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MONTHLY LABOR REVIEW U.S. Department of Labor Bureau of Labor Statistics April 1989 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis In this issue: Barriers to employment of older workers Inequality in wages and salaries, 1960-80 Unemployment insurance in the U.S. and Europe U.S. DEPARTMENT OF LABOR Elizabeth Dole, Secretary Regional Commissioners for Bureau of Labor Statistics Janet L. Norwood, Commissioner Region I—Boston: Anthony J Ferrara Kennedy Federal Building, Suite 1603 Boston, MA 02203 Phone: (617) 565-2327 Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont The Monthly Labor Review is published by the Bureau of Labor Statistics of the U.S. Department of Labor. Communications on editorial matters should be addressed to the Editor-in-Chief, Monthly Labor Review, Bureau of Labor Statistics, Washington, DC 20212. Phone: (202) 523-1327. Region II—New York: Samuel M. 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Box 3766 San Francisco, CA 94119 Phone: (415) 995-5605 IX American Samoa Arizona California Guam Hawaii Nevada Trust Territory of the Pacific Islands X Alaska Idaho Oregon Washington RESEARCH LIBRARY Federal Reserve Bank MONTHLY LABOR REVIEW of St. Louis APRIL 1989 VOLUME 112, NUMBER 4 MAY 0 3 1989 W. N. Grubb, R. H. Wilson Henry Lowenstern, Editor-in-Chief Robert W. Fisher, Executive Editor 3 Sources of increasing inequality in wages and salaries, 1960-80 Intersectoral employment shifts appear to be much more important in the increase of inequality than regional and demographic shifts Diane E. Herz, Philip L. Rones 14 Institutional barriers to employment of older workers Social Security and private pension rules often encourage early retirement; those who wish to keep working typically face less remunerative part-time work Beatrice G. Reubens 22 Unemployment insurance in the U.S. and Europe, 1973-83 In general, comparisons show rising costs and benefits, possible disincentives to work, but low income replacement ratios for those who are the unemployed John Duke, Lisa Usher https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 32 Multifactor productivity slips in the nonrubber footwear industry While output per employee hour rose modestly from 1958 to 1986, multifactor productivity declined on average, more so in the period before 1973 DEPARTMENTS 2 Labor month in review 39 Major agreements expiring next month 41 Developments in industrial relations 44 Book reviews 47 Current Labor Statistics Labor Month In Review KLEIN AWARD. The Lawrence R. Klein Award trustees selected the authors of three articles published in the Monthly Labor Review in 1988 as winners of the 20th annual Klein Award. The award will be presented at the Bureau of Labor Statistics awards ceremony on May 9. This year, the Klein Award trustees honored these authors: • Michael W. Horrigan and Steven E. Haugen of the Office of Employment and Unemployment Statistics, for “ The declining middle-class thesis: a sensitivity analysis,” which appeared in the May issue. First prize among articles by BLS authors. • Robert Blanchfield and W illiam Marsteller of the Office of Prices and Living Conditions, for “ Rising export and import prices in 1987 reversed the trend of recent years,” which appeared in the June issue. Second prize among articles by BLS authors. • Olivia S. M itchell of Cornell University and the National Bureau of Economic Research, for “ The relation of age to workplace injuries,” which appeared in the July issue. Best 1988 Monthly Labor Review article by an author outside BLS. Receiving honorable mention were Glenn Halm and Clinton R. Shiells of the Bureau of International Labor Affairs, for “ Damage control: yen appreciation and the Japanese labor market,” in the November issue. The Horrigan-Haugen article examines the popularly held thesis that, over the past one or two decades, the proportion of middleincome earners in the United States has declined relative to all earners. Several studies in fact point to this conclusion, but opinions differ on both the extent of the decline and how it has been reflected in the proportion of lower- and upper-income earners. Much of the difference in opinion is due to (1) definitional disagreement about what constitutes the middle-income class and (2) variations in the measurement of that class. Accordingly, what is required is a sensitivity analysis of results yielded from alternative definitions of the middle-income class and from different methods of measuring the size over time. Horrigan and Haugen choose several different income intervals for defining the 2 FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis three income classes and assess two alternative methods of measuring the changes in their size over time. An examination of these changes from both a secular and cyclical perspective then yields the conclusions that (1) in agreement with previous studies, the proportion of middleincome families has declined considerably within the last decade or two, but (2) contrary to the findings of many of those studies, most of the families that have left the middle-income category have moved to the upper- rather than lower-income class. Importantly, these conclusions are consistent with recent argum ents that income distribution is becoming more unequal: in terms of aggregate income, the disparity between what the lower-income class receives and what everybody else receives is growing. With regard to methodology, the authors show that, in an interval deflator approach to compare the sizes of the three classes over time (used in many analytical studies), the results are highly sensitive to the choice of price index used to deflate income intervals so as to maintain the purchasing power of the middle-income class at a constant level. Depending on the index used, the size of the lower class may remain stable, increase secularly, or decrease secularly. (In all of these cases, the lower-income class still receives a decreasing share of aggregate income.) Also, in studies that infer long-term trends in income distribution by year-to-year comparisons, it is clear that the results are highly sensitive to the years chosen. Especially if the years are at dissimilar points in the business cycle, the results will differ dramatically from results generated by means of secular comparisons because the size of the lower-income class typically increases during recessions and decreases during expansions. The Blanchfield-Marsteller article discusses the rise during 1987 in export and import prices, reversing a trend that began in the early years of the decade and continued unabated. The 6.9-percent rise in export prices was the first increase in the all-export index, established in 1983, while the 14.8percent upturn in import prices was the first increase in the all-import index, begun in 1982. Export prices were affected in large measure by rising commodity prices, especially for food and crude materials. The rise in import prices was due almost exclusively to a 43.8-percent increase in fuel prices. The falling value of the dollar exerted a significant influence on the upward movement of export and import prices. New indexes developed by BLS show that despite a 22.4-percent rise, in dollar terms, in the price of nonfuel imports, the trade-weighted value of the dollar fell 32.8 percent from March 1985 to December 1987. During the same period, nonfuel import prices in foreign currency terms fell 17.7 percent. The Mitchell article argues for the thesis that older workers show no more tendency toward incurring work-related illness and injury than do younger workers, but when they are stricken, they are more likely to suffer permanent impairment and fatalities. To remedy deficiencies in earlier analyses, Mitchell uses only data on reported illnesses and injuries, as opposed to less reliable workers’ self-evaluations, and controls closely for occupation, industry, and State-specific differences in workers’ compensation systems in testing for linkage between age and workplace injury and illness. Age effects are shown to be robust to controls for industry and occupation, and State-specific effects persist even in the presence of controls for age, industry, and occupational dispersion in jobs. About the award. Trustees of the Klein Award Fund are Lawrence R. Klein; Charles D. Stewart, president; Ben Burdetsky, secretary-treasurer; Peter Henle; Harold Goldstein; Howard Rosen; and Henry Lowenstern. The award was established in 1968 in honor of Lawrence R. Klein, editor-in-chief of the Monthly Labor Review for 22 years until his retirement in 1968. Instead of accepting a retirement gift, Klein donated it and matched the amount collected to initiate the fund. Since then, he has contributed regularly to the iund, as have others. The purpose of the award is to encourage Review articles that (1) exhibit originality of ideas or method of analysis, (2) adhere to the principles of scientific inquiry, and (3) are well written. Each winning article carries a cash prize. Tax-deductible contributions to the fund may be sent to Ben Burdetsky, SecretaryTreasurer, Lawrence R. Klein Fund, c/o School of Government and Business Administration, The George Washington University, Washington, DC 20052. □ Sources of increasing inequality in wages and salaries, 1960-80 Intersectoral employment shifts appear to be much more important than regional and demographic shifts in the increase in inequality; however, the trend seems to be driven chiefly by developments within labor force groups, rather than movements among them W. N orton G rubb a n d R obert H. W il s o n Interest in the distribution of income waxes and wanes. Concern intensified during the 1960’s with the “rediscov ery” of poverty and the initiation of the War on Poverty. It diminished during the 1970’s, as other economic diffi culties commanded the Nation’s attention. Evidence that the distribution of income had been relatively stable dur ing the post-World War II period tended to make the issue even less pressing. During the 1980’s, however, distributional questions have become more prominent. According to some ana lysts, evidence has accumulated that the distributions of income and earnings have become more unequal. The possible consequences— increasing poverty, more de mands on government programs, a growing underclass, the decline of the middle class, political instability, a gen eration of children with inadequate education— would be serious, and would affect almost every public and private institution in the country. An overview In examining inequality, it is important to distinguish inequality among individuals from inequality among famiW. Norton Grubb is professor of education at the University of California, Berkeley. Robert H. Wilson is associate professor of public affairs at the Lyndon B. Johnson School of Public Affairs, The University of Texas at Austin. