7 -1.2 -1.6 12.6 ( 4) -5.4 -2.1 -4.2 ( 4) ( 4) 3.8 ( 4) -1.2 2.3 1,123 1,141 4,744 1,075 1,224 990 1,524 1,429 1,375 1,059 493 682 984 1.1 1.1 ( 4) (4) 1.1 -4.2 3.6 -1.7 2.4 3.1 (4) 3.6 2.2 San Diego, CA ............................................................................. Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 100.0 98.8 .8 7.0 3.1 14.2 1.3 9.5 16.3 8.2 6.9 26.9 1.3 1,309.1 1,082.3 9.4 70.4 100.4 218.3 38.6 74.2 210.9 138.3 158.2 58.4 226.8 -3.0 -3.5 -11.4 -14.3 -3.3 -6.3 .6 -5.7 -4.4 4.2 -2.3 2.0 -.4 981 960 577 1,140 1,306 759 1,970 1,171 1,238 953 425 491 1,079 2.0 1.6 .2 5.5 .9 .7 2.3 -1.0 2.0 3.1 3.9 1.7 2.8 King, WA ...................................................................................... Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 77.6 77.0 .4 6.6 2.4 14.9 1.8 6.9 13.7 6.5 6.2 17.6 .5 1,175.3 1,018.2 2.9 63.8 108.8 221.8 81.4 72.4 185.4 129.3 108.6 43.7 157.1 -1.5 -2.0 7.0 -11.6 -3.3 -2.9 6.1 -5.0 -3.3 4.6 -2.5 -.8 1.9 1,130 1,140 1,573 1,197 1,449 955 1,982 1,418 1,378 894 450 631 1,069 4.0 4.0 11.8 6.8 7.0 1.0 3.9 2.6 4.6 3.8 1.6 3.6 4.2 Miami-Dade, FL ............................................................................ Private industry ........................................................................ Natural resources and mining .............................................. Construction ......................................................................... Manufacturing ...................................................................... Trade, transportation, and utilities ........................................ Information ........................................................................... Financial activities ................................................................ Professional and business services ..................................... Education and health services ............................................. Leisure and hospitality ......................................................... Other services ...................................................................... Government ............................................................................. 86.8 86.4 .5 6.4 2.6 23.5 1.5 10.2 18.2 9.4 6.0 7.6 .4 1,003.9 851.3 9.6 42.0 41.2 253.4 19.0 67.2 132.2 145.9 104.0 36.2 152.6 -4.2 -4.7 -10.6 -21.4 -11.7 -4.0 -8.1 -7.6 -5.2 2.8 -1.9 -3.3 -1.1 924 907 457 973 818 814 1,266 1,387 1,229 901 514 579 1,017 2.6 2.3 -11.1 5.3 1.0 1.2 5.2 .1 6.6 1.7 .6 6.0 3.7 1 Average weekly wages were calculated using unrounded data. 2 Percent changes were computed from quarterly employment and pay data adjusted for noneconomic county reclassifications. See Notes on Current Labor Statistics. 3 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 4 Data do not meet BLS or State agency disclosure standards. NOTE: Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. Data are preliminary. Monthly Labor Review • August 2009 77 Current Labor Statistics: Labor Force Data 23. Quarterly Census of Employment and Wages: by State, fourth quarter 2008. State Establishments, fourth quarter 2008 (thousands) December 2008 (thousands) Percent change, December 2007-08 Fourth quarter 2008 Percent change, fourth quarter 2007-08 United States2 ................................... 9,177.5 133,870.4 -2.3 $918 2.2 Alabama ............................................ Alaska ............................................... Arizona .............................................. Arkansas ........................................... California ........................................... Colorado ........................................... Connecticut ....................................... Delaware ........................................... District of Columbia ........................... Florida ............................................... 121.6 21.4 164.5 86.5 1,370.0 177.1 113.5 29.4 34.4 623.0 1,909.8 303.9 2,557.9 1,168.2 15,288.5 2,295.8 1,688.0 416.8 687.5 7,586.6 -3.1 1.6 -5.1 -1.5 -3.2 -1.5 -1.7 -3.0 .3 -5.3 790 927 848 706 1,042 932 1,164 943 1,570 824 3.5 5.7 2.7 -1.0 .7 .5 1.2 1.9 5.1 1.6 Georgia ............................................. Hawaii ............................................... Idaho ................................................. Illinois ................................................ Indiana .............................................. Iowa .................................................. Kansas .............................................. Kentucky ........................................... Louisiana ........................................... Maine ................................................ 276.7 39.3 57.2 371.5 161.4 94.6 87.2 108.4 128.5 51.1 3,970.3 614.7 634.1 5,795.8 2,831.3 1,483.7 1,370.2 1,783.2 1,907.5 595.3 -3.5 -3.5 -3.9 -2.3 -3.4 -1.0 -.2 -2.6 .1 -2.1 853 821 693 985 764 756 769 754 829 735 2.3 3.5 1.0 1.0 2.7 3.1 3.1 3.0 5.9 4.0 Maryland ........................................... Massachusetts .................................. Michigan ............................................ Minnesota ......................................... Mississippi ......................................... Missouri ............................................. Montana ............................................ Nebraska ........................................... Nevada .............................................. New Hampshire ................................ 164.3 215.1 258.2 172.0 71.0 175.7 43.2 60.4 77.5 49.9 2,531.8 3,239.6 3,993.3 2,658.8 1,117.2 2,700.9 433.8 923.1 1,206.5 626.2 -1.9 -1.1 -4.9 -1.9 -2.8 -1.7 -1.5 -.3 -6.5 -2.0 1,010 1,154 903 907 679 842 678 730 862 936 2.4 1.8 3.6 2.6 3.8 7.9 2.9 1.0 -1.1 2.2 New Jersey ....................................... New Mexico ...................................... New York .......................................... North Carolina ................................... North Dakota ..................................... Ohio .................................................. Oklahoma .......................................... Oregon .............................................. Pennsylvania ..................................... Rhode Island ..................................... 273.7 54.9 585.9 260.1 25.8 293.0 100.8 134.1 344.0 35.9 3,927.7 821.2 8,677.4 4,003.8 354.4 5,167.5 1,559.8 1,676.6 5,645.8 464.3 -2.4 -1.2 -1.0 -3.0 1.9 -3.2 .0 -3.7 -1.3 -3.4 1,123 768 1,169 793 725 816 755 808 897 887 2.8 3.9 1.4 1.9 5.1 2.6 4.9 1.3 2.6 5.7 South Carolina .................................. South Dakota .................................... Tennessee ........................................ Texas ................................................ Utah .................................................. Vermont ............................................ Virginia .............................................. Washington ....................................... West Virginia ..................................... Wisconsin .......................................... 119.5 30.8 143.1 566.6 88.3 25.1 233.5 222.8 48.9 161.1 1,837.1 395.2 2,695.7 10,510.8 1,215.0 304.4 3,656.8 2,885.0 713.8 2,753.2 -3.5 .4 -3.3 .4 -2.1 -1.7 -1.3 -1.8 -.1 -1.9 731 663 824 933 770 774 953 918 735 793 2.1 2.5 1.4 2.4 1.4 4.3 3.3 3.7 7.1 3.0 Wyoming ........................................... 25.2 284.5 1.5 850 4.3 Puerto Rico ....................................... Virgin Islands .................................... 55.3 3.6 1,028.5 45.5 -2.9 -1.4 528 731 2.3 -.8 1 Average weekly wages were calculated using unrounded data. 2 Totals for the United States do not include data for Puerto Rico or the Virgin Islands. 78 Average weekly wage1 Employment Monthly Labor Review • August 2009 NOTE: Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. Data are preliminary. 24. Annual data: Quarterly Census of Employment and Wages, by ownership Year Average establishments Average annual employment Total annual wages (in thousands) Average annual wage per employee Average weekly wage Total covered (UI and UCFE) 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 7,634,018 7,820,860 7,879,116 7,984,529 8,101,872 8,228,840 8,364,795 8,571,144 8,784,027 8,971,897 124,183,549 127,042,282 129,877,063 129,635,800 128,233,919 127,795,827 129,278,176 131,571,623 133,833,834 135,366,106 $3,967,072,423 4,235,579,204 4,587,708,584 4,695,225,123 4,714,374,741 4,826,251,547 5,087,561,796 5,351,949,496 5,692,569,465 6,018,089,108 $31,945 33,340 35,323 36,219 36,764 37,765 39,354 40,677 42,535 44,458 $614 641 679 697 707 726 757 782 818 855 $31,676 33,094 35,077 35,943 36,428 37,401 38,955 40,270 42,124 44,038 $609 636 675 691 701 719 749 774 810 847 $31,762 33,244 35,337 36,157 36,539 37,508 39,134 40,505 42,414 44,362 $611 639 680 695 703 721 753 779 816 853 $33,605 34,681 36,296 37,814 39,212 40,057 41,118 42,249 43,875 45,903 $646 667 698 727 754 770 791 812 844 883 $30,251 31,234 32,387 33,521 34,605 35,669 36,805 37,718 39,179 40,790 $582 601 623 645 665 686 708 725 753 784 $43,688 44,287 46,228 48,940 52,050 54,239 57,782 59,864 62,274 64,871 $840 852 889 941 1,001 1,043 1,111 1,151 1,198 1,248 UI covered 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 7,586,767 7,771,198 7,828,861 7,933,536 8,051,117 8,177,087 8,312,729 8,518,249 8,731,111 8,908,198 121,400,660 124,255,714 127,005,574 126,883,182 125,475,293 125,031,551 126,538,579 128,837,948 131,104,860 132,639,806 $3,845,494,089 4,112,169,533 4,454,966,824 4,560,511,280 4,570,787,218 4,676,319,378 4,929,262,369 5,188,301,929 5,522,624,197 5,841,231,314 Private industry covered 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 7,381,518 7,560,567 7,622,274 7,724,965 7,839,903 7,963,340 8,093,142 8,294,662 8,505,496 8,681,001 105,082,368 107,619,457 110,015,333 109,304,802 107,577,281 107,065,553 108,490,066 110,611,016 112,718,858 114,012,221 $3,337,621,699 3,577,738,557 3,887,626,769 3,952,152,155 3,930,767,025 4,015,823,311 4,245,640,890 4,480,311,193 4,780,833,389 5,057,840,759 State government covered 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 67,347 70,538 65,096 64,583 64,447 64,467 64,544 66,278 66,921 67,381 4,240,779 4,296,673 4,370,160 4,452,237 4,485,071 4,481,845 4,484,997 4,527,514 4,565,908 4,611,395 $142,512,445 149,011,194 158,618,365 168,358,331 175,866,492 179,528,728 184,414,992 191,281,126 200,329,294 211,677,002 Local government covered 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 137,902 140,093 141,491 143,989 146,767 149,281 155,043 157,309 158,695 159,816 12,077,513 12,339,584 12,620,081 13,126,143 13,412,941 13,484,153 13,563,517 13,699,418 13,820,093 14,016,190 $365,359,945 385,419,781 408,721,690 440,000,795 464,153,701 480,967,339 499,206,488 516,709,610 541,461,514 571,713,553 Federal government covered (UCFE) 1998 .................................................. 1999 .................................................. 2000 .................................................. 2001 .................................................. 2002 .................................................. 2003 .................................................. 2004 .................................................. 2005 .................................................. 2006 .................................................. 2007 .................................................. 47,252 49,661 50,256 50,993 50,755 51,753 52,066 52,895 52,916 63,699 2,782,888 2,786,567 2,871,489 2,752,619 2,758,627 2,764,275 2,739,596 2,733,675 2,728,974 2,726,300 $121,578,334 123,409,672 132,741,760 134,713,843 143,587,523 149,932,170 158,299,427 163,647,568 169,945,269 176,857,794 NOTE: Data are final. Detail may not add to total due to rounding. Monthly Labor Review • August 2009 79 Current Labor Statistics: Labor Force Data 25. Annual data: Quarterly Census of Employment and Wages, establishment size and employment, private ownership, by supersector, first quarter 2007 Size of establishments Industry, establishments, and employment 80 Total Fewer than 5 workers1 5 to 9 workers 10 to 19 workers 20 to 49 workers 50 to 99 workers 100 to 249 workers 250 to 499 workers 500 to 999 workers 1,000 or more workers Total all industries2 Establishments, first quarter .................. Employment, March ............................... 8,572,894 112,536,714 5,189,837 7,670,620 Natural resources and mining Establishments, first quarter .................. Employment, March ............................... 124,002 1,686,694 69,260 111,702 23,451 155,044 15,289 205,780 10,137 304,936 3,250 222,684 1,842 278,952 519 179,598 190 126,338 64 101,660 Construction Establishments, first quarter .................. Employment, March ............................... 883,409 7,321,288 580,647 835,748 141,835 929,707 84,679 1,137,104 52,336 1,564,722 15,341 1,046,790 6,807 1,004,689 1,326 443,761 350 232,556 88 126,211 Manufacturing Establishments, first quarter .................. Employment, March ............................... 361,070 13,850,738 136,649 238,848 61,845 415,276 54,940 755,931 53,090 1,657,463 25,481 1,785,569 19,333 2,971,836 6,260 2,140,531 2,379 1,613,357 1,093 2,271,927 Trade, transportation, and utilities Establishments, first quarter .................. Employment, March ............................... 1,905,750 25,983,275 1,017,012 1,683,738 381,434 2,539,291 248,880 3,335,327 160,549 4,845,527 53,721 3,709,371 34,536 5,140,740 7,315 2,510,273 1,792 1,167,986 511 1,051,022 Information Establishments, first quarter .................. Employment, March ............................... 143,094 3,016,454 81,414 113,901 20,986 139,730 16,338 222,710 13,384 411,218 5,609 387,996 3,503 533,877 1,134 392,350 489 335,998 237 478,674 Financial activities Establishments, first quarter .................. Employment, March ............................... 863,784 8,146,274 563,670 890,816 155,984 1,029,911 81,849 1,080,148 40,668 1,210,332 12,037 822,627 6,313 945,396 1,863 645,988 939 648,691 461 872,365 Professional and business services Establishments, first quarter .................. Employment, March ............................... 1,456,681 17,612,073 989,991 1,375,429 196,645 1,292,744 125,014 1,685,085 83,127 2,520,739 32,388 2,243,595 20,412 3,102,005 5,902 2,012,609 2,263 1,535,591 939 1,844,276 Education and health services Establishments, first quarter .................. Employment, March ............................... 812,914 17,331,231 388,773 700,195 179,011 1,189,566 116,031 1,559,689 75,040 2,258,922 27,393 1,908,595 18,815 2,828,678 4,153 1,409,073 1,906 1,319,128 1,792 4,157,385 Leisure and hospitality Establishments, first quarter .................. Employment, March ............................... 716,126 12,949,319 275,121 439,080 120,795 815,688 132,408 1,858,394 134,766 4,054,666 39,766 2,648,733 10,681 1,510,212 1,639 551,528 646 438,008 304 633,010 Other services Establishments, first quarter .................. Employment, March ............................... 1,119,209 4,402,263 908,792 1,109,065 118,963 776,354 57,419 756,783 25,169 732,313 5,562 379,320 2,731 401,371 457 152,994 95 62,295 21 31,768 1 Includes establishments that reported no workers in March 2007. 2 Includes data for unclassified establishments, not shown separately. Monthly Labor Review • August 2009 1,407,987 933,910 648,489 220,564 124,980 30,568 9,326,775 12,610,385 19,566,806 15,156,364 18,718,813 10,438,705 11,049 5,510 7,479,948 11,568,298 NOTE: Data are final. Detail may not add to total due to rounding. 26. Average annual wages for 2006 and 2007 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 2006 2007 Percent change, 2006-07 Metropolitan areas4 .............................................................. $44,165 $46,139 4.5 Abilene, TX ............................................................................ Aguadilla-Isabela-San Sebastian, PR ................................... Akron, OH .............................................................................. Albany, GA ............................................................................ Albany-Schenectady-Troy, NY .............................................. Albuquerque, NM ................................................................... Alexandria, LA ....................................................................... Allentown-Bethlehem-Easton, PA-NJ .................................... Altoona, PA ............................................................................ Amarillo, TX ........................................................................... 29,842 19,277 38,088 32,335 41,027 36,934 31,329 39,787 30,394 33,574 31,567 20,295 39,499 33,378 42,191 38,191 32,757 41,784 31,988 35,574 5.8 5.3 3.7 3.2 2.8 3.4 4.6 5.0 5.2 6.0 Ames, IA ................................................................................ Anchorage, AK ...................................................................... Anderson, IN .......................................................................... Anderson, SC ........................................................................ Ann Arbor, MI ........................................................................ Anniston-Oxford, AL .............................................................. Appleton, WI .......................................................................... Asheville, NC ......................................................................... Athens-Clarke County, GA .................................................... Atlanta-Sandy Springs-Marietta, GA ..................................... 35,331 42,955 32,184 30,373 47,186 32,724 35,308 32,268 33,485 45,889 37,041 45,237 32,850 31,086 49,427 34,593 36,575 33,406 34,256 48,111 4.8 5.3 2.1 2.3 4.7 5.7 3.6 3.5 2.3 4.8 Atlantic City, NJ ..................................................................... Auburn-Opelika, AL ............................................................... Augusta-Richmond County, GA-SC ...................................... Austin-Round Rock, TX ......................................................... Bakersfield, CA ...................................................................... Baltimore-Towson, MD .......................................................... Bangor, ME ............................................................................ Barnstable Town, MA ............................................................ Baton Rouge, LA ................................................................... Battle Creek, MI ..................................................................... 38,018 30,468 35,638 45,737 36,020 45,177 31,746 36,437 37,245 39,362 39,276 31,554 36,915 46,458 38,254 47,177 32,829 37,691 39,339 40,628 3.3 3.6 3.6 1.6 6.2 4.4 3.4 3.4 5.6 3.2 Bay City, MI ........................................................................... Beaumont-Port Arthur, TX ..................................................... Bellingham, WA ..................................................................... Bend, OR ............................................................................... Billings, MT ............................................................................ Binghamton, NY .................................................................... Birmingham-Hoover, AL ........................................................ Bismarck, ND ......................................................................... Blacksburg-Christiansburg-Radford, VA ................................ Bloomington, IN ..................................................................... 35,094 39,026 32,618 33,319 33,270 35,048 40,798 32,550 34,024 30,913 35,680 40,682 34,239 34,318 35,372 36,322 42,570 34,118 35,248 32,028 1.7 4.2 5.0 3.0 6.3 3.6 4.3 4.8 3.6 3.6 Bloomington-Normal, IL ......................................................... Boise City-Nampa, ID ............................................................ Boston-Cambridge-Quincy, MA-NH ...................................... Boulder, CO ........................................................................... Bowling Green, KY ................................................................ Bremerton-Silverdale, WA ..................................................... Bridgeport-Stamford-Norwalk, CT ......................................... Brownsville-Harlingen, TX ..................................................... Brunswick, GA ....................................................................... Buffalo-Niagara Falls, NY ...................................................... 41,359 36,734 56,809 50,944 32,529 37,694 74,890 25,795 32,717 36,950 42,082 37,553 59,817 52,745 33,308 39,506 79,973 27,126 32,705 38,218 1.7 2.2 5.3 3.5 2.4 4.8 6.8 5.2 0.0 3.4 Burlington, NC ....................................................................... Burlington-South Burlington, VT ............................................ Canton-Massillon, OH ........................................................... Cape Coral-Fort Myers, FL .................................................... Carson City, NV ..................................................................... Casper, WY ........................................................................... Cedar Rapids, IA ................................................................... Champaign-Urbana, IL .......................................................... Charleston, WV ..................................................................... Charleston-North Charleston, SC .......................................... 32,835 40,548 33,132 37,065 40,115 38,307 38,976 34,422 36,887 35,267 33,132 41,907 34,091 37,658 42,030 41,105 41,059 35,788 38,687 36,954 0.9 3.4 2.9 1.6 4.8 7.3 5.3 4.0 4.9 4.8 Charlotte-Gastonia-Concord, NC-SC .................................... Charlottesville, VA ................................................................. Chattanooga, TN-GA ............................................................. Cheyenne, WY ...................................................................... Chicago-Naperville-Joliet, IL-IN-WI ....................................... Chico, CA .............................................................................. Cincinnati-Middletown, OH-KY-IN ......................................... Clarksville, TN-KY ................................................................. Cleveland, TN ........................................................................ Cleveland-Elyria-Mentor, OH ................................................. 45,732 39,051 35,358 35,306 48,631 31,557 41,447 30,949 33,075 41,325 46,975 40,819 36,522 36,191 50,823 33,207 42,969 32,216 34,666 42,783 2.7 4.5 3.3 2.5 4.5 5.2 3.7 4.1 4.8 3.5 Coeur d’Alene, ID .................................................................. College Station-Bryan, TX ..................................................... Colorado Springs, CO ........................................................... Columbia, MO ........................................................................ Columbia, SC ........................................................................ Columbus, GA-AL .................................................................. Columbus, IN ......................................................................... Columbus, OH ....................................................................... Corpus Christi, TX ................................................................. Corvallis, OR ......................................................................... 29,797 30,239 38,325 32,207 35,209 32,334 40,107 41,168 35,399 40,586 31,035 32,630 39,745 33,266 36,293 34,511 41,078 42,655 37,186 41,981 4.2 7.9 3.7 3.3 3.1 6.7 2.4 3.6 5.0 3.4 See footnotes at end of table. Monthly Labor Review • August 2009 81 Current Labor Statistics: Labor Force Data 26. Continued — Average annual wages for 2006 and 2007 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 2007 Cumberland, MD-WV ............................................................ Dallas-Fort Worth-Arlington, TX ............................................ Dalton, GA ............................................................................. Danville, IL ............................................................................. Danville, VA ........................................................................... Davenport-Moline-Rock Island, IA-IL ..................................... Dayton, OH ............................................................................ Decatur, AL ............................................................................ Decatur, IL ............................................................................. Deltona-Daytona Beach-Ormond Beach, FL ......................... $29,859 47,525 33,266 33,141 28,870 37,559 39,387 34,883 39,375 31,197 $31,373 49,627 34,433 34,086 30,212 39,385 40,223 35,931 41,039 32,196 5.1 4.4 3.5 2.9 4.6 4.9 2.1 3.0 4.2 3.2 Denver-Aurora, CO ................................................................ Des Moines, IA ...................................................................... Detroit-Warren-Livonia, MI .................................................... Dothan, AL ............................................................................. Dover, DE .............................................................................. Dubuque, IA ........................................................................... Duluth, MN-WI ....................................................................... Durham, NC ........................................................................... Eau Claire, WI ....................................................................... El Centro, CA ......................................................................... 48,232 41,358 47,455 31,473 34,571 33,044 33,677 49,314 31,718 30,035 50,180 42,895 49,019 32,367 35,978 34,240 35,202 52,420 32,792 32,419 4.0 3.7 3.3 2.8 4.1 3.6 4.5 6.3 3.4 7.9 Elizabethtown, KY ................................................................. Elkhart-Goshen, IN ................................................................ Elmira, NY ............................................................................. El Paso, TX ............................................................................ Erie, PA ................................................................................. Eugene-Springfield, OR ......................................................... Evansville, IN-KY ................................................................... Fairbanks, AK ........................................................................ Fajardo, PR ........................................................................... Fargo, ND-MN ....................................................................... 32,072 35,878 33,968 29,903 33,213 33,257 36,858 41,296 21,002 33,542 32,701 36,566 34,879 31,354 34,788 34,329 37,182 42,345 22,075 35,264 2.0 1.9 2.7 4.9 4.7 3.2 0.9 2.5 5.1 5.1 Farmington, NM ..................................................................... Fayetteville, NC ..................................................................... Fayetteville-Springdale-Rogers, AR-MO ............................... Flagstaff, AZ .......................................................................... Flint, MI .................................................................................. Florence, SC .......................................................................... Florence-Muscle Shoals, AL .................................................. Fond du Lac, WI .................................................................... Fort Collins-Loveland, CO ..................................................... Fort Smith, AR-OK ................................................................. 36,220 31,281 35,734 32,231 39,409 33,610 29,518 33,376 37,940 30,932 38,572 33,216 37,325 34,473 39,310 34,305 30,699 34,664 39,335 31,236 6.5 6.2 4.5 7.0 -0.3 2.1 4.0 3.9 3.7 1.0 Fort Walton Beach-Crestview-Destin, FL .............................. Fort Wayne, IN ...................................................................... Fresno, CA ............................................................................ Gadsden, AL .......................................................................... Gainesville, FL ....................................................................... Gainesville, GA ...................................................................... Glens Falls, NY ...................................................................... Goldsboro, NC ....................................................................... Grand Forks, ND-MN ............................................................. Grand Junction, CO ............................................................... 34,409 35,641 33,504 29,499 34,573 34,765 32,780 29,331 29,234 33,729 35,613 36,542 35,111 30,979 36,243 36,994 33,564 30,177 30,745 36,221 3.5 2.5 4.8 5.0 4.8 6.4 2.4 2.9 5.2 7.4 Grand Rapids-Wyoming, MI .................................................. Great Falls, MT ...................................................................... Greeley, CO ........................................................................... Green Bay, WI ....................................................................... Greensboro-High Point, NC ................................................... Greenville, NC ....................................................................... Greenville, SC ....................................................................... Guayama, PR ........................................................................ Gulfport-Biloxi, MS ................................................................. Hagerstown-Martinsburg, MD-WV ......................................... 38,056 29,542 35,144 36,677 35,898 32,432 35,471 24,551 34,688 34,621 38,953 31,009 37,066 37,788 37,213 33,703 36,536 26,094 34,971 35,468 2.4 5.0 5.5 3.0 3.7 3.9 3.0 6.3 0.8 2.4 Hanford-Corcoran, CA ........................................................... Harrisburg-Carlisle, PA .......................................................... Harrisonburg, VA ................................................................... Hartford-West Hartford-East Hartford, CT ............................. Hattiesburg, MS ..................................................................... Hickory-Lenoir-Morganton, NC .............................................. Hinesville-Fort Stewart, GA ................................................... Holland-Grand Haven, MI ...................................................... Honolulu, HI ........................................................................... Hot Springs, AR ..................................................................... 31,148 39,807 31,522 51,282 30,059 31,323 31,416 36,895 39,009 27,684 32,504 41,424 32,718 54,188 30,729 32,364 33,210 37,470 40,748 28,448 4.4 4.1 3.8 5.7 2.2 3.3 5.7 1.6 4.5 2.8 Houma-Bayou Cane-Thibodaux, LA ...................................... Houston-Baytown-Sugar Land, TX ........................................ Huntington-Ashland, WV-KY-OH ........................................... Huntsville, AL ......................................................................... Idaho Falls, ID ....................................................................... Indianapolis, IN ...................................................................... Iowa City, IA .......................................................................... Ithaca, NY .............................................................................. Jackson, MI ........................................................................... Jackson, MS .......................................................................... 38,417 50,177 32,648 44,659 31,632 41,307 35,913 38,337 36,836 34,605 41,604 53,494 33,973 45,763 29,878 42,227 37,457 39,387 38,267 35,771 8.3 6.6 4.1 2.5 -5.5 2.2 4.3 2.7 3.9 3.4 See footnotes at end of table. 