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis lies or households, which is affected by marriage, separation or divorce, and changes in labor force participation, as well as inequality among individuals; and earnings must be dis tinguished from income, which includes government trans fers. In this article, we explore changes in the distribution of one important component of total income—the pretax wages and salaries of individuals—between 1960 and 1980,1 using data from the decennial census. The strategy we take is similar to that of other researchers—to examine a series of possible explanations of increasing inequality, rejecting some as unimportant and finding others responsi ble for some part of increases in inequality. Many previous analyses have concentrated on the earn ings distributions among men or have compared men and women.2 To develop a broader analysis, we examine the effects of both gender and race on the distribution of wages and salaries. The effects of gender are of particular interest, because the increasing labor force participation of women during the study period, together with the gen erally lower earnings of women compared to men, could increase overall inequality. In addition, most analyses have concentrated on na tional patterns. However, the two decades chosen for study were periods of important sectoral and regional shifts— from manufacturing to services, and from the Snowbelt to the Sunbelt— which increased employment 3 MONTHLY LABOR REVIEW April 1989 • Sources o f Inequality in Earnings in low-wage positions and could be responsible for in creasing inequality. Therefore, we examine the potential effects of regional and sectoral employment shifts.3 Finally, we use a measure of inequality—one devel oped by Henri Theil, which we refer to as Theil’s T — that is in several ways superior to the conventional measures of inequality (such as the Gini coefficient and the variance of log income), especially in its decomposition properties. Decomposing patterns of inequality One substantial and much-discussed change in the U.S. economy that might explain any deterioration of the earn ings distribution involves sectoral composition. If, as is sometimes claimed,4 well-paid manufacturing positions have been replaced by poorly paid positions in the service sector, then the distribution of earnings might have be come more unequal. Alternatively, because high paying industries (often those heavily unionized) tend to show less variation in earnings,5 it may be that the decline in unionized heavy manufacturing has caused a shift from sectors with greater equality of wages to sectors with greater inequality. For this study, the sectors were chosen to differentiate among various types of manufacturing and service sectors.6 A high-tech sector is included, de fined as those industries that employ technology-oriented workers and that have high research and development expenditures.7 The second major change involves employment shifts among regions— from the Northeast and North Central States to the southern tier of States— that has focused so much attention on the friction between the Snowbelt and the Sunbelt. Shifts among regions— from regions with high wages to those with low wages, or from regions of lesser inequality to those of greater inequality— may be responsible for changes in earnings patterns, rather than changes within regions. Both sectoral and regional shifts may be due partly to endogenous processes; for example, the mobility of employers in search of low wages means that wage patterns affect regional changes, which in turn generate greater inequality. Similarly, the relative decline of high-wage manufacturing—because of the export of production to overseas locations, or the cost advantages of firms already located in low-wage nations— describes a process whereby low-wage sectors in this country grow at the expense of high-wage sectors, potentially aggravating inequality. In addition to analyzing distributions by sector and region, we also differentiate between men and women be cause the employment of women has increased so much since World War II and because their earnings patterns have been quite different from those of men. Finally, we distinguish between racial groups, again because of the possibility that racial patterns diverge.8 Because of limita tions in the data available, we examine distributions for blacks and nonblacks; the latter group includes whites, Digitized for4 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Asian-Americans, a small number of American Indians, and most Hispanics.9 The method we use involves calculating inequality within and among groups. In our analysis, then, we have 2 genders, 2 races, 14 sectors, and either 9 census regions or 51 States (including Washington, d c ), for a possible total of 2,856 groups. The only data set with enough observa tions to permit this many groupings and still allow us to calculate within-group inequality is the decennial census. Examining other possible explanations of inequality would increase the number of groups beyond the limits of even the census data. The reference years of the census data— 1959, 1969, and 1979— were all years of economic expansion, though they differ because they occurred at different stages of their respective expansions. According to a 1980 analysis of data from the Current Population Survey ( c p s ) by Pe ter Henle and Paul Ryscavage, inequality in these years was not seriously affected by purely cyclical patterns,10 and the results obtained by Sheldon D an z ig er and P eter Gottschalk with decennial census data and with annual c p s data are consistent.11 Therefore, we can be reasonably sure that patterns in the census data are due to secular trends and not merely to cyclical events. (Later, we plan to replicate our results with annual c p s data, to examine cyclical variation and to analyze trends since 1979.) We examine wage and salary income for all those with nonzero earnings during the census year, rather than total earnings (which include wages, salaries, and self-employ ment income). By analyzing wages and salaries rather than total earned income, we concentrate on the conse quence of employment decisions by firms. Inequality in total earnings is greater than inequality in wages and sala ries, but the patterns of the two are similar.12 There has been no marked trend in the relative importance of the two components of total earnings: wages and salaries were 90.2 percent of total earnings in 1969, 91.5 percent in 1979, and 92.6 percent in 1983. Most studies of income inequality have used the Gini coefficient, the variance of the log of income, the coeffi cient of variation, or some measure based on fractiles of the income distribution. We have chosen to use a measure of inequality developed by Henri Theil, based on informa tion theory.13 The measure is: (1) T = 1/n 2 (Y j/ uy) log ( Y / uy) 2 (Yj log Y;) - (uYloguY) where uY refers to the mean of earnings Y. The second of the expressions clarifies that T is the dispersion of 7; log Yj around its mean, standardized by the mean. Theil’s mea sure is scale invariant, so that it is unaffected by inflation. It also adheres to the principle of transfers—that a mea sure of inequality should increase when income is trans ferred from a low-wage earner to a high-wage earner. The change in T for a transfer from a person with earnings Y] to one with earnings Y2 can be shown to depend on log (Y2/ Y j); thus, a transfer of $100 from someone with an income of $6,000 to one with an income of $5,000 de creases T as much as a transfer of $1,000 from someone earning $60,000 to a person earning $50,000. If we assume diminishing marginal utility of income, this is a desirable property. Finally, T is bounded from below by zero, when everyone has the same income; at the other extreme, when one person has all the income and the remaining n - 1 people have none, the upper bound is log n. Theil has argued that the tendency of the upper bound to increase with n is appropriate, because a society of 1,000 people in which one person has all the income is more unequal than a two-person society in which one person has all the in come. If the upper bound were a problem, then Theil’s T could be transformed into a measure with bounds of zero and 1 (like the Gini coefficient) by dividing through by log n. However, in the distributions we examine, which are approximately log normal, the upper bound is irrelevant, and so we use the conventional T bounded by log n .14 Aside from simplicity of calculation, another advantage of Theil’s T is that it can be readily decomposed into terms representing variation among groups and variation within groups. For any number of mutually exclusive and exhaustive groups: (2) T = E (Pj U j / u Y) log (Uj/uY) + 2 (pj u / u Y) Tj where pj is the proportion of individuals in the j th group, Uj is the mean income for the y'th group, uY is the overall mean, and Tj is Theil’s T for the jth group.15 The first term on the right is the among-group variation, and in creases with the dispersion of average group incomes Uj around the overall mean u Y. The second term is the within-group variation, a function of 7} ’s, suitably weighted; this term can also be expanded to show the contribution of individual groups— for example, specific sectors— to overall inequality. This decomposition makes it clear that inequality is affected by three factors: (1) The proportion of the pop ulation in different groups, particularly as there are shifts to higher (or lower) proportions in groups with greater inequality 7}, or higher proportions in groups with means Uj that are far from the overall mean uY. An example would be an employment shift from States near the na tional average to States with relatively high or low income averages. (2) Inequality within groups. As the individual T j’s increase, overall inequality increases as well. (3) In creasing variation of the group means Uj around the overall income mean uY. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Changes in inequality between two years— for exam ple, T80 - T70— can be expressed as changes in amonggroup inequality plus changes in within-group inequality. Such changes can be further decomposed into changes in the proportions in different groups, P j; changes in the dis persion of group incomes around the national mean Uj/u; and changes in the group specific inequality measured by T j.16 However, as there are three distinct components of inequality, such an approach becomes tedious.17 To under stand the causes of changing inequality, it is easier to simulate what inequality would have been if only certain changes had taken place—for example, what inequality would have been if there had been mobility among regions but the regional income distributions themselves had stayed constant.18 It is also straightforward to forecast in equality under different assumptions, such as further increases in women working (assuming male-female earn ings patterns remain constant), or a continued shift from manufacturing to services. In our analyses, there are a maximum of 2,856 groups, defined by gender, race, sector, and State. Keeping these groups separate allows us to examine all possible interac tions of these four characteristics of individuals; for example, we can examine not only changes in inequality due to regional shifts, but also whether these changes are due to shifts in the sectoral composition within the region rather than changes within sectors. For each of these groups, we also calculated other commonly used meas ures of inequality as a check on T.19 (To compare Theil’s T with other measures of the earnings distribution, an appen dix presents correlation coefficients between T and various measures, calculated across the 2,856 groupings, for 1980.) The results of this check reveal that Theil’s T behaves ap propriately, compared to better-known measures. One immediate finding of importance is that, contrary to results of some earlier work suggesting that inequality was stable during the 1960’s and increasing during the 1970’s, inequality in wages and salaries increased both during the 1960’s— with Theil’s T rising from 0.351 to 0.374— and again between 1970 and 1980, with T rising to 0.392. (See table 1.) Evidently, the worsening of in equality in pretax earnings has been occurring for longer than most observers have recognized, masked by changes in transfer payments and in family composition. Patterns by gender and race Our basic results for the four gender-race groups are presented in table 1. One obvious change between 1960 and 1980 is that women increased their rates of labor force participation; in 1960, women were 37.8 percent of the labor force in our sample, increasing to 45 percent by 1980. Over this period, the ratio of women’s earnings to those of men increased slightly, from 44.9 percent to 47.7 percent. More remarkable, however, is the fact that inequal ity among men increased steadily, especially for nonblack 5 MONTHLY LABOR REVIEW April 1989 • Sources o f Inequality in Earnings men, while inequality among women decreased somewhat. In 1960, women’s earnings were considerably more unequal than those of men (T = 0.364 versus 0.296); by 1980, inequality was virtually identical (T = 0.335 for women and 0.330 for men). Earnings patterns by race have diverged substantially between men and women. In 1960, black men earned an average of 55.5 percent as much as nonblack men. By 1980, this had increased to 68.0 percent, though this may partially reflect an increasing proportion of Hispanic men included among those considered nonblack, rather than any equalization of white and black male earnings.20 For women, however, a dramatic equalization of earnings took place: while black women earned 60.5 percent as much as nonblack women in 1960, mean earnings of these two groups were essentially identical by 1980. There was also a convergence of inequality: while earnings of black women were substantially more unequal than those of other women in 1960— with a correspondingly higher proportion of low earners—these measures of inequality were essentially identical in 1980. The tendency for these racial differences to disappear for women, though defi nitely not for men, apparently is due to the fact that black women have managed to move out of the occupations to which they were traditionally restricted— especially as domestic workers— into a broader range of occupations similar to those of white women; in addition, the greater numbers of Hispanic women among nonblack women workers may be partly responsible. Table 1. Overall, therefore, inequality in earnings among these four gender-race groups fell between 1960 and 1980, from 0.072 to 0.064. This decrease has several sources: the slight narrowing of male-female differences; the vanishing difference between black and nonblack women; and a par ticular interaction— the fact that employment was in creasing among women just as male-female differences were narrowing slightly. In contrast, the inequality ex plained by within-group variation increased from 0.279 to 0.328. Much of this was due to increasing inequality among nonblack men, but the increasing share of non black women with relatively high (though declining) within-group inequality also contributed substantially to increasing inequality. The results on low earnings in table 1 are also interest ing. (Low earners are defined as those whose wages and salaries are less than the Federal poverty standard for a family of three.) Although the Theil increased during this period, the proportion of low earners decreased by 2 per centage points between 1960 and 1970 (from 34.8 percent to 32.8 percent), and then increased during the 1970’s to 33.8 percent. The trends in low earnings vary by race and gender. While the proportion of low earners was rather stable for nonwhite men, decreasing slightly during the 1960’s and increasing during the 1970’s, it fell markedly for black women (from 75.5 percent to 45.6 percent), substantially for black men (from 40.0 percent to 31.4 percent), and slightly for nonblack women (from 51.5 percent to 47.1 percent). There is, then, some convergence in the proportions of low earnings, and this helps explain Components of the distribution of wages and salaries by race and gender, 1960,1970, and 1980 Year and worker category Mean income Ratio of mean income to total mean income Proportion of earners Theil’s Portion of T accounted for by variation — Percent of total within-group variation by worker group Proportion low income earners in group T Among groups Within groups 0.35104 0.07225 0.27879 100.00 0.348 _ _ .19188 .01097 68.83 3.93 .211 .400 .06853 .00741 24.58 2.66 .515 .755 .30331 100.00 .328 .20752 .01062 68.42 3.50 .208 .291 .07664 .00853 25.27 2.81 .477 .557 .32762 100.00 .338 .21964 .01387 67.04 4.23 .223 .314 .08368 .01043 25.54 3.18 .471 .456 1960 Total............................................................... Men: Nonblack................................................ B lack...................................................... Women: Nonblack................................................ B lack...................................................... $3,599.25 1.000 1.000 4,741.42 2,630.65 1.317 .731 .564 .057 .25820 .26201 2,145.50 1,297.65 .596 .361 .333 .045 .34507 .45246 5,836.18 1.000 1.000 .37398 7,812.86 4,922.46 1.339 .843 .533 .049 .29072 .25444 3,476.29 2,947.94 5.96 .505 3.72 .045 34604 .37127 11,641.91 1.000 1.000 .39175 15,678.82 10,665.48 1.347 .916 .500 .050 .32594 .30458 — 7,251.44 7,331.21 .623 .630 .399 .051 .33636 .32776 — — — 1970 Total.............................................................................. Men: Nonblack................................................ B lack...................................................... Women: Nonblack................................................ B lack...................................................... .07067 — — — — 1980 Total............................................................... Men: Nonblack................................................ B lack...................................................... Women: Nonblack................................................ B lack...................................................... 6 FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis .06143 — — the falling contribution of among-group variation to over all inequality. In these results, racial patterns make little difference to changes in overall inequality, simply because blacks are such a small and constant proportion of the labor force. The patterns among blacks are interesting in their own right, and the convergence of earnings between black women and nonblack women is particularly striking. However, there simply are not enough blacks to affect the overall distribution of earnings substantially, and there fore increasing inequality must arise from some other source. Another way to examine changes in inequality is to calculated a set of Theil’s measures for hypothetical changes. In terms of equation (2) above, we can calculate 7” s under the assumption that only the composition of the labor force pj changes, without earnings patterns for groups changing; under the assumption that only the mean income ratios u /u Y change; under the assumption that only the within-group inequality as measured by 7} changes; or under the assumption that any two of these change. Table 2 presents the results of calculating such hypothetical T ’s. (Components of T that do not change are held constant at 1960 levels.) The first row indicates that changes in the racial and gender composition of the labor force would, by themselves, have caused inequality to decrease. This surprising result is linked to increases in the proportion of women working; because Theil’s T is more sensitive to changes in low earnings than in high earnings, replacing high-earning nonblack men with low-earning nonblack women causes inequality to fall. However, changes in earnings means and changes in with in-group inequality each caused increases in inequality, as expected. Together, changes in earnings and patterns would have increased T to 0.45, and then shifts in the composition of the labor force reduced T to its actual value, 0.392. Thus, changing patterns of earnings, rather than changes in the composition of the labor force, are responsible for the overall increase in inequality. Based on these results, the finding of increasing in equality in wages and salaries should be qualified to reflect the differences among population groups. Increas ing inequality is the most striking for nonblack men, precisely the group for which most analysis has been done, and there are also increases in inequality for black men. But for women, and especially for black women, there has been a tendency for inequality to decrease. Overall, however, gender and race explain a declining proportion of inequality, and so we must look for other explanations for the deterioration of the earnings distribu tion between 1960 and 1980. Earnings patterns by region We can examine regional sources of inequality by ex amining either States or the nine census regions. Table 3 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Table 2. Theil's T for 1960 and 1980, and as recalculated for 1980 using hypothetical changes With hypothetical change in — item Baseyear r Employ ment shares Earn ings ratios Withingroup T ’s Earnings ratios and withingroup T ’ s Endyear T 4 race-gender groups, 1960-80 ......... 0.351 0.298 0.404 0.399 0.450 0.392 9 census regions, 1960-80 ......... .351 .344 .350 .396 .394 .392 14 sectors: 1960-80 ......... 1960-70 ..... 1970-80 ..... .351 .351 .374 .378 .382 .373 .330 .314 .382 .399 .389 .388 .370 .349 .396 .392 .374 .392 4 race-gender groups, 14 sectors, and 51 States: 1960-80 ......... 1960-70 ..... 1970-80 ..... .351 .351 .374 .321 .354 .339 .368 .337 .403 .407 .389 .395 .422 .374 .424 .392 .374 .392 presents the results for census regions, which are easier to interpret than similar results by State. For 1960, very little of earnings inequality can be explained by among-region differences— only 2.4 percent of the Theil of 0.351. Fur thermore, inter-region variation falls markedly by 1970 and 1980, to 0.6 percent of inequality in the latter year. When States are the units of analysis, 0.0126 of the 1960 Theil of 0.351 ( or 3.6 percent) is explained by inter-State variation, again falling markedly to 0.0045 of the Theil of 0.392 (or 1.1 percent) by 1980. Thus, inequality is largely intra-regional or intra-State, rather than reflecting differ ences among regions or States. The results in table 3 indicate that northern regions and the West have higher average earnings and lower inequal ity, but the table also confirms substantial convergence among regions in two dimensions of earnings. Mean earn ings have converged; for example, regional means relative to the national mean ranged from 0.75 to 1.125 in 1960, but only from 0.869 to 1.078 by 1980. In addition, varia tion within regions, as measured by the regional Theil’s, have also converged: in 1960, the region with the greatest inequality (East South Central) had a T of 0.407, while the region with the least inequality (the Mid-Atlantic) had a T of 0.307. By 1980, regional inequality ranged between 0.376 and 0.405. The same pattern of convergence is evi dent when we examine States rather than census regions: State mean incomes relative to the national mean ranged between 0.565 (Mississippi) and 1.20 (Connecticut) in 1960, but fell within the range of 0.785 (Mississippi) to 1.12 (Connecticut) in 198021; the range of State T ’s is 0.287 to 0.496 in 1960, but 0.345 to 0.444 in 1980. Of course, there is some stability in the ranking of mean earnings and inequality over time, for both States and census regions, but the most salient finding is simply that 7 MONTHLY LABOR REVIEW April 1989 • Sources o f Inequality in Earnings States and regions are becoming more similar to each other in patterns of earnings. With regard to the contribution of various regional changes to overall inequality, it is again clear from table 2 (row 2) that within-region inequality, rather than employ ment shifts among regions, is responsible for the changes between 1960 and 1980. Mobility among regions— re flected in table 3 by the relative increase in employment in the Mountain and Pacific regions, and the relative de clines in the New England, Mid-Atlantic, and East North Central regions— changed inequality very little, from 0.351 to 0.344, because inequality among regions was small in 1960 in any case, and because increase in popula tion shares occurred for both high-income and lowincome States and regions. Similarly, the convergence in regional mean earnings by itself left inequality virtually unchanged (from 0.351 to 0.350). When these 1960-80 changes are examined by decade, mobility made a slightly greater contribution to increases in inequality during the 1960’s and shifts in regional earnings were slightly more important in the 1970’s. The increases in inequality within regions, however, are far more important, and account for virtually all of the increase in inequality between 1960 and 1980. These results confirm the declining significance of region in the distribution of wage and salary income. Dif ferences among regions and among States have narrowed considerably since 1960, and, in any event, these differ ences explain very little of national inequality. These results suggest that regional patterns can be ignored in the analysis of national inequality. Contribution of sectoral shifts Table 4 presents results for earnings in 14 economic sectors. Variation among sectors explains a more substantial frac tion of overall inequality— 13.7 percent in 1960 and 9.0 percent in 1980—than does variation among regions. Still, among-sector variation declines over time, both absolutely and relatively, while the contribution of within-sector in equality increases steadily. The sector that contributes the most to the increase in national inequality is the high-tech sector, simply because the numbers of workers employed in this sector increased from 2.0 percent of the labor force in 1960 to 4.7 percent in 1980; producers’ services, in which there were substantial increases in employment (from 7.1 percent to 10.1 percent) and in inequality; and in health and education, where again both employment and inequality increased substantially. Average earnings vary among sectors in well-known ways, and are lowest in consumer services and retail trade and highest in the high-tech sector and distributive services. Inequality varies among sectors as well: those sectors with relatively few