82 Percent change, 2006-07 2006 Monthly Labor Review • August 2009 26. Continued — Average annual wages for 2006 and 2007 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 Percent change, 2006-07 2006 2007 Jackson, TN ........................................................................... Jacksonville, FL ..................................................................... Jacksonville, NC .................................................................... Janesville, WI ........................................................................ Jefferson City, MO ................................................................. Johnson City, TN ................................................................... Johnstown, PA ....................................................................... Jonesboro, AR ....................................................................... Joplin, MO ............................................................................. Kalamazoo-Portage, MI ......................................................... $34,477 40,192 25,854 36,732 31,771 31,058 29,972 28,972 30,111 37,099 $35,059 41,437 27,005 36,790 32,903 31,985 31,384 30,378 31,068 38,402 1.7 3.1 4.5 0.2 3.6 3.0 4.7 4.9 3.2 3.5 Kankakee-Bradley, IL ............................................................ Kansas City, MO-KS .............................................................. Kennewick-Richland-Pasco, WA ........................................... Killeen-Temple-Fort Hood, TX ............................................... Kingsport-Bristol-Bristol, TN-VA ............................................ Kingston, NY .......................................................................... Knoxville, TN ......................................................................... Kokomo, IN ............................................................................ La Crosse, WI-MN ................................................................. Lafayette, IN .......................................................................... 32,389 41,320 38,750 31,511 35,100 33,697 37,216 45,808 31,819 35,380 33,340 42,921 40,439 32,915 36,399 35,018 38,386 47,269 32,949 36,419 2.9 3.9 4.4 4.5 3.7 3.9 3.1 3.2 3.6 2.9 Lafayette, LA ......................................................................... Lake Charles, LA ................................................................... Lakeland, FL .......................................................................... Lancaster, PA ........................................................................ Lansing-East Lansing, MI ...................................................... Laredo, TX ............................................................................. Las Cruces, NM ..................................................................... Las Vegas-Paradise, NV ....................................................... Lawrence, KS ........................................................................ Lawton, OK ............................................................................ 38,170 35,883 33,530 36,171 39,890 28,051 29,969 40,139 29,896 29,830 40,684 37,447 34,394 37,043 40,866 29,009 31,422 42,336 30,830 30,617 6.6 4.4 2.6 2.4 2.4 3.4 4.8 5.5 3.1 2.6 Lebanon, PA .......................................................................... Lewiston, ID-WA .................................................................... Lewiston-Auburn, ME ............................................................ Lexington-Fayette, KY ........................................................... Lima, OH ............................................................................... Lincoln, NE ............................................................................ Little Rock-North Little Rock, AR ........................................... Logan, UT-ID ......................................................................... Longview, TX ......................................................................... Longview, WA ........................................................................ 31,790 30,776 32,231 37,926 33,790 33,703 36,169 26,766 35,055 35,140 32,876 31,961 33,118 39,290 35,177 34,750 39,305 27,810 36,956 37,101 3.4 3.9 2.8 3.6 4.1 3.1 8.7 3.9 5.4 5.6 Los Angeles-Long Beach-Santa Ana, CA ............................. Louisville, KY-IN .................................................................... Lubbock, TX .......................................................................... Lynchburg, VA ....................................................................... Macon, GA ............................................................................. Madera, CA ........................................................................... Madison, WI ........................................................................... Manchester-Nashua, NH ....................................................... Mansfield, OH ........................................................................ Mayaguez, PR ....................................................................... 48,680 38,673 31,977 33,242 34,126 31,213 40,007 46,659 33,171 20,619 50,480 40,125 32,761 34,412 34,243 33,266 41,201 49,235 33,109 21,326 3.7 3.8 2.5 3.5 0.3 6.6 3.0 5.5 -0.2 3.4 McAllen-Edinburg-Pharr, TX .................................................. Medford, OR .......................................................................... Memphis, TN-MS-AR ............................................................ Merced, CA ............................................................................ Miami-Fort Lauderdale-Miami Beach, FL .............................. Michigan City-La Porte, IN ..................................................... Midland, TX ........................................................................... Milwaukee-Waukesha-West Allis, WI .................................... Minneapolis-St. Paul-Bloomington, MN-WI ........................... Missoula, MT ......................................................................... 26,712 31,697 40,580 31,147 42,175 31,383 42,625 42,049 46,931 30,652 27,651 32,877 42,339 32,351 43,428 32,570 45,574 43,261 49,542 32,233 3.5 3.7 4.3 3.9 3.0 3.8 6.9 2.9 5.6 5.2 Mobile, AL .............................................................................. Modesto, CA .......................................................................... Monroe, LA ............................................................................ Monroe, MI ............................................................................ Montgomery, AL .................................................................... Morgantown, WV ................................................................... Morristown, TN ...................................................................... Mount Vernon-Anacortes, WA ............................................... Muncie, IN ............................................................................. Muskegon-Norton Shores, MI ................................................ 36,126 35,468 30,618 40,938 35,383 32,608 31,914 32,851 30,691 33,949 36,890 36,739 31,992 41,636 36,223 35,241 32,806 34,620 31,326 34,982 2.1 3.6 4.5 1.7 2.4 8.1 2.8 5.4 2.1 3.0 Myrtle Beach-Conway-North Myrtle Beach, SC .................... Napa, CA ............................................................................... Naples-Marco Island, FL ....................................................... Nashville-Davidson--Murfreesboro, TN ................................. New Haven-Milford, CT ......................................................... New Orleans-Metairie-Kenner, LA ......................................... New York-Northern New Jersey-Long Island, NY-NJ-PA ...... Niles-Benton Harbor, MI ........................................................ Norwich-New London, CT ..................................................... Ocala, FL ............................................................................... 27,905 41,788 39,320 41,003 44,892 42,434 61,388 36,967 43,184 31,330 28,576 44,171 41,300 42,728 47,039 43,255 65,685 38,140 45,463 31,623 2.4 5.7 5.0 4.2 4.8 1.9 7.0 3.2 5.3 0.9 See footnotes at end of table. Monthly Labor Review • August 2009 83 Current Labor Statistics: Labor Force Data 26. Continued — Average annual wages for 2006 and 2007 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 2007 Ocean City, NJ ...................................................................... Odessa, TX ............................................................................ Ogden-Clearfield, UT ............................................................. Oklahoma City, OK ................................................................ Olympia, WA .......................................................................... Omaha-Council Bluffs, NE-IA ................................................ Orlando, FL ............................................................................ Oshkosh-Neenah, WI ............................................................ Owensboro, KY ..................................................................... Oxnard-Thousand Oaks-Ventura, CA ................................... $31,801 37,144 32,890 35,846 37,787 38,139 37,776 39,538 32,491 45,467 $32,452 41,758 34,067 37,192 39,678 39,273 38,633 41,014 33,593 47,669 2.0 12.4 3.6 3.8 5.0 3.0 2.3 3.7 3.4 4.8 Palm Bay-Melbourne-Titusville, FL ........................................ Panama City-Lynn Haven, FL ............................................... Parkersburg-Marietta, WV-OH .............................................. Pascagoula, MS .................................................................... Pensacola-Ferry Pass-Brent, FL ........................................... Peoria, IL ............................................................................... Philadelphia-Camden-Wilmington, PA-NJ-DE-MD ................ Phoenix-Mesa-Scottsdale, AZ ............................................... Pine Bluff, AR ........................................................................ Pittsburgh, PA ........................................................................ 39,778 33,341 32,213 36,287 33,530 42,283 48,647 42,220 32,115 40,759 40,975 33,950 33,547 39,131 34,165 43,470 50,611 43,697 33,094 42,910 3.0 1.8 4.1 7.8 1.9 2.8 4.0 3.5 3.0 5.3 Pittsfield, MA .......................................................................... Pocatello, ID .......................................................................... Ponce, PR ............................................................................. Portland-South Portland-Biddeford, ME ................................ Portland-Vancouver-Beaverton, OR-WA ............................... Port St. Lucie-Fort Pierce, FL ................................................ Poughkeepsie-Newburgh-Middletown, NY ............................ Prescott, AZ ........................................................................... Providence-New Bedford-Fall River, RI-MA .......................... Provo-Orem, UT .................................................................... 36,707 28,418 20,266 36,979 42,607 34,408 39,528 30,625 39,428 32,308 38,075 29,268 21,019 38,497 44,335 36,375 40,793 32,048 40,674 34,141 3.7 3.0 3.7 4.1 4.1 5.7 3.2 4.6 3.2 5.7 Pueblo, CO ............................................................................ Punta Gorda, FL .................................................................... Racine, WI ............................................................................. Raleigh-Cary, NC .................................................................. Rapid City, SD ....................................................................... Reading, PA .......................................................................... Redding, CA .......................................................................... Reno-Sparks, NV ................................................................... Richmond, VA ........................................................................ Riverside-San Bernardino-Ontario, CA ................................. 30,941 32,370 39,002 41,205 29,920 38,048 33,307 39,537 42,495 36,668 32,552 32,833 40,746 42,801 31,119 39,945 34,953 41,365 44,530 37,846 5.2 1.4 4.5 3.9 4.0 5.0 4.9 4.6 4.8 3.2 Roanoke, VA ......................................................................... Rochester, MN ....................................................................... Rochester, NY ....................................................................... Rockford, IL ........................................................................... Rocky Mount, NC .................................................................. Rome, GA .............................................................................. Sacramento--Arden-Arcade--Roseville, CA ........................... Saginaw-Saginaw Township North, MI .................................. St. Cloud, MN ........................................................................ St. George, UT ...................................................................... 33,912 42,941 39,481 37,424 31,556 34,850 44,552 37,747 33,018 28,034 35,419 44,786 40,752 38,304 32,527 33,041 46,385 37,507 33,996 29,052 4.4 4.3 3.2 2.4 3.1 -5.2 4.1 -0.6 3.0 3.6 St. Joseph, MO-KS ................................................................ St. Louis, MO-IL ..................................................................... Salem, OR ............................................................................. Salinas, CA ............................................................................ Salisbury, MD ........................................................................ Salt Lake City, UT .................................................................. San Angelo, TX ..................................................................... San Antonio, TX .................................................................... San Diego-Carlsbad-San Marcos, CA ................................... Sandusky, OH ....................................................................... 31,253 41,354 32,764 37,974 33,223 38,630 30,168 36,763 45,784 33,526 31,828 42,873 33,986 39,419 34,833 40,935 30,920 38,274 47,657 33,471 1.8 3.7 3.7 3.8 4.8 6.0 2.5 4.1 4.1 -0.2 San Francisco-Oakland-Fremont, CA ................................... San German-Cabo Rojo, PR ................................................. San Jose-Sunnyvale-Santa Clara, CA .................................. San Juan-Caguas-Guaynabo, PR ......................................... San Luis Obispo-Paso Robles, CA ........................................ Santa Barbara-Santa Maria-Goleta, CA ................................ Santa Cruz-Watsonville, CA .................................................. Santa Fe, NM ........................................................................ Santa Rosa-Petaluma, CA .................................................... Sarasota-Bradenton-Venice, FL ............................................ 61,343 19,498 76,608 24,812 35,146 40,326 40,776 35,320 41,533 35,751 64,559 19,777 82,038 25,939 36,740 41,967 41,540 37,395 42,824 36,424 5.2 1.4 7.1 4.5 4.5 4.1 1.9 5.9 3.1 1.9 Savannah, GA ....................................................................... Scranton--Wilkes-Barre, PA .................................................. Seattle-Tacoma-Bellevue, WA .............................................. Sheboygan, WI ...................................................................... Sherman-Denison, TX ........................................................... Shreveport-Bossier City, LA .................................................. Sioux City, IA-NE-SD ............................................................. Sioux Falls, SD ...................................................................... South Bend-Mishawaka, IN-MI .............................................. Spartanburg, SC .................................................................... 35,684 32,813 49,455 35,908 34,166 33,678 31,826 34,542 35,089 37,077 36,695 34,205 51,924 37,049 35,672 34,892 33,025 36,056 36,266 37,967 2.8 4.2 5.0 3.2 4.4 3.6 3.8 4.4 3.4 2.4 See footnotes at end of table. 84 Percent change, 2006-07 2006 Monthly Labor Review • August 2009 26. Continued — Average annual wages for 2006 and 2007 for all covered workers1 by metropolitan area Average annual wages3 Metropolitan area2 Percent change, 2006-07 2006 2007 Spokane, WA ......................................................................... Springfield, IL ......................................................................... Springfield, MA ...................................................................... Springfield, MO ...................................................................... Springfield, OH ...................................................................... State College, PA .................................................................. Stockton, CA .......................................................................... Sumter, SC ............................................................................ Syracuse, NY ......................................................................... Tallahassee, FL ..................................................................... $34,016 40,679 37,962 30,786 31,844 35,392 36,426 29,294 38,081 35,018 $35,539 42,420 39,487 31,868 32,017 36,797 37,906 30,267 39,620 36,543 4.5 4.3 4.0 3.5 0.5 4.0 4.1 3.3 4.0 4.4 Tampa-St. Petersburg-Clearwater, FL .................................. Terre Haute, IN ...................................................................... Texarkana, TX-Texarkana, AR .............................................. Toledo, OH ............................................................................ Topeka, KS ............................................................................ Trenton-Ewing, NJ ................................................................. Tucson, AZ ............................................................................ Tulsa, OK ............................................................................... Tuscaloosa, AL ...................................................................... Tyler, TX ................................................................................ 38,016 31,341 32,545 37,039 34,806 54,274 37,119 37,637 35,613 36,173 39,215 32,349 34,079 38,538 36,109 56,645 38,524 38,942 36,737 37,184 3.2 3.2 4.7 4.0 3.7 4.4 3.8 3.5 3.2 2.8 Utica-Rome, NY ..................................................................... Valdosta, GA ......................................................................... Vallejo-Fairfield, CA ............................................................... Vero Beach, FL ...................................................................... Victoria, TX ............................................................................ Vineland-Millville-Bridgeton, NJ ............................................. Virginia Beach-Norfolk-Newport News, VA-NC ..................... Visalia-Porterville, CA ............................................................ Waco, TX ............................................................................... Warner Robins, GA ............................................................... 32,457 26,794 40,225 33,823 36,642 37,749 36,071 29,772 33,450 38,087 33,916 27,842 42,932 35,901 38,317 39,408 37,734 30,968 34,679 39,220 4.5 3.9 6.7 6.1 4.6 4.4 4.6 4.0 3.7 3.0 Washington-Arlington-Alexandria, DC-VA-MD-WV ............... Waterloo-Cedar Falls, IA ....................................................... Wausau, WI ........................................................................... Weirton-Steubenville, WV-OH ............................................... Wenatchee, WA ..................................................................... Wheeling, WV-OH ................................................................. Wichita, KS ............................................................................ Wichita Falls, TX .................................................................... Williamsport, PA .................................................................... Wilmington, NC ...................................................................... 58,057 34,329 34,438 31,416 28,340 30,620 38,763 30,785 31,431 32,948 60,711 35,899 35,710 32,893 29,475 31,169 39,662 32,320 32,506 34,239 4.6 4.6 3.7 4.7 4.0 1.8 2.3 5.0 3.4 3.9 Winchester, VA-WV ............................................................... Winston-Salem, NC ............................................................... Worcester, MA ....................................................................... Yakima, WA ........................................................................... Yauco, PR ............................................................................. York-Hanover, PA .................................................................. Youngstown-Warren-Boardman, OH-PA ............................... Yuba City, CA ........................................................................ Yuma, AZ ............................................................................... 34,895 37,712 42,726 28,401 19,001 37,226 33,852 33,642 28,369 36,016 38,921 44,652 29,743 19,380 38,469 34,698 35,058 30,147 3.2 3.2 4.5 4.7 2.0 3.3 2.5 4.2 6.3 1 Includes workers covered by Unemployment Insurance (UI) and Unemployment Compensation for Federal Employees (UCFE) programs. 2 Includes data for Metropolitan Statistical Areas (MSA) as defined by OMB Bulletin No. 04-03 as of February 18, 2004. 3 Each year’s total is based on the MSA definition for the specific year. Annual changes include differences resulting from changes in MSA definitions. 4 Totals do not include the six MSAs within Puerto Rico. Monthly Labor Review • August 2009 85 Current Labor Statistics: Labor Force Data 27. Annual data: Employment status of the population [Numbers in thousands] Employment status 19981 Civilian noninstitutional population........... Civilian labor force............................…… Labor force participation rate............... Employed............................………… Employment-population ratio.......... Unemployed............................……… Unemployment rate........................ Not in the labor force............................… 1 205,220 137,673 67.1 131,463 64.1 6,210 4.5 67,547 19991 207,753 139,368 67.1 133,488 64.3 5,880 4.2 68,385 20001 20011 2002 2003 2004 2005 2006 2007 2008 212,577 142,583 67.1 136,891 64.4 5,692 4.0 69,994 215,092 143,734 66.8 136,933 63.7 6,801 4.7 71,359 217,570 144,863 66.6 136,485 62.7 8,378 5.8 72,707 221,168 146,510 66.2 137,736 62.3 8,774 6.0 74,658 223,357 147,401 66.0 139,252 62.3 8,149 5.5 75,956 226,082 149,320 66.0 141,730 62.7 7,591 5.1 76,762 228,815 151,428 66.2 144,427 63.1 7,001 4.6 77,387 231,867 153,124 66.0 146,047 63.0 7,078 4.6 78,743 233,788 154,287 66.0 145,362 62.2 8,924 5.8 79,501 Not strictly comparable with prior years. 28. Annual data: Employment levels by industry [In thousands] Industry 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Total private employment............................… 106,021 108,686 110,995 110,708 108,828 108,416 109,814 111,899 114,113 115,420 114,792 Total nonfarm employment…………………… Goods-producing............................………… Natural resources and mining................. Construction............................…………… Manufacturing............................………… 125,930 24,354 645 6,149 17,560 128,993 24,465 598 6,545 17,322 131,785 24,649 599 6,787 17,263 131,826 23,873 606 6,826 16,441 130,341 22,557 583 6,716 15,259 129,999 21,816 572 6,735 14,510 131,435 21,882 591 6,976 14,315 133,703 22,190 628 7,336 14,226 136,086 22,531 684 7,691 14,155 137,623 22,221 723 7,614 13,884 137,248 21,404 774 7,175 13,455 Private service-providing.......................... Trade, transportation, and utilities.......... Wholesale trade............................……… Retail trade............................………… Transportation and warehousing......... Utilities............................……………… Information............................…………… Financial activities............................…… Professional and business services…… Education and health services………… Leisure and hospitality…………………… Other services…………………………… 81,667 25,186 5,795 14,609 4,168 613 3,218 7,462 15,147 14,446 11,232 4,976 84,221 25,771 5,893 14,970 4,300 609 3,419 7,648 15,957 14,798 11,543 5,087 86,346 26,225 5,933 15,280 4,410 601 3,630 7,687 16,666 15,109 11,862 5,168 86,834 25,983 5,773 15,239 4,372 599 3,629 7,808 16,476 15,645 12,036 5,258 86,271 25,497 5,652 15,025 4,224 596 3,395 7,847 15,976 16,199 11,986 5,372 86,600 25,287 5,608 14,917 4,185 577 3,188 7,977 15,987 16,588 12,173 5,401 87,932 25,533 5,663 15,058 4,249 564 3,118 8,031 16,394 16,953 12,493 5,409 89,709 25,959 5,764 15,280 4,361 554 3,061 8,153 16,954 17,372 12,816 5,395 91,582 26,276 5,905 15,353 4,470 549 3,038 8,328 17,566 17,826 13,110 5,438 93,199 26,608 6,028 15,491 4,536 553 3,029 8,308 17,962 18,327 13,474 5,491 93,387 26,332 6,012 15,265 4,495 560 2,987 8,192 17,863 18,878 13,615 5,520 19,909 20,307 20,790 21,118 21,513 21,583 21,621 21,804 21,974 22,203 22,457 Government…………………………………… 86 Monthly Labor Review • August 2009 29. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm payrolls, by industry Industry 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Private sector: Average weekly hours.......……................................ Average hourly earnings (in dollars)......................... Average weekly earnings (in dollars)........................ 34.5 13.01 448.56 34.3 13.49 463.15 34.3 14.02 481.01 34.0 14.54 493.79 33.9 14.97 506.75 33.7 15.37 518.06 33.7 15.69 529.09 33.8 16.13 544.33 33.9 16.76 567.87 33.8 17.42 589.72 33.6 18.05 606.84 Goods-producing: Average weekly hours............................................. Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... 40.8 14.23 580.99 40.8 14.71 599.99 40.7 15.27 621.86 39.9 15.78 630.01 39.9 16.33 651.61 39.8 16.80 669.13 40.0 17.19 688.13 40.1 17.60 705.31 40.5 18.02 730.16 40.6 18.67 757.06 40.2 19.31 775.28 44.9 16.20 727.28 44.2 16.33 721.74 44.4 16.55 734.92 44.6 17.00 757.92 43.2 17.19 741.97 43.6 17.56 765.94 44.5 18.07 803.82 45.6 18.72 853.71 45.6 19.90 907.95 45.9 20.96 961.78 45.0 22.42 1008.27 Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Manufacturing: 38.8 16.23 629.75 39.0 16.80 655.11 39.2 17.48 685.78 38.7 18.00 695.89 38.4 18.52 711.82 38.4 18.95 726.83 38.3 19.23 735.55 38.6 19.46 750.22 39.0 20.02 781.21 39.0 20.95 816.06 38.5 21.86 841.46 Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Private service-providing: 41.4 13.45 557.09 41.4 13.85 573.25 41.3 14.32 590.77 40.3 14.76 595.19 40.5 15.29 618.75 40.4 15.74 635.99 40.8 16.14 658.49 40.7 16.56 673.33 41.1 16.81 691.02 41.2 17.26 711.36 40.8 17.72 723.51 Average weekly hours..………................................ Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... 32.8 12.61 413.50 32.7 13.09 427.98 32.7 13.62 445.74 32.5 14.18 461.08 32.5 14.59 473.80 32.3 14.99 484.68 32.3 15.29 494.22 32.4 15.74 509.58 32.5 16.42 532.78 32.4 17.10 554.78 32.3 17.73 572.96 Trade, transportation, and utilities: Average weekly hours............................................. Average hourly earnings (in dollars)....................... Average weekly earnings (in dollars)...................... Wholesale trade: 34.2 12.39 423.30 33.9 12.82 434.31 33.8 13.31 449.88 33.5 13.70 459.53 33.6 14.02 471.27 33.6 14.34 481.14 33.5 14.58 488.42 33.4 14.92 498.43 33.4 15.39 514.34 33.3 15.79 526.38 33.2 16.19 537.00 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Retail trade: 38.6 15.07 582.21 38.6 15.62 602.77 38.8 16.28 631.40 38.4 16.77 643.45 38.0 16.98 644.38 37.9 17.36 657.29 37.8 17.65 667.09 37.7 18.16 685.00 38.0 18.91 718.63 38.2 19.59 748.90 38.2 20.13 769.74 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 30.9 10.05 582.21 30.8 10.45 602.77 30.7 10.86 631.40 30.7 11.29 643.45 30.9 11.67 644.38 30.9 11.90 657.29 30.7 12.08 667.09 30.6 12.36 685.00 30.5 12.57 718.63 30.2 12.76 748.90 30.0 12.90 769.74 Transportation and warehousing: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 38.7 14.12 546.86 37.6 14.55 547.97 37.4 15.05 562.31 36.7 15.33 562.70 36.8 15.76 579.75 36.8 16.25 598.41 37.2 16.52 614.82 37.0 16.70 618.58 36.9 17.28 636.97 36.9 17.73 654.83 36.4 18.39 669.44 Utilities: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 42.0 21.48 902.94 42.0 22.03 924.59 42.0 22.75 955.66 41.4 23.58 977.18 40.9 23.96 979.09 41.1 24.77 1017.27 40.9 25.61 1048.44 41.1 26.68 1095.90 41.4 27.40 1135.34 42.4 27.87 1182.17 42.6 28.84 1230.08 Information: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Financial activities: 36.6 17.67 646.34 36.7 18.40 675.47 36.8 19.07 700.86 36.9 19.80 730.88 36.5 20.20 737.77 36.2 21.01 760.45 36.3 21.40 777.25 36.5 22.06 805.08 36.6 23.23 850.42 36.5 23.94 873.63 36.7 24.74 907.02 Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 36.0 13.93 500.98 35.8 14.47 517.57 35.9 14.98 537.37 35.8 15.59 557.92 35.6 16.17 575.54 35.5 17.14 609.08 35.5 17.52 622.87 35.9 17.95 644.99 35.7 18.80 672.21 35.9 19.64 705.29 35.9 20.28 727.38 Professional and business services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 34.3 14.27 490.00 34.4 14.85 510.99 34.5 15.52 535.07 34.2 16.33 557.84 34.2 16.81 574.66 34.1 17.21 587.02 34.2 17.48 597.56 34.2 18.08 618.87 34.6 19.13 662.27 34.8 20.13 700.15 34.8 21.15 736.55 Education and health services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. 32.2 13.00 418.82 32.1 13.44 431.35 32.2 13.95 449.29 32.3 14.64 473.39 32.4 15.21 492.74 32.3 15.64 505.69 32.4 16.15 523.78 32.6 16.71 544.59 32.5 17.38 564.94 32.6 18.11 590.18 32.5 18.78 611.03 26.2 7.67 200.82 26.1 7.96 208.05 26.1 8.32 217.20 25.8 8.57 220.73 25.8 8.81 227.17 25.6 9.00 230.42 25.7 9.15 234.86 25.7 9.38 241.36 25.7 9.75 250.34 25.5 10.41 265.45 25.2 10.83 272.97 32.6 11.79 384.25 32.5 12.26 398.77 32.5 12.73 413.41 32.3 13.27 428.64 32.0 13.72 439.76 31.4 13.84 434.41 31.0 13.98 433.04 30.9 14.34 443.37 30.9 14.77 456.50 30.9 15.42 476.80 30.8 15.86 488.22 Natural resources and mining Average weekly hours............................................ Average hourly earnings (in dollars)...................... Average weekly earnings (in dollars)..................... Construction: Leisure and hospitality: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. Other services: Average weekly hours......................................... Average hourly earnings (in dollars)................... Average weekly earnings (in dollars).................. NOTE: Data reflect the conversion to the 2002 version of the North American Industry Classification System (NAICS), replacing the Standard Industrial Classification (SIC) system. N AICS-based data by industry are not comparable with SIC-based data. Monthly Labor Review • August 2009 87 Current Labor Statistics: Compensation & Industrial Relations 30. Employment Cost Index, compensation,1 by occupation and industry group [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 2 Civilian workers ……….…….........…………………………………….