low earners—high-tech, distributive services, and machinery—tend to have relatively low inequality, while agriculture, retail trade, and consumer services all 8 FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis have high proportions of low earners and high levels of inequality. Contrary to the conventional image of the hightech sector as one with great inequality because it consists of a few highly paid professionals and many poorly paid assemblers, this sector has relatively low inequality. The reason is that high-tech has only half the proportion of low earners as the average sector; the conventional depiction of this sector does not take into account the large number of jobs with very low pay in consumer services, retail trade, and agriculture. As in the case of regions, there is evidence of some convergence among sectors in patterns of earnings. Sec toral means relative to the national average ranged from 0.510 to 1.57 in 1960, but from 0.615 to 1.38 in 1980; inequality within sectors ranged between 0.155 and 0.635 in 1960, but between 0.205 and 0.515 in 1980. Sec tors are still remarkably different in 1980, of course, but this tendency toward convergence implies again that among-sector inequality is decreasing while within-sector inequality is increasing. In fact, inequality increased between 1960 and 1980 within every sector except agriculture and consumer serv ices. The increase was especially sharp in health and educa tion, with much greater increases in inequality for men than for women (as is true in general, of course). The other sectors with substantial increases in inequality include con struction, petrochemicals, high-tech, producers’ services, and public administration—all with above-average employ ment of skilled workers or well-trained professionals and below-average proportions of low earners. Conversely, the two sectors with falling inequality—agriculture and con sumers’ services—hire a great deal of low-skilled labor, and have above-average proportions of low-wage labor. This suggests a hypothesis for subsequent examination: that changes in inequality within sectors are related to the use of highly-skilled or well-educated labor and to the wages and salaries paid these workers. Unlike regional shifts, which explain little of the increasing inequality between 1960 and 1980, sectoral changes did have some influence on inequality. Shifts in employment among sectors— out of agricultural, nondur able manufacturing, and miscellaneous durable manu facturing to high-tech sectors, producers’ services, and health and education— would, by themselves, have ac counted for a substantial part of the increase in inequality between 1960 and 1980, with employment changes in creasing T from 0.351 to 0.378. (See table 2, row 3.) Results for each decade are also reported in table 2, and it is clear that these sectoral shifts were particularly impor tant in increasing inequality in the 1960’s but not during the 1970’s. The convergence in earnings ratios among sec tors substantially reduced inequality in the 1960’s but made a slight contribution to increased inequality in the 1970’s. During both decades, the single most important contribution to increased total inequality was the increase Table 3. Components of the distribution of wages and salaries by census region, 1960, 1970, and 1980 Year and region Mean income Ratio of mean income to total mean income Proportion of earners Theil’s Portion of T accounted for by variation — Percent of total within-group variation by worker group Proportion low income earners in group T Among groups Within groups 0.00837 0.34267 .02041 .06819 .07099 .02808 100.00 5.96 19.90 20.72 8.20 0.348 .315 .274 .306 .397 .01830 .04723 .03079 .01295 .04573 13.78 5.34 8.99 3.78 13.34 .411 .474 .437 .383 .310 .36910 .02373 .07261 .07664 -.02896 100.00 6.43 19.67 20.76 7.85 .328 .324 .277 .306 .386 .05060 .01710 .03097 .01452 .05397 13.71 4.63 8.39 3.93 14.62 .341 .373 .3/b .382 .317 .38952 .02265 .06385 .07494 .02838 100.00 5.81 16.39 19.24 7.28 .338 .346 .314 .324 .3/5 .05946 .02001 .03968 .01906 .06150 15.26 5.14 10.19 4.89 15./9 .344 .371 .349 .361 .324 I960 East North Central...................................... West North Central..................................... South A tlantic............................................ East South Central..................................... West South Central..................................... Pacific......................................................... $3,599.25 3,627.53 4,008.29 3,963.12 3,281.81 1.000 1.008 1.114 1.101 .912 1.000 .062 .200 .199 .081 0.35104 .32513 .30666 .32349 .37834 3,072.64 2,683.61 3,057.75 3,426.04 4,047.51 .854 .746 .850 .952 1.125 .144 .060 .089 .038 .125 .38289 .40658 .40576 .35962 .32445 5,836.18 5,907.29 6,462.40 6,244.08 5,283.75 1.000 1.012 1.107 1.070 .898 1.000 .064 .187 .204 .079 .37398 .36882 .35083 .35060 .40818 5,321.42 4,771.04 5,119.12 5,285.69 6,317.91 .912 .817 .877 .906 1.083 .148 .057 .088 .040 .133 .37583 .36759 .39980 .40173 .37378 11,641.91 11,291.07 12,287.30 12,329.56 10,730.99 1.000 .970 1.055 1.059 .922 1.000 .058 .160 .188 .077 .39175 .39988 .37740 .37581 .40010 10,909.50 10,115.75 11,273.63 11,109.09 12,552.53 .937 .869 .968 .954 1.078 .161 .060 .101 .051 .144 .39425 .38683 .40482 .39302 .39729 — — — — — — — — 1970 New England............................................. Mid-Atlantic................................................ East North Central...................................... West North Central.................................... South A tlantic............................................ East South Central..................................... West South Central..................................... Pacific......................................................... .00489 — — — — — — — — — 1980 Mid-Atlantic................................................ East North Central...................................... West North Central..................................... South Atlantic ............................................ East South Central..................................... West South Central.................................... Pacific......................................................... in within-sector inequality. Indeed, increasing within-sector inequality by itself would have increased T to 0.399, and thus the convergence of average earnings (which de creases inequality) and the shifts among sectors (which increase inequality) approximately offset each other. These results illustrate how the three components of over all inequality can behave in different ways, and indicate that sectoral changes have several different, and partially offsetting, influences on inequality. To some extent, these findings appear to justify fears about “deindustrialization” : The employment shifts from manufacturing to services have made the distribution of earnings in this country more unequal, particularly be tween 1960 and 1970. However, a more pervasive finding is that inequality has increased within almost all sectors, especially in those with well-trained or highly educated workers. Interactions among groups The census data permit us to examine any combination of race, gender, region (or State), and sector and, there fore, the interactions among these groups can be examined. Table 5 presents some figures for several interactions, describing among-group and within-group sources of in https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis .00223 — — — — — — — — equality between 1960 and 1980. Of course, the sources of among-group inequality are not additive. For example, according to tables 1, 3, and 4, inequality among 4 racegender groups in 1980 was 0.064, among 9 census regions was 0.002, and among 124 sectors was 0.035, summing to 0.101— somewhat greater than the actual inequality among the 504 race-gender-region-sector groupings of 0.092. However, the results in table 5 add little to those presented earlier. Even for the most detailed figures, describing variation among and within 2,856 groups classified by sector, State, race, and gender, among-group inequality accounted for only 24 percent (.095/.392) of overall inequality in 1980, having declined from 32.8 per cent (.115/.351) in 1960. Therefore, within-group in equality is responsible for the majority of inequality and for the increases in inequality between 1960 and 1980. These results also demonstrate that different compo nents of change affect inequality differently. The national discussion of regional and sectoral shifts, for example, has concentrated on changes in employment, but the conver gence in mean earnings—which by itself decreased in equality (in rows 2 and 4 of table 2)—along with the 9 MONTHLY LABOR REVIEW April 1989 • Sources o f Inequality in Earnings increases in within-sector and within-region inequality have been less frequently mentioned. Both trends in mean incomes and in within-group inequality have increased overall inequality (row 6 of table 2), while the changing composition of employment— specifically, gender and ra cial changes—have decreased inequality. The causes of trends in inequality are complex, and the decomposition of Theil’s T helps clarify these complexities. between 1960 and 1980. However, this increase was not evenly spread throughout the population. Inequality has gone up among men (especially nonblack men), but has actually decreased among women (especially black women). Contrary to expectations, changes in the gender and racial composition of the labor force— especially the increasing proportions of women working—by themselves decreased earnings inequality, while changes in the earnings distri butions— particularly the increasing inequality among nonblack men— more than offset these changes. Again contrary to expectations, regional shifts explain almost none of the changing inequality. There was instead a marked convergence among regions, so that differences Conclusion and future directions These results have confirmed with detailed census data what others have found using Current Population Survey data: overall inequality in wages and salaries increased Table 4. Components of the distribution of wages and salaries by sector, 1960, 1970, and 1980 Portion of T accounted for by variation — Mean income Ratio of mean income to total mean income Proportion Of earners Theil’s T Among groups Total.............................................................. Agriculture............................................... Construction.......................................... Nondurable goods.................................. Petrochemicals...................................... Machinery........................................ Miscellaneous durable goods.................... Technological Industries............................. $3,599.25 2,172.82 4,164.58 3,535.16 5,451.16 5,143.94 3,737.82 5,635.63 1.000 .604 1.157 .982 1.515 1.429 1.038 1.566 1.000 .056 .065 .116 .026 .065 .039 .020 0.35104 .63529 .24022 .32200 .18114 .15507 .27103 .15635 0.04815 Distributive services........................ Wholesale trade................................... Retail trade............................................. Producer services...................................... Consumer services............................... Health and education................................. Public administration.................................. 4,746.50 4,652.92 2,520.24 4,321.93 1,834.25 3,257.17 4,496.54 1.319 1.293 .700 1.201 .510 .905 1.249 .089 .039 .162 .071 .097 .107 .049 .16807 .30667 .46199 .35504 .56801 .33803 .17860 Total........................................................... Agriculture.................................................. Construction............................................... Nondurable goods................................. Petrochemicals....................................... Machinery............................................. Miscellaneous durable goods.................... Technological Industries............................. 5,836.18 4,154.24 7,267.37 5,462.92 7,307.31 7,868.03 6,151.90 8,056.64 1.000 .712 1.245 .936 1.252 1.348 1.054 1.380 1.000 .035 .057 .087 .016 .078 .037 .052 .37398 .58555 .25873 .35935 .24669 .18418 .29600 .21442 Distributive services................................... Wholesale trade......................................... Retail trade.............................................. Producer services...................................... Consumer services.................................... Health and education................................. Public administration.................................. 7,298.17 7,389.55 3,668.62 6,804.58 3,306.30 5,188.64 7,292.43 1.251 1.266 .629 1.166 .567 .889 1.250 .077 .042 .155 .084 .079 .150 .051 .20110 .33400 .52461 .41281 .57089 .38672 .23428 Total............................................................... Agriculture.................................................. Construction............................................... Nondurable goods...................................... Petrochemicals........................................... Machinery.................................................. Miscellaneous durable goods.................... Technological industries............................. 11,641.91 10,706.53 13,128.93 11,076.20 14,790.86 15,835.04 11,672.99 15,921.25 1.000 .920 1.128 .951 1.270 1.360 1.003 1.368 1.000 .032 .059 .068 .015 .070 .032 .047 .39175 .49426 .30950 .35581 .26489 .20530 .31555 .23064 Distributive services................................... Wholesale trade.......................................... Retail trade................................................. Producer services ...................................... Consumer services..................................... Health and education................................. Public administration.................................. 16,088.10 14,567.88 7,305.39 12,809.31 7,158.82 10,626.20 13,517.81 1.382 1.251 .628 1.100 .615 .914 1.161 .071 .042 .169 .101 .071 .168 .055 .20782 .35766 .51489 .42197 .49392 .45545 .25811 Year and sector Within groups Percent of total within-group variation by worker group Proportion low income earners in group 0.30290 .02129 .01794 .03679 .00708 .01430 .01091 .00501 100.00 7.03 5.92 12.14 2.34 4.72 3.60 1.65 0.348 .664 234 308 .113 103 272 .093 — .01982 .01529 .05234 .03032 .02812 .03280 .01088 6.54 5.05 17.28 10.01 9.28 10.83 3.59 .145 .223 .520 .272 666 375 .167 .03983 _ _ _ _ _ _ — .33416 .01455 .01834 .02931 .00479 .01945 .01157 .01546 100.00 4.35 5.40 8.77 1.43 5.82 3.46 4.63 .328 499 202 301 .175 122 234 .132 .01932 .01795 .05117 .04025 .02552 .05160 .01489 5.78 5.37 15.31 12.05 7.64 15.44 4.45 165 .219 .555 .281 598 375 .190 _ _ _ _ - .35638 .01474 .02070 .02290 .00489 .01948 .01027 .01483 100.00 4.13 5.81 6.43 1.37 5.47 2.88 4.16 .338 .388 259 .316 .189 144 272 .150 _ _ _ _ _ — .02047 .01883 .05471 .04674 .02146 .06997 .01640 5.74 5.28 15.35 13.11 6.02 19.63 4.60 .155 .232 .567 .298 .555 .367 .223 1960 _ _ _ _ _ _ — _ _ _ _ _ 1970 _ _ _ _ _ .— 1980 Note: See text footnote 6 for detailed definitions of sectors. 10 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis .03537 _ _ among regions and therefore inequality among regions— were of diminishing importance. This finding, which holds whether we examine 9 census regions or 51 States, seems so robust that regional patterns— which are expen sive to examine in terms of data requirements—can be ignored in subsequent analyses of inequality. However, sectoral shifts— the much debated increase in services and high-tech employment at the expense of agriculture and manufacturing— were, as hypothesized, partly responsible for increasing inequality. By them selves, changes in the sectoral composition of employment accounted for almost two-thirds of the overall increase in Theil’s T between 1960 and 1980—but these effects were augmented by even larger increases in inequality within most sectors, and offset somewhat by a tendency for mean wages and salaries among sectors to converge. Aside from indications that inequality has increased most in sectors with high skill and education levels, the results do not suggest why inequality has increased within sectors. Our findings so far are similar to those of earlier re searchers: we have eliminated some potential explanations of increasing inequality, such as regional shifts and changes in the numbers of women working, and confirmed the im portance of sectoral shifts, but much of the recent increase in inequality remains unexplained. Two potential explana tions merit further attention. Occupational patterns may be important, particularly because of the tantalizing finding that the sectors with the greatest increases in inequality are those with more highly skilled or highly educated workers. Changing patterns of part-time and part-year employment, which Chris Tilly, Barry Bluestone, and Bennett Harrison have cited and which Saul Schwartz found important to increasing inequality among black men,22 might explain why inequality has increased so consistently within sectors and within regions, and why it has increased for men but decreased for women. Table 5. Sources of inequality in wage and salary income for selected labor force groupings, 1960,1970, and 1980 1980 1970 1960 Labor force group Among groups Within groups Among groups Within groups Among groups Within groups 14 sectors by 2 gender groups ... 0.097 0.254 0.092 0.282 0.085 0.307 9 census regions by 4 race - gen der groups......... .079 .272 .075 .299 .066 .325 14 sectors by 9 census regions .. .056 .295 .045 .329 .039 .353 14 sectors by 9 census regions by 4 race - gender groups............... .110 .241 .101 .273 .092 .300 14 sectors by 51 States by 4 race-gender groups............... .115 .236 .105 .269 .095 .296 Overall inequality . .351 - .374 - .392 - There is nothing in our results to diminish the impor tance of the issue, however. Indeed, inequality in wages and salaries has been increasing for nonblack men for longer than most observers have thought. Nothing in these results indicates that the trend of inequality will abate; to the con trary, for men (especially black men) and for several sectors (health and education, and construction), the increase in inequality was greater during the 1970’s than during the 1960’s. The conclusion that increasing inequality within various groups and sectors is responsible for most of the increasing inequality — rather than well-known shifts among sectors and regions and changes in the composition of the labor force—adds to the importance of further analy sis, for the reasons behind within-group developments remain poorly understood. □ FOOTNOTES A c k n o w l e d g m e n t : The research described in this report has been supported by the Policy Research Institute of The University of Texas at Austin. The authors wish to acknowledge exceptional computer programming support from Alan Doyle of the Population Research Center at The University of Texas at Austin. Marcia Van Wagner pro vided assistance in the early phase of this work. We also thank Isabel Sawhill, Sheldon Danziger, and two anonymous references for helpful comments on an earlier version of this article. ‘in this article, we are interested in the fundamental shifts in the economy underlying inequality, rather than with changes in household demographics and transfer programs; therefore we confine our analysis to individuals and to wages and salaries rather than total income. 2See, for example, Martin Dooley and Peter Gottschalk, “Does a Younger Male Labor Force Mean Greater Earnings Inequality?” Monthly Labor Review, April 1977, pp. 7 -11; Martin Dooley and Peter Gottschalk, “Earning Inequality among Males in the United States: Trends and Effects of Labor Force Growth,” Journal o f Political Econ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis omy, February 1984, pp. 59-89; Peter Henle and Paul Ryscavage, “The Distribution of Earned Income Among Men and Women, 1958-1977,” Monthly Labor Review, April 1980, pp. 3-10; Robert Plotnick, “Trends in Male Earnings Inequality,” Southern Economic Journal, January 1982, pp. 724-732; and Saul Schwartz “Earnings Capacity and the Trend in Inequality Among Black Men,” Journal o f Human Resources, Winter 1986, pp. 44-63. 3Among other possible explanations for trends in inequality that ap pear to have little influence, and that we therefore do not consider here, are changes in the age and experience of at the labor force; cyclical variation in unemployment; and changes in the educational composition of the labor force. In addition to the references in footnote 2, see also Bradley Reif, “Industry and Occupation Employment Structure and Income Distribution” (Massachusetts Institute of Technology, May 1986); and Chris Tilly, Barry Bluestone, and Bennett Harrison, “What is Making American Wages More Unequal?” (Boston College, December 1986). In subsequent analyses with both Census and c p s data, we plan to consider the effects of part-time versus full-time employment and educa tion in addition to gender and sectoral composition. 11 MONTHLY LABOR REVIEW April 1989 Sources o f Inequality in Earnings 4Robert Kuttner, “The Declining Middle,” Atlantic Monthly, July 1983. See Carl B. Barsky and Martin E. Personick, “Measuring wage dis persion: pay ranges reflect industry traits,” Monthly Labor Review, April 1981, pp. 35-41. 6For purposes of this analysis, sectors were defined as follows: Agriculture, forestry, fishing, and mining (010-050) Construction (060) Nondurable, nonchemical manufacturing: food and kindred products (100-130), textile products and apparel (132-152), paper and allied products (132-152), printing and publishing (171-172), and leather and leather products (220-222) Chemicals, petrochemicals, and plastics: chemicals and allied products (180-192, except 181 and 192), and petroleum, coal, rubber, and plastics ( 2 0 0 - 212 ) Metal, machinery (except electrical), and transportation equipment: metal industries (270-301); machinery, except electrical (310-332, ex cept 321 and 322); and transportation equipment (351- 370, except 352 and 362) Miscellaneous durable goods: lumber, wood products, stone, glass, clay, and concrete (230-262); electrical machinery except high-tech (340350, except 341 and 342); and miscellaneous (390-392) Advanced technology sectors (181, 192, 321-322, 341-342 352 362, 371-382) Distributive services (400-472) Wholesale trade (500-571) Retail trade (580-691) Producer services: finance, insurance, and real estate and business and professional services (700-742, 881-892) Consumer services: repair; household and personal services; and social services (750-802, 862-880) Private-sector health and education (812-861) Public administration (900-932) The census codes in parentheses are taken from Census o f Population and Housing: 1980: Public Use Microdata Sample— Technical Docu mentation (Bureau of the Census, March 1983), appendix H, pp. 142-48. Advanced technology sectors are based on the third definition of high-tech sectors, those that both use technology-oriented workers and have high research and development expenditures, developed in Richard W. Riche, Daniel E. Hecker, and John U. Burgan, “High tech nology today and tomorrow: a small slice of the employment pie,” Monthly Labor Review, November 1983, pp. 50-58. 7See Riche and others, “High technology today and tomorrow.” 8For example, James P. Smith and Finis R. Welch found convergence of the wages of black and white men between 1940 and 1980 in Closing the Gap: Forty Years o f Economic Progress for Blacks, r - 3 3 3 0 - d o l (Santa Monica, c a , The r a n d Corporation, February 1986). Michael Reich argued that the pattern of narrowing racial differentials during the 1960’s has been replaced by a growing differential for men during the 1970’s in “Postwar Racial Income Differences: Trends and Theories” APPENDIX: 9The census definition of Hispanics was not consistent over the years 1960, 1970, and 1980. l0See Peter Henle and Paul Ryscavage, “The distribution of earned income among men and women, 1958-77,” Monthly Labor Review, April 1980, pp. 3-10. HSee Sheldon Danziger and Peter Gottschalk, “How Have Families with Children Been Faring?” report presented to the Joint Economic Committee of the U.S. Congress, November 1985. 12Henle and Ryscavage, “The distribution of earned income.” 13Henri Theil, Economics and Information Theory (Amsterdam, North-Holland Publishing Co., 1967). uFor comparisons of different measures of inequality, see Paul Alli son, “Measures of Inequality,"American Sociological Review, December 1978, pp. 865-80. 15See Henri Theil, Statistical Decomposition Analysis (Amsterdam, North—Holland Publishing Co., 1972); and Allison, “Measures of In equality.” 16For such a decomposition of the variance of log income, see Bradley Reiff, “Industry and Occupation Employment Structure and Income Distribution” (Cambridge, m a , Massachusetts Institute of Technology, May 1986). 