… 105.0 106.1 106.7 107.6 108.3 109.2 109.5 109.9 110.3 0.4 1.8 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… 105.5 105.2 105.7 104.8 103.6 105.5 106.7 106.2 107.0 105.5 104.1 106.4 107.2 106.6 107.6 106.4 105.2 107.1 108.3 108.2 108.4 106.8 105.0 108.0 109.0 108.9 109.0 107.7 106.1 108.6 110.1 109.7 110.4 108.2 106.0 109.5 110.4 109.8 110.7 108.3 105.5 110.0 110.9 110.0 111.3 108.4 104.3 110.8 111.1 110.1 111.6 108.7 104.5 111.3 .2 .1 .3 .3 .2 .5 1.9 1.1 2.4 .9 -1.5 2.5 Natural resources, construction, and maintenance………… Construction and extraction……………………………… Installation, maintenance, and repair…………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 105.1 105.7 104.4 103.5 102.8 104.4 105.5 106.1 106.5 105.6 104.2 103.3 105.3 106.9 106.8 107.4 106.2 104.7 104.1 105.6 107.7 107.7 108.5 106.7 105.6 104.8 106.6 108.4 108.4 109.6 107.0 106.2 105.3 107.3 109.1 109.3 110.3 108.0 106.9 105.9 108.1 110.2 109.8 110.8 108.6 107.2 106.2 108.4 110.6 110.1 111.0 109.1 108.0 107.2 108.9 111.5 110.7 111.6 109.5 108.5 107.7 109.5 111.9 .5 .5 .4 .5 .5 .6 .4 2.1 1.8 2.3 2.2 2.3 2.1 2.6 Workers by industry Goods-producing……………………………………………… Manufacturing………………………………………………… Service-providing……………………………………………… Education and health services…………………………… Health care and social assistance……………………… Hospitals………………………………………………… Nursing and residential care facilities……………… Education services……………………………………… Elementary and secondary schools………………… 103.9 102.9 105.2 105.5 106.1 105.7 105.0 104.9 105.0 104.4 103.2 106.4 107.2 107.1 106.7 105.6 107.3 107.4 105.0 103.8 107.0 107.9 107.9 107.5 106.3 107.9 107.9 106.1 104.7 107.8 108.6 108.9 108.4 107.3 108.3 108.2 106.8 105.1 108.5 109.2 109.6 109.2 108.2 108.9 108.8 107.3 105.6 109.5 110.8 110.4 110.2 109.0 111.1 111.1 107.5 105.9 109.8 111.1 110.8 110.8 109.6 111.3 111.4 108.0 106.5 110.3 111.7 111.7 111.7 110.3 111.8 111.9 108.2 106.7 110.6 112.2 112.2 112.3 110.8 112.1 112.1 .2 .2 .3 .4 .4 .5 .5 .3 .2 1.3 1.5 1.9 2.7 2.4 2.8 2.4 2.9 3.0 106.6 108.0 109.1 109.7 110.1 111.6 112.0 113.0 113.8 .7 3.4 104.9 105.7 106.3 107.3 108.0 108.7 108.9 109.3 109.6 .3 1.5 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… Natural resources, construction, and maintenance………… Construction and extraction………………………………… Installation, maintenance, and repair……………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 105.5 105.1 105.9 104.7 103.6 105.4 105.0 105.7 104.1 103.3 102.8 104.1 105.2 106.4 106.0 106.7 105.3 104.2 106.0 105.9 106.5 105.2 103.9 103.2 104.9 106.4 106.8 106.3 107.3 106.1 105.2 106.7 106.7 107.4 105.8 104.5 104.0 105.3 107.0 108.1 108.0 108.3 106.6 105.0 107.8 107.6 108.6 106.3 105.5 104.8 106.4 107.8 108.9 108.7 109.0 107.5 106.2 108.5 108.3 109.7 106.6 106.0 105.2 107.2 108.7 109.6 109.3 109.9 107.9 106.0 109.2 109.0 110.3 107.4 106.6 105.8 107.7 109.4 109.9 109.5 110.3 107.9 105.5 109.6 109.6 110.8 108.1 106.9 106.1 107.9 109.8 110.4 109.6 111.0 107.9 104.3 110.5 109.9 110.9 108.6 107.7 107.1 108.4 110.7 110.5 109.7 111.1 108.3 104.5 110.9 110.3 111.5 108.9 108.1 107.6 108.9 110.9 .1 .1 .1 .4 .2 .4 .4 .5 .3 .4 .5 .5 .2 1.5 .9 1.9 .7 -1.6 2.2 1.8 1.6 2.2 2.0 2.3 1.6 2.0 Workers by industry and occupational group Goods-producing industries…………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. 103.9 103.8 103.7 105.3 102.9 104.4 104.3 104.1 106.1 103.3 105.0 104.4 104.8 107.0 104.0 106.1 106.1 105.1 108.1 104.8 106.8 106.6 106.3 109.0 105.3 107.2 106.7 106.7 109.8 105.8 107.5 106.6 107.1 110.4 106.2 107.9 106.8 107.3 110.4 107.0 108.2 106.7 107.4 110.9 107.5 .3 -.1 .1 .5 .5 1.3 .1 1.0 1.7 2.1 Construction………………………………………………… Manufacturing………………………………………………… Management, professional, and related………………… Sales and office…………………………………………… Natural resources, construction, and maintenance…… Production, transportation, and material moving…….. 105.9 102.9 103.3 103.2 102.4 102.6 106.9 103.2 103.3 103.5 102.8 103.1 107.6 103.8 103.5 104.3 103.9 103.8 108.9 104.7 104.9 105.0 104.6 104.5 110.1 105.1 105.2 106.1 104.5 105.0 110.6 105.6 105.4 106.7 105.3 105.5 110.9 105.9 105.4 107.0 106.0 105.8 110.9 106.5 105.7 107.3 106.6 106.7 111.2 106.7 105.7 107.1 107.1 107.2 .3 .2 .0 -.2 .5 .5 1.0 1.5 .5 .9 2.5 2.1 Service-providing industries………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. Service occupations………………………………………… 105.2 105.9 104.8 104.5 104.0 105.3 106.1 106.8 105.4 105.7 104.7 106.4 106.7 107.3 106.3 106.2 105.2 107.1 107.7 108.5 106.8 106.7 106.4 107.9 108.5 109.3 107.7 107.3 107.0 108.7 109.1 110.2 108.0 107.8 107.6 109.5 109.4 110.6 108.0 108.4 107.8 109.8 109.8 111.1 108.0 109.0 108.5 110.7 110.1 111.2 108.4 109.5 109.0 111.0 .3 .1 .4 .5 .5 .3 1.5 1.7 .6 2.1 1.9 2.1 Trade, transportation, and utilities………………………… 104.2 104.7 105.5 106.1 107.3 107.6 107.5 107.8 108.1 .3 .7 3 Public administration ……………………………………… Private industry workers……………………………………… See footnotes at end of table. 88 Monthly Labor Review • August 2009 30. Continued—Employment Cost Index, compensation,1 by occupation and industry group [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 Wholesale trade…………………………………………… Retail trade………………………………………………… Transportation and warehousing……………………… Utilities……………………………………………………… Information………………………………………………… Financial activities………………………………………… Finance and insurance………………………………… Real estate and rental and leasing…………………… Professional and business services……………………… Education and health services…………………………… Education services……………………………………… Health care and social assistance…………………… Hospitals……………………………………………… Leisure and hospitality…………………………………… Accommodation and food services…………………… Other services, except public administration…………… 104.6 103.9 104.0 104.7 105.6 104.6 104.9 103.0 105.9 105.7 104.9 105.9 105.6 106.0 106.4 106.1 104.2 105.1 104.5 105.0 105.8 105.4 105.7 104.1 106.9 106.9 106.7 106.9 106.5 107.5 108.1 107.1 105.3 106.1 104.5 105.6 106.1 105.6 106.1 103.7 107.5 107.7 107.5 107.8 107.3 108.1 108.6 107.6 105.7 106.6 105.6 106.5 106.1 106.8 107.0 105.5 109.0 108.6 108.1 108.8 108.2 109.0 109.5 108.7 107.2 107.6 106.4 108.1 106.2 107.3 107.7 105.7 109.9 109.4 109.1 109.4 109.1 109.3 110.0 109.4 107.1 108.2 106.8 108.1 107.2 107.4 107.6 106.4 110.8 110.3 111.4 110.1 110.1 110.6 111.4 109.9 106.8 108.1 106.9 108.9 107.4 107.1 107.2 106.6 111.6 110.6 111.3 110.5 110.7 111.4 112.1 109.9 107.1 108.3 107.4 109.6 107.7 106.8 106.9 106.6 111.9 111.5 111.9 111.5 111.5 112.2 113.0 110.8 106.9 108.8 107.9 110.9 107.5 107.9 108.1 106.9 111.9 111.9 112.0 111.9 112.0 112.0 112.6 110.8 -0.2 .5 .5 1.2 -.2 1.0 1.1 .3 .0 .4 .1 .4 .4 -.2 -.4 .0 -0.3 1.1 1.4 2.6 1.2 .6 .4 1.1 1.8 2.3 2.7 2.3 2.7 2.5 2.4 1.3 105.7 107.6 108.4 108.9 109.4 111.3 111.6 112.3 112.9 .5 3.2 Workers by occupational group Management, professional, and related……………………… Professional and related…………………………………… Sales and office………………………………………………… Office and administrative support………………………… Service occupations…………………………………………… 105.4 105.3 106.2 106.4 106.3 107.5 107.5 107.9 108.2 108.0 108.3 108.2 108.6 108.9 109.1 108.8 108.6 108.8 109.3 109.7 109.3 109.1 109.3 109.8 110.0 111.3 111.1 111.0 111.4 111.9 111.6 111.4 111.3 111.8 112.4 112.0 111.9 112.4 112.8 113.4 112.6 112.4 113.0 113.3 114.0 .5 .4 .5 .4 .5 3.0 3.0 3.4 3.2 3.6 Workers by industry Education and health services……………………………… Education services……………………………………… Schools………………………………………………… Elementary and secondary schools……………… Health care and social assistance……………………… Hospitals………………………………………………… 105.3 105.0 104.9 105.0 107.6 106.3 107.5 107.4 107.4 107.4 108.6 107.5 108.2 108.0 108.0 108.0 109.3 108.2 108.6 108.4 108.4 108.3 110.1 109.2 109.1 108.8 108.8 108.8 111.1 109.7 111.2 111.0 111.0 111.1 112.7 110.8 111.5 111.2 111.2 111.4 113.2 111.3 111.9 111.8 111.8 112.0 113.3 112.4 112.4 112.1 112.1 112.2 114.8 113.5 .4 .3 .3 .2 1.3 1.0 3.0 3.0 3.0 3.1 3.3 3.5 106.6 108.0 109.1 109.7 110.1 111.6 112.0 113.0 113.8 .7 3.4 State and local government workers………………………… 3 Public administration ……………………………………… 1 Cost (cents per hour worked) measured in the Employment Cost Index consists of wages, salaries, and employer cost of employee benefits. 2 Consists of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers. 3 Consists of legislative, judicial, administrative, and regulatory activities. NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. Monthly Labor Review • August 2009 89 Current Labor Statistics: Compensation & Industrial Relations 31. Employment Cost Index, wages and salaries, by occupation and industry group [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 1 Civilian workers ……….…….........…………………………………….… 105.0 106.0 106.7 107.6 108.4 109.3 109.6 110.0 110.4 0.4 1.8 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… 105.4 105.4 105.3 104.8 103.9 105.3 106.6 106.4 106.7 105.4 104.3 106.1 107.1 106.7 107.4 106.2 105.5 106.8 108.2 108.2 108.3 106.7 105.2 107.8 109.0 109.0 109.0 107.7 106.6 108.5 110.1 109.8 110.3 108.1 106.3 109.3 110.5 110.1 110.7 108.1 105.6 109.8 111.0 110.4 111.2 108.1 104.3 110.6 111.2 110.5 111.5 108.6 104.7 111.2 .2 .1 .3 .5 .4 .5 2.0 1.4 2.3 .8 -1.8 2.5 Natural resources, construction, and maintenance………… Construction and extraction……………………………… Installation, maintenance, and repair…………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 105.1 105.7 104.4 103.9 103.6 104.2 105.3 106.3 106.6 105.8 104.7 104.3 105.1 106.5 107.1 107.7 106.4 105.1 104.7 105.5 107.3 108.1 109.0 107.0 106.1 105.7 106.6 108.0 109.0 109.9 107.8 106.9 106.5 107.3 108.7 109.9 110.7 108.8 107.7 107.2 108.2 109.9 110.6 111.3 109.6 108.0 107.5 108.5 110.3 110.7 111.4 110.0 108.5 108.2 108.8 111.2 111.2 111.8 110.5 109.0 108.7 109.5 111.6 .5 .4 .5 .5 .5 .6 .4 2.0 1.7 2.5 2.0 2.1 2.1 2.7 Workers by industry Goods-producing……………………………………………… Manufacturing………………………………………………… Service-providing……………………………………………… Education and health services…………………………… Health care and social assistance……………………… Hospitals………………………………………………… Nursing and residential care facilities……………… Education services……………………………………… Elementary and secondary schools………………… 104.7 103.9 105.1 104.9 105.9 105.6 104.7 104.0 103.8 105.4 104.5 106.2 106.6 107.1 106.7 105.8 106.2 106.0 106.0 104.9 106.8 107.4 107.9 107.4 106.4 106.9 106.6 107.1 105.9 107.7 108.0 108.9 108.4 107.4 107.3 107.0 108.0 106.7 108.5 108.7 109.6 109.4 108.1 107.9 107.5 108.6 107.4 109.4 110.2 110.4 110.5 109.1 110.0 109.9 109.0 107.7 109.7 110.5 110.9 111.3 109.7 110.2 110.1 109.2 108.1 110.2 111.0 111.7 112.0 110.3 110.5 110.4 109.5 108.4 110.5 111.4 112.2 112.6 110.9 110.7 110.5 .3 .3 .3 .4 .4 .5 .5 .2 .1 1.4 1.6 1.8 2.5 2.4 2.9 2.6 2.6 2.8 105.2 106.4 107.4 108.2 108.6 109.9 110.4 111.3 112.3 .9 3.4 105.1 106.0 106.6 107.6 108.4 109.1 109.4 109.8 110.1 .3 1.6 Workers by occupational group Management, professional, and related……………………… Management, business, and financial…………………… Professional and related…………………………………… Sales and office………………………………………………… Sales and related…………………………………………… Office and administrative support………………………… Natural resources, construction, and maintenance………… Construction and extraction………………………………… Installation, maintenance, and repair……………………… Production, transportation, and material moving…………… Production…………………………………………………… Transportation and material moving……………………… Service occupations…………………………………………… 105.8 105.5 106.0 104.8 104.0 105.4 105.1 105.8 104.2 103.8 103.6 104.1 105.3 106.7 106.3 107.0 105.3 104.4 106.0 106.2 106.7 105.6 104.5 104.2 105.0 106.5 107.2 106.6 107.6 106.2 105.5 106.7 107.1 107.8 106.1 105.0 104.6 105.4 107.1 108.5 108.2 108.7 106.7 105.3 107.7 108.1 109.2 106.8 106.0 105.6 106.5 107.9 109.3 109.0 109.5 107.7 106.6 108.5 109.0 110.1 107.6 106.8 106.4 107.4 108.8 110.1 109.7 110.4 108.0 106.4 109.2 109.8 110.8 108.5 107.5 107.2 108.0 109.7 110.5 110.0 110.9 108.0 105.7 109.7 110.5 111.5 109.3 107.8 107.4 108.3 110.1 111.1 110.3 111.6 107.9 104.3 110.6 110.6 111.4 109.7 108.3 108.1 108.5 111.0 111.1 110.3 111.8 108.3 104.7 111.1 111.0 111.7 110.2 108.8 108.5 109.2 111.2 .0 .0 .2 .4 .4 .5 .4 .3 .5 .5 .4 .6 .2 1.6 1.2 2.1 .6 -1.8 2.4 1.8 1.5 2.4 1.9 2.0 1.7 2.2 Workers by industry and occupational group Goods-producing industries…………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. 104.7 105.3 104.1 105.6 103.7 105.4 105.9 104.7 106.5 104.4 106.0 106.0 105.5 107.6 104.8 107.1 107.7 105.8 108.8 105.7 108.0 108.4 107.2 109.6 106.6 108.6 108.7 107.6 110.5 107.3 109.0 108.8 107.9 111.3 107.6 109.2 109.3 108.1 111.1 108.0 109.5 109.3 108.3 111.4 108.5 .3 .0 .2 .3 .5 1.4 .8 1.0 1.6 1.8 Construction………………………………………………… Manufacturing………………………………………………… Management, professional, and related………………… Sales and office…………………………………………… Natural resources, construction, and maintenance…… Production, transportation, and material moving…….. 106.0 103.9 104.6 103.2 104.3 103.6 107.0 104.5 105.0 103.9 105.0 104.2 107.8 104.9 105.3 104.7 105.9 104.5 109.0 105.9 106.7 105.5 106.8 105.4 110.0 106.7 107.2 106.9 107.1 106.3 110.6 107.4 107.6 107.6 108.1 107.1 111.1 107.7 107.8 108.1 109.0 107.3 111.2 108.1 108.4 108.2 108.8 107.7 111.4 108.4 108.5 108.2 109.2 108.2 .2 .3 .1 .0 .4 .5 1.3 1.6 1.2 1.2 2.0 1.8 Service-providing industries………………………………… Management, professional, and related…………………… Sales and office……………………………………………… Natural resources, construction, and maintenance……… Production, transportation, and material moving……….. Service occupations………………………………………… 105.3 105.9 104.9 104.3 104.0 105.3 106.1 106.8 105.4 105.7 104.6 106.6 106.8 107.4 106.3 106.3 105.2 107.2 107.7 108.6 106.8 106.9 106.3 108.0 108.6 109.4 107.7 108.0 107.1 108.8 109.3 110.3 108.0 108.6 107.8 109.7 109.6 110.8 108.0 109.3 108.1 110.1 110.0 111.4 107.9 109.9 108.6 111.0 110.3 111.5 108.3 110.5 109.3 111.3 .3 .1 .4 .5 .6 .3 1.6 1.9 .6 2.3 2.1 2.3 Trade, transportation, and utilities………………………… 104.3 104.6 105.5 105.9 107.2 107.5 107.4 107.8 108.2 .4 .9 2 Public administration ……………………………………… Private industry workers……………………………………… 90 Monthly Labor Review • August 2009 31. Continued—Employment Cost Index, wages and salaries, by occupation and industry group [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 Wholesale trade…………………………………………… Retail trade………………………………………………… Transportation and warehousing……………………… Utilities……………………………………………………… Information………………………………………………… Financial activities………………………………………… Finance and insurance………………………………… Real estate and rental and leasing…………………… Professional and business services……………………… Education and health services…………………………… Education services……………………………………… Health care and social assistance…………………… Hospitals……………………………………………… Leisure and hospitality…………………………………… Accommodation and food services…………………… Other services, except public administration…………… 104.8 104.2 103.7 105.5 104.9 104.9 105.5 102.4 105.9 105.6 104.6 105.8 105.4 106.4 106.5 106.1 104.0 105.1 104.1 106.1 105.2 106.0 106.5 103.6 106.7 106.9 106.4 107.0 106.5 108.1 108.4 107.3 105.2 106.1 104.2 106.8 105.3 105.9 106.6 103.1 107.5 107.7 107.4 107.8 107.2 108.8 109.0 107.9 105.2 106.4 105.0 108.0 105.3 107.2 107.9 104.5 109.1 108.6 107.9 108.7 108.2 109.7 110.0 109.2 107.2 107.6 106.0 109.3 106.3 107.7 108.4 104.7 110.0 109.2 108.6 109.4 109.2 109.9 110.4 109.9 106.8 108.1 106.7 109.3 107.3 107.7 108.2 105.3 111.0 110.2 110.8 110.1 110.3 111.4 111.9 110.4 106.4 108.1 106.9 109.6 107.5 107.2 107.6 105.7 111.9 110.6 110.8 110.6 111.1 112.3 112.8 110.4 106.8 108.3 107.2 111.0 107.8 106.8 107.1 105.6 112.3 111.4 111.1 111.5 111.8 113.1 113.7 111.4 106.5 108.9 107.9 112.0 108.1 107.9 108.5 105.8 112.2 111.8 111.2 111.9 112.3 112.8 113.2 111.4 -0.3 .6 .7 .9 .3 1.0 1.3 .2 -.1 .4 .1 .4 .4 -.3 -.4 .0 -0.7 1.2 1.8 2.5 1.7 .2 .1 1.1 2.0 2.4 2.4 2.3 2.8 2.6 2.5 1.4 104.6 106.4 107.1 107.7 108.2 110.1 110.4 110.9 111.5 .5 3.0 Workers by occupational group Management, professional, and related……………………… Professional and related…………………………………… Sales and office………………………………………………… Office and administrative support………………………… Service occupations…………………………………………… 104.3 104.2 104.8 105.0 105.2 106.3 106.3 106.3 106.5 106.5 107.0 107.0 107.0 107.3 107.7 107.6 107.5 107.4 107.8 108.3 108.2 108.1 107.9 108.3 108.6 110.1 110.1 109.3 109.7 110.4 110.4 110.3 109.7 110.1 110.9 110.7 110.6 110.5 111.0 112.0 111.2 111.1 111.2 111.6 112.7 .5 .5 .6 .5 .6 2.8 2.8 3.1 3.0 3.8 Workers by industry Education and health services……………………………… Education services……………………………………… Schools………………………………………………… Elementary and secondary schools……………… Health care and social assistance……………………… Hospitals………………………………………………… 104.2 103.9 103.9 103.8 107.2 106.5 106.3 106.1 106.1 106.0 108.2 107.6 107.1 106.8 106.8 106.6 109.2 108.6 107.5 107.2 107.2 106.9 110.1 109.8 108.1 107.7 107.7 107.5 111.0 110.3 110.2 109.9 109.9 109.8 112.8 111.4 110.5 110.1 110.1 110.1 113.4 112.1 110.7 110.4 110.4 110.3 113.1 112.8 111.1 110.7 110.7 110.5 114.8 114.0 .4 .3 .3 .2 1.5 1.1 2.8 2.8 2.8 2.8 3.4 3.4 105.2 106.4 107.4 108.2 108.6 109.9 110.4 111.3 112.3 .9 3.4 State and local government workers………………………… 2 Public administration ……………………………………… 1 Consists of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers. 2 Consists of legislative, judicial, administrative, and regulatory activities. NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. Monthly Labor Review • August 2009 91 Current Labor Statistics: Compensation & Industrial Relations 32. Employment Cost Index, benefits, by occupation and industry group [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 Civilian workers…………………………………………………. 105.1 106.1 106.8 107.6 108.1 108.9 109.1 109.7 110.0 0.3 1.8 Private industry workers………………………………………… 104.3 105.0 105.6 106.5 107.0 107.5 107.7 108.2 108.4 .2 1.3 Workers by occupational group Management, professional, and related……………………… Sales and office………………………………………………… Natural resources, construction, and maintenance………… Production, transportation, and material moving…………… 104.9 104.3 104.8 102.4 105.6 105.2 105.3 102.7 106.0 106.0 105.9 103.7 107.3 106.5 106.5 104.4 107.9 107.0 107.0 104.5 108.5 107.6 107.5 104.8 108.5 107.8 107.7 105.1 108.8 108.0 108.2 106.4 108.8 108.1 108.8 106.8 .0 .1 .6 .4 .8 1.0 1.7 2.2 Service occupations…………………………………………… 105.1 106.0 106.7 107.6 108.5 108.7 108.8 109.7 110.0 .3 1.4 Goods-producing……………………………………………… 102.2 Manufacturing………………………………………………… 101.0 Service-providing……………………………………………… 105.2 102.4 100.7 106.0 103.2 101.7 106.6 104.0 102.3 107.6 104.4 102.2 108.1 104.6 102.3 108.7 104.7 102.5 108.9 105.4 103.5 109.3 105.7 103.6 109.5 .3 .1 .2 1.2 1.4 1.3 110.3 111.0 111.4 111.8 113.9 114.2 115.2 115.8 .5 3.6 Workers by industry State and local government workers………………………… 108.0 NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior 92 Monthly Labor Review • August 2009 to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. 33. Employment Cost Index, private industry workers by bargaining status and region [December 2005 = 100] 2007 Series June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. Percent change June 3 months ended 12 months ended June 2009 COMPENSATION Workers by bargaining status1 Union………………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 103.9 102.8 100.0 104.7 104.4 103.1 100.0 105.4 105.1 104.0 101.0 106.0 105.9 104.6 101.4 107.0 106.7 105.6 101.7 107.5 107.4 106.2 102.1 108.3 108.0 106.9 102.8 108.8 109.1 108.0 104.4 109.9 109.8 108.9 104.8 110.6 0.6 .8 .4 .6 2.9 3.1 3.0 2.9 Nonunion…………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 105.1 104.2 103.7 105.3 105.9 104.8 104.1 106.2 106.5 105.4 104.6 106.8 107.5 106.5 105.6 107.7 108.3 107.1 106.2 108.6 108.9 107.6 106.6 109.2 109.1 107.7 106.8 109.4 109.4 107.9 107.1 109.8 109.6 108.0 107.3 110.0 .2 .1 .2 .2 1.2 .8 1.0 1.3 Workers by region1 Northeast…………………………………………………………… South………………………………………………………………… Midwest……………………………………………………………… West………………………………………………………………… 105.1 105.3 104.2 104.9 106.2 106.1 104.6 105.7 106.8 106.7 105.3 106.5 107.4 107.8 106.0 107.8 108.1 108.5 107.0 108.4 108.7 109.1 107.4 109.3 109.5 109.3 107.6 109.4 109.8 109.8 107.9 109.9 110.2 110.1 108.1 110.1 .4 .3 .2 .2 1.9 1.5 1.0 1.6 Workers by bargaining status1 Union………………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 103.7 103.6 102.5 103.8 104.4 104.3 102.9 104.6 104.7 104.3 102.6 104.9 105.5 105.2 103.4 105.8 106.7 106.4 104.4 106.9 107.4 107.1 104.9 107.7 108.1 107.7 105.5 108.3 108.8 108.2 106.0 109.2 109.6 108.8 106.4 110.1 .7 .6 .4 .8 2.7 2.3 1.9 3.0 Nonunion…………………………………………………………… Goods-producing………………………………………………… Manufacturing………………………………………………… Service-providing………………………………………………… 105.3 105.0 104.2 105.4 106.2 105.8 104.9 106.3 106.9 106.4 105.5 107.0 107.9 107.7 106.6 107.9 108.7 108.4 107.3 108.8 109.4 109.0 108.0 109.4 109.6 109.3 108.2 109.7 110.0 109.5 108.6 110.1 110.2 109.7 108.9 110.3 .2 .2 .3 .2 1.4 1.2 1.5 1.4 Workers by region1 Northeast…………………………………………………………… South………………………………………………………………… Midwest……………………………………………………………… West………………………………………………………………… 105.0 105.6 104.4 105.4 106.1 106.5 105.0 106.2 106.6 107.0 105.6 107.0 107.5 108.1 106.3 108.3 108.2 109.1 107.5 108.9 108.7 109.8 107.9 109.9 109.6 110.0 108.0 110.1 109.9 110.4 108.4 110.5 110.3 110.7 108.6 110.8 .4 .3 .2 .3 1.9 1.5 1.0 1.7 WAGES AND SALARIES 1 The indexes are calculated differently from those for the occupation and industry groups. For a detailed description of the index calculation, see the Monthly Labor Review Technical Note, "Estimation procedures for the Employment Cost Index," May 1982. NOTE: The Employment Cost Index data reflect the conversion to the 2002 North American Classification System (NAICS) and the 2000 Standard Occupational Classification (SOC) system. The NAICS and SOC data shown prior to 2006 are for informational purposes only. Series based on NAICS and SOC became the official BLS estimates starting in March 2006. Monthly Labor Review • August 2009 93 Current Labor Statistics: Compensation & Industrial Relations 34. National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 1 2006 All retirement Percentage of workers with access All workers……………………………………………………… 57 59 60 60 White-collar occupations 2 …………………………………… 67 69 70 69 - - - - - 76 64 Management, professional, and related ………………. 61 Sales and office …………………………………………… - - - - Blue-collar occupations 2……………………………………… 59 59 60 62 - - - - - 61 Natural resources, construction, and maintenance...… - - - - 65 Service occupations…………………………………………… Production, transportation, and material moving…...… 28 31 32 34 36 Full-time………………………………………………………… 67 68 69 69 70 Part-time……………………………………………………… 24 27 27 29 31 Union…………………………………………………………… 86 84 88 84 84 Non-union……………………………………………………… 54 56 56 57 58 Average wage less than $15 per hour……...……………… 45 46 46 47 47 Average wage $15 per hour or higher……...……………… 76 77 78 77 76 Goods-producing industries………………………………… 70 70 71 73 70 Service-providing industries………………………………… 53 55 56 56 58 Establishments with 1-99 workers…………………………… 42 44 44 44 45 Establishments with 100 or more workers………………… 75 77 78 78 78 All workers……………………………………………………… 49 50 50 51 51 White-collar occupations 2 …………………………………… 59 61 61 60 - - - - - 69 54 Percentage of workers participating Management, professional, and related ………………. Sales and office …………………………………………… - - - - Blue-collar occupations 2……………………………………… 50 50 51 52 - - - - - 51 Natural resources, construction, and maintenance…... - - - - 54 Service occupations…………………………………………… Production, transportation, and material moving…...… 21 22 22 24 25 Full-time………………………………………………………… 58 60 60 60 60 Part-time……………………………………………………… 18 20 19 21 23 Union…………………………………………………………… 83 81 85 80 81 Non-union……………………………………………………… 45 47 46 47 47 Average wage less than $15 per hour……...……………… 35 36 35 36 36 Average wage $15 per hour or higher……...……………… 70 71 71 70 69 Goods-producing industries………………………………… 63 63 64 64 61 Service-providing industries………………………………… 45 47 47 47 48 Establishments with 1-99 workers…………………………… 35 37 37 37 37 Establishments with 100 or more workers………………… 65 67 67 67 66 - - 85 85 84 20 21 22 21 21 23 24 25 23 - - - - - 29 19 3 Take-up rate (all workers) …………………………………… Defined Benefit Percentage of workers with access All workers……………………………………………………… 2 White-collar occupations …………………………………… Management, professional, and related ………………. Sales and office …………………………………………… 2 Blue-collar occupations ……………………………………… Natural resources, construction, and maintenance...… - - - 26 26 25 - - - - - 26 26 Production, transportation, and material moving…...… - - - - Service occupations…………………………………………… 8 6 7 8 8 Full-time………………………………………………………… 24 25 25 24 24 Part-time……………………………………………………… 8 9 10 9 10 Union…………………………………………………………… 74 70 73 70 69 Non-union……………………………………………………… 15 16 16 15 15 Average wage less than $15 per hour……...……………… 12 11 12 11 11 Average wage $15 per hour or higher……...……………… 34 35 35 34 33 Goods-producing industries………………………………… 31 32 33 32 29 Service-providing industries………………………………… 17 18 19 18 19 9 9 10 9 9 34 35 37 35 34 Establishments with 1-99 workers…………………………… Establishments with 100 or more workers………………… See footnotes at end of table. 94 24 Monthly Labor Review • August 2009 34. Continued—National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 2006 1 Percentage of workers participating All workers……………………………………………………… 2 White-collar occupations …………………………………… Management, professional, and related ………………. Sales and office …………………………………………… Blue-collar occupations 2…………………………………… Natural resources, construction, and maintenance...… Production, transportation, and material moving…...… Service occupations………………………………………… Full-time……………………………………………………… Part-time……………………………………………………… Union…………………………………………………………… Non-union……………………………………………………… Average wage less than $15 per hour……...……………… 20 22 24 7 24 8 72 15 11 21 24 25 6 24 9 69 15 11 21 24 26 7 25 9 72 15 11 20 22 25 7 23 8 68 14 10 20 28 17 25 25 7 23 9 67 15 10 Average wage $15 per hour or higher……...……………… 33 35 34 33 32 Goods-producing industries………………………………… 31 31 32 31 28 Service-providing industries………………………………… 16 18 18 17 18 Establishments with 1-99 workers………………………… 8 9 9 9 9 Establishments with 100 or more workers………………… 33 34 36 33 32 Take-up rate (all workers) 3…………………………………… - - 97 96 95 All workers……………………………………………………… 51 53 53 54 55 White-collar occupations 2 …………………………………… 62 64 64 65 - - - - - 71 60 Defined Contribution Percentage of workers with access Management, professional, and related ………………. - - - - Blue-collar occupations 2…………………………………… Sales and office …………………………………………… 49 49 50 53 - Natural resources, construction, and maintenance...… - - - - 51 56 Production, transportation, and material moving…...… - - - - Service occupations………………………………………… 23 27 28 30 32 Full-time……………………………………………………… 60 62 62 63 64 Part-time……………………………………………………… 21 23 23 25 27 Union…………………………………………………………… 45 48 49 50 49 Non-union……………………………………………………… 51 53 54 55 56 Average wage less than $15 per hour……...……………… 40 41 41 43 44 Average wage $15 per hour or higher……...……………… 67 68 69 69 69 Goods-producing industries………………………………… 60 60 61 63 62 Service-providing industries………………………………… 48 50 51 52 53 Establishments with 1-99 workers………………………… 38 40 40 41 42 Establishments with 100 or more workers………………… 65 68 69 70 70 All workers……………………………………………………… 40 42 42 43 43 White-collar occupations 2 …………………………………… 51 53 53 53 - - - - - 60 47 Percentage of workers participating Management, professional, and related ………………. - - - - Blue-collar occupations 2…………………………………… Sales and office …………………………………………… 38 38 38 40 - Natural resources, construction, and maintenance...… - - - - 40 41 Production, transportation, and material moving…...… - - - - Service occupations………………………………………… 16 18 18 20 20 Full-time……………………………………………………… 48 50 50 51 50 Part-time……………………………………………………… 14 14 14 16 18 Union…………………………………………………………… 39 42 43 44 41 Non-union……………………………………………………… 40 42 41 43 43 Average wage less than $15 per hour……...……………… 29 30 29 31 30 Average wage $15 per hour or higher……...……………… 57 59 59 58 57 Goods-producing industries………………………………… 49 49 50 51 49 Service-providing industries………………………………… 37 40 39 40 41 Establishments with 1-99 workers………………………… 31 32 32 33 33 Establishments with 100 or more workers………………… 51 53 53 54 53 - - 78 79 77 Take-up rate (all workers) 3…………………………………… See footnotes at end of table. Monthly Labor Review • August 2009 95 Current Labor Statistics: Compensation & Industrial Relations 34. Continued—National Compensation Survey: Retirement benefits in private industry by access, participation, and selected series, 2003–2007 Series Year 2003 2004 2005 2007 1 2006 Employee Contribution Requirement Employee contribution required………………………… Employee contribution not required……………………… Not determinable…………………………………………… - - 61 31 8 61 33 6 65 35 0 Percent of establishments Offering retirement plans…………………………………… Offering defined benefit plans……………………………… Offering defined contribution plans………………………. 47 10 45 48 10 46 51 11 48 48 10 47 46 10 44 1 The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC) System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable. Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system. Only service occupations are considered comparable. 2 The white-collar and blue-collar occupation series were discontinued effective 2007. 3 The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan. Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. 96 Monthly Labor Review • August 2009 35. National Compensation Survey: Health insurance benefits in private industry by access, particpation, and selected series, 2003-2007 Series Year 2003 2004 2005 2007 2006 1 Medical insurance Percentage of workers with access All workers………………………………………………………………………… 60 69 70 71 2 White-collar occupations ……………………………………………………… 65 76 77 77 - - - - - 85 71 Management, professional, and related ………………………………… Sales and office……………………………………………………………… Blue-collar occupations 2……………………………………………………… Natural resources, construction, and maintenance……………………… 71 - - - - 64 76 77 77 - - - - - 76 Production, transportation, and material moving………………………… - - - - 78 Service occupations…………………………………………………………… 38 42 44 45 46 Full-time………………………………………………………………………… 73 84 85 85 85 Part-time………………………………………………………………………… 17 20 22 22 24 Union……………………………………………………………………………… 67 89 92 89 88 Non-union………………………………………………………………………… 59 67 68 68 69 Average wage less than $15 per hour………………………………………… 51 57 58 57 57 Average wage $15 per hour or higher………………………………………… 74 86 87 88 87 Goods-producing industries…………………………………………………… 68 83 85 86 85 Service-providing industries…………………………………………………… 57 65 66 66 67 Establishments with 1-99 workers……………………………………………… 49 58 59 59 59 Establishments with 100 or more workers…………………………………… 72 82 84 84 84 All workers………………………………………………………………………… 45 53 53 52 52 White-collar occupations 2 ……………………………………………………… 50 59 58 57 - - - - - 67 48 Percentage of workers participating Management, professional, and related ………………………………… Sales and office……………………………………………………………… Blue-collar occupations 2……………………………………………………… Natural resources, construction, and maintenance……………………… - - - - 51 60 61 60 - - - - - 61 Production, transportation, and material moving………………………… - - - - 60 Service occupations…………………………………………………………… 22 24 27 27 28 Full-time………………………………………………………………………… 56 66 66 64 64 Part-time………………………………………………………………………… 9 11 12 13 12 Union……………………………………………………………………………… 60 81 83 80 78 Non-union………………………………………………………………………… 44 50 49 49 49 Average wage less than $15 per hour………………………………………… 35 40 39 38 37 Average wage $15 per hour or higher………………………………………… 61 71 72 71 70 Goods-producing industries…………………………………………………… 57 69 70 70 68 Service-providing industries…………………………………………………… 42 48 48 47 47 Establishments with 1-99 workers……………………………………………… 36 43 43 43 42 Establishments with 100 or more workers…………………………………… 55 64 65 63 62 Take-up rate (all workers) 3……………………………………………………… - - 75 74 73 All workers………………………………………………………………………… 40 46 46 46 46 2 White-collar occupations ……………………………………………………… 47 53 54 53 - - - - - 62 47 Dental Percentage of workers with access Management, professional, and related ………………………………… Sales and office……………………………………………………………… 2 Blue-collar occupations ……………………………………………………… Natural resources, construction, and maintenance……………………… - - - - 40 47 47 46 - - - - - 43 Production, transportation, and material moving………………………… - - - - 49 Service occupations…………………………………………………………… 22 25 25 27 28 Full-time………………………………………………………………………… 49 56 56 55 56 Part-time………………………………………………………………………… 9 13 14 15 16 Union……………………………………………………………………………… 57 73 73 69 68 Non-union………………………………………………………………………… 38 43 43 43 44 Average wage less than $15 per hour………………………………………… 30 34 34 34 34 Average wage $15 per hour or higher………………………………………… 55 63 62 62 61 Goods-producing industries…………………………………………………… 48 56 56 56 54 Service-providing industries…………………………………………………… 37 43 43 43 44 Establishments with 1-99 workers……………………………………………… 27 31 31 31 30 Establishments with 100 or more workers…………………………………… 55 64 65 64 64 See footnotes at end of table. Monthly Labor Review • August 2009 97 Current Labor Statistics: Compensation & Industrial Relations 35. Continued—National Compensation Survey: Health insurance benefits in private industry by access, particpation, and selected series, 2003-2007 Series Year 2003 2004 2005 2007 2006 1 Percentage of workers participating All workers…………………………………………………………………………… 32 37 36 36 White-collar occupations 2 ……………………………………………………… 37 43 42 41 - Management, professional, and related …………………………………… - - - - 51 33 Sales and office………………………………………………………………… Blue-collar occupations 2………………………………………………………… Natural resources, construction, and maintenance………………………… 36 - - - - 33 40 39 38 - - - - - 36 Production, transportation, and material moving…………………………… - - - - 38 Service occupations……………………………………………………………… 15 16 17 18 20 Full-time…………………………………………………………………………… 40 46 45 44 44 Part-time…………………………………………………………………………… 6 8 9 10 9 Union……………………………………………………………………………… 51 68 67 63 62 Non-union………………………………………………………………………… 30 33 33 33 33 Average wage less than $15 per hour………………………………………… 22 26 24 23 23 Average wage $15 per hour or higher………………………………………… 47 53 52 52 51 Goods-producing industries……………………………………………………… 42 49 49 49 45 Service-providing industries……………………………………………………… 29 33 33 32 33 Establishments with 1-99 workers……………………………………………… 21 24 24 24 24 Establishments with 100 or more workers……………………………………… 44 52 51 50 49 Take-up rate (all workers) 3………………………………………………………… - - 78 78 77 Percentage of workers with access……………………………………………… 25 29 29 29 29 Percentage of workers participating……………………………………………… 19 22 22 22 22 Percentage of workers with access……………………………………………… - - 64 67 68 Percentage of workers participating……………………………………………… - - 48 49 49 Percent of estalishments offering healthcare benefits …………………......