17Because the proportions pj and income ratios u / u Yenter both terms of equation (2), the decomposition of changes in T involves several complex interaction terms. This does prove to be a drawback of using Theil’s T rather than the variance of the log of earnings, for which the decomposition is more tractable. 18For an application, see Theil, Economics and Information Theory. 19In the census data files, earnings are given in $10 intervals, so that the problem of underestimating inequality because of ignoring inequality within large earnings intervals— as is necessary with published census data— does not arise. However, there is always an open-ended earnings group— those above $25,000 of earnings in 1960, $50,000 in 1970, and $75,000 in 1980. For those very few individuals in these open-ended cate gories, we followed the standard procedure of fitting a Pareto distribution to the upper 30 percent of the earnings distribution to estimate the mean earnings for this group. 20See Michael Reich, “Postwar Racial Income Differences.” 2'In these comparisons, we eliminate Alaska, which is an outlier with values of 1.20 in 1960 and 1.413 in 1980. -2See Chris Tilly, Barry Bluestone, and Bennett Harrison, “What Is Making American Wages More Unequal?” unpublished paper (Boston College, December 1986); and Schwartz, “Earnings Capacity.” Theil’s T compared to other measures As indicated in the text, for each gender-race-sectorState group, we calculated not only the mean and Theil’s T of wages and salaries, but also other commonly used measures of inequality— the Gini coefficient and the pro portions of earnings going to the bottom 5 percent and 20 percent and to the top 5 percent and 20 percent of earners as a check on T. These fractiles also allow us to calculate the fraction of earnings going to the middle 60 percent of earners— one measure of the middle of the distribution, and therefore relevant to the thesis of the “vanishing mid Digitized for 12 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis (University of California at Berkeley, October 1985). For women, the convergence in average earnings between whites and blacks has been even more marked than for men, and in fact the black-white differential has almost vanished, according to James P. Smith and Michael P. Ward, Women's Wages and Work in the Twentieth Century, r - 3 1 1 9 - n i c h d (Santa Monica, CA, The r a n d Corporation, October 1984). dle.” In addition, we also calculate a measure of low earnings; the proportion of earners whose wages and sala ries are under the Federal poverty standard for a family of three. (Over a very large number of observations the Gini coefficient is very time-consuming to calculate, and so we have not calculated Gini coefficients for the country.) To give some sense of the magnitude of Theil’s T com pared to the Gini coefficient, table A - l presents both measures for sectors in California in 1980. To compare Theil’s T against other measures of the earnings dis- Table A -1 . Pearson correlation coefficients for various inequality measures, 1980 Measure Theil’s T Gini coefficient Percent low earners Top Bottom Bottom Middle Top 5 20 60 20 5 percent percent percent percent percent 1.00000 0.96072 0.59459 -0.38677 -0.60264 -0.68233 0.71588 0.29841 Gini coefficient............................................... — 1.00000 .58359 -.32686 -.55793 -.57601 .61353 .13654 Percent low earners....................................... — — 1.00000 -.40965 -.56526 -.41552 .45563 .31355 Bottom 5 percent........................................... — — — 1.00000 .74437 .47081 -.27236 -.39858 1.00000 Theil’s T ......................................................... .57895 -.33960 -.44869 1.00000 -.99429 -.92078 — — 1.00000 .86501 — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — — Bottom 20 percent........................................ — — — — Middle 60 percent.......................................... — — — — - Top 20 percent............................................... — - — — California Agriculture ..................................................... Construction................................................... Nondurable goods.......................................... Petrochemicals............................................... Machinery...................................................... Miscellaneous durable goods........................ High-technology industries............................. .429 .297 .318 .247 .236 .310 .181 .489 .410 .417 .372 .361 .414 .320 — — — — — — — Distributive services....................................... Wholesale tra d e ............................................ Retail tra d e .................................................... Producer services.......................................... Consumer services........................................ Health and education..................................... Public administration...................................... .196 .320 .415 .392 .478 .534 .163 .323 .416 .503 .465 .506 .516 .279 — — — — — — — — — — — — — — — — — — — — — Note: See text footnote 6 for detailed definition of sectors. tribution, the table also presents correlation coefficients between T and various measures, calculated across the 2,856 groupings, for 1980. The correlation between T and the Gini coefficient is very high, at 0.96; the Spearman rank order correlation is even higher, at 0.99. Theil’s T is correlated about equally with the proportion of earnings https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis held by the top and bottom tails of the earnings distribu tion. The correlation between T and the middle 60 percent of the distribution is negative, indicating that a declining middle would indeed increase inequality as measured by T. In sum, TheiPs T appears to behave appropriately when compared to other measures of inequality. 13 Institutional barriers to employment of older workers Social Security and private pension rules often encourage early retirement; those who wish to keep working typically face a part-time job market which provides few well-paid jobs D ia n e E. H erz a n d P h i l i p L. R o n e s Retirement ages have fallen steadily since World War II. Early retirement, a term often used to describe labor force withdrawal prior to age 65, has become the norm. By age 62, almost half of all men are out of the labor force (they are neither working nor looking for work), and by age 64, three-fifths are “retired” by that definition.1 The trend toward early retirement has generally been regarded as a positive one, as it primarily reflects improve ments in retirement resources— Social Security, pensions, and wealth. Some retirements, however, may not be strictly voluntary; rather, they may be in response to actual or probable job loss, or to a lack of acceptable job opportuni ties for older workers. These retirements may be voluntary only to the extent that leaving the labor force is the best available option. Some workers might prefer another choice— either phased retirement or a “second career” upon job loss or pension acceptance. But this choice is often not feasible because of institutional rules and job market realities. Usually, workers must choose between continued full-time employment (during which some pen sion benefits often are lost), part-time work for relatively low wages, or complete retirement. Given these limitations, many workers choose complete retirement. Anticipating a dramatic decline in the ratio of workers to retirees as the baby-boom generation becomes eligible for retirement early in the next century, Federal policy has been directed toward encouraging workers to extend their worklives.2 Social Security regulations have been al tered to encourage later withdrawal from the labor force, Diane E. Herz and Philip L. Rones are economists in the Division of Labor Force Statistics, Bureau of Labor Statistics. This article has been adapted from a broader report submitted to Congress in January 1989. Digitized for 14 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis and mandatory retirement has been prohibited— regard less of age. Also, researchers are examining ways in which work schedules and environments could be designed to address the needs and desires of older persons. At the same time that Federal efforts have been di rected at extending worklives, however, an opposite and, for some workers, more dominant force has influenced retirement decisions; many employers have made early retirement possible or have liberalized options already of fered in their pension plans. Such efforts may be the result of labor management negotiations, employers’ desires to attract workers by offering the prospect of generous and early pensions, or employers’ attempts to reduce employ ment by inducing older workers to retire earlier than they might have planned. Both by liberalizing provisions in their normal pension plans and by offering Early Retire ment Incentive Plans ( e r i p ’s ), employers have made retirement increasingly affordable for many older workers. This article discusses various institutional obstacles faced by older persons who might want to work. It is divided into three sections: (1) the impact of Social Secu rity regulations and pension policies on work activity; (2) the market for part-time jobs; and (3) age discrimination. Social Security Social Security benefits are the major source of income for the elderly. In 1986, 9 of 10 nonmarried persons or married couples in which the husband was age 65 or older received some portion of their income from Social Secu rity, and 60 percent relied on Social Security for more than half of their total income.3 Thus, changes in Social Security policies could affect the majority of older persons. Researchers have examined the effects of Social Secu rity rules on the work activity of older persons for many years. While findings are sometimes contradictory, most studies have concluded that Social Security regulations provide substantial disincentives to work at older ages. Policymakers concerned about reducing financial burdens on the Social Security system have recognized these disin centives to work; several reforms designed to encourage older persons to remain in the labor force were passed as part of the Social Security Amendments of 1983.4 Opera tions of the current program, evidence that work disin centives exist, and long-term reforms to the program and their potential effects are discussed below. How the current program works. Social Security bene fits are based on lifetime earnings in covered employment. While the process of determining benefits is complex, in general, annual earnings between 1951 and the year of eligibility for retirement first are averaged and adjusted for inflation to derive an Average Index of Monthly Earn ings (aime ). A benefit formula is then applied to the AIME to determine an individual’s full benefit amount— or Primary Insurance Amount (pia ). The percentage of the pia that an individual actually receives depends on both age at retirement and current earnings, if the individ ual continues to work.5 Currently, individuals are eligible to receive full bene fits (equal to 100 percent of pia ) at age 65— the “normal” retirement age as defined in the Social Security program. Reduced benefits equal to 80 percent of the pia are avail able at age 62. For every month after age 62 that receipt is deferred, the 20-percent early retirement penalty is re duced by 0.56 percent (or 6.67 percent per year) so that the full pia level is earned at age 65. If an individual chooses to continue working beyond age 65, he or she receives a delayed retirement credit of 3 percent per year. For example, a person working (and deferring Social Se curity receipt) to age 68 could expect to receive benefits equal to 109 percent of his or her determined pia . Social Security rules have been based on a longstanding policy that benefits are insurance against earnings lost due to retirement. Therefore, recipients who work may only earn up to a specified exempt amount before their Social Security benefits are reduced. Currently, Social Security recipients younger than age 65 can earn up to $6,480, beyond which point their benefit amount is reduced by $1 for every $2 earned. Workers ages 65 to 70 can earn $8,800 before benefit reductions begin. After age 70, these reductions no longer apply. Effects on work incentives. Studies have examined how these regulations may affect the work activity of older persons. Most studies have indicated that disincen tives to work do exist, but a few have not. After examining the benefit stream available to an “illustrative” worker at https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis various retirement ages in 1982, Gary Fields and Olivia Mitchell concluded that, although the level of benefits increased for each year of additional work, gains from additional benefits were more than offset by the smaller number of years of benefit receipt.6 In fact, the present value of total future benefits for a person who worked until age 68 was only 90 percent of that for a worker who retired at age 60. This “penalty” for retiring at age 68 is largely the result of the 3-percent delayed retirement credit being far below the actuarially neutral level (the level at which the value of benefits for an average worker would be the same regardless of when he or she retires). Thus, Fields and Mitchell concluded, the current system provides incentives to retire before age 65 rather than after. Studies by other researchers have produced similar results.7 The effect of the earnings test on work activity has also been widely examined. Using data from the Social Secu rity Newly Entitled Beneficiary Survey (nbs ), Howard M. lams found that male beneficiaries in 1982 had median earnings of $4,391—just below the $4,400 earnings test level that year. Social Security benefit recipients ages 65 to 71, who could earn up to $6,000 before benefits were reduced, consistently had higher earnings than recipients younger than age 65.8 Median earnings for men in the older group were $5,460. In another study on the effect of the earnings test, Gary Burtless and Robert Moffitt found that workers kept post-retirement hours to the level at which total earnings equaled the exempt amount.9 Avoidance of earnings in excess of the exempt amount is understandable. Not only would half of any excess earnings be lost through Social Security reductions, but, in addition, all earnings would be subject to Federal, State, and local income taxes as well as Social Security withholdings. Another effect of the earnings test, al though impossible to quantify, is that some persons might work “off the books” rather than pay Social Security and income taxes on their earnings. For retirees with pension incomes, Social Security ben efits, and a lifelong accumulation of savings, the earnings test is probably of little or no consequence. These workers often prefer early retirement. Some retirees may choose to work part time or part year to supplement their retire ment income. For those who limit their activity so as not to exceed the exempt amount, the liberalization or elimi nation of the earnings test could increase their work effort. However, among the smaller group of part-timers who earn more than the exempt amount while receiving reduced benefits, work effort may actually be reduced, as they could work fewer hours without a loss in income. What is still not clear, however, is the extent to which Social Security encourages retirement or discourages con tinued work. Some researchers believe that the method of calculating Social Security benefits may cause some work ers to postpone retirement. Because the most recent (and 15 MONTHLY LABOR REVIEW April 1989 Barriers to Employment o f Older Workers presumably highest) years of earnings are averaged in benefit computation, some researchers believe that work ers may choose to work longer, replacing low earnings years with higher ones, and therefore increasing their So cial Security benefit.10 (still only 3.1 months) occurred when the percentage of total benefits received at age 62 was reduced from 80 to 55 percent (the reforms only reduced the percentage to 70 percent) and the delayed retirement credit was increased to 20 percent (from the current 9 percent) at age 68.13 Changes in the program. The Social Security Amend ments of 1983 contained several long-term provisions designed to remove work disincentives. These included the following:11 Other pensions 1- An increase in the normal retirement age. Beginning in the year 2000, the retirement age at which beneficiaries are eligible to receive full benefits will increase gradually from 65 to 67. The normal retirement age will remain at 67 for those reaching age 62 after 2022. 2. An increase in the early retirement penalty. Reduced ben efits will continue to be available at age 62, but reduction factors will be revised to a maximum of 30 percent (for workers entitled at 62 when normal retirement age is 67) compared to the prior 20-percent reduction. 3. An increase in the delayed retirement credit. The delayed retirement credit will increase by half a percentage point every other year, from 3 percent for workers age 62 prior to 1987 to 8 percent per year for workers age 62 after 2004. 4. A decrease in the withholding rate under the earnings test. Beginning in 1990, the withholding rate will decrease from $1 of every $2 above the exempt amount for persons who attain full retirement age to $1 of every $3. Beginning in 2000, the age at which this occurs will increase as the normal retirement age increases. Potential effects o f the changes. Despite the fact that Social Security is an important income source for almost all older persons, most analysts believe that changes in retirement ages, as a result of the Social Security amend ments, will be small. This is particularly clear when the changes are dissected. For example, while earnings above the exempt amount will be subject to a one-third offset under the new law (rather than the present one-half), those earnings will continue to be subject to Federal, State, and local taxes and Social Security withholdings. Thus, the system will still provide disincentives to exceed the exempt amount. Alan Gustman and Thomas Steinmeier studied the po tential effect of 1983 reforms and concluded that “in comparison with the previous rules, the 1983 rules, when they take full effect, should have a fairly small impact on the number of people working full time and the number retired before age 65, but at age 65 and thereafter, the percentage of individuals working full time would be no ticeably increased [largely due to the scheduled increase in the delayed retirement credit] and the percentages working part time and retired would both decline.” 12 Fields and Mitchell found that increasing the normal re tirement age from 65 to 68 (legislation raises it to age 67) could be expected to increase average retirement age by only 1.6 months. They also found that the largest increase Digitized for 16 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Retirement decisions are rarely based on Social Secu rity benefit levels alone; they also depend, among other things, on preferences for leisure over work, on health status, and on other income sources. Although most workers can no longer be forced to retire because of their age, many other provisions in pension plans encourage workers to retire at specific ages, often well before the normal retirement age of 65 in the Social Security program. Pension policies do not affect all workers. In fact, of those persons receiving Social Security benefits (of any type) in 1980-81, only about 57 percent of men and 31 percent of women were either receiving or expecting to receive a pension.14 For those who do receive pensions, however, plan policies greatly affect retirement decisions. And, in general, it does not take a large pension to induce workers to retire.15 Retirement provisions. While individuals are not eligi ble for full Social Security benefits before age 65, normal (full-benefit) retirement ages in private and governmental pension plans tend to be much lower. In recent years, retirement programs have become increasingly liberal, al lowing full benefits at earlier ages. Seventy-nine percent of pension plans surveyed by the Bureau of Labor Statistics in 1983 had no minimum retirement age or provided full benefits at age 62 or earlier, up from 55 percent in 1974. And 37 percent of those plans allowed for full-benefit retirement as early as age 55, usually with 30 years of service.16 Almost all private pensions surveyed by bls in both 1974 and 1983 permitted early retirement, although at reduced benefits. Over the 1974—83 period, however, both age and years-of-service requirements for early retirement declined. In 1983, the length of service required for early retirement (with reduced benefits) at age 55 averaged 7 years and 2 months, down from 10 years and 3 months in 1974.17 Are pensions actuarially neutral? Individuals who opt for early retirement usually receive reduced benefits. However, reduction percentages are not always actuari ally neutral; the greater number of years of pension receipt (due to early retirement) often more than offset any decline in benefits. In a study of 10 pension plans surveyed in the 1978 Benefits Amounts Survey, Fields and Mitchell found that, in half of the plans, the present value of net pension benefits was greatest for workers retiring at age 60.18 Four of the 10 plans paid the highest benefits at age 61 or 62, and the remaining plan at age 66. Similarly, Lawrence J. Kotlikoff and David A. Wise, in a study of more than 2,000 pension plans, found that plan provisions strongly discouraged work after a normal re tirement age— some after an early retirement age.19 Con tinued work does provide additional earnings; however, the foregone pension benefits (as with deferred Social Se curity benefits) result in an implicit tax on earnings which may be as high as 100 percent.20 Some pension provisions penalize continued work ac tivity. Since passage of the Omnibus Budget Act of 1986, pension plans are no longer allowed to deny continued pension accrual for persons over age 65. Caps are still permitted, however, on years of service that may be counted toward a pension and on total benefit levels.21 Also, rates of accrual may be less than actuarially neutral for those who delay retirement. These provisions, in ef fect, reduce total compensation levels for persons who continue working after reaching either the maximum lev els of credited service or pension benefits. Combining pensions and Social Security. Not only do pension plans provide different options and retirement incentives than Social Security, but, in many cases, pen sion benefits are derived using a formula that accounts for Social Security benefits. Thus, changes in Social Security policy designed to alter work patterns may be undermined by the structure of pension plans. A 1986 survey of employee benefits in medium- and large-sized firms found that 62 percent of all full-time participants in defined-benefit pension plans were in plans “integrated,” or combined in some way, with Social Secu rity.22 Sixty-nine percent of the employees in these inte grated plans had offset provisions; pension benefits were derived as a function of Social Security payments (usually pension levels were reduced by 50 percent of an individ ual’s Social Security benefit). For example, workers with expected pension benefits of $8,000 and expected Social Security benefits of $2,000 would actually receive pension benefits of $7,000 [$8,000 - (.50 x $2,000)] in addition to their $2,000 Social Security benefit. In this way, public policy efforts to increase incentives to work by reducing benefits would be countered by a 50-percent increase in private benefits. A reduction of $1,000 in Social Security benefits, for example, would be countered by a $500 cor responding increase in pension benefits. Plans with excess formulas also recognize the structure of Social Security benefits and attempt to increase benefits to workers with higher earnings (whose Social Security benefits replace a smaller share of earnings). This is accomplished by apply ing higher benefit accrual percentages to earnings above a specified limit— usually equal to the Social Security tax able maximum.23 Some retirees receive supplemental benefits to their pensions to compensate for retiring prior to eligibility for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Social Security payments. A 1984 bls survey of pension plans found that 11 percent of all plan participants could receive supplements upon early retirement. Ten percent were eligible for supplements on top of their full benefits if they retired “normally” before age 62— when they would become eligible for reduced Social Security benefits.24 These supplemental payments are often equal to or greater than the Social Security benefits they would later receive. Each of these pension provisions that integrate Social Security and pension benefits may mitigate any changes in incentives that Social Security reforms are in tended to