… 58 61 63 62 60 Vision care Outpatient Prescription drug coverage Percentage of medical premium paid by Employer and Employee Single coverage Employer share…………………………………………………………………… 82 82 82 82 81 Employee share………………………………………………………………… 18 18 18 18 19 Family coverage Employer share…………………………………………………………………… 70 69 71 70 71 Employee share………………………………………………………………… 30 31 29 30 29 1 The 2002 North American Industry Classification System (NAICS) replaced the 1987 Standard Industrial Classification (SIC) System. Estimates for goods-producing and service-providing (formerly service-producing) industries are considered comparable. Also introduced was the 2000 Standard Occupational Classification (SOC) to replace the 1990 Census of Population system. Only service occupations are considered comparable. 2 The white-collar and blue-collar occupation series were discontinued effective 2007. 3 The take-up rate is an estimate of the percentage of workers with access to a plan who participate in the plan. Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. 98 Monthly Labor Review • August 2009 36. National Compensation Survey: Percent of workers in private industry with access to selected benefits, 2003-2007 Year Benefit 2003 2004 2005 2006 2007 Life insurance…………………………………………………… 50 51 52 52 58 Short-term disabilty insurance………………………………… 39 39 40 39 39 Long-term disability insurance………………………………… 30 30 30 30 31 Long-term care insurance……………………………………… 11 11 11 12 12 Flexible work place……………………………………………… 4 4 4 4 5 Flexible benefits……………………………………………… - - 17 17 17 Dependent care reimbursement account…………..……… - - 29 30 31 Healthcare reimbursement account……………………...… - - 31 32 33 Health Savings Account………………………………...……… - - 5 6 8 Employee assistance program……………………….………… - - 40 40 42 Section 125 cafeteria benefits Paid leave Holidays…………………………………………...…………… 79 77 77 76 77 Vacations……………………………………………..……… 79 77 77 77 77 Sick leave………………………………………..…………… - 59 58 57 57 Personal leave…………………………………………..…… - - 36 37 38 Paid family leave…………………………………………….… - - 7 8 8 Unpaid family leave………………………………………..… - - 81 82 83 Employer assistance for child care…………………….……… 18 14 14 15 15 Nonproduction bonuses………………………...……………… 49 47 47 46 47 Family leave Note: Where applicable, dashes indicate no employees in this category or data do not meet publication criteria. 37. Work stoppages involving 1,000 workers or more Annual average Measure 2007 Number of stoppages: Beginning in period............................. In effect during period…...................... 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. Junep May 21 23 15 16 2 2 1 1 2 2 2 2 1 2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Workers involved: Beginning in period (in thousands)….. In effect during period (in thousands)… 189.2 220.9 72.2 136.8 4.2 4.2 8.5 8.5 7.0 7.0 28.2 28.2 6.0 33.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.5 2.5 Days idle: Number (in thousands)….................... 1264.8 1954.1 12.3 42.5 100.6 469.8 600.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 30.0 0.01 0.01 0 0 0 0.02 0.02 0 0 0 0 0 0 0 0 1 Percent of estimated working time …… 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. NOTE: p = preliminary. Monthly Labor Review • August 2009 99 Current Labor Statistics: Price Data 38. Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] Annual average Series 2007 CONSUMER PRICE INDEX FOR ALL URBAN CONSUMERS All items........................................................................... 207.342 All items (1967 = 100)...................................................... 621.106 Food and beverages...................................................... 203.300 Food..................…......................................................... 202.916 Food at home…........................................................... 201.245 Cereals and bakery products…................................. 222.107 Meats, poultry, fish, and eggs…................................ 195.616 2008 215.303 644.951 214.225 214.106 214.125 244.853 204.653 2009 2008 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June 218.815 655.474 213.383 213.243 213.171 245.758 202.914 219.964 658.915 215.326 215.299 215.785 250.321 205.075 219.086 656.284 216.419 216.422 217.259 250.080 207.488 218.783 655.376 217.672 217.696 218.629 250.924 209.937 216.573 648.758 218.705 218.738 219.660 252.832 210.706 212.425 636.332 218.752 218.749 219.086 252.723 209.602 210.228 629.751 218.839 218.805 218.683 253.063 208.890 211.143 632.491 219.729 219.675 219.744 254.445 208.616 212.193 635.637 219.333 219.205 218.389 254.187 207.963 212.709 637.182 218.794 218.600 217.110 253.698 206.348 213.240 638.771 218.364 218.162 215.783 252.709 205.699 213.856 640.616 218.076 217.826 215.088 252.714 203.789 215.693 646.121 218.030 217.740 214.824 253.008 204.031 1 Dairy and related products ……….…………………………194.770 Fruits and vegetables…............................................. 262.628 Nonalcoholic beverages and beverage 210.396 209.117 213.981 214.748 213.533 212.733 213.102 210.838 209.632 204.537 199.687 197.124 196.055 194.197 278.932 277.957 280.209 283.296 285.986 285.484 283.677 281.706 282.601 278.721 274.759 274.297 274.006 272.608 materials….............................................................. 153.432 Other foods at home…............................................... 173.275 Sugar and sweets…................................................. 176.772 Fats and oils…......................................................... 172.921 Other foods…........................................................... 188.244 160.045 184.166 186.577 196.751 198.103 1,2 Other miscellaneous foods 1 ……….………………… 115.105 Food away from home ……….………………………………… 206.659 1,2 Other food away from home ……….…………………… 144.068 Alcoholic beverages….................................................. 207.026 Housing.......................................................................... 209.586 Shelter...............…....................................................... 240.611 Rent of primary residence…...................................... 234.679 Lodging away from home………………………………142.813 3 Owners' equivalent rent of primary residence ………. 246.235 1,2 158.320 183.804 185.558 196.150 197.888 159.346 185.725 187.067 201.205 199.566 160.055 186.991 187.813 203.059 200.961 161.499 187.944 189.929 206.274 201.388 163.727 189.348 190.515 208.300 202.993 163.015 189.301 191.756 205.806 203.058 162.750 190.203 193.312 206.710 203.902 164.882 192.492 197.429 206.886 206.343 164.213 192.404 196.676 205.359 206.621 165.656 192.234 197.137 204.776 206.367 162.889 191.352 197.301 200.464 205.734 162.803 191.144 196.403 200.679 205.587 162.571 191.328 197.009 201.127 205.654 119.924 118.453 120.510 121.033 121.144 122.699 123.543 123.791 124.012 122.580 122.402 122.883 122.838 122.224 215.769 150.640 214.484 216.264 246.666 243.271 215.015 149.873 213.912 217.941 247.083 242.640 216.376 151.120 214.394 219.610 248.075 243.367 217.063 151.133 215.094 219.148 247.985 244.181 218.225 152.040 216.055 218.184 247.737 244.926 219.290 153.544 216.972 217.383 247.844 245.855 220.043 153.978 217.492 216.467 247.463 246.681 220.684 154.062 217.975 216.073 247.085 247.278 221.319 153.402 219.113 216.928 248.292 247.974 221.968 154.726 219.682 217.180 248.878 248.305 222.216 154.414 219.999 217.374 249.597 248.639 222.905 155.099 219.671 217.126 249.855 248.899 223.023 155.099 220.005 216.971 249.779 249.069 223.163 155.841 220.477 218.071 250.243 249.092 143.664 148.621 153.032 149.146 143.597 141.140 133.555 129.157 133.559 135.809 137.715 137.700 135.680 138.318 252.426 252.170 252.504 252.957 253.493 253.902 254.669 254.875 255.500 255.779 256.321 256.622 256.875 256.981 Tenants' and household insurance ……….…………… 117.004 Fuels and utilities…................................................... 200.632 Fuels...............…...................................................... 181.744 Fuel oil and other fuels…....................................... 251.453 Gas (piped) and electricity….................................. 186.262 Household furnishings and operations…................... 126.875 Apparel .......................................................................... 118.998 Men's and boys' apparel…......................................... 112.368 Women's and girls' apparel….................................... 110.296 118.843 220.018 200.808 334.405 202.212 127.800 118.907 113.032 107.460 119.092 231.412 213.762 389.423 213.375 127.625 117.019 112.011 104.312 118.764 239.039 221.742 395.706 221.805 127.884 114.357 109.669 100.049 118.562 235.650 217.455 367.794 218.656 128.013 116.376 110.180 104.211 119.944 228.450 209.501 349.164 210.950 128.584 121.168 112.720 111.774 119.916 221.199 201.176 318.667 203.503 128.789 122.243 115.067 111.833 120.232 216.285 195.599 281.869 199.435 128.554 121.262 114.239 110.588 120.019 215.184 194.335 256.209 199.487 128.535 117.078 110.767 105.456 120.402 215.232 194.149 247.163 199.791 128.761 114.764 110.797 100.638 120.683 213.520 192.168 242.264 197.886 129.170 118.825 115.202 105.777 120.737 210.501 188.736 230.837 194.752 129.669 122.545 117.748 111.079 120.675 207.175 184.903 228.107 190.686 129.654 123.208 117.195 111.871 120.728 206.358 183.783 225.164 189.619 129.644 121.751 117.146 109.460 121.083 212.677 190.647 232.638 196.754 129.623 118.799 112.849 106.455 Infants' and toddlers' apparel ……….………………………113.948 Footwear…................................................................ 122.374 Transportation................................................................ 184.682 Private transportation...............…................................ 180.778 1 113.762 124.157 195.549 191.039 111.555 123.568 211.787 207.257 109.218 122.421 212.806 208.038 109.558 121.982 206.739 201.779 113.494 124.907 203.861 199.153 116.158 126.442 192.709 187.976 116.010 126.788 173.644 168.527 112.568 124.093 164.628 159.411 112.321 122.363 166.738 161.788 113.544 124.301 169.542 164.871 115.548 126.707 169.647 165.023 117.084 128.057 171.987 167.516 114.142 127.519 175.997 171.757 113.915 125.515 183.735 179.649 2 New and used motor vehicles ……….…………………… 94.303 New vehicles…........................................................ 136.254 93.291 134.194 133.951 279.652 277.457 128.747 233.859 250.549 364.065 296.045 384.943 310.968 533.953 113.254 102.632 123.631 93.598 134.516 135.980 347.418 344.981 127.824 233.162 264.681 363.616 295.194 384.685 311.317 531.606 112.991 102.306 122.828 93.650 134.397 135.840 349.731 347.357 129.118 234.788 270.002 363.963 294.777 385.361 311.926 533.558 113.277 102.203 123.445 93.260 133.404 135.405 323.822 321.511 130.327 236.125 268.487 364.477 295.003 385.990 312.396 535.501 113.786 102.546 124.653 92.480 132.399 132.916 315.078 313.535 131.048 237.121 261.318 365.036 295.461 386.579 312.527 537.728 114.032 102.706 125.505 92.071 132.264 129.733 268.537 266.382 131.917 238.227 252.323 365.746 295.791 387.440 312.914 540.853 114.169 102.193 125.686 91.618 132.359 126.869 187.189 184.235 132.947 239.048 243.385 366.613 297.317 387.992 313.328 543.183 114.078 101.831 125.758 91.408 132.308 125.883 149.132 146.102 133.077 239.356 237.638 367.133 298.361 388.267 313.886 543.585 113.674 101.629 125.921 91.831 133.273 124.863 156.604 154.488 133.414 241.076 234.394 369.830 299.998 391.365 315.603 551.305 113.822 101.347 126.151 92.224 134.186 122.837 167.395 166.118 134.108 241.689 231.529 372.405 302.184 394.047 316.992 558.373 114.461 101.704 126.190 92.109 134.611 121.061 168.404 167.826 134.484 242.118 230.735 373.189 302.908 394.837 317.460 560.995 114.625 102.000 126.187 92.381 134.863 121.213 177.272 176.704 134.640 242.649 229.827 374.170 303.979 395.753 317.661 564.785 114.261 102.300 126.273 92.701 135.162 122.650 193.609 193.727 134.347 242.488 228.878 375.026 304.697 396.648 319.333 564.112 114.264 101.947 126.467 93.020 135.719 124.323 225.021 225.526 134.270 242.683 232.540 375.093 304.683 396.750 319.652 564.406 114.643 101.871 126.519 1 Used cars and trucks ……….………………………………135.747 Motor fuel…............................................................... 239.070 Gasoline (all types)…............................................... 237.959 Motor vehicle parts and equipment…........................ 121.583 Motor vehicle maintenance and repair…................... 222.963 Public transportation...............….................................. 230.002 Medical care................................................................... 351.054 Medical care commodities...............…......................... 289.999 Medical care services...............…................................ 369.302 Professional services…............................................. 300.792 Hospital and related services…................................. 498.922 2 Recreation ……….………………………………………….………111.443 1,2 Video and audio ……….………………………………………102.949 2 Education and communication ……….……………………… 119.577 2 Education ……….………………………………………….………171.388 Educational books and supplies…........................... 420.418 181.277 178.385 179.229 183.184 186.148 186.669 186.733 186.916 187.175 187.256 187.298 187.416 187.853 188.179 450.187 443.309 444.382 458.989 462.787 463.825 462.694 464.544 468.432 469.996 472.185 472.507 472.588 476.974 Tuition, other school fees, and child care…............. 494.079 1,2 Communication ……….……………………………………… 83.367 1,2 Information and information processing ……….…… 80.720 1,2 Telephone services ……….…………………………… 98.247 Information and information processing 522.098 513.743 516.264 527.230 536.082 537.606 537.906 538.309 538.765 538.878 538.813 539.149 540.498 541.119 84.185 84.394 84.840 84.701 84.524 84.535 84.601 84.737 84.928 84.945 84.922 84.985 85.049 84.975 1,4 other than telephone services ……….…………… 10.597 81.352 81.513 81.965 81.815 81.635 81.652 81.723 81.886 82.030 82.052 82.022 82.090 82.038 81.909 100.451 100.677 101.339 101.301 101.311 101.407 101.538 101.688 101.880 101.895 101.991 102.072 102.267 102.182 10.061 10.071 10.087 10.012 9.901 9.874 9.867 9.906 9.919 9.926 9.872 9.881 9.775 9.731 Personal computers and peripheral 1,2 equipment ……….……………………………………108.411 Other goods and services.............................................. 333.328 Tobacco and smoking products...............…................ 554.184 94.944 95.663 94.711 92.921 90.797 89.945 88.984 88.529 88.522 87.696 86.213 85.714 84.366 83.476 345.381 345.885 346.810 346.990 348.166 349.276 349.040 349.220 350.259 351.223 361.156 370.606 369.901 370.595 588.682 589.904 596.782 597.361 597.581 599.744 599.820 602.644 607.403 611.549 679.078 742.443 740.311 746.283 1 Personal care ……….………………………………………….…195.622 1 Personal care products ……….…………………………… 158.285 1 Personal care services ……….…………………………… 216.559 201.279 201.537 201.545 201.623 202.486 203.107 202.921 202.774 203.080 203.391 204.117 204.896 204.578 204.503 159.290 158.868 158.989 159.252 159.643 159.826 161.000 161.397 162.588 162.508 162.696 163.777 163.051 162.301 223.669 223.520 223.719 224.151 224.614 225.564 226.197 226.281 225.734 225.895 227.982 227.913 227.607 227.572 See footnotes at end of table. 100 Monthly Labor Review • August 2009 38. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] Series Annual average 2007 2008 June July Aug. 2008 Sept. Oct. Nov. Dec. Jan. Feb. 2009 Mar. Apr. May June Miscellaneous personal services...............….... 324.984 338.921 340.547 340.077 341.053 343.431 343.131 340.174 339.698 340.608 341.188 341.570 342.641 343.051 344.232 Commodity and service group: Commodities...........…............................................ 167.509 174.764 180.534 181.087 179.148 179.117 175.257 167.673 163.582 164.360 165.891 166.645 167.816 169.060 171.593 Food and beverages…......................................... Commodities less food and beverages…............. Nondurables less food and beverages…............ Apparel …......................................................... 203.300 147.515 182.526 118.998 214.225 153.034 196.192 118.907 213.383 161.337 213.489 117.019 215.326 161.301 213.363 114.357 216.419 158.179 207.284 116.376 217.672 157.621 206.919 121.168 218.705 151.874 195.127 122.243 218.752 141.397 173.346 121.262 218.839 135.720 161.681 117.078 219.729 136.427 162.938 114.764 219.333 138.702 167.560 118.825 218.794 139.962 170.200 122.545 218.364 141.753 173.855 123.208 218.076 143.587 177.480 121.751 218.030 147.099 184.581 118.799 Non durables less food, beverages, and apparel…................................................. 226.224 248.809 278.584 280.062 268.740 265.100 244.935 209.569 192.948 196.490 201.554 203.557 209.177 216.090 229.692 Durables….......................................................... 112.473 110.877 Services….............................................................. 246.848 255.498 3 Rent of shelter ……….…………………………………… 250.813 257.152 Transportation services….................................... 233.731 244.074 Other services….................................................. 285.559 295.780 111.232 256.668 257.585 245.759 294.668 111.275 258.422 258.637 247.869 295.677 110.779 258.638 258.547 248.806 297.923 110.077 258.059 258.255 248.047 299.598 109.677 257.559 258.368 247.762 299.923 109.191 256.967 257.961 247.030 299.996 108.811 256.731 257.567 246.287 300.067 109.025 257.780 258.830 247.006 300.614 109.221 258.328 259.440 248.114 301.471 109.264 258.597 260.197 247.912 302.024 109.404 258.466 260.469 248.696 301.668 109.650 258.433 260.388 248.628 302.132 109.983 259.544 260.869 249.194 303.000 Special indexes: All items less food…............................................ 208.098 215.528 219.757 220.758 219.552 218.991 216.250 211.421 208.855 209.777 211.076 211.775 212.464 213.236 215.389 All items less shelter…........................................ All items less medical care…............................... Commodities less food…..................................... Nondurables less food…..................................... Nondurables less food and apparel…................. Nondurables…..................................................... 3 Services less rent of shelter ……….………………… Services less medical care services…................ Energy….............................................................. All items less energy…........................................ All items less food and energy…....................... Commodities less food and energy….............. Energy commodities...................................... Services less energy….................................... 196.639 200.080 149.720 184.012 223.411 193.468 260.764 236.847 207.723 208.925 210.729 140.053 241.018 253.058 205.453 207.777 155.310 197.297 244.443 205.901 273.000 244.987 236.666 214.751 215.572 140.246 284.352 261.017 210.242 211.408 163.385 213.538 271.235 214.783 275.200 246.219 275.621 214.600 215.553 139.925 351.886 261.216 211.468 212.576 163.364 213.447 272.612 215.628 277.982 248.007 280.833 215.335 216.045 139.535 354.423 262.323 210.264 211.653 160.341 207.769 262.470 212.882 278.606 248.198 266.283 215.873 216.476 139.785 328.240 262.867 209.936 211.321 159.825 207.483 259.278 213.274 277.615 247.563 258.020 216.397 216.862 140.528 318.918 262.980 206.776 209.021 154.250 196.442 241.183 207.435 276.297 246.997 231.561 216.695 217.023 140.659 272.921 263.156 201.075 204.721 144.055 175.979 209.344 195.773 275.425 246.351 189.938 216.417 216.690 140.236 193.395 262.901 198.127 202.442 138.536 165.032 194.403 189.557 275.370 246.090 171.158 215.930 216.100 139.228 155.745 262.636 198.936 203.281 139.258 166.282 197.704 190.649 276.227 247.013 174.622 216.586 216.719 139.111 162.395 263.759 200.184 204.265 141.491 170.665 202.323 192.943 276.739 247.439 178.741 217.325 217.685 140.270 172.428 264.547 200.626 204.766 142.728 173.167 204.159 194.105 276.407 247.675 177.454 218.033 218.639 141.662 172.787 265.147 201.271 205.275 144.464 176.587 209.195 195.864 275.752 247.490 179.704 218.388 219.143 142.489 181.102 265.399 202.171 205.876 146.261 180.017 215.459 197.673 275.777 247.406 186.909 218.323 219.128 142.360 196.528 265.466 204.578 207.764 149.697 186.726 227.768 201.461 277.777 248.557 205.408 218.440 219.283 141.990 226.881 265.993 CONSUMER PRICE INDEX FOR URBAN WAGE EARNERS AND CLERICAL WORKERS All items.................................................................... 202.767 211.053 215.223 216.304 215.247 214.935 212.182 207.296 204.813 205.700 206.708 207.218 207.925 208.774 210.972 All items (1967 = 100)............................................... 603.982 628.661 Food and beverages................................................ 202.531 213.546 Food..................….................................................. 202.134 213.376 Food at home….................................................... 200.273 213.017 Cereals and bakery products….......................... 222.409 245.472 Meats, poultry, fish, and eggs…......................... 195.193 204.255 1 Dairy and related products ……….…………………… 194.474 209.773 Fruits and vegetables…...................................... 260.484 276.759 641.082 212.700 212.514 212.079 246.493 202.424 208.510 276.641 644.303 214.662 214.577 214.679 250.972 204.557 213.582 278.885 641.155 215.850 215.812 216.214 250.842 207.211 214.139 282.171 640.226 217.098 217.090 217.594 251.448 209.515 212.841 284.612 632.025 218.141 218.120 218.600 253.561 210.314 211.808 283.549 617.472 218.178 218.114 217.956 253.498 209.297 212.184 281.279 610.075 218.269 218.155 217.498 253.759 208.639 209.922 278.835 612.719 219.123 218.998 218.485 255.055 208.161 208.530 279.906 615.719 218.645 218.449 217.111 254.775 207.656 203.023 275.884 617.239 218.119 217.855 215.922 254.395 206.094 198.048 271.727 619.344 217.653 217.376 214.654 253.556 205.527 195.714 271.771 621.875 217.308 216.975 213.876 253.430 203.409 194.694 271.530 628.422 217.258 216.890 213.657 253.701 203.503 192.898 270.653 Nonalcoholic beverages and beverage materials…....................................................... 152.786 Other foods at home…....................................... 172.630 Sugar and sweets…......................................... 175.323 Fats and oils….................................................. 173.640 Other foods…................................................... 188.405 1,2 Other miscellaneous foods ……….…………… 115.356 1 Food away from home ……….…………………………… 206.412 1,2 Other food away from home ……….……………… 143.462 Alcoholic beverages…........................................... 207.097 159.324 157.309 158.527 159.024 160.850 163.265 162.472 162.280 164.514 163.821 165.437 162.464 162.468 162.167 183.637 185.494 197.512 198.303 120.348 215.613 149.731 214.579 183.342 184.378 197.155 198.153 118.879 214.851 149.306 213.976 185.174 186.054 201.821 199.722 121.015 216.177 150.232 214.440 186.458 186.860 203.721 201.119 121.443 217.002 150.301 214.931 187.467 188.914 207.069 201.632 121.589 218.147 151.321 215.728 188.806 189.574 208.973 203.138 123.026 219.219 152.910 216.953 188.685 190.501 206.870 203.126 123.837 220.107 153.464 217.626 189.527 192.120 207.439 203.937 124.144 220.847 153.646 218.445 191.782 195.867 207.400 206.490 124.477 221.497 153.397 219.458 191.620 195.395 206.185 206.547 122.994 222.101 154.520 220.029 191.594 196.015 205.693 206.468 122.837 222.336 154.054 220.500 190.650 195.858 201.474 205.820 123.112 222.957 154.414 220.243 190.401 194.928 201.470 205.641 123.126 223.082 154.409 220.729 190.657 195.773 202.004 205.759 122.537 223.186 155.091 221.179 204.795 232.998 233.806 142.339 223.175 117.366 211.839 239.128 242.196 143.164 228.758 119.136 213.441 239.198 241.623 148.378 228.536 119.293 215.026 239.845 242.276 152.248 228.824 119.006 214.743 240.038 243.010 148.368 229.219 118.894 213.954 240.163 243.741 142.591 229.670 120.279 213.156 240.517 244.624 140.763 230.028 120.258 212.591 240.740 245.425 133.747 230.743 120.589 212.452 240.752 246.026 129.982 230.926 120.360 213.078 241.651 246.696 134.235 231.503 120.715 213.192 242.051 246.991 136.255 231.746 120.960 213.213 242.605 247.285 138.008 232.235 121.099 212.885 242.857 247.517 138.008 232.503 121.084 212.881 242.941 247.710 136.113 232.739 121.160 214.034 243.238 247.691 139.246 232.837 121.529 198.863 179.031 251.121 184.357 122.477 118.518 112.224 110.202 1 Infants' and toddlers' apparel ……….……………… 116.278 Footwear…......................................................... 122.062 217.883 197.537 331.784 200.265 123.635 118.735 113.490 107.489 116.266 124.102 228.843 209.843 381.903 211.398 123.434 116.706 112.395 104.062 114.057 123.381 236.381 217.640 388.208 219.612 123.798 113.978 109.969 99.772 111.502 122.380 233.373 213.807 363.535 216.557 123.944 116.214 110.513 104.584 111.593 122.026 226.709 206.544 345.907 209.442 124.500 120.990 112.973 112.304 115.764 124.873 219.325 198.191 317.012 201.651 124.719 121.957 115.495 111.880 118.496 126.352 214.700 193.000 283.747 197.507 124.466 121.149 114.651 110.612 118.611 126.689 213.861 192.050 260.185 197.545 124.314 117.006 111.232 105.413 115.003 124.152 213.882 191.852 251.976 197.703 124.454 114.969 111.879 100.751 114.775 122.753 212.353 190.110 246.781 196.040 124.865 118.766 116.332 105.538 116.001 124.494 209.400 186.809 236.237 192.922 125.337 122.162 118.735 110.380 117.944 126.858 205.840 182.795 232.068 188.735 125.458 122.709 117.834 110.990 119.873 128.312 205.270 181.977 229.019 187.982 125.589 121.364 117.687 108.637 116.912 127.802 211.929 189.108 235.869 195.445 125.526 118.547 113.416 105.676 116.645 126.150 Housing.................................................................... Shelter...............…................................................ Rent of primary residence…............................... 2 Lodging away from home ……….…………………… 3 Owners' equivalent rent of primary residence … 1,2 Tenants' and household insurance ……….…… Fuels and utilities…........................................... Fuels...............….............................................. Fuel oil and other fuels…................................ Gas (piped) and electricity….......................... Household furnishings and operations…............ Apparel ................................................................... Men's and boys' apparel…................................. Women's and girls' apparel…............................. Transportation.......................................................... 184.344 195.692 213.633 214.533 207.796 204.785 192.198 170.870 160.914 163.215 165.976 165.978 168.539 173.055 181.730 Private transportation...............…......................... 181.496 192.492 210.423 211.201 204.348 201.476 188.871 167.301 157.272 159.719 162.645 162.659 165.299 169.957 178.734 2 92.146 92.714 92.686 92.287 91.305 90.530 89.783 89.482 89.774 89.728 89.418 89.620 90.039 90.588 New and used motor vehicles ……….……………… 93.300 See footnotes at end of table. Monthly Labor Review • August 2009 101 Current Labor Statistics: Price Data 38. Continued—Consumer Price Indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average, by expenditure category and commodity or service group [1982–84 = 100, unless otherwise indicated] Annual average Series 2007 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June New vehicles…............................................ 137.415 135.338 135.728 135.556 134.540 133.504 133.351 133.380 133.317 134.490 135.248 135.744 135.911 136.113 136.800 1 Used cars and trucks ……….…………………… 136.586 Motor fuel…................................................... 239.900 Gasoline (all types)….................................. 238.879 Motor vehicle parts and equipment…............ 121.356 Motor vehicle maintenance and repair…....... 225.535 Public transportation...............…..................... 228.531 Medical care....................................................... Medical care commodities...............…............ Medical care services...............…................... Professional services…................................. Hospital and related services…..................... 350.882 282.558 370.111 303.169 493.740 134.731 280.817 278.728 128.776 236.353 247.865 136.790 348.762 346.459 127.750 235.550 261.779 136.639 351.124 348.888 128.997 237.324 266.259 136.186 325.116 322.930 130.228 238.583 264.755 133.669 316.717 315.324 131.072 239.571 258.142 130.444 269.639 267.580 132.088 240.688 249.168 127.540 187.770 184.855 133.125 241.509 240.496 126.526 149.650 146.644 133.295 241.855 235.199 125.485 157.265 155.204 133.645 243.594 232.422 123.443 168.028 166.831 134.264 244.219 229.404 121.669 169.060 168.574 134.485 244.650 229.034 121.850 177.982 177.510 134.614 245.180 228.525 123.339 194.339 194.569 134.439 245.036 227.522 125.056 225.876 226.515 134.273 245.129 230.926 364.208 287.970 386.317 313.446 530.193 363.628 287.033 385.911 313.618 527.948 363.942 286.562 386.560 314.235 529.798 364.652 286.880 387.420 314.893 532.065 365.250 287.397 388.036 314.977 534.394 366.000 287.725 388.947 315.458 537.382 366.800 289.046 389.493 315.825 539.864 367.301 290.080 389.744 316.435 540.101 370.001 291.710 392.831 318.110 547.655 372.630 293.917 395.563 319.663 554.390 373.541 294.728 396.489 320.231 557.167 374.599 295.699 397.553 320.407 561.516 375.420 296.431 398.387 322.043 560.906 375.479 296.369 398.497 322.346 561.337 2 Recreation ……….……………………………………… 108.572 110.143 109.905 110.198 110.698 110.904 110.947 110.826 110.487 110.630 111.257 111.436 111.182 111.152 111.471 1,2 Video and audio ……….……………………………102.559 102.654 102.306 102.267 102.643 102.819 102.267 101.974 101.810 101.488 101.857 102.153 102.516 102.214 102.193 2 Education and communication ……….…………… 116.301 119.827 119.264 119.852 120.809 121.439 121.569 121.636 121.819 122.025 122.092 122.087 122.152 122.293 122.333 2 Education ……….………………………………………169.280 178.892 176.148 176.879 180.819 183.613 184.091 184.115 184.352 184.642 184.765 184.824 184.892 185.291 185.626 Educational books and supplies….............. 423.730 452.880 445.740 446.741 461.104 465.570 466.885 465.576 467.179 471.061 473.012 474.880 474.950 475.213 480.024 Tuition, other school fees, and child care… 477.589 504.163 496.449 498.598 509.241 517.389 518.726 518.938 519.500 519.987 520.159 520.146 520.348 521.550 522.076 1,2 Communication ……….…………………………… 85.782 86.807 87.017 87.490 87.369 87.224 87.226 87.300 87.444 87.599 87.640 87.615 87.671 87.712 87.652 1,2 Information and information processing … 83.928 84.828 85.007 85.484 85.355 85.208 85.214 85.292 85.454 85.581 85.624 85.595 85.655 85.624 85.524 1,2 Telephone services ……….………………… 98.373 100.502 100.723 101.375 101.339 101.350 101.436 101.564 101.720 101.876 101.890 101.977 102.048 102.231 102.153 Information and information processing other than telephone services 1,4 ……….… 11.062 10.567 10.585 10.600 10.525 10.414 10.375 10.367 10.406 10.418 10.442 10.378 10.385 10.271 10.238 Personal computers and peripheral 1,2 equipment ……….……………………… 108.164 94.863 95.766 94.691 92.931 90.722 89.690 88.631 88.176 88.178 87.622 86.004 85.406 84.017 83.278 Other goods and services.................................. 344.004 357.906 358.419 359.961 360.102 361.125 362.354 362.550 362.986 364.333 365.522 380.208 394.902 394.061 395.052 Tobacco and smoking products...............….... 555.502 591.100 592.248 599.180 599.823 600.293 602.533 602.881 605.662 610.503 615.012 682.115 747.906 746.009 752.078 1 Personal care ……….………………………………… 193.590 199.170 199.404 199.495 199.501 200.284 200.930 201.036 200.918 201.209 201.426 202.099 203.010 202.631 202.406 1 Personal care products ……….………………… 158.268 159.410 159.052 159.237 159.345 159.730 159.914 160.994 161.295 162.683 162.543 162.516 163.911 163.119 162.165 1 Personal care services ……….………………… 216.823 223.978 223.838 223.994 224.464 224.910 225.800 226.433 226.578 225.951 226.088 228.201 228.119 227.829 227.800 Miscellaneous personal services...............… 326.100 340.533 341.921 341.763 342.974 345.175 344.622 342.853 342.530 343.022 343.443 344.021 345.016 345.326 346.411 Commodity and service group: Commodities...........…....................................... Food and beverages….................................... Commodities less food and beverages…........ Nondurables less food and beverages…...... Apparel …................................................... 169.554 202.531 150.865 189.507 118.518 177.618 213.546 157.481 205.279 118.735 184.495 212.700 167.344 225.585 116.706 185.105 214.662 167.376 225.595 113.978 182.846 215.850 163.761 218.454 116.214 182.647 217.098 162.971 217.828 120.990 177.906 218.141 155.982 203.762 121.957 168.926 218.178 143.544 178.209 121.149 164.233 218.269 137.015 164.879 117.006 165.151 219.123 137.932 166.694 114.969 166.673 218.645 140.235 171.698 118.766 167.514 218.119 141.615 174.838 122.162 169.005 217.653 143.871 179.415 122.709 170.532 217.308 146.125 183.813 121.364 173.662 217.258 150.477 192.478 118.547 Nondurables less food, beverages, and apparel…............................................ 237.858 263.756 298.593 300.341 287.124 283.056 259.204 217.500 198.108 202.400 208.255 211.287 218.502 226.621 242.726 Durables….................................................... 112.640 111.217 111.769 111.820 111.357 110.451 109.782 109.038 108.576 108.689 108.592 108.413 108.596 108.933 109.430 Services…......................................................... 241.696 250.272 251.365 252.991 253.304 252.861 252.369 252.144 252.176 253.033 253.456 253.591 253.403 253.482 254.624 3 Rent of shelter ……….……………………………… 224.617 230.555 230.620 231.255 231.445 231.541 231.885 232.096 232.112 232.981 233.365 233.903 234.148 234.229 234.511 Transporatation services…............................ 233.420 242.563 243.395 245.005 246.041 245.722 246.003 246.126 245.881 246.931 248.029 247.862 248.809 248.795 249.312 Other services…............................................. 275.218 284.319 283.449 284.449 286.389 287.792 287.898 288.082 288.227 288.627 289.432 290.043 289.738 290.116 290.845 Special indexes: All items less food…....................................... All items less shelter…................................... All items less medical care…......................... Commodities less food…............................... Nondurables less food…................................ Nondurables less food and apparel…............ Nondurables…............................................... 3 Services less rent of shelter ……….…………… Services less medical care services…........... Energy…........................................................ All items less energy…................................... All items less food and energy….................. Commodities less food and energy…........ Energy commodities................................. Services less energy…............................... 1 2 3 102 202.698 193.940 196.564 152.875 190.698 234.201 196.772 210.452 203.102 204.626 159.538 206.047 258.423 210.333 215.498 208.817 208.906 169.169 225.276 290.127 220.813 216.407 210.069 210.002 169.213 225.309 291.760 221.740 214.950 208.544 208.900 165.689 218.562 279.753 218.473 214.361 208.068 208.563 164.937 218.010 276.112 218.725 210.949 204.149 205.726 158.132 204.734 254.473 211.680 205.214 197.342 200.707 145.985 180.533 216.516 198.009 202.292 193.918 198.153 139.620 167.933 198.909 190.910 203.186 194.811 198.978 140.543 169.708 202.906 192.284 204.465 196.052 199.928 142.809 174.484 208.291 194.740 205.167 196.551 200.421 144.172 177.487 211.094 196.174 206.081 197.432 201.112 146.371 181.815 217.649 198.408 207.148 198.571 201.955 148.589 186.012 225.091 200.601 209.744 201.488 204.200 152.856 194.254 239.808 205.219 230.876 232.195 208.066 203.002 203.554 140.612 241.257 247.888 241.567 240.275 237.414 208.719 208.147 141.084 284.270 255.598 243.780 241.422 277.597 208.458 208.007 140.878 351.873 255.513 246.411 243.071 282.579 209.062 208.317 140.492 354.402 256.365 246.834 243.354 267.624 209.718 208.857 140.802 328.310 257.072 245.787 242.868 259.864 210.325 209.329 141.428 319.507 257.411 244.331 242.316 232.106 210.649 209.511 141.375 272.894 257.774 243.599 242.058 188.375 210.541 209.383 140.793 192.494 258.008 243.646 242.079 168.726 210.168 208.925 139.731 154.744 258.039 244.376 242.819 172.463 210.707 209.404 139.614 161.781 258.976 244.791 243.128 177.033 211.279 210.203 140.554 171.978 259.643 244.413 243.223 175.947 211.989 211.178 142.077 172.563 260.158 243.718 242.980 178.485 212.472 211.857 143.237 181.021 260.439 243.784 243.022 186.321 212.462 211.926 143.170 196.706 260.615 245.833 244.196 205.662 212.552 212.051 142.943 227.444 261.014 Not seasonally adjusted. Indexes on a December 1997 = 100 base. Indexes on a December 1982 = 100 base. Monthly Labor Review • August 2009 4 Indexes on a December 1988 = 100 base. NOTE: Index applied to a month as a whole, not to any specific date. 39. Consumer Price Index: U.S. city average and available local area data: all items [1982–84 = 100, unless otherwise indicated] Pricing All Urban Consumers sched- 2009 ule U.S. city average…………………………………………… 1 Jan. Feb. Mar. Urban Wage Earners 2009 Apr. May June Jan. Feb. Mar. Apr. May June M 211.143 212.193 212.709 213.240 213.856 215.693 205.700 206.708 207.218 207.925 208.774 210.972 Northeast urban……….………………………………………….……… M 225.436 226.754 227.309 227.840 228.136 229.930 221.704 222.945 223.626 224.252 224.748 226.695 Size A—More than 1,500,000........................................... M 227.852 229.262 229.749 230.400 230.611 232.058 222.707 224.084 224.597 225.214 225.657 227.337 M 133.308 133.967 134.411 134.547 134.857 136.488 133.345 133.908 134.558 134.951 135.329 136.888 M 200.815 201.453 202.021 202.327 203.195 205.350 195.245 195.813 196.453 196.933 197.971 200.487 M 202.001 202.639 203.240 203.463 204.443 206.308 195.621 196.147 196.855 197.192 198.271 200.356 M 128.636 129.057 129.334 129.604 129.967 131.640 127.768 128.167 128.468 128.968 129.524 131.554 Region and area size2 3 Size B/C—50,000 to 1,500,000 ……….………………………… 4 Midwest urban ……….………………………………………….……… Size A—More than 1,500,000........................................... 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size D—Nonmetropolitan (less than 50,000)…………..... M 195.843 196.421 197.267 197.644 198.911 201.157 192.907 193.527 194.393 194.651 196.047 198.674 South urban…….….............................................................. M 204.288 205.343 206.001 206.657 207.265 209.343 200.067 201.150 201.737 202.619 203.500 205.968 Size A—More than 1,500,000........................................... M 207.035 207.929 208.529 208.934 209.235 211.390 203.519 204.501 205.066 205.733 206.271 208.909 M 129.615 130.380 130.873 131.370 131.777 133.056 127.529 128.276 128.686 129.309 129.885 131.382 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size D—Nonmetropolitan (less than 50,000)…………..... M 205.766 206.671 206.927 207.898 209.563 211.815 204.316 205.337 205.744 206.921 208.989 211.721 West urban…….…............................................................... M 215.923 217.095 217.357 217.910 218.567 219.865 209.367 210.492 210.661 211.386 212.263 213.973 Size A—More than 1,500,000........................................... M 219.806 220.955 221.124 221.790 222.659 223.908 211.857 212.890 212.965 213.646 214.734 216.395 M 130.682 131.636 131.775 131.912 131.990 132.952 129.639 130.649 130.674 131.103 131.389 132.517 M M M 193.412 194.354 194.750 195.207 195.745 197.214 191.023 191.927 192.327 192.861 193.597 195.414 130.135 130.855 131.230 131.557 131.876 133.220 128.783 129.488 129.833 130.361 130.847 132.384 203.409 203.999 204.672 205.421 206.717 208.543 200.057 200.681 201.485 202.351 203.883 206.327 Chicago–Gary–Kenosha, IL–IN–WI………………………….. Los Angeles–Riverside–Orange County, CA……….………… M M 207.616 207.367 207.462 207.886 209.809 211.010 200.222 199.944 200.218 200.607 202.464 203.691 220.719 221.439 221.376 221.693 222.522 223.906 212.454 213.234 213.013 213.405 214.446 216.145 New York, NY–Northern NJ–Long Island, NY–NJ–CT–PA… M 233.402 234.663 235.067 235.582 235.975 237.172 227.503 228.653 229.064 229.639 230.307 231.916 Boston–Brockton–Nashua, MA–NH–ME–CT……….………… 1 230.806 – 232.155 – 231.891 – 230.095 – 231.884 – 231.420 – Cleveland–Akron, OH…………………………………………… 1 198.232 – 199.457 – 200.196 – 188.798 – 190.107 – 191.297 – Dallas–Ft Worth, TX…….……………………………………… 1 198.623 – 200.039 – 199.311 – 199.416 – 200.770 – 200.955 – Washington–Baltimore, DC–MD–VA–WV ……….…………… 1 137.598 – 138.620 – 139.311 – 136.359 – 137.539 – 138.510 – Atlanta, GA……………………..………………………………… 2 – 199.190 – 199.210 – 203.585 – 197.528 – 197.676 – 202.632 Detroit–Ann Arbor–Flint, MI…………………………………… 2 – 201.913 – 202.373 – 204.537 – 196.191 – 197.239 – 199.977 Houston–Galveston–Brazoria, TX……………………………… 2 – 187.972 – 189.701 – 192.325 – 185.015 – 186.970 – 189.979 Miami–Ft. Lauderdale, FL……………...……………………… 2 – 220.589 – 220.740 – 221.485 – 217.635 – 217.900 – 219.091 Philadelphia–Wilmington–Atlantic City, PA–NJ–DE–MD…… 2 – 220.262 – 221.686 – 223.810 – 219.356 – 220.732 – 223.361 San Francisco–Oakland–San Jose, CA…….………………… 2 – 222.166 – 223.854 – 225.692 – 216.797 – 218.587 – 220.996 Seattle–Tacoma–Bremerton, WA………………...…………… 2 – 224.737 – 225.918 – 227.257 – 218.752 – 220.208 – 221.993 3 Size B/C—50,000 to 1,500,000 ……….………………………… Size classes: 5 A ……….………………………………………….…………..…………… 3 B/C ……………………….….………………………………………….… D…………….…………...................................................... Selected local areas 6 7 1 Foods, fuels, and several other items priced every month in all areas; most other goods and services priced as indicated: M—Every month. 1—January, March, May, July, September, and November. 2—February, April, June, August, October, and December. 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. 5 Indexes on a December 1986 = 100 base. 6 In addition, the following metropolitan areas are published semiannually and appear in tables 34 and 39 of the January and July issues of the CPI Detailed Report : Anchorage, AK; Cincinnatti, OH–KY–IN; Kansas City, MO–KS; Milwaukee–Racine, WI; Minneapolis–St. Paul, MN–WI; Pittsburgh, PA; Port-land–Salem, OR–WA; St Louis, MO–IL; San Diego, CA; Tampa–St. Petersburg–Clearwater, FL. 7 Indexes on a November 1996 = 100 base. NOTE: Local area CPI indexes are byproducts of the national CPI program. Each local index has a smaller sample size and is, therefore, subject to substantially more sampling and other measurement error. As a result, local area indexes show greater volatility than the national index, although their long-term trends are similar. Therefore, the Bureau of Labor Statistics strongly urges users to consider adopting the national average CPI for use in their escalator clauses. Index applies to a month as a whole, not to any specific date. Dash indicates data not available. Monthly Labor Review • August 2009 103 Current Labor Statistics: Price Data 40. Annual data: Consumer Price Index, U.S. city average, all items and major groups [1982–84 = 100] Series Consumer Price Index for All Urban Consumers: All items: Index..................……............................................... Percent change............................…………………… Food and beverages: Index................……................................................. Percent change............................…………………… Housing: Index....………………............................................... Percent change............................…………………… Apparel: Index........................……......................................... Percent change............................…………………… Transportation: Index........................………...................................... Percent change............................…………………… Medical care: Index................……................................................. Percent change............................…………………… Other goods and services: Index............……..................................................... Percent change............................…………………… Consumer Price Index for Urban Wage Earners and Clerical Workers: All items: Index....................……………................................... Percent change............................…………………… 104 Monthly Labor Review • August 2009 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 163.0 1.6 166.6 2.2 172.2 3.4 177.1 2.8 179.9 1.6 184.0 2.3 188.9 2.7 195.3 3.4 201.6 3.2 207.342 2.8 215.303 3.8 161.1 2.2 164.6 2.2 168.4 2.3 173.6 3.1 176.8 1.8 180.5 2.1 186.6 3.3 191.2 2.5 195.7 2.4 203.300 3.9 214.225 5.4 160.4 2.3 163.9 2.2 169.6 3.5 176.4 4.0 180.3 2.2 184.8 2.5 189.5 2.5 195.7 3.3 203.2 3.8 209.586 3.1 216.264 3.2 133.0 .1 131.3 –1.3 129.6 –1.3 127.3 –1.8 124.0 –2.6 120.9 –2.5 120.4 –.4 119.5 –.7 119.5 .0 118.998 -0.4 118.907 -0.1 141.6 –1.9 144.4 2.0 153.3 6.2 154.3 0.7 152.9 –.9 157.6 3.1 163.1 3.5 173.9 6.6 180.9 4.0 184.682 2.1 195.549 5.9 242.1 3.2 250.6 3.5 260.8 4.1 272.8 4.6 285.6 4.7 297.1 4.0 310.1 4.4 323.2 4.2 336.2 4.0 351.054 4.4 364.065 3.7 237.7 5.7 258.3 8.7 271.1 5.0 282.6 4.2 293.2 3.8 298.7 1.9 304.7 2.0 313.4 2.9 321.7 2.6 333.328 3.6 345.381 3.6 159.7 1.3 163.2 2.2 168.9 3.5 173.5 2.7 175.9 1.4 179.8 2.2 184.5 5.1 191.0 1.1 197.1 3.2 202.767 2.9 211.053 4.1 41. Producer Price Indexes, by stage of processing [1982 = 100] Grouping Finished goods....…………………………… Finished consumer goods......................... Finished consumer foods........................ Annual average 2007 2008 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar.p Apr.p Mayp Junep 166.6 173.5 167.0 177.1 186.3 178.3 182.4 193.8 180.0 185.1 197.2 181.0 182.2 193.2 181.3 182.2 193.0 181.5 177.4 185.5 180.7 172.0 178.2 179.8 168.8 173.7 177.7 170.4 175.8 177.7 169.9 175.2 175.0 168.9 173.9 174.0 169.9 175.5 175.8 170.8 176.8 173.9 174.1 181.3 176.0 excluding foods..................................... Nondurable goods less food................. Durable goods...................................... Capital equipment................................... 175.6 191.7 138.3 149.5 189.1 210.5 141.2 153.8 199.0 226.4 139.7 152.7 203.4 233.1 139.6 153.3 197.5 223.9 140.2 153.9 197.2 223.4 140.3 154.3 187.0 205.4 144.8 157.0 177.0 190.6 144.2 156.9 171.5 182.1 144.4 157.2 174.4 186.5 144.3 157.4 174.5 186.6 144.3 157.2 173.1 184.6 144.2 157.0 174.6 186.8 144.3 156.6 176.9 190.5 144.1 156.3 182.2 198.0 144.7 156.6 Intermediate materials, supplies, and components........………… 170.7 188.3 197.2 203.1 199.4 198.6 189.0 179.2 171.6 171.4 169.7 168.1 167.7 168.7 172.6 162.4 161.4 184.0 189.8 136.3 177.2 180.4 214.3 203.3 140.3 182.4 185.4 222.8 215.4 140.1 187.4 187.6 234.8 219.2 141.3 188.7 187.5 238.6 218.9 141.9 186.7 185.2 234.7 214.5 142.4 180.3 179.4 222.4 202.2 142.5 171.1 175.5 200.6 190.0 142.3 163.7 170.8 185.0 178.6 141.9 162.7 167.3 186.8 172.8 141.7 161.0 164.3 185.6 168.2 141.5 160.2 163.6 184.8 166.0 141.2 158.4 164.1 181.3 162.7 140.6 158.2 166.1 180.9 162.0 140.6 160.7 166.1 189.2 162.9 140.6 for construction......................................... Processed fuels and lubricants................... Containers.................................................. Supplies...................................................... 192.5 173.9 180.3 161.7 205.4 206.2 191.8 173.8 206.5 238.4 189.2 174.6 209.8 250.1 191.9 178.3 212.9 225.2 195.0 178.9 214.0 224.5 198.4 179.0 212.2 193.9 199.1 177.0 210.2 168.7 199.0 175.3 207.9 151.2 198.1 173.4 207.0 153.4 200.8 172.9 204.8 150.7 199.5 172.3 204.2 145.0 198.4 172.0 202.5 148.6 196.7 171.8 202.2 153.9 195.5 172.2 202.2 167.0 195.4 172.8 Crude materials for further processing.......................………………… Foodstuffs and feedstuffs........................... Crude nonfood materials............................ 207.1 146.7 246.3 251.8 163.4 313.9 301.2 178.1 393.0 313.3 178.9 414.9 274.6 170.6 350.0 254.2 167.6 314.2 212.0 147.9 253.9 183.3 144.2 203.2 172.6 135.5 191.6 170.2 136.1 186.5 160.7 133.3 171.5 159.9 130.5 172.7 164.8 136.7 175.8 172.5 140.8 186.3 180.8 141.2 201.5 Special groupings: Finished goods, excluding foods................ Finished energy goods............................... Finished goods less energy........................ Finished consumer goods less energy....... Finished goods less food and energy......... 166.2 156.3 162.8 168.7 161.7 176.6 178.7 169.8 176.9 167.2 182.8 204.6 169.4 176.8 166.0 185.9 214.0 170.2 177.7 166.7 182.2 198.6 170.8 178.3 167.4 182.1 197.0 171.2 178.7 167.9 176.3 167.8 173.1 180.2 170.8 169.6 144.1 172.7 179.7 170.6 166.1 130.6 172.3 179.0 170.8 168.0 136.4 172.7 179.4 171.3 168.0 136.3 172.1 178.6 171.3 167.0 132.4 171.9 178.5 171.4 167.9 135.7 172.3 179.3 171.3 169.3 141.6 171.7 178.5 171.1 172.8 153.1 172.4 179.5 171.5 and energy................................................ Consumer nondurable goods less food 170.0 176.4 175.2 175.9 176.6 177.2 180.2 180.0 180.1 180.7 181.0 181.4 181.5 181.3 181.8 and energy.............................................. 197.0 206.8 206.0 207.6 208.5 209.7 210.7 210.9 211.0 212.4 212.9 213.8 214.0 213.8 214.1 171.5 154.4 174.6 167.6 188.7 181.6 208.1 180.9 197.8 186.6 240.3 183.9 203.6 195.5 253.5 187.9 199.7 194.3 231.3 188.9 199.1 190.0 227.5 188.8 189.5 179.9 197.4 184.5 179.4 174.7 167.3 179.8 171.8 167.9 147.7 175.3 171.8 165.8 152.2 174.0 170.1 164.6 149.3 172.7 168.4 164.0 142.6 172.3 167.9 164.4 146.2 170.9 168.8 167.3 151.4 170.9 172.8 169.6 167.8 171.6 and energy................................................ 168.4 180.9 183.8 187.5 188.7 188.8 184.8 180.2 175.9 174.6 173.4 173.0 171.5 171.2 171.7 Crude energy materials.............................. Crude materials less energy....................... Crude nonfood materials less energy......... 232.8 182.6 282.6 309.4 205.4 324.4 400.4 228.2 373.8 426.5 231.7 386.1 339.1 222.3 374.2 303.7 211.7 337.5 244.4 182.0 276.7 194.9 167.6 224.8 181.1 159.8 221.3 173.0 161.2 225.2 152.1 158.8 224.9 153.8 155.7 221.7 158.2 160.6 220.5 166.4 167.2 235.4 184.1 168.7 240.9 Finished consumer goods Materials and components for manufacturing...................................... Materials for food manufacturing.............. Materials for nondurable manufacturing... Materials for durable manufacturing......... Components for manufacturing................ Materials and components Finished consumer goods less food Intermediate materials less foods and feeds.................................................. Intermediate foods and feeds..................... Intermediate energy goods......................... Intermediate goods less energy.................. Intermediate materials less foods p = preliminary. Monthly Labor Review • August 2009 105 Current Labor Statistics: Price Data 42. Producer Price Indexes for the net output of major industry groups [December 2003 = 100, unless otherwise indicated] NAICS Industry 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. p Apr.p May p Junep Total mining industries (December 1984=100)............................. Oil and gas extraction (December 1985=100) ............................. Mining, except oil and gas…………………………………………… Mining support activities……………………………………………… 341.4 456.0 185.8 173.1 363.8 490.4 191.8 175.9 299.2 383.6 190.4 177.1 273.4 341.2 188.9 177.6 223.3 259.4 184.1 179.3 184.9 199.5 174.7 179.9 174.8 184.1 173.0 177.0 173.4 180.3 178.4 174.0 159.0 154.1 184.7 172.0 157.2 152.9 181.6 168.2 161.1 159.4 184.6 162.2 168.3 170.1 188.9 159.5 181.0 191.7 189.6 154.3 Total manufacturing industries (December 1984=100)................ Food manufacturing (December 1984=100)………………………… Beverage and tobacco manufacturing........................................... Textile mills.................................................................................... Apparel manufacturing………………………………...……………… Leather and allied product manufacturing (December 1984=100) Wood products manufacturing……………………………………… Paper manufacturing..................................................................... Printing and related support activities........................................... Petroleum and coal products manufacturing 182.0 176.1 114.1 111.7 102.1 153.4 109.2 120.9 109.5 406.0 185.6 180.3 115.0 112.6 102.3 153.8 108.9 121.8 109.8 429.6 182.6 180.5 114.8 114.2 102.5 154.1 109.1 124.5 110.0 382.2 182.9 179.2 115.2 114.9 102.7 154.8 109.1 126.6 110.4 382.6 176.8 176.4 116.1 114.9 103.0 154.6 107.6 127.3 110.3 300.0 169.4 173.4 116.0 114.7 103.2 154.3 106.7 127.2 110.2 221.4 164.1 171.1 116.3 113.5 103.2 154.3 106.2 127.0 110.3 167.0 164.7 170.1 117.6 113.4 103.5 154.3 105.0 126.7 110.2 178.6 163.9 168.7 119.2 113.0 103.5 154.7 104.0 126.0 109.6 176.4 163.0 167.7 120.3 112.7 103.8 155.0 103.0 125.6 109.4 166.6 163.8 168.5 119.9 112.9 103.7 154.5 102.7 124.6 109.5 182.5 165.6 170.4 119.3 112.2 103.8 153.4 102.3 123.1 109.3 205.2 168.5 171.4 119.5 112.4 103.5 153.6 102.1 122.3 109.0 238.4 325 326 (December 1984=100)………………………………….………… Chemical manufacturing (December 1984=100)…………………… 228.5 159.4 Plastics and rubber products manufacturing 234.5 162.9 238.2 165.2 240.4 166.9 239.3 167.8 234.5 166.9 229.7 165.0 226.7 163.4 225.1 161.6 226.9 160.6 224.0 160.5 222.9 160.4 223.3 159.8 331 332 333 334 335 336 337 Primary metal manufacturing (December 1984=100)……………… Fabricated metal product manufacturing (December 1984=100)… Machinery manufacturing………………………..…………………… Computer and electronic products manufacturing………………… Electrical equipment, appliance, and components manufacturing Transportation equipment manufacturing…………………………… Furniture and related product manufacturing 227.8 174.7 116.4 92.8 128.2 105.9 171.3 232.7 177.2 117.9 92.8 129.1 105.9 172.3 233.5 178.8 118.3 92.7 129.3 106.5 173.5 228.9 179.6 118.8 92.7 129.8 106.6 174.3 214.9 179.6 119.4 92.7 129.4 110.4 175.1 199.9 179.3 119.9 92.6 127.3 110.0 175.3 185.6 178.5 120.0 92.4 126.9 110.1 175.7 177.6 178.9 120.5 92.5 126.8 110.0 176.1 173.3 177.7 120.4 92.4 126.8 109.9 177.0 169.1 176.6 120.5 92.3 126.9 109.5 176.9 163.8 175.1 120.3 92.5 127.7 109.2 176.5 162.2 174.7 120.3 92.5 128.3 108.9 176.5 163.7 174.3 120.2 92.3 128.4 109.5 177.0 339 Miscellaneous manufacturing………………………………………… 109.9 110.8 110.5 110.4 110.6 110.4 110.8 111.4 111.4 111.6 111.1 111.5 111.5 118.1 119.6 105.8 127.8 67.6 141.8 118.4 120.3 106.5 133.8 77.2 140.6 117.5 122.0 111.0 133.3 72.7 162.4 117.6 121.1 110.8 134.0 81.7 150.6 116.8 121.0 108.9 134.6 76.8 148.7 118.5 120.8 108.1 136.4 76.3 154.1 117.1 120.6 107.8 136.4 77.7 155.2 116.9 120.8 107.8 136.0 68.9 150.9 118.4 121.0 103.7 136.0 71.0 153.9 117.2 120.7 102.4 137.9 62.4 159.0 118.5 121.4 106.9 139.7 59.2 146.5 118.3 123.7 104.6 137.4 59.2 142.5 119.3 121.9 103.0 136.5 69.6 140.0 Air transportation (December 1992=100)…………………………… 213.5 Water transportation…………………………………………………… 127.0 Postal service (June 1989=100)……………………………………… 180.5 213.6 130.4 180.5 213.0 133.7 180.5 208.6 135.1 180.5 209.3 135.0 180.5 203.8 130.6 180.5 198.5 128.0 180.5 198.4 122.4 180.5 190.5 118.5 181.6 184.9 117.5 181.6 186.7 118.0 181.6 176.1 117.5 186.8 177.0 110.6 186.8 146.8 145.7 140.8 136.0 133.4 133.1 133.9 132.9 130.2 126.7 126.9 129.1 123.2 106.9 125.4 162.6 118.6 118.5 123.5 106.9 125.6 163.2 119.4 118.6 123.6 106.9 126.3 163.2 119.7 118.7 123.7 107.6 126.5 163.0 119.8 118.9 124.0 107.7 127.3 164.9 120.6 119.1 124.3 107.7 127.3 164.9 120.6 119.2 124.2 107.8 127.4 165.3 120.7 119.2 125.6 108.3 127.2 166.5 122.0 120.3 125.6 108.7 127.6 166.8 122.2 120.3 125.7 108.4 127.4 166.4 121.7 120.4 125.8 109.0 127.2 166.6 122.6 120.5 125.7 108.8 127.3 166.9 122.7 121.5 125.9 108.7 127.7 167.1 123.1 121.1 110.4 104.4 101.1 100.8 120.2 110.4 106.9 108.2 125.4 161.1 112.7 111.0 103.9 101.0 100.9 119.1 110.9 106.8 109.2 136.7 161.5 115.3 111.1 105.5 101.5 101.0 120.2 112.7 104.4 109.3 135.0 161.5 115.5 110.2 107.0 101.5 101.1 120.5 111.7 103.8 108.6 131.3 162.6 115.4 110.9 112.0 101.2 101.3 117.7 111.5 103.1 109.2 128.2 163.2 115.6 111.1 111.5 101.2 101.3 115.8 111.7 103.0 108.2 126.9 163.2 115.0 110.7 109.3 101.4 101.3 115.2 112.8 102.8 109.8 123.7 163.2 115.7 111.9 107.9 101.2 101.0 113.5 111.0 101.6 109.9 128.3 164.8 115.3 111.9 108.1 101.1 100.9 111.7 109.0 101.6 108.6 133.0 165.5 115.2 111.4 109.3 101.0 100.8 108.4 110.1 101.6 110.8 133.0 166.0 115.3 111.5 106.6 100.6 100.9 110.9 109.1 101.9 109.6 134.9 166.1 115.2 111.7 107.1 101.8 100.9 111.8 109.0 101.9 109.7 134.6 166.1 115.3 111.8 107.4 101.2 101.0 110.9 109.4 101.9 108.9 138.1 166.2 115.3 141.3 106.3 122.8 98.8 109.1 112.6 147.0 141.6 106.3 123.0 98.8 109.0 112.3 149.9 141.6 106.3 123.4 98.8 109.3 113.3 150.9 141.6 106.3 123.1 101.4 109.4 114.0 146.9 141.8 106.3 123.6 101.4 109.4 113.0 145.6 141.8 106.3 124.1 101.4 109.4 113.3 144.3 141.9 106.3 124.2 101.4 109.1 111.3 141.6 142.9 105.6 123.8 101.4 109.6 112.2 140.6 142.9 105.4 124.0 101.8 109.7 113.3 139.9 142.3 105.3 123.2 102.6 109.5 116.4 142.3 142.9 105.4 124.1 99.7 109.6 116.3 142.0 142.9 105.4 123.3 99.7 109.6 115.8 143.8 142.9 105.2 123.8 100.2 109.7 115.0 144.6 211 212 213 311 312 313 315 316 321 322 323 324 (December 1984=100)………….………………………………… (December 1984=100)……………………………………………… Retail trade 441 442 443 446 447 454 Motor vehicle and parts dealers……………………………………… Furniture and home furnishings stores……………………………… Electronics and appliance stores…………………………………… Health and personal care stores……………………………………… Gasoline stations (June 2001=100)………………………………… Nonstore retailers……………………………………………………… Transportation and warehousing 481 483 491 Utilities 221 Utilities…………………………………………………………………… 141.7 Health care and social assistance 6211 6215 6216 622 6231 62321 Office of physicians (December 1996=100)………………………… Medical and diagnostic laboratories………………………………… Home health care services (December 1996=100)………………… Hospitals (December 1992=100)…………………………………… Nursing care facilities………………………………………………… Residential mental retardation facilities……………………………… Other services industries 511 515 517 5182 523 53112 5312 5313 5321 5411 541211 5413 Publishing industries, except Internet ……………………………… Broadcasting, except Internet………………………………………… Telecommunications…………………………………………………… Data processing and related services……………………………… Security, commodity contracts, and like activity…………………… Lessors or nonresidental buildings (except miniwarehouse)……… Offices of real estate agents and brokers…………………………… Real estate support activities………………………………………… Automotive equipment rental and leasing (June 2001=100)……… Legal services (December 1996=100)……………………………… Offices of certified public accountants……………………………… Architectural, engineering, and related services (December 1996=100)……………………………………………… 54181 Advertising agencies…………………………………………………… 5613 Employment services (December 1996=100)……………………… 56151 Travel agencies………………………………………………………… 56172 Janitorial services……………………………………………………… 5621 Waste collection………………………………………………………… 721 Accommodation (December 1996=100)…………………………… p = preliminary. 106 Monthly Labor Review • August 2009 43. Annual data: Producer Price Indexes, by stage of processing [1982 = 100] Index 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Finished goods Total............................................................................... Foods............................…………………………….…… Energy............……………………………………….….… Other…...............................………………………….…… 130.7 134.3 75.1 143.7 133.0 135.1 78.8 146.1 138.0 137.2 94.1 148.0 140.7 141.3 96.7 150.0 138.9 140.1 88.8 150.2 143.3 145.9 102.0 150.5 148.5 152.7 113.0 152.7 155.7 155.7 132.6 156.4 160.4 156.7 145.9 158.7 166.6 167.0 156.3 161.7 177.1 178.3 178.7 167.2 123.0 123.2 80.8 133.5 123.2 120.8 84.3 133.1 129.2 119.2 101.7 136.6 129.7 124.3 104.1 136.4 127.8 123.2 95.9 135.8 133.7 134.4 111.9 138.5 142.6 145.0 123.2 146.5 154.0 146.0 149.2 154.6 164.0 146.2 162.8 163.8 170.7 161.4 174.6 168.4 188.3 180.4 208.1 180.9 96.8 103.9 68.6 84.5 98.2 98.7 78.5 91.1 120.6 100.2 122.1 118.0 121.0 106.1 122.3 101.5 108.1 99.5 102.0 101.0 135.3 113.5 147.2 116.9 159.0 127.0 174.6 149.2 182.2 122.7 234.0 176.7 184.8 119.3 226.9 210.0 207.1 146.7 232.8 238.7 251.8 163.4 309.4 308.5 Intermediate materials, supplies, and components Total............................................................................... Foods............……………………………………….….… Energy…...............................………………………….… Other.................…………...………..........………….…… Crude materials for further processing Total............................................................................... Foods............................…………………………….…… Energy............……………………………………….….… Other…...............................………………………….…… 44. U.S. export price indexes by end-use category [2000 = 100] Category 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June ALL COMMODITIES…………….................................... 126.1 128.0 125.9 124.9 122.3 118.4 115.8 116.6 116.3 115.5 116.1 116.7 118.0 Foods, feeds, and beverages……………...…………… Agricultural foods, feeds, and beverages…............. Nonagricultural (fish, beverages) food products…… 198.0 204.0 146.1 211.5 218.9 147.0 189.6 194.7 145.7 190.4 195.6 145.5 175.0 178.3 147.8 164.8 166.9 148.3 155.1 156.6 143.5 165.4 167.6 147.9 162.1 164.1 145.7 156.7 158.3 144.4 162.8 165.0 145.4 167.0 170.0 141.7 175.2 178.9 143.7 Industrial supplies and materials……………...………… 173.2 177.8 174.0 169.4 161.8 148.2 139.6 139.0 137.9 136.5 136.9 138.1 141.2 Agricultural industrial supplies and materials…........ 158.0 162.8 160.9 157.4 148.5 134.2 126.1 125.6 126.2 122.9 123.5 133.3 136.2 Fuels and lubricants…...............................………… 297.2 312.3 275.8 267.2 239.2 193.4 166.8 165.8 156.2 146.9 156.9 160.5 174.1 Nonagricultural supplies and materials, excluding fuel and building materials…………...… Selected building materials…...............................… 161.6 113.8 165.1 114.5 165.3 115.2 160.8 115.4 155.5 116.6 145.6 115.6 138.8 115.1 138.2 115.5 138.2 115.3 138.2 114.0 137.2 113.3 137.6 112.0 139.3 112.1 Capital goods……………...…………………………….… 102.0 Electric and electrical generating equipment…........ 108.9 Nonelectrical machinery…...............................……… 94.2 101.9 109.3 94.0 101.9 109.2 94.1 101.8 109.5 93.9 101.7 109.7 93.6 101.6 109.2 93.5 101.5 109.0 93.3 102.1 107.3 93.7 102.3 106.7 94.0 102.3 106.8 93.8 102.8 106.7 94.3 103.0 106.9 94.4 103.2 106.8 94.5 Automotive vehicles, parts, and engines……………... 107.4 107.7 107.8 107.9 108.2 108.1 108.0 108.4 108.1 108.2 108.1 108.1 108.0 Consumer goods, excluding automotive……………... 108.2 Nondurables, manufactured…...............................… 110.1 Durables, manufactured…………...………..........…… 105.2 108.5 109.8 106.0 109.0 109.6 107.2 109.3 109.0 108.7 109.9 108.9 109.9 109.1 107.4 109.8 109.0 107.2 109.7 109.2 108.8 109.7 109.3 109.0 109.8 108.5 107.1 109.9 107.6 107.3 107.6 108.0 108.0 107.9 108.5 108.8 108.0 Agricultural commodities……………...………………… Nonagricultural commodities……………...…………… 208.2 122.3 188.2 121.5 188.3 120.4 172.5 118.7 160.6 115.4 150.8 113.2 159.7 113.5 157.0 113.3 151.6 112.9 157.2 113.1 163.0 113.4 170.8 114.3 195.2 121.2 Monthly Labor Review • August 2009 107 Current Labor Statistics: Price Data 45. U.S. import price indexes by end-use category [2000 = 100] Category 2008 June July Aug. Sept. 2009 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May ALL COMMODITIES…………….................................... 145.5 147.5 143.0 137.8 129.6 120.0 114.5 113.0 113.0 113.6 114.9 116.5 120.2 Foods, feeds, and beverages……………...…………… Agricultural foods, feeds, and beverages…............. Nonagricultural (fish, beverages) food products…… 147.7 165.1 108.4 149.7 167.6 109.1 150.4 167.9 110.9 147.9 165.1 109.1 146.0 162.8 108.0 139.5 154.4 105.8 142.3 159.4 103.8 142.3 159.0 104.5 137.8 153.0 103.4 137.0 151.3 104.8 139.0 154.5 103.9 139.3 155.2 103.4 140.0 155.8 104.1 Industrial supplies and materials……………...………… 283.0 290.7 270.7 248.9 213.5 174.6 150.4 143.7 144.9 149.3 154.3 161.7 178.3 Fuels and lubricants…...............................………… Petroleum and petroleum products…………...…… 423.7 450.3 437.6 465.0 392.0 419.5 346.3 371.5 274.1 288.9 197.8 201.6 153.9 150.8 146.6 143.8 150.5 151.6 162.3 168.5 174.4 185.5 188.6 202.7 223.8 243.8 Paper and paper base stocks…............................... 117.3 118.9 119.7 119.9 116.4 115.1 113.2 110.3 108.8 106.6 104.5 103.3 101.9 Materials associated with nondurable supplies and materials…...............................……… Selected building materials…...............................… Unfinished metals associated with durable goods… Nonmetals associated with durable goods…........... 152.9 119.2 273.2 107.6 157.4 121.3 273.4 110.7 159.6 122.1 270.3 111.8 162.4 122.7 255.4 111.4 160.2 120.4 236.7 110.9 155.0 118.8 209.3 110.4 148.5 118.1 185.7 109.0 138.8 117.2 176.5 107.1 137.1 116.5 175.9 106.2 136.7 116.2 171.6 105.2 135.3 115.3 170.9 104.6 139.5 114.5 171.9 103.8 138.7 115.8 176.5 103.7 Capital goods……………...…………………………….… 93.2 Electric and electrical generating equipment…........ 112.0 Nonelectrical machinery…...............................……… 88.2 93.4 112.7 88.4 93.4 113.0 88.3 93.3 112.9 88.2 93.3 112.3 88.1 92.9 111.8 87.7 92.7 111.4 87.5 92.7 111.1 87.5 92.3 110.3 87.2 91.8 109.4 86.6 91.9 109.2 86.8 91.9 110.0 86.7 91.8 110.2 86.6 Automotive vehicles, parts, and engines……………... 107.9 108.1 108.3 108.1 108.3 107.9 107.8 108.0 107.9 107.7 107.7 107.9 108.0 Consumer goods, excluding automotive……………... Nondurables, manufactured…...............................… Durables, manufactured…………...………..........…… Nonmanufactured consumer goods…………...……… 104.9 107.9 101.5 106.6 105.1 108.2 101.7 106.7 105.2 108.4 101.7 106.6 105.1 108.2 101.8 106.6 105.1 108.1 101.8 105.9 104.6 108.0 101.1 103.2 104.4 108.2 100.7 103.6 104.4 108.9 100.1 102.7 104.4 108.9 100.0 104.4 103.9 108.4 99.8 101.2 104.1 108.4 100.0 102.7 104.1 108.2 100.1 101.3 104.2 108.3 100.3 101.4 46. U.S. international price Indexes for selected categories of services [2000 = 100, unless indicated otherwise] Category 108 June 2007 June Sept. 2008 Dec. Mar. June 2009 Sept. Dec. Mar. June Import air freight……………........................................... Export air freight……………...…………………………… 132.3 117.0 134.2 119.8 141.8 127.1 144.4 132.0 158.7 140.8 157.1 144.3 138.5 135.0 132.9 124.1 133.9 117.4 Import air passenger fares (Dec. 2006 = 100)…………… Export air passenger fares (Dec. 2006 = 100)…............ 144.6 147.3 140.2 154.6 135.3 155.7 131.3 156.4 171.6 171.4 161.3 171.9 157.3 164.6 134.9 141.7 147.3 135.9 Monthly Labor Review • August 2009 47. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted [1992 = 100] 2006 Item II 2007 III IV I 138.7 169.1 120.3 121.9 136.7 127.4 138.0 169.7 119.7 123.0 137.3 128.3 138.7 173.3 122.5 124.9 135.1 128.7 139.0 175.2 122.7 126.0 136.7 130.0 137.7 168.0 119.6 122.0 139.0 128.3 137.0 168.6 118.9 123.0 139.5 129.1 137.8 172.3 121.8 125.0 136.9 129.3 142.1 159.4 113.4 114.0 112.2 118.9 175.8 134.4 119.6 143.4 159.8 112.7 113.5 111.4 119.1 191.4 138.7 120.6 172.5 148.8 105.9 86.3 174.4 149.4 105.4 85.7 II 2008 III IV I 140.2 176.5 122.4 125.9 139.4 130.9 142.1 177.8 122.6 125.1 141.9 131.4 142.6 179.6 122.1 125.9 141.9 131.9 142.7 180.3 121.2 126.3 141.7 132.1 138.2 174.2 122.1 126.0 138.2 130.5 139.2 175.1 121.4 125.8 140.9 131.4 141.1 176.3 121.5 125.0 143.3 131.7 141.8 178.5 121.3 125.9 143.0 132.2 143.6 162.5 114.9 115.3 113.2 120.9 175.8 135.9 120.8 143.5 164.2 115.0 116.8 114.4 123.1 171.2 136.2 121.8 144.5 165.2 114.6 117.2 114.4 124.9 171.8 137.7 122.2 144.1 166.2 114.5 118.6 115.3 127.4 155.6 135.1 122.0 175.3 153.0 108.2 87.3 176.9 156.1 109.3 88.2 178.2 156.1 108.2 87.6 180.1 156.1 107.6 86.7 II 2009 III IV I II 143.8 181.0 120.4 125.9 143.8 132.5 143.9 183.0 119.9 127.2 145.4 134.0 144.2 184.2 123.3 127.7 143.6 133.6 144.3 183.0 123.3 126.9 146.9 134.3 146.5 183.1 122.9 125.0 149.9 134.3 141.7 179.2 120.5 126.4 142.5 132.3 142.8 179.8 119.6 125.9 144.9 132.9 142.8 181.8 119.1 127.3 146.6 134.4 143.1 183.1 122.6 128.0 145.3 134.3 143.2 182.0 122.6 127.1 149.2 135.2 145.5 182.1 122.2 125.2 152.3 135.1 145.9 168.3 114.4 118.7 115.3 127.9 149.9 133.9 121.6 145.0 168.6 113.4 119.8 116.3 129.1 133.0 130.2 121.0 147.4 169.7 112.9 118.9 115.1 129.2 134.7 130.7 120.4 148.6 171.8 112.5 119.4 115.6 129.8 145.3 134.0 121.8 148.0 173.7 116.3 121.8 117.3 134.1 129.5 132.8 122.5 145.8 172.6 116.2 123.8 118.4 138.6 127.1 135.5 124.1 – – – – – – – – – 181.6 158.6 107.8 87.3 182.8 158.6 106.6 86.8 181.6 159.7 106.2 87.9 180.3 161.4 105.7 89.5 178.1 166.0 111.2 93.2 177.0 166.9 112.4 94.3 179.2 169.3 113.7 94.5 Business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfarm business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfinancial corporations Output per hour of all employees................................... Compensation per hour…………………………….……… Real compensation per hour……………………………… Total unit costs…...............................…………………… Unit labor costs............................................................. Unit nonlabor costs...................................................... Unit profits...................................................................... Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Manufacturing Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… NOTE: Dash indicates data not available. Monthly Labor Review • August 2009 109 Current Labor Statistics: Productivity Data 48. Annual indexes of multifactor productivity and related measures, selected years [2000 = 100, unless otherwise indicated] Item 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Private business Productivity: Output per hour of all persons......…………….............. 90.0 Output per unit of capital services……………………… 105.3 Multifactor productivity…………………………………… 95.3 Output…...............................………………………….…… 82.8 91.7 105.3 96.2 87.2 94.3 103.8 97.4 91.5 97.2 102.3 98.8 96.2 100.0 100.0 100.0 100.0 102.8 96.0 100.4 100.5 107.1 94.7 102.5 102.0 111.2 95.5 105.4 105.2 114.5 97.2 108.2 109.7 116.6 98.1 109.7 113.6 117.6 98.4 110.3 117.1 119.5 97.7 110.7 119.5 122.7 95.6 112.0 120.4 90.8 78.7 86.9 85.5 94.4 82.9 90.7 87.1 96.5 88.2 93.9 90.9 98.8 94.1 97.4 95.0 100.0 100.0 100.0 100.0 98.2 104.6 100.0 107.0 96.2 107.7 99.5 113.1 95.8 110.2 99.9 116.5 96.9 112.9 101.4 117.8 98.8 115.8 103.6 118.9 101.2 119.1 106.2 119.6 102.3 122.3 108.0 122.3 100.3 125.9 107.6 128.3 Productivity: Output per hour of all persons........……………………… 90.5 Output per unit of capital services……………………… 106.1 95.8 Multifactor productivity…………………………………… Output…...............................………………………….…… 82.8 92.0 105.8 96.5 87.2 94.5 104.2 97.7 91.5 97.3 102.6 99.0 96.3 100.0 100.0 100.0 100.0 102.7 96.0 100.4 100.5 107.1 94.5 102.5 102.1 111.1 95.2 105.2 105.2 114.2 96.9 108.0 109.6 116.1 97.7 109.3 113.5 117.2 97.9 109.9 117.1 118.9 97.0 110.1 119.4 122.3 95.1 111.4 120.4 90.4 78.1 86.5 85.3 94.0 82.4 90.4 86.9 96.3 87.8 93.7 90.7 98.8 93.9 97.3 94.8 100.0 100.0 100.0 100.0 98.4 104.7 100.2 107.0 96.4 107.9 99.6 113.2 96.0 110.5 100.0 116.7 97.1 113.1 101.5 117.8 99.1 116.1 103.8 118.9 101.6 119.6 106.6 119.7 102.8 123.1 108.4 122.6 100.9 126.7 108.1 128.8 Productivity: Output per hour of all persons...………………………… Output per unit of capital services……………………… Multifactor productivity…………………………………… Output…...............................………………………….…… 82.7 98.0 91.2 83.1 87.3 100.6 93.8 89.2 92.0 100.7 95.9 93.8 96.1 100.4 96.7 97.4 100.0 100.0 100.0 100.0 101.6 93.5 98.7 94.9 108.6 92.3 102.4 94.3 115.3 93.2 105.2 95.2 117.9 95.4 108.0 96.9 123.5 98.9 108.4 100.4 125.0 100.2 110.1 102.3 – – – – – – – – Inputs: Hours of all persons..................................................... Capital services…………...………..........………….…… Energy……………….………......................................... Nonenergy materials.................................................... Purchased business services....................................... Combined units of all factor inputs…………...………... 100.4 84.8 110.4 86.0 88.5 91.1 102.2 88.7 108.2 92.9 92.1 95.1 101.9 93.2 105.4 97.7 95.0 97.8 101.3 97.0 105.5 102.6 100.0 100.7 100.0 100.0 100.0 100.0 100.0 100.0 93.5 101.5 90.6 93.3 100.7 96.2 86.8 102.1 89.3 88.4 98.2 92.1 82.6 102.1 84.4 87.7 99.1 90.5 82.2 101.6 84.0 87.3 97.0 89.7 81.3 101.5 91.6 92.4 104.5 92.7 81.8 102.0 86.6 91.5 106.6 92.9 – – – – – – – – – – – – – – Inputs: Labor input................................................................... Capital services…………...………..........………….…… Combined units of labor and capital input……………… Capital per hour of all persons.......................…………… Private nonfarm business Inputs: Labor input................................................................... Capital services…………...………..........………….…… Combined units of labor and capital input……………… Capital per hour of all persons......………………………… Manufacturing [1996 = 100] NOTE: Dash indicates data not available. 110 Monthly Labor Review • August 2009 49. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years [1992 = 100] Item 1963 1973 1983 1993 2000 2001 2002 2003 2004 2005 2006 2007 2008 Business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… 55.0 15.6 66.6 28.4 26.6 27.7 73.4 28.9 85.1 39.4 37.5 38.7 83.0 66.3 90.5 79.8 76.3 78.5 100.4 102.2 99.8 101.8 102.6 102.1 116.1 134.7 112.0 116.0 107.2 112.7 119.1 140.3 113.5 117.9 110.0 114.9 123.9 145.3 115.7 117.3 114.2 116.1 128.7 151.2 117.7 117.5 118.3 117.8 132.4 157.0 119.0 118.5 124.6 120.8 134.8 163.2 119.7 121.0 130.5 124.6 136.1 169.4 120.3 124.5 134.8 128.3 138.2 176.5 121.9 127.7 137.7 131.4 141.9 182.8 121.6 128.8 142.1 133.8 57.8 16.1 68.7 27.8 26.3 27.3 75.3 29.1 85.5 38.6 35.3 37.4 84.5 66.6 91.1 78.9 76.1 77.9 100.4 102.0 99.5 101.6 103.1 102.1 115.7 134.2 111.6 116.0 108.7 113.3 118.6 139.5 112.8 117.7 111.6 115.4 123.5 144.6 115.1 117.1 116.0 116.7 128.0 150.4 117.1 117.5 119.6 118.3 131.6 156.0 118.2 118.5 125.5 121.1 133.9 162.1 118.9 121.1 132.1 125.1 135.1 168.3 119.5 124.5 136.8 129.1 137.0 175.2 121.0 127.9 138.4 131.7 140.9 181.7 120.8 129.0 143.3 134.2 62.6 17.9 76.4 27.2 28.6 23.4 57.3 32.5 29.9 74.8 31.0 91.2 39.9 41.4 35.7 54.9 40.8 41.2 85.7 68.9 94.2 80.7 80.4 81.6 91.2 84.2 81.7 100.3 101.8 99.3 101.0 101.4 99.9 114.1 103.7 102.2 122.5 133.0 110.6 107.4 108.6 104.2 108.7 105.4 107.5 124.7 138.6 112.1 111.6 111.2 112.6 82.2 104.5 108.9 129.7 143.6 114.3 110.7 110.7 110.8 98.0 107.4 109.6 134.6 149.5 116.4 111.0 111.0 111.1 109.9 110.7 110.9 139.7 154.0 116.8 110.0 110.3 109.3 144.8 118.8 113.1 143.4 159.6 117.1 111.7 111.3 112.7 163.0 126.2 116.3 146.0 165.4 117.5 113.6 113.3 114.6 183.5 133.0 119.9 147.1 172.2 118.9 117.4 117.1 118.3 167.3 131.4 121.9 151.2 178.9 119.0 119.1 118.3 121.3 149.9 129.0 121.9 – – – – – – – – – – – – – – – – – – 102.6 102.0 99.6 99.5 101.1 100.6 139.1 134.7 112.0 96.9 103.5 101.4 141.2 137.8 111.5 97.6 102.0 100.6 151.0 147.8 117.7 97.9 100.3 99.5 160.4 158.2 123.2 98.7 102.9 101.5 164.0 161.5 122.5 98.5 110.2 106.4 171.9 164.5 120.7 95.7 122.2 113.5 173.7 171.2 121.6 98.6 126.6 117.4 179.2 177.4 122.5 99.0 – – 180.7 184.7 122.8 102.2 – – Nonfarm business Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Nonfinancial corporations Output per hour of all employees................................... Compensation per hour…………………………….……… Real compensation per hour……………………………… Total unit costs…...............................…………………… Unit labor costs............................................................. Unit nonlabor costs...................................................... Unit profits...................................................................... Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Manufacturing Output per hour of all persons........................................ Compensation per hour…………………………….……… Real compensation per hour……………………………… Unit labor costs…...............................…………………… Unit nonlabor payments…………...………..........……… Implicit price deflator……………………………………… Dash indicates data not available. Monthly Labor Review • August 2009 111 Current Labor Statistics: Productivity Data 50. Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS 112 Industry Mining 21 211 2111 212 2121 2122 2123 213 2131 Mining……………………………..……………………… Oil and gas extraction………………………………… Oil and gas extraction………………………………… Mining, except oil and gas…………………………… Coal mining……………………………………………. Metal ore mining………………………………………… Nonmetallic mineral mining and quarrying………… Support activities for mining…………………………… Support activities for mining…………………………… 2211 2212 Power generation and supply………………………… Natural gas distribution………………………………… 311 3111 3112 3113 3114 Food……………………………..……………………… Animal food……………………………………………… Grain and oilseed milling……………………………… Sugar and confectionery products…………………… Fruit and vegetable preserving and specialty……… 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 85.3 80.1 80.1 69.3 57.8 71.0 88.0 79.4 79.4 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 103.5 101.2 101.2 104.5 106.5 108.9 101.2 96.0 96.0 111.4 107.9 107.9 105.8 110.3 112.3 101.2 98.5 98.5 111.0 119.4 119.4 106.3 115.8 121.5 96.1 100.9 100.9 109.1 121.6 121.6 109.0 114.3 132.2 99.4 110.4 110.4 113.5 123.8 123.8 110.7 111.7 138.2 103.6 103.5 103.5 116.0 130.1 130.1 113.8 113.4 142.2 108.3 136.3 136.3 106.8 111.7 111.7 116.2 113.4 137.1 114.3 170.3 170.3 96.0 107.8 107.8 114.2 107.8 129.9 118.4 144.9 144.9 87.3 100.4 100.4 111.0 99.8 123.1 120.0 147.0 147.0 81.7 97.0 97.0 105.2 101.0 104.2 109.8 156.8 156.8 65.6 67.8 100.0 100.0 103.7 99.0 103.5 102.7 107.0 113.2 106.4 110.1 102.9 115.4 105.1 114.1 107.5 118.3 114.3 122.2 115.4 119.1 113.3 119.7 94.1 83.6 81.1 87.6 92.4 100.0 100.0 100.0 100.0 100.0 103.9 109.0 107.5 103.5 107.1 105.9 110.9 116.1 106.5 109.5 107.1 109.7 113.1 109.9 111.8 109.5 131.4 119.5 108.6 121.4 113.8 142.7 122.4 108.0 126.9 116.8 165.8 123.9 112.5 123.0 117.3 149.5 130.3 118.2 126.2 123.3 165.5 133.0 130.7 132.0 121.1 150.4 130.7 129.2 126.9 - 3115 3116 3117 3118 3119 Dairy products…………………………………………… 82.7 Animal slaughtering and processing………………… 97.4 Seafood product preparation and packaging………. 123.1 Bakeries and tortilla manufacturing…………………… 100.9 Other food products…………………………………… 97.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 120.2 103.8 107.8 93.6 101.2 131.6 108.6 111.4 95.9 102.6 140.5 108.3 112.6 97.1 103.7 153.0 109.9 106.2 105.0 107.3 169.8 108.9 111.9 110.5 106.6 173.2 109.3 118.8 107.4 108.0 162.2 113.8 119.3 109.6 117.4 186.1 115.4 116.2 110.2 116.9 203.8 110.5 116.3 - 312 3121 3122 313 3131 Beverages and tobacco products…………………… Beverages……………………………………………… Tobacco and tobacco products……………………… Textile mills……………………………………………… Fiber, yarn, and thread mills…………………………… 78.1 77.1 71.9 73.7 66.5 100.0 100.0 100.0 100.0 100.0 97.6 99.0 98.5 102.6 102.1 87.3 90.7 91.0 106.2 103.9 88.3 90.8 95.9 106.7 101.3 89.5 92.7 98.2 109.5 109.1 82.6 99.4 67.0 125.3 133.3 90.9 108.3 78.7 136.1 148.8 94.7 114.1 82.4 138.6 154.1 100.5 120.3 93.1 152.8 143.5 94.0 112.0 94.9 150.5 139.7 - 3132 3133 314 3141 3149 Fabric mills……………………………………………… Textile and fabric finishing mills……………………… Textile product mills…………………………………… Textile furnishings mills………………………………… Other textile product mills……………………………… 68.0 91.3 93.0 91.2 92.2 100.0 100.0 100.0 100.0 100.0 104.2 101.2 98.7 99.3 96.7 110.0 102.2 102.5 99.1 107.6 110.1 104.4 107.1 104.5 108.9 110.3 108.5 104.5 103.1 103.1 125.4 119.8 107.3 105.5 105.1 137.3 125.1 112.7 114.4 104.2 138.6 127.7 123.4 122.3 120.4 164.2 139.8 128.0 125.7 128.9 170.5 126.2 121.1 117.3 126.1 - 315 3151 3152 3159 316 Apparel…………………………………………………. Apparel knitting mills…………………………………… Cut and sew apparel…………………………………… Accessories and other apparel……………………… Leather and allied products…………………………… 71.9 76.2 69.8 97.8 71.6 100.0 100.0 100.0 100.0 100.0 101.8 96.1 102.3 109.0 106.6 111.7 101.4 114.6 99.3 112.7 116.8 108.9 119.8 98.3 120.3 116.5 105.6 119.5 105.2 122.4 102.9 112.0 103.9 76.1 97.7 112.4 105.6 117.2 78.7 99.8 103.4 96.6 108.4 70.8 109.5 110.9 120.0 113.5 74.0 123.6 114.0 123.7 117.6 67.3 132.5 - 3161 3162 3169 321 3211 Leather and hide tanning and finishing……………… Footwear………………………………………………… Other leather products………………………………… Wood products………………………………………… Sawmills and wood preservation……………………… 94.0 76.7 92.3 95.0 77.6 100.0 100.0 100.0 100.0 100.0 100.3 102.1 113.3 101.2 100.3 98.1 117.3 110.4 102.9 104.7 100.1 122.3 122.8 102.7 105.4 100.3 130.7 117.6 106.1 108.8 81.2 102.7 96.2 113.6 114.4 82.2 104.8 100.3 114.7 121.3 93.5 100.7 127.7 115.6 118.2 118.7 105.6 149.7 123.1 127.3 118.1 115.4 174.6 124.9 129.7 - 3212 3219 322 3221 3222 Plywood and engineered wood products…………… 99.7 Other wood products…………………………………… 103.0 Paper and paper products…………………………… 85.8 Pulp, paper, and paperboard mills…………………… 81.7 Converted paper products…………………………… 89.0 100.0 100.0 100.0 100.0 100.0 105.1 101.0 102.3 102.5 102.5 98.7 104.5 104.1 111.1 100.1 98.8 103.0 106.3 116.3 101.1 105.2 104.7 106.8 119.9 100.5 110.3 113.9 114.2 133.1 105.6 107.0 113.9 118.9 141.4 109.6 102.9 119.6 123.4 148.0 112.9 110.2 126.3 124.5 147.7 114.8 117.4 125.3 127.3 151.1 116.6 - 323 3231 324 3241 325 Printing and related support activities………………… Printing and related support activities………………… Petroleum and coal products………………………… Petroleum and coal products………………………… Chemicals……………………………………………… 97.6 97.6 71.1 71.1 85.9 100.0 100.0 100.0 100.0 100.0 100.6 100.6 102.2 102.2 99.9 102.8 102.8 107.1 107.1 103.5 104.6 104.6 113.5 113.5 106.6 105.3 105.3 112.1 112.1 105.3 110.2 110.2 118.0 118.0 114.2 111.1 111.1 119.2 119.2 118.4 114.5 114.5 123.4 123.4 125.8 119.5 119.5 123.8 123.8 134.1 121.1 121.1 122.8 122.8 137.5 - 3251 3252 3253 3254 3255 Basic chemicals………………………………………… Resin, rubber, and artificial fibers…………………… Agricultural chemicals………………………………… Pharmaceuticals and medicines……………………… Paints, coatings, and adhesives……………………… 94.6 77.4 80.4 87.3 89.4 100.0 100.0 100.0 100.0 100.0 102.8 106.0 98.8 93.8 100.1 115.7 109.8 87.4 95.7 100.3 117.5 109.8 92.1 95.6 100.8 108.8 106.2 90.0 99.5 105.6 123.8 123.1 99.2 97.4 108.9 136.0 122.2 108.4 101.5 115.2 154.4 121.9 117.4 104.1 119.1 165.2 130.5 132.5 110.0 120.8 169.3 134.9 130.7 115.0 115.4 - 3256 3259 326 3261 3262 Soap, cleaning compounds, and toiletries…………… Other chemical products and preparations………… Plastics and rubber products………………………… Plastics products……………………………………… Rubber products………………………………………… 84.4 75.4 80.9 83.1 75.5 100.0 100.0 100.0 100.0 100.0 98.0 99.2 103.2 104.2 99.4 93.0 109.3 107.9 109.9 100.2 102.8 119.7 110.2 112.3 101.7 106.0 110.4 112.3 114.6 102.3 124.1 120.8 120.8 123.8 107.1 118.2 123.0 126.0 129.5 111.0 135.3 121.3 128.7 131.9 114.4 153.1 123.5 132.6 135.6 118.7 162.9 118.1 132.8 133.8 124.9 - 327 3271 Nonmetallic mineral products………………………… Clay products and refractories………………………… 87.6 86.9 100.0 100.0 103.7 101.2 104.3 102.7 102.5 102.9 100.0 98.4 104.6 99.7 111.2 103.5 108.7 109.2 115.3 114.6 114.6 111.9 - Utilities Manufacturing Monthly Labor Review • August 2009 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS Industry 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 3272 3273 3274 3279 331 Glass and glass products……………………………… Cement and concrete products……………………… Lime and gypsum products…………………………… Other nonmetallic mineral products………………… Primary metals………………………………………… 82.4 93.6 88.2 83.0 81.0 100.0 100.0 100.0 100.0 100.0 101.3 105.1 114.9 99.0 102.0 106.7 105.9 104.4 95.6 102.8 108.1 101.6 98.5 96.6 101.3 102.9 98.0 101.8 98.6 101.0 107.5 102.4 99.0 106.9 115.2 115.3 108.3 107.1 113.6 118.2 113.8 102.8 104.7 110.6 132.0 123.1 106.5 119.3 118.9 135.5 132.9 103.1 116.5 116.3 134.3 - 3311 3312 3313 3314 3315 Iron and steel mills and ferroalloy production……… Steel products from purchased steel………………… Alumina and aluminum production…………………… Other nonferrous metal production…………………… Foundries………………………………………………… 64.8 79.7 90.5 96.8 81.4 100.0 100.0 100.0 100.0 100.0 101.3 100.6 101.5 111.3 101.2 104.8 93.8 103.5 108.4 104.5 106.0 96.4 96.6 102.3 103.6 104.4 97.9 96.2 99.5 107.4 125.1 96.8 124.5 107.6 116.7 130.4 93.9 126.8 120.6 116.3 164.9 88.6 137.3 123.1 123.9 163.1 90.8 154.4 122.3 128.6 163.5 86.1 151.7 115.7 131.8 - 332 3321 3322 3323 3324 Fabricated metal products…………………………… Forging and stamping………………………………… Cutlery and handtools………………………………… Architectural and structural metals…………………… Boilers, tanks, and shipping containers……………… 87.3 85.4 86.3 88.7 86.0 100.0 100.0 100.0 100.0 100.0 101.3 103.5 99.9 100.9 100.0 103.0 110.9 108.0 102.0 96.5 104.8 121.1 105.9 100.6 94.2 104.8 120.7 110.3 101.6 94.4 110.9 125.0 113.4 106.0 98.9 114.4 133.1 113.2 108.8 101.6 113.4 142.0 107.6 105.4 93.6 116.9 147.6 114.1 109.2 95.7 119.7 152.7 116.6 113.5 96.6 - 3325 3326 3327 3328 3329 Hardware………………………………………………… Spring and wire products……………………………… Machine shops and threaded products……………… Coating, engraving, and heat treating metals……… Other fabricated metal products……………………… 88.7 82.2 76.9 75.5 91.0 100.0 100.0 100.0 100.0 100.0 100.5 110.6 99.6 100.9 101.9 105.2 111.4 104.2 101.0 99.6 114.3 112.6 108.2 105.5 99.9 113.5 111.9 108.8 107.3 96.7 115.5 125.7 114.8 116.1 106.5 125.4 135.3 115.7 118.3 111.6 126.0 133.8 114.6 125.3 111.2 131.8 143.2 116.3 136.5 112.5 131.1 140.6 117.1 135.5 117.7 - 333 3331 3332 3333 3334 Machinery……………………………………………… Agriculture, construction, and mining machinery…… Industrial machinery…………………………………… Commercial and service industry machinery………… HVAC and commercial refrigeration equipment…… 82.3 74.6 75.1 87.0 84.0 100.0 100.0 100.0 100.0 100.0 102.9 103.3 95.1 106.3 106.2 104.7 94.3 105.8 110.0 110.2 111.5 100.3 130.0 101.3 107.9 109.0 100.3 105.8 94.5 110.8 116.6 103.7 117.6 97.8 118.6 125.2 116.1 117.0 104.7 130.0 127.0 125.4 126.5 106.5 132.8 134.1 129.4 122.4 115.1 137.1 137.4 129.1 135.3 122.3 133.4 - 3335 3336 3339 334 3341 Metalworking machinery……………………………… Turbine and power transmission equipment………… Other general purpose machinery…………………… Computer and electronic products…………………… Computer and peripheral equipment………………… 85.1 80.2 83.5 28.4 11.0 100.0 100.0 100.0 100.0 100.0 99.1 105.0 103.7 118.4 140.4 100.3 110.8 106.0 149.5 195.9 106.1 114.9 113.7 181.8 235.0 103.3 126.9 110.5 181.4 252.2 112.7 130.7 117.9 188.0 297.4 115.2 143.0 128.1 217.2 373.4 117.1 126.4 127.1 244.3 415.1 127.3 132.5 138.4 259.6 543.3 128.3 128.5 143.8 282.2 715.7 - 3342 3343 3344 3345 3346 Communications equipment…………………………… Audio and video equipment…………………………… Semiconductors and electronic components………… Electronic instruments………………………………… Magnetic media manufacturing and reproduction…… 39.8 61.7 17.0 70.2 85.7 100.0 100.0 100.0 100.0 100.0 107.1 105.4 125.8 102.3 106.4 135.4 119.6 173.9 106.7 108.9 164.1 126.3 232.2 116.7 105.8 152.9 128.4 230.0 119.3 99.8 128.2 150.1 263.1 118.1 110.4 143.1 171.0 321.6 125.3 126.1 148.4 239.3 360.0 145.4 142.6 143.7 230.2 381.6 146.6 142.1 178.2 240.7 380.4 150.6 137.7 - 335 3351 3352 3353 3359 Electrical equipment and appliances………………… Electric lighting equipment…………………………… Household appliances………………………………… Electrical equipment…………………………………… Other electrical equipment and components………… 75.5 91.1 73.3 68.7 78.8 100.0 100.0 100.0 100.0 100.0 103.9 104.4 105.2 100.2 105.8 106.6 102.8 104.0 98.7 114.7 111.5 102.0 117.2 99.4 119.7 111.4 106.7 124.6 101.0 113.1 113.4 112.4 132.3 101.8 114.0 117.2 111.4 146.7 103.4 116.2 123.3 122.7 159.6 110.8 115.6 130.0 130.3 164.5 118.5 121.6 129.4 136.7 173.2 118.1 115.7 - 336 3361 3362 3363 3364 Transportation equipment……………………………… Motor vehicles…………………………………………… Motor vehicle bodies and trailers……………………… Motor vehicle parts……………………………………… Aerospace products and parts………………………… 81.6 75.4 85.0 78.7 87.2 100.0 100.0 100.0 100.0 100.0 109.7 113.4 102.9 104.9 119.1 118.0 122.6 103.1 110.0 120.8 109.4 109.7 98.8 112.3 103.4 113.6 110.0 88.7 114.8 115.7 127.4 126.0 105.4 130.5 118.6 137.5 140.7 109.8 137.0 119.0 134.9 142.1 110.7 138.0 113.2 140.9 148.4 114.2 144.1 125.0 142.4 163.8 110.9 143.7 117.9 - 3365 3366 3369 337 3371 Railroad rolling stock…………………………………… Ship and boat building………………………………… Other transportation equipment……………………… Furniture and related products………………………… Household and institutional furniture………………… 55.6 95.5 73.8 84.8 85.2 100.0 100.0 100.0 100.0 100.0 103.3 99.3 111.5 102.0 102.2 116.5 112.0 113.8 101.6 103.1 118.5 122.0 132.4 101.4 101.9 126.1 121.5 140.2 103.4 105.5 146.1 131.0 150.9 112.6 111.8 139.8 133.9 163.0 117.0 114.7 131.5 138.7 168.3 118.4 113.6 137.3 131.7 184.1 125.0 120.8 148.0 127.3 197.8 127.8 124.0 - 3372 3379 339 3391 3399 Office furniture and fixtures…………………………… Other furniture related products……………………… Miscellaneous manufacturing………………………… Medical equipment and supplies……………………… Other miscellaneous manufacturing………………… 85.8 86.3 81.1 76.3 85.4 100.0 100.0 100.0 100.0 100.0 100.0 106.9 105.2 109.0 102.1 98.2 102.0 107.8 111.1 105.0 100.2 99.5 114.7 115.5 113.6 98.0 105.0 116.6 120.7 111.8 115.9 110.2 124.2 129.1 118.0 125.2 110.0 132.7 138.9 124.7 130.7 121.3 134.9 139.5 128.6 134.9 128.3 144.6 148.5 137.8 134.4 130.8 149.8 152.8 143.2 - 42 423 4231 4232 4233 4234 Wholesale trade………………………………………… 73.2 Durable goods………………………………………… 62.3 Motor vehicles and parts……………………………… 74.5 Furniture and furnishings……………………………… 80.5 Lumber and construction supplies…………………… 109.1 Commercial equipment………………………………… 28.0 100.0 100.0 100.0 100.0 100.0 100.0 103.4 107.1 106.4 99.9 105.4 125.5 111.2 119.2 120.4 102.3 109.3 162.0 116.5 125.0 116.7 112.5 107.7 181.9 117.7 128.9 120.0 110.7 116.6 217.9 123.3 140.2 133.4 116.0 123.9 264.9 127.5 146.6 137.6 123.9 133.0 299.1 134.8 161.5 143.5 130.0 139.4 352.8 135.8 167.4 146.5 127.1 140.2 402.0 138.6 174.5 162.7 130.6 135.4 447.3 141.5 178.4 161.8 131.1 124.5 508.5 4235 4236 4237 4238 Metals and minerals…………………………………… 101.7 Electric goods…………………………………………… 42.8 Hardware and plumbing……………………………… 82.2 Machinery and supplies……………………………… 74.1 100.0 100.0 100.0 100.0 100.9 105.9 101.8 104.3 94.0 127.5 104.4 102.9 93.9 152.8 103.7 105.5 94.4 147.6 100.5 102.9 96.3 159.5 102.6 100.3 97.5 165.7 103.9 103.4 106.3 194.1 107.3 112.4 104.2 204.6 104.5 117.6 99.9 222.1 105.6 121.2 94.4 235.1 105.8 121.5 Wholesale trade Monthly Labor Review • August 2009 113 Current Labor Statistics: Productivity Data 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS 114 Industry 1987 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 4239 424 4241 4242 4243 Miscellaneous durable goods………………………… Nondurable goods……………………………………… Paper and paper products…………………………… Druggists' goods………………………………………… Apparel and piece goods……………………………… 89.8 91.0 85.6 70.7 86.3 100.0 100.0 100.0 100.0 100.0 100.8 99.1 98.4 94.2 103.6 113.7 100.8 100.1 93.1 105.1 114.7 105.1 100.9 85.9 108.8 116.8 105.1 104.6 84.9 115.2 124.6 105.8 116.6 89.8 122.8 119.6 110.5 119.7 100.2 125.9 135.0 113.6 130.9 105.8 131.0 135.5 114.3 141.7 112.1 140.8 122.3 113.1 136.9 109.7 146.6 118.4 115.0 146.5 104.3 148.3 4244 4245 4246 4247 4248 Grocery and related products………………………… Farm product raw materials…………………………… Chemicals……………………………………………… Petroleum……………………………………………… Alcoholic beverages…………………………………… 87.9 81.6 90.4 84.4 99.3 100.0 100.0 100.0 100.0 100.0 101.1 94.3 97.1 88.5 106.5 101.0 101.6 93.3 102.9 105.6 102.4 105.1 87.9 138.1 108.4 101.9 102.1 85.3 140.6 106.4 98.6 98.1 89.1 153.6 106.8 104.9 98.2 92.2 151.1 107.9 104.1 109.3 91.2 163.2 103.1 103.4 111.0 87.4 153.3 104.0 103.8 117.9 85.1 149.4 107.4 109.7 125.1 86.4 149.1 108.5 4249 425 4251 Miscellaneous nondurable goods…………………… Electronic markets and agents and brokers………… Electronic markets and agents and brokers………… 111.2 64.3 64.3 100.0 100.0 100.0 105.4 102.4 102.4 106.8 112.3 112.3 115.0 120.1 120.1 111.9 110.7 110.7 106.1 109.8 109.8 109.8 104.5 104.5 120.7 101.6 101.6 124.1 91.5 91.5 121.9 95.0 95.0 117.1 98.3 98.3 44-45 441 4411 4412 4413 Retail trade……………………………………………… Motor vehicle and parts dealers……………………… Automobile dealers…………………………………… Other motor vehicle dealers…………………………… Auto parts, accessories, and tire stores……………… 79.2 78.4 79.2 74.1 71.8 100.0 100.0 100.0 100.0 100.0 105.7 106.4 106.5 109.6 105.1 112.7 115.1 116.3 114.8 107.6 116.1 114.3 113.7 115.3 108.4 120.1 116.0 115.5 124.6 101.3 125.6 119.9 117.2 133.6 107.7 131.6 124.3 119.5 133.8 115.1 137.9 127.3 124.7 143.3 110.1 141.3 126.7 123.5 134.6 115.5 147.3 129.3 125.8 142.6 115.9 152.7 132.2 129.8 146.9 112.0 442 4421 4422 443 4431 Furniture and home furnishings stores……………… Furniture stores………………………………………… Home furnishings stores……………………………… Electronics and appliance stores……………………… Electronics and appliance stores……………………… 75.1 77.3 71.3 38.0 38.0 100.0 100.0 100.0 100.0 100.0 104.1 104.3 104.1 122.6 122.6 110.8 107.5 115.2 150.6 150.6 115.9 112.0 121.0 173.7 173.7 122.4 119.7 126.1 196.7 196.7 129.3 125.2 134.9 233.5 233.5 134.6 128.8 142.6 292.7 292.7 146.7 139.2 156.8 334.1 334.1 150.5 142.3 161.4 367.5 367.5 158.2 151.1 168.3 412.0 412.0 168.7 156.6 184.6 471.1 471.1 444 4441 4442 445 4451 Building material and garden supply stores………… Building material and supplies dealers……………… Lawn and garden equipment and supplies stores… Food and beverage stores…………………………… Grocery stores………………………………………… 75.8 77.6 66.9 110.8 111.1 100.0 100.0 100.0 100.0 100.0 107.4 108.3 102.4 99.9 99.6 113.8 115.3 105.5 101.9 102.5 113.3 115.1 103.1 101.0 101.1 116.8 116.7 118.4 103.8 103.3 120.8 121.3 118.3 104.7 104.8 127.1 127.4 125.7 107.2 106.7 134.6 134.0 140.1 112.9 112.2 134.8 134.9 134.7 117.9 116.8 137.9 138.0 138.3 120.6 118.2 142.2 140.0 162.1 123.8 120.6 4452 4453 446 4461 447 Specialty food stores…………………………………… 138.5 Beer, wine, and liquor stores………………………… 93.6 Health and personal care stores……………………… 84.0 Health and personal care stores……………………… 84.0 Gasoline stations……………………………………… 83.9 100.0 100.0 100.0 100.0 100.0 100.5 104.6 104.0 104.0 106.7 96.4 99.1 107.1 107.1 110.7 98.5 105.7 112.2 112.2 107.7 108.2 107.1 116.2 116.2 112.9 105.3 110.1 122.9 122.9 125.1 112.2 117.0 129.5 129.5 119.9 120.3 127.8 134.3 134.3 122.2 125.3 139.8 133.4 133.4 124.7 139.4 146.1 139.3 139.3 124.9 145.4 156.8 139.0 139.0 129.3 4471 448 4481 4482 4483 Gasoline stations……………………………………… Clothing and clothing accessories stores…………… Clothing stores………………………………………… Shoe stores……………………………………………… Jewelry, luggage, and leather goods stores………… 83.9 66.3 67.1 65.3 64.5 100.0 100.0 100.0 100.0 100.0 106.7 106.3 108.7 94.2 108.7 110.7 114.0 114.2 104.9 122.5 107.7 123.5 125.0 110.0 130.5 112.9 126.4 130.3 111.5 123.9 125.1 131.3 136.0 125.2 118.7 119.9 138.9 141.8 132.5 132.9 122.2 139.1 140.9 124.8 144.3 124.7 147.6 153.0 132.0 138.9 124.9 162.4 169.4 145.1 148.3 129.3 176.6 186.9 141.6 162.9 451 4511 4512 452 4521 Sporting goods, hobby, book, and music stores…… Sporting goods and musical instrument stores……… Book, periodical, and music stores…………………… General merchandise stores………………………… Department stores……………………………………… 74.9 73.2 78.9 73.5 87.2 100.0 100.0 100.0 100.0 100.0 107.9 111.5 101.0 105.3 100.4 114.0 119.8 103.2 113.4 104.5 121.1 129.4 105.8 120.2 106.2 127.1 134.5 113.0 124.8 103.8 127.6 136.0 111.6 129.1 102.0 131.5 141.1 113.7 136.9 106.8 151.1 166.0 123.6 140.7 109.0 163.5 179.3 134.3 145.0 110.0 170.5 191.4 132.4 149.8 112.7 167.8 189.2 128.3 152.5 107.0 4529 453 4531 4532 4533 Other general merchandise stores…………………… Miscellaneous store retailers………………………… Florists…………………………………………………. Office supplies, stationery and gift stores…………… Used merchandise stores……………………………… 54.8 65.1 77.6 61.4 64.5 100.0 100.0 100.0 100.0 100.0 114.7 108.9 102.3 111.5 119.1 131.0 111.3 116.2 119.2 113.4 147.3 114.1 115.2 127.3 116.5 164.7 112.6 102.7 132.3 121.9 179.3 119.1 113.8 141.5 142.0 188.8 126.1 108.9 153.9 149.7 192.9 130.8 103.4 172.8 152.6 199.8 139.2 123.7 182.4 156.6 204.8 155.0 145.1 204.8 167.6 219.3 160.8 132.9 224.5 182.0 4539 454 4541 4542 4543 Other miscellaneous store retailers…………………… Nonstore retailers……………………………………… Electronic shopping and mail-order houses………… Vending machine operators…………………………… Direct selling establishments………………………… 68.3 50.7 39.4 95.5 70.8 100.0 100.0 100.0 100.0 100.0 105.3 114.3 120.2 106.3 101.9 103.0 128.9 142.6 105.4 104.3 104.4 152.2 160.2 111.1 122.5 96.9 163.6 179.6 95.7 127.9 94.4 182.1 212.7 91.3 135.1 99.9 195.5 243.6 102.3 127.0 96.9 215.5 273.0 110.5 130.3 101.6 220.6 290.1 114.4 119.6 114.0 261.9 355.9 125.7 127.5 115.4 290.8 397.2 132.4 138.4 481 482111 48412 48421 491 4911 Air transportation……………………………………… 78.0 Line-haul railroads……………………………………… 58.9 General freight trucking, long-distance……………… 85.7 Used household and office goods moving…………… 106.7 U.S. Postal service……………………………………… 90.9 U.S. Postal service……………………………………… 90.9 100.0 100.0 100.0 100.0 100.0 100.0 96.4 102.1 99.4 91.0 101.6 101.6 95.9 105.5 99.1 96.1 102.8 102.8 97.7 114.3 101.9 94.8 105.5 105.5 92.5 121.9 103.2 84.0 106.3 106.3 101.7 131.9 107.0 81.6 106.4 106.4 112.1 138.5 110.7 86.2 107.8 107.8 126.3 141.4 110.7 88.6 110.0 110.0 135.9 136.3 113.3 88.5 111.2 111.2 142.9 144.2 113.3 88.9 111.3 111.3 145.4 137.7 115.3 93.2 112.0 112.0 492 493 4931 49311 49312 Couriers and messengers……………………………… 148.3 Warehousing and storage……………………………… Warehousing and storage……………………………… General warehousing and storage…………………… Refrigerated warehousing and storage……………… - 100.0 100.0 100.0 100.0 100.0 114.8 106.4 106.4 112.1 97.9 122.2 107.7 107.7 112.9 103.4 128.8 109.3 109.3 115.8 95.4 132.6 115.3 115.3 126.3 85.4 143.2 122.1 122.1 136.1 87.2 146.4 124.8 124.8 138.9 92.2 138.5 122.5 122.5 130.9 99.3 136.5 123.5 123.5 132.0 88.8 140.3 119.4 119.4 130.1 80.4 132.5 115.5 115.5 124.2 85.1 Retail trade Transportation and warehousing Monthly Labor Review • August 2009 50. Continued - Annual indexes of output per hour for selected NAICS industries [1997=100] NAICS Industry 1987 1997 Information 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 511 5111 5112 51213 515 Publishing industries, except internet………………… 64.1 Newspaper, book, and directory publishers………… 105.0 Software publishers…………………………………… 10.2 Motion picture and video exhibition…………………… 90.7 Broadcasting, except internet………………………… 99.5 100.0 100.0 100.0 100.0 100.0 116.1 103.9 134.8 99.8 100.8 116.3 104.1 129.2 101.8 102.9 117.1 107.7 119.2 106.5 103.6 116.6 105.8 117.4 101.6 99.2 117.2 104.7 122.1 99.8 104.0 126.4 109.6 138.1 100.4 107.9 130.7 106.7 160.6 103.6 112.5 136.7 107.9 173.5 102.4 116.1 144.3 112.2 178.7 107.3 123.1 150.1 114.1 184.6 110.6 132.8 5151 5152 5171 5172 5175 Radio and television broadcasting…………………… 98.1 Cable and other subscription programming………… 105.6 Wired telecommunications carriers…………………… 56.9 Wireless telecommunications carriers……………… 75.6 Cable and other program distribution………………… 105.2 100.0 100.0 100.0 100.0 100.0 91.5 136.2 107.7 110.5 97.1 92.6 139.1 116.7 145.2 95.8 92.1 141.2 122.7 152.8 91.6 89.6 128.1 116.7 191.9 87.7 95.1 129.8 124.1 217.9 95.0 94.6 146.0 130.5 242.6 101.3 96.6 158.7 131.9 292.4 113.8 99.0 163.7 138.3 381.9 110.5 106.8 168.1 142.4 431.6 110.7 110.8 192.5 142.2 456.5 123.8 52211 Commercial banking…………………………………… 73.6 100.0 97.7 100.8 104.8 102.4 106.9 111.7 117.8 119.3 122.7 123.8 92.7 60.3 77.0 100.0 100.0 100.0 100.1 115.4 113.2 112.2 121.0 129.4 112.3 121.8 134.9 111.1 113.5 133.3 114.6 114.0 130.3 121.1 116.3 148.5 118.2 137.7 154.5 109.8 147.1 144.2 111.4 168.9 176.2 130.1 173.8 223.0 82.9 90.0 90.2 95.9 98.1 100.0 100.0 100.0 100.0 100.0 107.6 111.4 98.2 89.2 124.8 105.8 106.8 98.0 97.9 109.8 100.9 107.6 102.0 107.5 108.9 94.4 111.0 100.1 106.9 102.2 111.4 107.6 100.5 113.1 97.6 110.0 112.6 100.5 121.1 104.2 99.9 118.3 107.8 133.5 93.1 103.7 119.8 112.3 132.9 93.6 103.2 118.9 113.1 134.1 98.8 117.4 124.5 110.0 139.1 104.5 89.3 75.1 100.0 100.0 100.0 86.8 111.4 95.3 93.2 115.5 98.6 89.8 119.4 101.0 99.6 115.2 102.1 116.8 127.6 105.6 115.4 147.2 118.8 119.8 167.2 116.6 116.0 179.2 120.7 123.8 183.4 116.1 132.8 190.6 122.3 - 100.0 100.0 100.0 118.8 117.2 121.4 124.7 121.4 129.7 131.9 127.4 139.9 135.3 127.7 148.3 137.6 123.1 163.3 140.8 128.6 160.0 140.8 130.7 153.5 137.8 125.8 154.1 139.7 127.3 156.8 136.0 130.0 138.9 Finance and insurance Real estate and rental and leasing 532111 53212 53223 Passenger car rental…………………………………… Truck, trailer, and RV rental and leasing…………… Video tape and disc rental…………………………… 541213 54131 54133 54181 541921 Tax preparation services……………………………… Architectural services…………………………………… Engineering services…………………………………… Advertising agencies…………………………………… Photography studios, portrait………………………… 56131 56151 56172 Employment placement agencies…………………… Travel agencies………………………………………… Janitorial services……………………………………… 6215 621511 621512 Medical and diagnostic laboratories………………… Medical laboratories…………………………………… Diagnostic imaging centers…………………………… 71311 71395 Amusement and theme parks………………………… Bowling centers………………………………………… 111.9 106.0 100.0 100.0 110.5 89.9 105.2 89.4 106.0 93.4 93.0 94.3 106.5 96.4 113.2 102.4 101.4 107.9 109.9 106.5 97.7 102.6 103.2 122.8 72 721 7211 722 7221 7222 7223 7224 Accommodation and food services…………………… 93.1 Accommodation………………………………………… 85.8 Traveler accommodation……………………………… 84.8 Food services and drinking places…………………… 96.0 Full-service restaurants………………………………… 92.1 Limited-service eating places………………………… 96.5 Special food services…………………………………… 89.9 Drinking places, alcoholic beverages………………… 136.7 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.7 100.0 99.6 101.0 100.9 101.2 100.6 99.7 102.2 105.3 105.4 100.9 100.8 100.4 105.2 98.8 105.8 110.3 111.2 103.5 103.0 102.0 115.0 100.6 104.7 107.9 108.4 103.8 103.6 102.5 115.3 97.6 105.7 112.0 112.2 104.4 104.4 102.7 114.9 102.9 107.3 113.1 113.2 106.3 104.2 105.4 117.6 118.6 109.0 119.2 119.4 107.0 104.8 106.8 118.0 112.2 108.6 114.3 114.9 107.9 105.2 107.4 119.2 120.6 108.7 110.8 110.9 109.1 105.5 109.1 117.9 134.2 107.9 109.0 109.0 108.7 104.0 109.1 120.4 137.6 8111 81142 81211 81221 8123 81292 Automotive repair and maintenance………………… 85.9 Reupholstery and furniture repair…………………… 105.3 Hair, nail, and skin care services……………………… 83.5 Funeral homes and funeral services………………… 103.7 Drycleaning and laundry services…………………… 97.1 Photofinishing…………………………………………… 95.8 100.0 100.0 100.0 100.0 100.0 100.0 103.6 95.8 108.6 106.8 100.1 69.3 106.1 105.0 108.6 103.3 105.0 76.3 109.4 105.5 108.2 94.8 107.6 73.8 108.9 105.0 114.6 91.8 110.9 81.2 103.7 102.0 110.4 94.6 112.5 100.5 104.1 97.2 119.7 95.7 103.8 100.5 112.0 99.8 125.0 92.9 110.6 102.0 112.1 101.4 130.0 93.1 121.1 112.4 111.4 100.0 129.8 99.5 119.7 111.3 110.4 105.8 134.5 97.0 114.6 110.2 Professional and technical services Administrative and waste services Health care and social assistance Arts, entertainment, and recreation Accommodation and food services Other services NOTE: Dash indicates data are not available. 51. Unemployment rates, approximating U.S. concepts, 10 countries, seasonally adjusted [Percent] 2006 Country 2006 2007 I II 2008 2007 III IV I II III IV I II III United States……… 4.6 4.6 4.7 4.7 4.7 4.4 4.5 4.5 4.7 4.8 4.9 5.3 Canada……………… 5.5 5.3 5.7 5.4 5.6 5.4 5.4 5.3 5.2 5.2 5.2 5.3 5.3 Australia…………… 4.8 4.4 5.0 4.9 4.7 4.5 4.5 4.3 4.3 4.3 4.1 4.3 4.2 Japan………………… 4.2 3.9 4.2 4.2 4.2 4.1 4.0 3.8 3.8 3.9 3.9 4.0 4.1 France……………… 9.5 8.6 9.9 9.5 9.5 9.2 9.1 8.7 8.5 8.2 8.0 8.0 8.3 Germany…………… 10.4 8.7 11.1 10.6 10.1 9.6 9.3 8.9 8.5 8.1 7.8 7.6 7.5 Italy………………… 6.9 6.2 7.3 6.9 6.7 6.5 6.2 6.1 6.2 6.4 6.7 6.8 - Netherlands………… 3.9 3.2 4.3 3.9 3.8 3.8 3.6 3.2 3.0 3.0 2.9 2.8 2.5 Sweden……………… 7.0 6.1 7.3 7.3 6.7 6.5 6.4 6.1 5.8 5.9 5.8 5.8 5.9 United Kingdom…… 5.5 5.4 5.3 5.5 5.5 5.5 5.5 5.4 5.3 5.2 5.3 5.4 - NOTE: Dash indicates data not available. Quarterly figures for France, Germany, Italy, and the Netherlands are calculated by applying annual adjustment factors to current published data and therefore should be viewed as less precise indicators of unemployment under U.S. concepts than the annual figures. Quarterly figures for Sweden are BLS seasonally adjusted estimates derived from Swedish not seasonally adjusted data. For further qualifications and historical annual data, see the BLS report International comparisons of annual labor force statistics, 10 countries (on the internet at 6.0 http://www.bls.gov/fls/flscomparelf.htm). For monthly unemployment rates, as well as the quarterly and annual rates published in this table, see the BLS report Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted (on the Internet at http://www.bls.gov/fls/flsjec.pdf). Unemployment rates may differ between the two reports mentioned, because the former is updated annually, whereas the latter is updated monthly and reflects the most recent revisions in source data. Monthly Labor Review • August 2009 115 Current Labor Statistics: International Comparisons 52. Annual data: employment status of the working-age population, approximating U.S. concepts, 10 countries [Numbers in thousands] Employment status and country 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 137,673 15,135 9,339 67,240 25,434 39,752 23,004 7,744 4,401 28,474 139,368 15,403 9,414 67,090 25,791 39,375 23,176 7,881 4,423 28,786 142,583 15,637 9,590 66,990 26,099 39,302 23,361 8,052 4,482 28,962 143,734 15,891 9,744 66,860 26,393 39,459 23,524 8,199 4,522 29,092 144,863 16,366 9,893 66,240 26,646 39,413 23,728 8,345 4,537 29,343 146,510 16,733 10,079 66,010 26,851 39,276 24,020 8,379 4,557 29,564 147,401 16,955 10,221 65,770 26,937 39,711 24,084 8,439 4,571 29,802 149,320 17,108 10,506 65,850 27,092 40,760 24,179 8,459 4,694 30,138 151,428 17,351 10,699 65,960 27,322 41,250 24,395 8,541 4,748 30,600 153,124 17,696 10,949 66,080 27,535 41,416 24,459 8,686 4,823 30,790 67.1 65.1 64.3 63.2 55.6 57.3 47.3 61.1 63.2 62.5 67.1 65.4 64.3 62.8 56.0 57.7 47.7 61.8 62.8 62.4 67.1 65.9 64.0 62.4 56.3 56.9 47.9 62.5 62.7 62.8 67.1 66.0 64.4 62.0 56.6 56.7 48.1 63.4 63.7 62.8 66.8 66.1 64.4 61.6 56.7 56.7 48.3 64.0 63.6 62.7 66.6 67.1 64.3 60.8 56.8 56.4 48.5 64.7 63.9 62.9 66.2 67.7 64.6 60.3 56.8 56.0 49.1 64.6 63.8 62.9 66.0 67.7 64.6 60.0 56.6 56.4 49.1 64.8 63.6 63.0 66.0 67.4 65.3 60.0 56.5 57.6 48.7 64.7 64.8 63.1 66.2 67.4 65.6 60.0 56.6 58.2 48.9 65.1 64.9 63.5 66.0 67.7 66.0 60.0 56.7 58.4 48.6 65.9 65.3 63.4 United States……………………………………………… 129,558 Canada…………………………………………………… 13,637 Australia…………………………………………………… 8,444 Japan……………………………………………………… 64,900 France……………………………………………………… 22,176 Germany…………………………………………………… 35,508 Italy………………………………………………………… 20,169 Netherlands……………………………………………… 7,189 Sweden…………………………………………………… 3,969 United Kingdom…………………………………………… 26,413 131,463 13,973 8,618 64,450 22,597 36,059 20,370 7,408 4,033 26,684 133,488 14,331 8,762 63,920 23,080 36,042 20,617 7,605 4,110 27,058 136,891 14,681 8,989 63,790 23,714 36,236 20,973 7,813 4,222 27,375 136,933 14,866 9,086 63,460 24,167 36,350 21,359 8,014 4,295 27,603 136,485 15,223 9,264 62,650 24,312 36,018 21,666 8,114 4,303 27,815 137,736 15,586 9,480 62,510 24,373 35,615 21,972 8,069 4,293 28,077 139,252 15,861 9,668 62,640 24,354 35,604 22,124 8,052 4,271 28,379 141,730 16,080 9,975 62,910 24,493 36,185 22,290 8,056 4,334 28,674 144,427 16,393 10,186 63,210 24,717 36,978 22,721 8,205 4,416 28,930 146,047 16,767 10,470 63,510 25,162 37,815 22,953 8,408 4,530 29,138 63.8 59.6 59.0 61.0 49.1 51.6 41.9 57.7 56.8 58.1 64.1 60.4 59.3 60.2 49.7 52.3 42.2 59.1 57.6 58.5 64.3 61.3 59.6 59.4 50.4 52.1 42.6 60.3 58.3 59.0 64.4 62.0 60.3 59.0 51.4 52.2 43.2 61.5 60.0 59.4 63.7 61.9 60.0 58.4 51.9 52.2 43.8 62.6 60.4 59.5 62.7 62.4 60.2 57.5 51.8 51.5 44.3 62.9 60.6 59.6 62.3 63.1 60.7 57.1 51.5 50.8 44.9 62.2 60.1 59.8 62.3 63.3 61.1 57.1 51.1 50.6 45.1 61.8 59.4 60.0 62.7 63.4 62.0 57.3 51.1 51.2 44.9 61.6 59.9 60.0 63.1 63.6 62.5 57.5 51.2 52.2 45.5 62.5 60.4 60.1 63.0 64.2 63.1 57.6 51.8 53.3 45.6 63.8 61.3 60.0 6,739 1,248 759 2,300 2,940 3,907 2,584 423 445 1,991 6,210 1,162 721 2,790 2,837 3,693 2,634 337 368 1,790 5,880 1,072 652 3,170 2,711 3,333 2,559 277 313 1,728 5,692 956 602 3,200 2,385 3,065 2,388 239 260 1,587 6,801 1,026 658 3,400 2,226 3,110 2,164 186 227 1,488 8,378 1,143 629 3,590 2,334 3,396 2,062 231 234 1,528 8,774 1,147 599 3,500 2,478 3,661 2,048 310 264 1,488 8,149 1,093 553 3,130 2,583 4,107 1,960 387 300 1,422 7,591 1,028 531 2,940 2,599 4,575 1,889 402 361 1,463 7,001 958 512 2,750 2,605 4,272 1,673 336 332 1,670 7,078 929 478 2,570 2,374 3,601 1,506 278 293 1,652 4.9 8.4 8.3 3.4 11.7 9.9 11.4 5.6 10.1 7.0 4.5 7.7 7.7 4.1 11.2 9.3 11.5 4.4 8.4 6.3 4.2 7.0 6.9 4.7 10.5 8.5 11.0 3.5 7.1 6.0 4.0 6.1 6.3 4.8 9.1 7.8 10.2 3.0 5.8 5.5 4.7 6.5 6.8 5.1 8.4 7.9 9.2 2.3 5.0 5.1 5.8 7.0 6.4 5.4 8.8 8.6 8.7 2.8 5.2 5.2 6.0 6.9 5.9 5.3 9.2 9.3 8.5 3.7 5.8 5.0 5.5 6.4 5.4 4.8 9.6 10.3 8.1 4.6 6.6 4.8 5.1 6.0 5.1 4.5 9.6 11.2 7.8 4.8 7.7 4.9 4.6 5.5 4.8 4.2 9.5 10.4 6.9 3.9 7.0 5.5 4.6 5.3 4.4 3.9 8.6 8.7 6.2 3.2 6.1 5.4 Civilian labor force United States……………………………………………… 136,297 Canada…………………………………………………… 14,884 Australia…………………………………………………… 9,204 Japan……………………………………………………… 67,200 France……………………………………………………… 25,116 Germany…………………………………………………… 39,415 Italy………………………………………………………… 22,753 Netherlands……………………………………………… 7,612 Sweden…………………………………………………… 4,414 United Kingdom…………………………………………… 28,403 Participation rate1 United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France……………………………………………………… Germany…………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom…………………………………………… Employed Employment-population ratio2 United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France……………………………………………………… Germany…………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom…………………………………………… Unemployed United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France……………………………………………………… Germany…………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom…………………………………………… Unemployment rate United States……………………………………………… Canada…………………………………………………… Australia…………………………………………………… Japan……………………………………………………… France……………………………………………………… Germany…………………………………………………… Italy………………………………………………………… Netherlands……………………………………………… Sweden…………………………………………………… United Kingdom…………………………………………… 1 2 Labor force as a percent of the working-age population. Employment as a percent of the working-age population. NOTE: There are breaks in series for the United States (1997, 1998, 1999, 2000, 2003, 2004), Australia (2001), Germany (1999, 2005), the Netherlands (2000, 2003), and Sweden (2005). For further qualifications and historical annual data, see the BLS report International comparisons of annual labor force statistics, 10 countries (on the 116 Monthly Labor Review • August 2009 Internet at http://www.bls.gov/fls/flscomparelf.htm ). Unemployment rates may differ from those in the BLS report Unemployment rates in 10 countries, civilian labor force basis, approximating U.S. concepts, seasonally adjusted (on the Internet at http://www.bls.gov/fls/flsjec.pdf ), because the former is updated annually, whereas the latter is updated monthly and reflects the most recent revisions in source data. 53. Annual indexes of manufacturing productivity and related measures, 17 economies [1996 = 100] Measure and economy 1980 1990 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Output per hour United States……………………… Canada………………………….…… Australia…………………….……… Japan………………………………… Korea, Rep. of……………………… Singapore…………………………… Taiwan……………………………… Belgium…………………………...… Denmark…………………………… France……………………………… Germany………………………...…… Italy……………………………...…… Netherlands…………………...…… Norway……………………………… Spain……………………………….. Sweden…………………………….. United Kingdom……………….…… 58.6 66.5 72.5 54.8 – – 40.4 57.2 75.3 56.9 67.1 60.1 57.2 77.3 62.8 60.0 55.9 80.1 85.2 91.1 81.3 58.0 68.2 73.9 84.7 90.3 84.2 86.1 82.5 81.4 96.8 86.8 73.9 87.8 88.1 94.0 95.8 87.6 75.9 82.3 83.4 89.6 92.0 90.0 89.1 87.2 86.2 98.3 94.9 82.6 100.1 92.7 99.3 98.4 89.0 82.8 89.5 86.6 94.4 103.4 95.9 95.8 94.9 94.1 98.3 97.8 91.1 102.7 96.2 100.5 97.1 95.6 90.9 95.5 93.0 98.6 103.4 99.7 97.3 99.5 97.9 97.1 101.2 96.8 101.0 104.2 104.5 102.0 103.5 112.8 103.2 104.1 106.3 108.0 105.9 105.9 102.0 100.3 100.2 101.0 109.1 102.0 111.5 109.6 106.9 104.5 125.7 111.2 109.2 107.6 107.4 111.4 106.3 100.6 103.2 97.7 102.7 115.6 102.9 117.1 114.2 108.5 107.3 139.8 122.5 116.0 106.8 109.1 116.2 108.9 101.4 107.4 101.1 104.5 126.2 108.0 126.1 121.1 115.1 113.0 151.7 130.8 122.2 110.9 113.0 124.5 116.5 106.7 115.2 104.2 105.6 134.8 115.4 127.4 118.5 117.9 110.6 150.6 122.9 127.7 111.0 113.2 127.0 119.5 107.0 115.7 107.1 108.0 131.0 119.4 140.9 120.5 122.9 114.7 165.3 133.8 139.2 114.6 113.9 132.4 120.7 105.7 119.2 110.2 108.4 145.3 123.0 149.8 121.1 125.2 122.5 176.8 138.7 143.6 117.8 118.7 138.4 125.0 103.5 121.7 119.7 111.1 157.1 128.2 159.0 122.4 126.8 131.0 197.2 147.3 150.9 123.7 125.5 142.2 129.7 105.0 129.9 126.8 113.2 173.9 136.2 162.2 126.6 127.6 139.6 212.1 149.9 162.3 127.0 129.6 148.7 137.1 106.4 135.8 131.2 115.4 184.7 141.9 169.9 129.3 128.8 141.0 233.5 153.5 173.4 131.8 135.5 154.6 148.6 105.9 140.2 128.5 117.7 202.0 149.1 177.8 132.8 131.3 145.8 253.9 147.5 188.5 137.6 136.0 158.5 155.9 105.4 144.0 128.2 122.2 203.0 153.0 Output United States…………………..…… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Singapore…………………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 60.5 71.2 80.2 59.0 20.5 – 38.2 74.8 85.6 83.2 92.3 74.7 68.7 96.7 75.5 67.1 80.3 80.7 88.7 93.1 94.3 63.2 66.2 76.7 96.6 94.7 97.5 107.2 92.6 89.2 92.9 94.6 80.4 96.9 85.7 87.7 92.7 93.5 75.5 78.5 85.0 92.8 90.3 93.8 99.9 89.9 90.2 93.2 92.4 74.1 93.4 92.2 94.4 97.5 92.1 84.1 88.4 90.1 97.0 100.0 96.8 103.1 95.9 95.0 95.7 94.0 85.5 97.8 96.4 98.7 96.9 95.9 94.0 97.3 95.0 99.6 104.8 100.3 102.1 100.5 98.6 96.1 97.6 96.8 99.3 106.1 106.3 102.3 102.5 104.9 104.3 105.7 104.8 108.2 104.7 104.4 101.5 101.4 104.3 106.4 107.8 101.8 113.2 111.7 105.2 97.1 96.6 103.5 109.1 106.5 109.1 109.7 105.6 102.4 104.8 103.6 112.9 116.7 102.4 118.1 121.0 105.0 96.7 117.6 117.0 117.1 106.9 110.0 113.4 106.6 102.2 108.7 103.5 119.3 127.6 103.6 125.5 133.1 110.0 101.8 137.6 134.7 125.7 111.6 113.9 118.6 113.9 106.5 116.0 102.9 124.6 138.1 105.9 118.5 128.0 108.9 96.2 140.6 119.1 116.4 111.8 114.0 119.8 115.8 106.2 115.8 102.2 128.6 134.9 104.5 121.8 129.0 114.2 94.7 151.2 129.1 126.7 110.9 110.7 119.7 113.4 105.0 115.9 101.6 128.4 143.4 102.2 123.2 128.3 116.2 99.8 159.6 132.9 133.5 109.3 107.6 121.9 114.2 102.2 114.6 105.0 130.0 150.4 101.9 130.1 130.9 116.3 105.6 177.3 151.3 146.5 113.2 109.3 123.0 118.3 103.0 118.5 111.0 130.9 164.2 104.2 131.2 132.9 115.8 111.1 189.8 165.7 156.7 113.1 109.9 125.9 122.3 102.5 120.9 115.9 132.4 171.8 104.0 138.4 132.3 114.7 114.9 205.9 185.4 167.9 116.3 114.5 127.2 131.2 103.7 124.1 119.4 134.8 185.3 105.8 142.4 131.1 118.4 119.1 219.3 196.2 185.3 119.3 118.6 128.8 139.2 104.8 128.1 125.7 138.6 189.6 106.5 Total hours United States……………………… 103.3 Canada……………………………… 107.0 Australia……………………………… 110.6 Japan………………………………… 107.6 – Korea, Rep. of……………………… Singapore…………………………… – Taiwan……………………………… 94.5 Belgium……………………………… 130.9 Denmark…………………………… 113.7 France……………………………… 146.3 Germany…………………………… 137.4 Italy…………………………………… 124.3 Netherlands………………………… 120.1 Norway……………………………… 125.1 Spain……………………………….. 120.3 Sweden……………………………… 111.8 United Kingdom…………………… 143.8 100.7 104.1 102.2 115.9 109.0 96.9 103.7 114.1 104.8 115.8 124.6 112.2 109.6 96.0 109.0 108.8 110.4 97.3 93.3 96.9 106.7 99.5 95.3 101.9 103.5 98.1 104.1 112.1 103.1 104.6 94.8 97.4 89.7 93.3 99.5 95.1 99.1 103.5 101.6 98.8 104.0 102.8 96.7 101.0 107.6 101.1 100.9 97.3 96.1 93.9 95.2 100.2 98.3 99.8 100.4 103.3 101.9 102.2 101.0 101.4 100.6 105.0 100.9 100.7 99.0 96.4 100.0 98.3 101.8 101.6 100.3 99.1 93.0 101.1 101.6 98.6 100.2 98.9 98.6 99.5 101.0 104.1 105.4 98.8 99.8 101.5 101.9 98.4 92.9 76.8 93.1 99.9 98.9 101.5 98.5 99.4 101.8 101.5 106.1 109.9 100.9 99.6 100.9 105.9 96.7 90.2 84.1 95.6 101.0 100.0 100.8 97.6 97.9 100.8 101.2 102.4 114.1 101.1 95.9 99.6 109.9 95.6 90.1 90.7 103.0 102.9 100.7 100.8 95.3 97.7 99.9 100.7 98.8 118.0 102.4 91.8 93.0 107.9 92.4 87.0 93.3 96.9 91.1 100.7 100.7 94.3 96.9 99.3 100.1 95.4 119.0 103.0 87.5 86.5 107.1 92.9 82.6 91.5 96.5 91.1 96.8 97.2 90.4 94.0 99.3 97.2 92.3 118.4 98.7 83.1 82.2 105.9 92.8 81.4 90.2 95.8 92.9 92.8 90.7 88.1 91.4 98.8 94.1 87.7 117.0 95.7 79.5 81.8 106.9 91.7 80.6 89.9 102.8 97.1 91.5 87.1 86.5 91.2 98.1 91.2 87.5 115.6 94.4 76.5 80.9 105.0 90.7 79.6 89.5 110.5 96.5 89.0 84.8 84.7 89.2 96.4 89.0 88.4 114.7 93.0 73.3 81.5 102.3 89.1 81.5 88.2 120.8 96.8 88.2 84.5 82.3 88.3 97.9 88.5 92.9 114.6 91.7 71.0 80.1 98.7 90.2 81.6 86.4 133.0 98.3 86.7 87.2 81.2 89.3 99.4 88.9 98.0 113.4 93.4 69.6 82.7 82.4 79.5 83.0 36.1 64.6 66.5 81.4 83.1 78.9 72.3 70.5 78.8 81.2 65.9 77.4 82.8 93.3 93.5 88.9 94.1 61.6 84.3 82.6 94.8 90.9 91.8 86.7 85.1 91.6 89.2 90.3 85.8 96.2 96.3 96.2 90.0 96.0 70.8 89.1 86.6 95.5 94.1 95.3 90.6 89.6 95.6 91.9 93.6 88.0 98.6 98.1 98.5 95.6 99.2 85.9 93.1 93.8 98.2 96.0 98.1 95.5 94.9 98.1 96.0 97.6 92.8 100.3 102.6 102.4 102.7 103.3 108.7 104.4 103.1 103.8 103.4 102.9 102.0 104.7 102.6 104.5 102.4 105.4 104.4 108.6 107.7 106.9 105.9 118.4 110.5 107.0 105.3 106.1 103.7 103.4 102.8 106.9 110.6 103.2 109.4 112.3 112.9 110.0 111.2 105.7 119.0 101.0 108.9 106.7 108.8 107.0 105.8 105.4 110.5 116.9 102.9 112.8 118.9 123.2 113.6 116.1 105.1 127.1 103.7 111.0 108.5 110.9 112.8 111.3 108.1 115.9 123.5 104.5 117.2 126.2 126.1 116.7 123.5 106.5 131.1 111.8 118.1 113.1 116.2 115.8 114.7 111.8 120.8 130.9 108.7 122.8 131.8 135.2 120.6 129.0 107.2 144.4 114.9 114.4 118.0 121.2 122.8 117.5 115.0 127.5 138.8 111.8 129.4 139.1 144.7 125.5 134.1 104.9 151.5 115.6 116.3 122.0 129.4 125.7 120.2 119.3 132.6 144.5 117.4 135.2 146.1 147.7 129.9 141.1 105.9 173.0 112.5 118.2 125.2 134.4 129.7 120.8 123.4 138.2 149.2 121.5 138.9 153.2 150.5 135.5 150.1 106.8 186.8 111.3 122.8 129.0 142.0 134.4 122.4 127.4 140.3 156.2 127.3 143.6 163.2 156.7 139.7 160.2 105.6 202.9 108.7 126.7 133.7 149.0 140.9 127.4 129.9 144.2 165.8 132.7 147.8 173.7 162.2 144.6 168.6 105.4 218.6 104.1 130.6 140.7 152.9 145.0 129.5 132.7 148.5 173.7 139.2 154.8 174.9 Hourly compensation (national currency basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Singapore…………………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… See notes at end of table. 51.2 43.8 – 53.7 – – 23.1 47.5 39.5 34.6 43.3 22.6 52.3 34.3 23.1 32.9 33.4 Monthly Labor Review • August 2009 117 Current Labor Statistics: International Comparisons 53. Continued— Annual indexes of manufacturing productivity and related measures, 17 economies [1996 = 100] Measure and economy 1980 1990 1993 1994 1995 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Unit labor costs (national currency basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Singapore…………………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 87.4 65.9 – 98.0 33.6 – 57.1 83.0 52.5 60.9 64.5 37.6 91.5 44.4 36.8 54.9 59.8 103.3 96.7 87.3 102.1 62.3 94.7 89.9 96.1 91.9 93.7 84.0 85.4 96.8 83.9 76.0 104.8 94.3 106.0 99.5 92.8 107.5 81.2 102.5 99.1 105.7 98.9 102.0 97.3 97.5 106.3 90.7 95.1 103.9 96.1 103.9 96.9 91.5 107.9 85.5 99.5 100.0 101.2 91.0 99.4 94.6 94.4 101.6 93.4 95.7 96.6 96.0 102.0 98.0 98.4 103.8 94.5 97.5 100.9 99.6 92.9 98.5 98.2 95.3 100.3 98.9 96.5 95.8 99.4 98.5 98.0 100.7 99.8 96.4 101.2 99.0 97.6 95.7 97.2 96.3 102.7 102.3 104.2 101.4 96.6 102.4 97.4 98.3 100.0 101.3 94.2 99.3 97.9 97.9 98.8 93.1 97.3 102.2 103.6 113.2 100.4 94.7 109.2 96.4 96.3 102.4 98.6 85.1 82.5 93.9 99.9 99.7 92.1 97.1 104.0 102.9 115.7 98.5 89.4 110.1 97.7 93.8 100.9 93.0 83.8 79.3 90.9 97.9 98.1 90.6 95.5 101.4 100.6 118.5 99.0 86.9 109.4 99.0 98.5 104.8 96.2 87.0 91.0 92.5 101.9 102.7 91.2 96.0 104.5 104.4 122.2 100.6 93.8 110.4 96.0 100.0 105.0 93.5 87.3 85.9 82.2 103.0 106.4 92.8 97.4 108.7 106.9 126.0 103.1 89.1 113.1 96.6 103.6 107.1 85.6 85.7 83.3 81.0 103.5 109.0 90.8 96.1 115.3 108.9 120.7 105.6 86.1 113.9 92.9 106.1 111.3 80.8 87.8 76.4 78.4 101.2 107.0 91.2 93.2 117.6 106.3 117.6 107.3 79.9 112.4 92.8 107.1 117.6 76.5 88.1 74.2 75.7 101.5 109.6 90.4 89.3 119.8 103.3 119.1 110.3 77.8 115.1 92.2 108.0 124.4 74.9 86.9 70.8 73.1 101.4 109.9 91.2 85.8 122.6 102.9 129.0 112.7 73.2 116.6 91.2 108.9 128.4 72.3 86.1 70.6 69.2 102.3 112.4 91.5 83.1 125.8 103.1 135.5 113.9 76.3 114.3 Unit labor costs (U.S. dollar basis) United States……………………… Canada……………………………… Australia……………………………… Japan………………………………… Korea, Rep. of……………………… Singapore…………………………… Taiwan……………………………… Belgium……………………………… Denmark…………………………… France……………………………… Germany…………………………… Italy…………………………………… Netherlands………………………… Norway……………………………… Spain……………………………….. Sweden……………………………… United Kingdom…………………… 87.4 76.8 – 47.0 44.6 – 43.6 87.9 54.1 73.7 53.4 67.7 77.7 58.1 65.0 87.0 89.1 103.3 113.1 87.1 76.6 70.5 73.7 91.8 89.1 86.2 88.0 78.2 110.0 89.6 86.6 94.4 118.7 107.8 106.0 105.2 80.6 105.2 81.1 89.4 103.0 94.7 88.4 92.1 88.5 95.6 96.4 82.6 94.5 89.4 92.5 103.9 96.7 85.5 114.8 85.3 91.9 103.8 93.7 83.1 91.7 87.8 90.4 94.1 85.5 90.5 84.0 94.3 102.0 97.4 93.1 120.2 98.4 97.0 104.6 104.7 96.2 101.0 103.2 90.2 105.4 100.8 98.0 90.0 100.5 98.5 96.5 95.7 89.7 81.9 96.0 94.5 84.4 84.0 85.2 83.5 93.0 88.4 95.0 87.6 84.7 107.4 97.4 90.4 80.4 84.1 54.1 83.7 80.2 83.5 85.5 80.7 83.2 90.8 88.0 96.8 85.1 79.8 116.0 96.4 88.4 84.5 94.3 57.6 68.6 79.8 81.7 82.7 76.5 79.6 88.2 83.9 95.7 79.9 72.5 114.1 97.7 86.1 75.0 93.9 59.6 64.8 79.9 69.4 70.3 65.2 67.8 74.6 71.1 86.9 69.6 63.6 106.3 99.0 86.7 69.2 86.1 54.2 71.6 75.1 70.0 71.5 63.7 66.1 74.5 71.5 87.8 68.6 60.8 101.9 96.0 86.9 72.9 81.2 56.2 67.6 65.4 74.8 78.2 68.4 70.8 81.9 77.4 101.9 74.2 61.4 108.9 96.6 100.9 89.3 80.3 57.9 67.4 64.6 90.0 96.1 80.2 83.7 104.0 94.3 110.1 91.1 71.5 119.3 92.9 111.2 104.7 81.3 61.7 63.7 64.5 96.6 103.7 88.5 89.2 116.5 101.2 112.7 101.6 72.9 132.0 92.8 120.5 114.6 75.6 69.3 62.9 64.7 97.0 106.0 87.8 85.5 118.8 98.4 119.4 104.5 69.8 134.2 92.2 129.9 119.7 70.1 73.3 62.8 61.7 97.8 107.3 89.3 82.9 122.7 98.9 130.0 107.8 66.6 137.7 91.2 138.4 137.6 66.7 74.6 66.1 57.9 107.6 119.8 97.8 87.6 137.5 108.1 149.4 118.9 75.7 146.7 NOTE: Data for Germany for years before 1993 are for the former West Germany. Data for 1993 onward are for unified Germany. Dash indicates data not available. 118 Monthly Labor Review • August 2009 1 54. Occupational injury and illness rates by industry, United States Incidence rates per 100 full-time workers 3 Industry and type of case 2 1989 1 1990 1991 1992 1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 2000 4 2001 4 5 PRIVATE SECTOR 8.6 4.0 78.7 8.8 4.1 84.0 8.4 3.9 86.5 8.9 3.9 93.8 8.5 3.8 – 8.4 3.8 – 8.1 3.6 – 7.4 3.4 – 7.1 3.3 – 6.7 3.1 – 6.3 3.0 – 6.1 3.0 – 5.7 2.8 – Agriculture, forestry, and fishing Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 10.9 5.7 100.9 11.6 5.9 112.2 10.8 5.4 108.3 11.6 5.4 126.9 11.2 5.0 – 10.0 4.7 – 9.7 4.3 – 8.7 3.9 – 8.4 4.1 – 7.9 3.9 – 7.3 3.4 – 7.1 3.6 – 7.3 3.6 – Mining Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 8.5 4.8 137.2 8.3 5.0 119.5 7.4 4.5 129.6 7.3 4.1 204.7 6.8 3.9 – 6.3 3.9 – 6.2 3.9 – 5.4 3.2 – 5.9 3.7 – 4.9 2.9 – 4.4 2.7 – 4.7 3.0 – 4.0 2.4 – Construction Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 14.3 6.8 143.3 14.2 6.7 147.9 13.0 6.1 148.1 13.1 5.8 161.9 12.2 5.5 – 11.8 5.5 – 10.6 4.9 – 9.9 4.5 – 9.5 4.4 – 8.8 4.0 – 8.6 4.2 – 8.3 4.1 – 7.9 4.0 – General building contractors: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 13.9 6.5 137.3 13.4 6.4 137.6 12.0 5.5 132.0 12.2 5.4 142.7 11.5 5.1 – 10.9 5.1 – 9.8 4.4 – 9.0 4.0 – 8.5 3.7 – 8.4 3.9 – 8.0 3.7 – 7.8 3.9 – 6.9 3.5 – Heavy construction, except building: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 13.8 6.5 147.1 13.8 6.3 144.6 12.8 6.0 160.1 12.1 5.4 165.8 11.1 5.1 – 10.2 5.0 – 9.9 4.8 – 9.0 4.3 – 8.7 4.3 – 8.2 4.1 – 7.8 3.8 – 7.6 3.7 – 7.8 4.0 – Special trades contractors: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 14.6 6.9 144.9 14.7 6.9 153.1 13.5 6.3 151.3 13.8 6.1 168.3 12.8 5.8 – 12.5 5.8 – 11.1 5.0 – 10.4 4.8 – 10.0 4.7 – 9.1 4.1 – 8.9 4.4 – 8.6 4.3 – 8.2 4.1 – Manufacturing Total cases ............................…………………………. Lost workday cases..................................................... 13.1 5.8 13.2 5.8 12.7 5.6 12.5 5.4 12.1 5.3 12.2 5.5 11.6 5.3 10.6 4.9 10.3 4.8 9.7 4.7 9.2 4.6 9.0 4.5 8.1 4.1 Lost workdays........………........................................... 113.0 120.7 121.5 124.6 – – – – – – – – – 14.1 6.0 116.5 14.2 6.0 123.3 13.6 5.7 122.9 13.4 5.5 126.7 13.1 5.4 – 13.5 5.7 – 12.8 5.6 – 11.6 5.1 – 11.3 5.1 – 10.7 5.0 – 10.1 4.8 – – – – 8.8 4.3 – Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.4 9.4 177.5 18.1 8.8 172.5 16.8 8.3 172.0 16.3 7.6 165.8 15.9 7.6 – 15.7 7.7 – 14.9 7.0 – 14.2 6.8 – 13.5 6.5 – 13.2 6.8 – 13.0 6.7 – 12.1 6.1 – 10.6 5.5 – Furniture and fixtures: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 16.1 7.2 – 16.9 7.8 – 15.9 7.2 – 14.8 6.6 128.4 14.6 6.5 – 15.0 7.0 – 13.9 6.4 – 12.2 5.4 – 12.0 5.8 – 11.4 5.7 – 11.5 5.9 – 11.2 5.9 – 11.0 5.7 – Stone, clay, and glass products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 15.5 7.4 149.8 15.4 7.3 160.5 14.8 6.8 156.0 13.6 6.1 152.2 13.8 6.3 – 13.2 6.5 – 12.3 5.7 – 12.4 6.0 – 11.8 5.7 – 11.8 6.0 – 10.7 5.4 – 10.4 5.5 – 10.1 5.1 – Primary metal industries: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.7 8.1 168.3 19.0 8.1 180.2 17.7 7.4 169.1 17.5 7.1 175.5 17.0 7.3 – 16.8 7.2 – 16.5 7.2 – 15.0 6.8 – 15.0 7.2 – 14.0 7.0 – 12.9 6.3 – 12.6 6.3 – 10.7 5.3 11.1 Fabricated metal products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 18.5 7.9 147.6 18.7 7.9 155.7 17.4 7.1 146.6 16.8 6.6 144.0 16.2 6.7 – 16.4 6.7 – 15.8 6.9 – 14.4 6.2 – 14.2 6.4 – 13.9 6.5 – 12.6 6.0 – 11.9 5.5 – 11.1 5.3 – Industrial machinery and equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 12.1 4.8 86.8 12.0 4.7 88.9 11.2 4.4 86.6 11.1 4.2 87.7 11.1 4.2 – 11.6 4.4 – 11.2 4.4 – 9.9 4.0 – 10.0 4.1 – 9.5 4.0 – 8.5 3.7 – 8.2 3.6 – 11.0 6.0 – Electronic and other electrical equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 9.1 3.9 77.5 9.1 3.8 79.4 8.6 3.7 83.0 8.4 3.6 81.2 8.3 3.5 – 8.3 3.6 – 7.6 3.3 – 6.8 3.1 – 6.6 3.1 – 5.9 2.8 – 5.7 2.8 – 5.7 2.9 – 5.0 2.5 – Transportation equipment: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 17.7 6.8 138.6 17.8 6.9 153.7 18.3 7.0 166.1 18.7 7.1 186.6 18.5 7.1 – 19.6 7.8 – 18.6 7.9 – 16.3 7.0 – 15.4 6.6 – 14.6 6.6 – 13.7 6.4 – 13.7 6.3 – 12.6 6.0 – Instruments and related products: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 5.6 2.5 55.4 5.9 2.7 57.8 6.0 2.7 64.4 5.9 2.7 65.3 5.6 2.5 – 5.9 2.7 – 5.3 2.4 – 5.1 2.3 – 4.8 2.3 – 4.0 1.9 – 4.0 1.8 – 4.5 2.2 – 4.0 2.0 – Miscellaneous manufacturing industries: Total cases ............................………………………… Lost workday cases.................................................. Lost workdays........………........................................ 11.1 5.1 97.6 11.3 5.1 113.1 11.3 5.1 104.0 10.7 5.0 108.2 10.0 4.6 – 9.9 4.5 – 9.1 4.3 – 9.5 4.4 – 8.9 4.2 – 8.1 3.9 – 8.4 4.0 – 7.2 3.6 – 6.4 3.2 – Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... 5 Durable goods: Total cases ............................…………………………. Lost workday cases..................................................... Lost workdays........………........................................... Lumber and wood products: See footnotes at end of table. Monthly Labor Review • August 2009 119 Current Labor Statistics: Injury and Illness Data 54. Continued—Occupational injury and illness rates by industry,1 United States Industry and type of case2 Incidence rates per 100 workers 3 1989 1 1990 1991 1993 4 1994 4 1995 4 1996 4 1997 4 1998 4 1999 4 2000 4 2001 4 1992 Nondurable goods: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 11.6 5.5 107.8 11.7 5.6 116.9 11.5 5.5 119.7 11.3 5.3 121.8 10.7 5.0 – 10.5 5.1 – 9.9 4.9 – 9.2 4.6 – 8.8 4.4 – 8.2 4.3 7.8 4.2 – 7.8 4.2 – 6.8 3.8 – Food and kindred products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 18.5 9.3 174.7 20.0 9.9 202.6 19.5 9.9 207.2 18.8 9.5 211.9 17.6 8.9 – 17.1 9.2 – 16.3 8.7 – 15.0 8.0 – 14.5 8.0 – 13.6 7.5 12.7 7.3 – 12.4 7.3 – 10.9 6.3 – Tobacco products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 8.7 3.4 64.2 7.7 3.2 62.3 6.4 2.8 52.0 6.0 2.4 42.9 5.8 2.3 – 5.3 2.4 – 5.6 2.6 – 6.7 2.8 – 5.9 2.7 – 6.4 3.4 - 5.5 2.2 – 6.2 3.1 – 6.7 4.2 – Textile mill products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 10.3 4.2 81.4 9.6 4.0 85.1 10.1 4.4 88.3 9.9 4.2 87.1 9.7 4.1 – 8.7 4.0 – 8.2 4.1 – 7.8 3.6 – 6.7 3.1 – 7.4 3.4 – 6.4 3.2 – 6.0 3.2 – 5.2 2.7 – Apparel and other textile products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 8.6 3.8 80.5 8.8 3.9 92.1 9.2 4.2 99.9 9.5 4.0 104.6 9.0 3.8 – 8.9 3.9 – 8.2 3.6 – 7.4 3.3 – 7.0 3.1 – 6.2 2.6 - 5.8 2.8 – 6.1 3.0 – 5.0 2.4 – Paper and allied products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 12.7 5.8 132.9 12.1 5.5 124.8 11.2 5.0 122.7 11.0 5.0 125.9 9.9 4.6 – 9.6 4.5 – 8.5 4.2 – 7.9 3.8 – 7.3 3.7 – 7.1 3.7 – 7.0 3.7 – 6.5 3.4 – 6.0 3.2 – Printing and publishing: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 6.9 3.3 63.8 6.9 3.3 69.8 6.7 3.2 74.5 7.3 3.2 74.8 6.9 3.1 – 6.7 3.0 – 6.4 3.0 – 6.0 2.8 – 5.7 2.7 – 5.4 2.8 – 5.0 2.6 – 5.1 2.6 – 4.6 2.4 – Chemicals and allied products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 7.0 3.2 63.4 6.5 3.1 61.6 6.4 3.1 62.4 6.0 2.8 64.2 5.9 2.7 – 5.7 2.8 – 5.5 2.7 – 4.8 2.4 – 4.8 2.3 – 4.2 2.1 – 4.4 2.3 – 4.2 2.2 – 4.0 2.1 – Petroleum and coal products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 6.6 3.3 68.1 6.6 3.1 77.3 6.2 2.9 68.2 5.9 2.8 71.2 5.2 2.5 – 4.7 2.3 – 4.8 2.4 – 4.6 2.5 – 4.3 2.2 – 3.9 1.8 – 4.1 1.8 – 3.7 1.9 – 2.9 1.4 – Rubber and miscellaneous plastics products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 16.2 8.0 147.2 16.2 7.8 151.3 15.1 7.2 150.9 14.5 6.8 153.3 13.9 6.5 – 14.0 6.7 – 12.9 6.5 – 12.3 6.3 – 11.9 5.8 – 11.2 5.8 – 10.1 5.5 – 10.7 5.8 – 8.7 4.8 – Leather and leather products: Total cases ............................………………………….. Lost workday cases...................................................... Lost workdays........………............................................ 13.6 6.5 130.4 12.1 5.9 152.3 12.5 5.9 140.8 12.1 5.4 128.5 12.1 5.5 – 12.0 5.3 – 11.4 4.8 – 10.7 4.5 – 10.6 4.3 – 9.8 4.5 – 10.3 5.0 – 9.0 4.3 – 8.7 4.4 – Transportation and public utilities Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 9.2 5.3 121.5 9.6 5.5 134.1 9.3 5.4 140.0 9.1 5.1 144.0 9.5 5.4 – 9.3 5.5 – 9.1 5.2 – 8.7 5.1 – 8.2 4.8 – 7.3 4.3 – 7.3 4.4 – 6.9 4.3 – 6.9 4.3 – Wholesale and retail trade Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 8.0 3.6 63.5 7.9 3.5 65.6 7.6 3.4 72.0 8.4 3.5 80.1 8.1 3.4 – 7.9 3.4 – 7.5 3.2 – 6.8 2.9 – 6.7 3.0 – 6.5 2.8 – 6.1 2.7 – 5.9 2.7 – 6.6 2.5 – Wholesale trade: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 7.7 4.0 71.9 7.4 3.7 71.5 7.2 3.7 79.2 7.6 3.6 82.4 7.8 3.7 – 7.7 3.8 – 7.5 3.6 – 6.6 3.4 – 6.5 3.2 – 6.5 3.3 – 6.3 3.3 – 5.8 3.1 – 5.3 2.8 – Retail trade: Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 8.1 3.4 60.0 8.1 3.4 63.2 7.7 3.3 69.1 8.7 3.4 79.2 8.2 3.3 – 7.9 3.3 – 7.5 3.0 – 6.9 2.8 – 6.8 2.9 – 6.5 2.7 – 6.1 2.5 – 5.9 2.5 – 5.7 2.4 – Finance, insurance, and real estate Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 2.0 .9 17.6 2.4 1.1 27.3 2.4 1.1 24.1 2.9 1.2 32.9 2.9 1.2 – 2.7 1.1 – 2.6 1.0 – 2.4 .9 – 2.2 .9 – .7 .5 – 1.8 .8 – 1.9 .8 – 1.8 .7 – Services Total cases ............................…………………………..… Lost workday cases......................................................... Lost workdays........………............................................... 5.5 2.7 51.2 6.0 2.8 56.4 6.2 2.8 60.0 7.1 3.0 68.6 6.7 2.8 – 6.5 2.8 – 6.4 2.8 – 6.0 2.6 – 5.6 2.5 – 5.2 2.4 – 4.9 2.2 – 4.9 2.2 – 4.6 2.2 – - 1 Data for 1989 and subsequent years are based on the Standard Industrial Classification Manual, 1987 Edition. For this reason, they are not strictly comparable with data for the years 1985–88, which were based on the Standard Industrial Classification Manual, 1972 Edition, 1977 Supplement. N = number of injuries and illnesses or lost workdays; EH = total hours worked by all employees during the calendar year; and 200,000 = base for 100 full-time equivalent workers (working 40 hours per week, 50 weeks per year). 2 Beginning with the 1992 survey, the annual survey measures only nonfatal injuries and illnesses, while past surveys covered both fatal and nonfatal incidents. To better address fatalities, a basic element of workplace safety, BLS implemented the Census of Fatal Occupational Injuries. 4 Beginning with the 1993 survey, lost workday estimates will not be generated. As of 1992, BLS began generating percent distributions and the median number of days away from work by industry and for groups of workers sustaining similar work disabilities. 5 Excludes farms with fewer than 11 employees since 1976. 3 The incidence rates represent the number of injuries and illnesses or lost workdays per 100 full-time workers and were calculated as (N/EH) X 200,000, where: 120 - Monthly Labor Review • August 2009 NOTE: Dash indicates data not available. 55. Fatal occupational injuries by event or exposure, 1996-2005 20053 1996-2000 (average) 2001-2005 (average)2 All events ............................................................... 6,094 5,704 5,734 100 Transportation incidents ................................................ Highway ........................................................................ Collision between vehicles, mobile equipment ......... Moving in same direction ...................................... Moving in opposite directions, oncoming .............. Moving in intersection ........................................... Vehicle struck stationary object or equipment on side of road ............................................................. Noncollision ............................................................... Jack-knifed or overturned--no collision ................. Nonhighway (farm, industrial premises) ........................ Noncollision accident ................................................ Overturned ............................................................ Worker struck by vehicle, mobile equipment ................ Worker struck by vehicle, mobile equipment in roadway .................................................................. Worker struck by vehicle, mobile equipment in parking lot or non-road area .................................... Water vehicle ................................................................ Aircraft ........................................................................... 2,608 1,408 685 117 247 151 2,451 1,394 686 151 254 137 2,493 1,437 718 175 265 134 43 25 13 3 5 2 264 372 298 378 321 212 376 310 335 274 335 277 175 369 345 318 273 340 281 182 391 6 6 5 6 5 3 7 129 136 140 2 171 105 263 166 82 206 176 88 149 3 2 3 Assaults and violent acts ............................................... Homicides ..................................................................... Shooting .................................................................... Suicide, self-inflicted injury ............................................ 1,015 766 617 216 850 602 465 207 792 567 441 180 14 10 8 3 Contact with objects and equipment ............................ Struck by object ............................................................ Struck by falling object .............................................. Struck by rolling, sliding objects on floor or ground level ......................................................................... Caught in or compressed by equipment or objects ....... Caught in running equipment or machinery .............. Caught in or crushed in collapsing materials ................ 1,005 567 364 952 560 345 1,005 607 385 18 11 7 77 293 157 128 89 256 128 118 94 278 121 109 2 5 2 2 Falls .................................................................................. Fall to lower level .......................................................... Fall from ladder ......................................................... Fall from roof ............................................................. Fall to lower level, n.e.c. ........................................... 714 636 106 153 117 763 669 125 154 123 770 664 129 160 117 13 12 2 3 2 Exposure to harmful substances or environments ..... Contact with electric current .......................................... Contact with overhead power lines ........................... Exposure to caustic, noxious, or allergenic substances Oxygen deficiency ......................................................... 535 290 132 112 92 498 265 118 114 74 501 251 112 136 59 9 4 2 2 1 Fires and explosions ...................................................... Fires--unintended or uncontrolled ................................. Explosion ...................................................................... 196 103 92 174 95 78 159 93 65 3 2 1 Event or exposure1 Number Percent 1 Based on the 1992 BLS Occupational Injury and Illness Classification Manual. 2 Excludes fatalities from the Sept. 11, 2001, terrorist attacks. 3 The BLS news release of August 10, 2006, reported a total of 5,702 fatal work injuries for calendar year 2005. Since then, an additional 32 job-related fatalities were identified, bringing the total job-related fatality count for 2005 to 5,734. NOTE: Totals for all years are revised and final. Totals for major categories may include subcategories not shown separately. Dashes indicate no data reported or data that do not meet publication criteria. N.e.c. means "not elsewhere classified." SOURCE: U.S. Department of Labor, Bureau of Labor Statistics, in cooperation with State, New York City, District of Columbia, and Federal agencies, Census of Fatal Occupational Injuries. Monthly Labor Review • August 2009 121 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Recent Modification of Imputation Methods for National Compensation Survey Benefits Data by Sarah Stafira Bureau of Labor Statistics Originally Posted: August 28, 2009 The NCS modified its methodology for imputing benefits data for March 2009 because prior methods allowed for errors in imputed data to be carried forward from one quarter to the next. Introduction The Bureau of Labor Statistics (BLS) collects and publishes a variety of data on employee benefits as part of the National Compensation Survey (NCS) program. The NCS modified its methodology for imputing benefits data for March 2009 because prior methods allowed for errors in imputed data to be carried forward from one quarter to the next. This article describes the NCS imputation methodology for benefits data item nonresponse, notes the change to the imputation process that is applied to the data from the March 2009 quarter, and explains why the change is necessary. Background The NCS comprises a sample of private industry and State and local government establishments that are selected using a multistage sample design. All sampled establishments are asked to supply data on wages, and a subset also provides data on employer-provided benefits and associated costs. During the initial contact with a sampled establishment, the NCS selects occupations and collects data for these sampled occupations, along with establishment information. The establishment is periodically recontacted to determine if there are any changes in the data collected previously.1 The NCS is a voluntary survey, so selected establishments can decline to participate or can participate partially by supplying responses to only certain survey items. As in any sample survey, estimates generated as part of the NCS program are subject to both sampling error and nonsampling error. Sampling error occurs because a sample makes up only a part of the population being studied; different samples of the population can produce different estimates.2 Standard errors are calculated for benefit estimates to serve as a measure of sampling error. Nonsampling error is error coming from sources other than the sampling process. The primary sources of nonsampling error are survey nonresponse, mistakes in data collection, and data processing errors. Nonsampling error is generally not measured, but the NCS employs procedures to mitigate nonsampling error, such as weight adjustments for nonresponse and quality assurance programs to reduce collection and processing errors. The NCS has three kinds of nonresponse: establishment, occupational, and item nonresponse. Establishment nonresponse is addressed by adjusting the weights of responding establishments (respondents) that are similar to the nonresponding establishments. Occupational nonresponse is handled in a similar fashion; that is, weights of responding occupations, in the same establishment or another, are adjusted to represent similar occupations for which data were not provided. Item nonresponse happens when a respondent supplies some, but not all, data for an occupation. For example, a respondent may know the provisions of the retirement plans offered, but be unable or unwilling to supply the percentage of workers who participate in each type of plan. Item nonresponse is addressed with item imputation. Imputation of data is a process by which a missing data element is assigned a value obtained from a responding unit with similar characteristics. Imputation Methodology For NCS Benefits Data There are several methods of imputation that can be used to address item nonresponse, including regression modeling, cell mean imputation, and nearest neighbor imputation. The NCS benefits program uses a nearest neighbor, within-cell approach to impute for missing participation, access, and provisions data.3 In this method, imputation classes, or cells, are formed Page 1 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS based on auxiliary data. The auxiliary data used by the NCS are establishment and occupational characteristics known for all units and include the following: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. Census region (Midwest, South, Northeast, or West) Two-digit North American Industry Classification System (NAICS) code Full-time/part-time status Union/nonunion status Occupational grouping (based on the Standard Occupational Classification System) Industry grouping (based on the NAICS) Establishment size (based on the establishments number of employees) Selected benefit provisions4 Ownership (private industry or public sector) Benefit type5 An “unusable” unit, or recipient, receives (is assigned) the value for the characteristic of interest from a “usable” unit, or donor, within the same cell that is “nearest” to the unusable unit; “nearness” is defined as the minimum absolute difference in reported employment between the recipient and donors within a cell. If a donor unit is not found when all variables are used to form the imputation cells, then the cells are redefined by disregarding one of the variables, thus expanding the pool of donors. For the NCS, the first variable dropped is census region. At this point, if a donor unit is not found, then the imputation cells are redefined again by ignoring the two-digit NAICS code. The process of dropping variables to increase the donor pool continues using a predetermined hierarchy until a donor unit is identified. The list of auxiliary characteristics given above provides the order in which the variables are dropped. It should be noted that benefit type and ownership are never dropped. In rare situations a recipient will not find a donor, even when the imputation cell is based only on benefit type and ownership. If this happens, the data item will remain missing. Exhibit 1 shows the selection of a donor unit for a recipient in nearest neighbor, within-cell imputation. Suppose unit R1 is a recipient and units D1, D2, and D3 are donors in the imputation process used to impute missing participation for defined benefit retirement plans. The imputation cell is formed based on the following characteristics: benefit type, ownership, selected benefit provisions, establishment size, industry grouping, occupational grouping, union/nonunion status, full-time/ part-time status, two-digit North American Industry Classification System (NAICS) code, and census region. The reported employment of each unit is also given. Exhibit 1. Donor selection in nearest neighbor, within-cell imputation Unit Benefit Type Ownership Benefit Provision No Establishment Size D1 (donor) Defined Private benefit employee industry contribution required Union / Nonunion Fulltime / Parttime Twodigit NAICS Census Region Reported Employment Office & Less than Wholesale Adminis- Defined Private employee R1 100 & Retail (recipient) benefit industry contribution employees Trade required No Occupational Grouping Industry Grouping trative Nonunion Support Full- Wholesale time Trade Full- Wholesale time Trade Midwest 50 Occupations Office & Less than Wholesale Adminis- 100 & Retail employees Trade trative Support Occupations Page 2 Nonunion South 25 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Unit Benefit Type Ownership Benefit Provision Defined Private benefit employee industry contribution required Defined Private benefit Union / Nonunion Fulltime / Parttime Twodigit NAICS Census Region Reported Employment Less than Wholesale Adminis- 100 & Retail employees Trade trative Nonunion Support Full- Wholesale time Trade Full- Retail time Trade West 65 West 55 Occupations Office & No D3 (donor) Occupational Grouping Industry Grouping Office & No D2 (donor) Establishment Size employee industry contribution required Less than Wholesale Adminis- 100 & Retail employees Trade trative Nonunion Support Occupations There are no donor units that match the recipient unit based on all of the variables used to form the imputation cell. By ignoring census region and only considering the remaining cell variables, there are now two potential donors, specifically D1 and D2. Unit D3 is not a potential donor based on the cell formation including the two-digit NAICS because its value does not match that of R1. In order to determine which unit, D1 or D2, will serve as the donor for R1, the minimum absolute difference in reported employment between the donor and recipient is calculated. The absolute difference in employment between R1 and D1 is 25, while the absolute difference in employment between R1 and D2 is 15. Because 15 is the minimum, D2 is determined to be the donor for R1 because it is the donor “nearest” to the recipient within the cell. Imputation At Initiation And Update Collection At initiation--the first collection cycle for the establishment--the nearest neighbor, within-cell imputation methodology is used to fill in missing benefits access, participation, and provisions data, as needed. If there are missing benefits data in subsequent data collection, imputed data will generally be the value from the prior collection period, even if that value was imputed. NCS first introduced the “carrying forward” of prior collected or prior imputed data in the publication National Compensation Survey: Employee Benefits in Private Industry in the United States, March 2007.6 The benefit publications for March 2003 through March 2006 relied solely on nearest neighbor, within-cell imputation. Consider the example shown in exhibit 2. Unit B is initiated in cycle 1 and is missing a provision related to its life insurance plan. The life insurance plan is known to use a “multiple of earnings” formula that has a maximum payout amount, but the maximum is not known. Nearest neighbor, within-cell imputation is used at initiation to fill in the missing maximum so that the unit can be used in estimation. Unit A, a donor unit, is matched to unit B because they have the same type of life insurance plan, as well as similar establishment and occupational characteristics. All provisions are known for unit A, so the maximum life insurance value coded for unit A is used to fill in the missing life insurance maximum for unit B. Exhibit 2. Example of nearest neighbor, within-cell imputation at initiation (cycle 1) Prior to imputation: Cycle 1 1 Unit Type of Life Insurance Is there a maximum? Maximum value? A (donor) Multiple of Earnings Formula Yes $70,000 Multiple of Earnings Formula Yes Unknown Is there a maximum? Maximum value B (recipient) After imputation: Cycle Unit Type of life insurance Page 3 Source of maximum value COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Prior to imputation: 1 A (donor) B 1 (recipient) Multiple of Earnings Formula Yes $70,000 Multiple of Earnings Formula Yes $70,000 Collected Imputed from Unit A Exhibit 3 shows the imputation of unit B at update collection by carrying forward the prior imputed data. At the next collection period, cycle 2, the respondent is still unable or unwilling to supply the maximum value associated with the life insurance plan for unit B. Because the provision was previously imputed to be $70,000, unit B retains or carries forward the maximum of $70,000. Exhibit 3. Example of imputation at update collection by carrying forward prior imputed data (cycle 2) Prior to imputation: Cycle 2 Unit B (recipient) Maximum Type of Life Insurance Is there a maximum? Multiple of Earnings Formula Yes Unknown Is there a maximum? Maximum value value? After imputation: Cycle 2 Unit B (recipient) Type of life insurance Source of maximum value Imputed from Unit Multiple of Earnings Formula Yes $70,000 B, Cycle 1 (carried forward) Effect Of Nonsampling Error On Imputation In addition to nonresponse, collection and processing errors are sources of nonsampling error that impact all surveys. Errors can occur when an interviewer fails to ask for all data items or incorrectly records a data element. Also, a respondent may misunderstand the survey question and supply an incorrect answer. To limit the number of data errors, the NCS program has a number of quality assurance programs in place, including computer edits of data, systematic review of collection units, and data collection reinterviews. Also, data collectors are extensively trained so that high standards in data collection are maintained. Data errors in collection impact survey estimates by increasing the amount of nonsampling error. These data errors affect the imputation process when the erroneous data are assigned to a recipient record. With the application of the “carry forward” methodology in the benefit portion of the NCS program, there is the potential for data errors to remain in the imputed data, cycle after cycle, even if the data on the collected unit are corrected. Without some kind of change to the imputation methods, data errors on imputed records could be repeated in the data for the rest of the time the establishment is in the survey. Consider the example discussed previously in which unit A, the donor used at initiation, had a maximum life insurance amount of $70,000. At update collection in cycle 3, it is discovered that the life insurance maximum amount is really $700,000, not $70,000. The data coder corrects the collected data on unit A, but due to the imputed data, the maximum amount for unit B will continue to be $70,000 because the prior imputed value of $70,000 is carried forward. Exhibit 4 illustrates this scenario. Page 4 COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Exhibit 4. Example of imputation at update collection by carrying forward prior imputed data (cycle 3), original donor unit is corrected Prior to imputation: Cycle 3 Unit Type of Life Insurance Is there a maximum? Maximum value A (donor) Multiple of Earnings Formula Yes $700,000 Multiple of Earnings Formula Yes Unknown B 3 (recipient) After imputation: Cycle 3 Unit Type of life insurance Is there a maximum? Maximum value A (donor) Multiple of Earnings Formula Yes $700,000 B 3 (recipient) Source of maximum value Collected Imputed from Unit Multiple of Earnings Formula Yes $70,000 B, Cycle 2 (carried forward) Minimization Of Nonsampling Error In The March 2009 Quarter To address the potential problem of carrying forward erroneous data, a change in the imputation methodology was needed, especially given that the NCS has greatly expanded the number of detailed estimates available. Percentile estimates (10th, 25th, 50th — median, 75th, 90th) of a given quantity, such as the maximum value of multiple of earnings formula life insurance plans, are of particular risk of nonsampling error because coding errors are often found among the extreme values or outliers, which could show up in the 10th or 90th percentiles. To help minimize nonsampling error, the NCS has conducted additional reviews of the collected benefits data over the last several quarters. Also, the NCS modified its computer programs that assign missing participation, access, and benefit provisions data, starting with data collected and updated in the March 2009 quarter. These computer programs were changed so that all data items for a recipient unit were imputed using the nearest neighbor, within-cell methodology. That is, no prior imputed or collected data were carried forward for recipients of benefits participation, access, and provisions imputation. Using the earlier example, exhibit 5 provides an example of imputation at update collection in which no prior data were carried forward. It shows that at update collection in Cycle 4, when all recipients are imputed using nearest neighbor, withincell imputation, the maximum value assigned to unit B is no longer $70,000. Exhibit 5. Example of imputation at update collection using nearest neighbor, within-cell imputation (cycle 4) Prior to imputation: Cycle 4 4 Unit Type of Life Insurance Is there a maximum? Maximum value A (donor) Multiple of Earnings Formula Yes $700,000 Multiple of Earnings Formula Yes Unknown B (recipient) After imputation: Cycle 4 4 Unit Type of life insurance Is there a maximum? Maximum value A (donor) Multiple of Earnings Formula Yes $700,000 B (recipient) Multiple of Earnings Formula Yes Page 5 $700,000 Source of maximum value Collected Imputed from Unit A COMPENSATION AND WORKING CONDITIONS U.S. BUREAU OF LABOR STATISTICS Conclusion The NCS benefits imputation methodology for the imputation of missing access, participation, and provisions data included a process that carried forward collected or imputed data from previous collection cycles. This proved to be a potential source of additional nonsampling error. To address this problem, the NCS modified its imputation methodology for the March 2009 quarter so that prior imputed or prior collected data are not carried forward. The BLS is committed to publishing accurate, timely, and relevant data; as such, the NCS program not only strives for accuracy of its collected data through validation, but also through regular evaluation of its methods, including imputation techniques, to find ways to improve the quality of its published data. The first benefits estimates using the modified imputation methodology were published in July 2009.7 Sarah Stafira Mathematical Statistician, Statistical Methods Group, Office of Compensation and Working Conditions, Bureau of Labor Statistics. Telephone: (202) 691-6146; E-mail: Stafira.Sarah@bls.gov. Notes 1 Generally, sampled establishments remain in NCS sample for five years before being replaced by a new panel. For more information on the sample selection process, see Larry Ernst, Christopher Guciardo, Chester Ponikowski, and Jason Tehonica, “Sample Allocation and Selection for the National Compensation Survey,” Proceedings of the Section on Survey Research Methods, 2002, American Statistical Association, available online at: http://www.bls.gov/osmr/pdf/st020150.pdf. Additional information can also be found in the BLS Handbook of Methods, Chapter 8, National Compensation Survey, Description of the Survey, available online at: http://www.bls.gov/opub/hom/homch8_b.htm. 2 BLS Handbook of Methods, Chapter 8, National Compensation Survey, Reliability of Estimates, available online at: http://www.bls.gov/opub/ hom/homch8_d.htm. 3 Separate imputation processes are used to impute for missing access, missing participation, and missing benefit provisions, as needed. Access is a measure used to indicate whether employees have a benefit plan available for their use while participation is used to indicate the percentage of those employees who actually participate in the plan. Benefit provisions are characteristics or features of a benefit plan such as the type of life insurance or the employee contribution requirement of a defined benefit retirement plan. 4 Benefit provisions data are used to define the cells if they are known for recipients. For example, in participation imputation for life insurance, if the type of life insurance plan (for example, a multiple of earnings formula) is known for a recipient, then it will be used in forming the imputation cell. If the type of life insurance is not known for the recipient, then this variable is not used in the formation of the imputation cell. 5 For a more comprehensive description of the imputation of benefits data in the NCS, see James A. Buszuwski, Daniel J. Elmore, Lawrence R. Ernst, Michael K. Lettau, Lowell G. Mason, Steven P. Paben, and Chester H. Ponikowski, “Imputation of Benefit Related Data for the National Compensation Survey,” Proceedings of the Section on Survey Research Methods, 2003, American Statistical Association, available on the internet at http://www.bls.gov/osmr/abstract/st/st030190.htm. 6 See National Compensation Survey: Employee Benefits in Private Industry in the United States, March 2007, Summary 07-05. 7 See the BLS Economic News Release, Employee Benefits in the United States, March 2009, at http://www.bls.gov/news.release/ ebs2.nr0.htm. U.S. Bureau of Labor Statistics | Division of Information and Marketing Services, PSB Suite 2850, 2 Massachusetts Avenue, NE Washington, DC 20212-0001 | www.bls.gov/OPUB | Telephone: 1-202-691-5200 | Contact Us Page 6
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