produce. Recently, researchers have begun to compare the incentive effects of Social Security and private pension provisions on individual retirement decisions. A study by James H. Stock and David A. Wise modeled the re tirement behavior of employees in one large firm and simulated the effects of changes in Social Security and of alternative pension plans. The researchers found that in creases in the firm’s early retirement age dramatically reduced the number of workers retiring by age 60. In contrast, the effects of changes in Social Security rules were minimal.25 Also, the researchers concluded that “Changes in Social Security provisions that would other wise encourage workers to continue working can easily be offset by countervailing changes in the provisions of the firm’s pension plan.” Early Retirement Incentive Plans Early withdrawal from the labor force has expanded with the increasing use of Early Retirement Incentive Plans (erip ’s). These plans allow workers to retire earlier than the normal terms of their pension plans would allow. Typically, erip ’s either liberalize the requirements for pension eligibility or provide employees with richer pen sion benefits. Some also offer early retirees either a continuation of or improvement in medical coverage after their separation from service, erip ’s are typically offered for only a short period, after which the normal plan rules apply. erip ’s, in many ways, are simply an extension of the trend toward early retirement made possible by pension plan provisions already discussed in this article. The key issue related to erip ’s is whether they are truly voluntary: Do workers perceive turning down these offers as being a viable option? Are workers satisfied with the early retire ment decision? Two facts are critical to the discussion of erip ’s. First, no one knows how prevalent they are. The few surveys of employers conducted to date often are not representative samples of all employers and often have low response rates; hence, the results based on data from reporting firms may not reflect the experience of all firms. Second, and probably the most important for policy considerations, it is difficult to determine the extent of 17 MONTHLY LABOR REVIEW April 1989 • Barriers to Employment o f Older Workers involuntary separations resulting from these plans. A study by Phyllis H. Mutschler and others indicates that companies, workers, and unions have embraced them.26 At the same time, a study conducted for the Public Policy Institute of the American Association of Retired Persons (aarp ) concludes that such plans are primarily “older worker termination programs,” and that neither the indi viduals involved nor the Nation’s interests are well served by them.27 The plans seem to be voluntary, given that the majority of eligible workers do not accept them. A study by Hewitt Associates indicates that, on average, about 1 in 3 workers accept erip ’s when offered.28 Indeed, some companies have had far more workers accept these offers than they had expected, causing a damaging loss .of experienced per sonnel. On the other hand, numerous lawsuits related to these plans suggest that some older workers view them as forced retirement schemes.29 The Hewitt Associates’ analysis of the prevalence of erip ’s is the most extensive to date. Of the 529 companies responding to their 1985 survey, a third reported that they had used early retirement windows (whereby the employee is given a specific period of time in which to decide whether to retire with the improved benefit package) or other types of voluntary separation plans. About 40 per cent of the companies using erip ’s had offered them more than once. Plans were offered far more frequently by the larger firms than by smaller ones; over half of the compa nies employing 25,000 persons or more had used them. And, as mentioned, about a third of all eligible employees accepted these offers, although about 1 in 4 plans had acceptance rates of at least 75 percent. Employees’ views of such plans are difficult to inter pret. The aarp report makes no mention of erip ’s as a welcome offer to many older workers who may view re tirement quite positively. Yet, substantial numbers of workers welcome the opportunity to retire earlier than “normal.” In a survey of workers age 40 and older, con ducted for aarp by the Gallup Organization, 41 percent of all workers surveyed responded that they would be likely to accept incentive offers for early retirement.30 Af firmative responses were most common among workers with high levels of income and education. Mutschler and others studied persons who had retired from an unidentified Fortune 500 company with and without special incentives. They found that employees clearly responded to the economic incentives of the erip ’s under study— the better the retirement package, the more likely workers were to accept it.31 Also, there was no evidence that those accepting the offer had suffered finan cially as a result (which would have suggested coercion); however, the authors did express some concern over the long-term effects of inflation on the value of retirees’ pen sions. Other than this study, little is known about the 18FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis conditions under which workers accept outcomes of their decisions. erip ’s and the The hazy distinction between voluntary and involun tary retirement makes analysis of this labor force issue difficult. The voluntary nature of erip ’s may not even be a static concept. An individual who had positive views about accepting an “early out” at the time of the offer may have a very negative view after the fact, or vice versa. While it certainly is possible to better quantify the use of erip ’s than has been done so far, to evaluate the effect of these programs on workers’ financial and nonfinancial well-being would be far more complicated. In summary, the incentives in Social Security and pri vate pension policies often operate in opposite directions. It is unclear exactly what long-term effect Social Security reforms will have on the work activity of older persons; however, it is clear that private pensions have not fol lowed Social Security’s lead in encouraging later retire ment. While pension policies that allow retirement well before age 65 are undoubtedly attractive to many older workers, those who might prefer to continue to work part time often do not or cannot. Some reasons for this are discussed in the next section. The market for part-time jobs Many observers have noted that older workers often are faced with a choice between continuing full time in a long-held job or withdrawing from the labor force; the majority reject part-time employment, which usually pays relatively low wages and provides very few benefits. Whether part-time work by older persons will become more common in the future depends on many diverse factors, including pension and Social Security regulations that determine levels of nonwage income and place re strictions on employment; the characteristics of part-time jobs; and the preference for leisure over work at older ages. Relatively few older persons choose to work after first receiving retirement benefits, and those who do usually have very low levels of non wage retirement income.32 However, many older men still do not seek employment despite very small pension benefit levels.33 According to data from the Social Security New Beneficiary Survey, fewer than 1 in 4 persons was employed at all 18 months to 2 years after first receiving retired-worker benefits.34 And, among those who were not in the labor force, 95 percent responded in the Current Population Survey that they “do not want a job now, either full or part time.”35 Does this low level of work activity beyond retirement mean that older persons simply do not want to work, or is it a reflection of poor employment options? While the preference for leisure over work is very strong for many older persons, it is also possible that many say they do not want to work because they see only very limited choices. As discussed previously, substantial institutional barri ers— especially the Social Security earnings test—provide strong disincentives to full-time work at later ages. And pension provisions often make continued work for one’s employer unjustifiable. Older workers, then, tend to be funneled into the part-time job market, where options are frequently limited to low-paid employment. The solution, many argue, would be to expand opportunities for parttime work to include jobs that are well paid and provide non wage benefits.36 There is little doubt that part-time work done by older workers is relatively low paid. Jondrow and others, cited earlier, have found that hourly wages tend to decline about 30 to 40 percent when weekly hours are reduced from 35 to 20.37 However, low pay is not necessarily evi dence of age discrimination. In fact, the same researchers found that “ . . . the scarcity of well-paid part-time jobs is not a matter of discrimination against older workers; such jobs are scarce throughout the economy.”38 A primary reason for the scarcity of well-paying parttime jobs is the high cost of such schedules to employers. Training costs, for example, are virtually identical for fulland part-time workers, as are many administrative costs. A short workweek raises the hourly costs to employers for such expenses. In contrast, jobs that generally require little training do not significantly raise the costs to em ployers offering part-time schedules, especially if the benefit packages are more limited than those given full time workers. These jobs, by their nature, are usually low skilled and provide low pay. Whether such a restrictive market for part-time jobs for older persons is the only possible scenario is still open to question. Hilda Kahne, in her book Reconceiving PartTime Work, distinguishes between “New Concept” parttime work and “Old Concept” work.39 The latter was described above— work at very low pay rates, often in low-wage industries, and with few benefits. The former, Kahne envisions, would be work done in the full range of industries and occupations and would generally provide prorated full-time wages and benefits. Kahne presents a convincing argument for the potential interest in such employment from the older workers’ point of view; how ever, she does less to explain how such jobs make sense for employers, particularly those not facing labor short ages. For now, at least, it appears that such “New Concept” job market offers lag behind workers’ desire for them. As the younger population declines and the growth rate in the female labor force slows,40 some service-sector em ployers are beginning to target jobs to older workers. Such employment will attract a narrow range of elderly persons, however, as it is typically part-time work with few fringe benefits. While widespread worker shortages may occur in the future,41 their effect on employment opportunities for older workers is difficult to predict, par ticularly in the context of today’s institutional structures that strongly favor early retirement. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Age discrimination When any group’s labor market experiences are found to be inferior to another’s, the issue of discrimination is a subject for discussion. However, discrimination is one of the most difficult labor market issues to identify and quantify. This is because it is difficult to discern whether between-group differences in earnings or unemployment, for example, are the result of discrimination or of real differences in productivity or labor market goals. These measurement problems have limited the amount of re search conducted on age discrimination in employment. It would appear, however, that discrimination does take place in the job market— that hiring, training, and pro motion decisions involving older persons are not entirely age, sex, and race neutral. Regarding the earnings of older workers, Richard A. Wanner and Lynn McDonald, using National Longitudi nal Survey (nls ) data for mature men, found that as the men in the sample aged between 1966 and 1976 (and gained tenure and experience), they had a substantial de cline (in real terms) in earnings.42 This occurred during a period of sizable increases in earnings among all workers. The poor earnings performance among older workers was determined to be unrelated to any decrease that might have been associated with job changing. The authors identified three theoretical explanations for this. First, human capital theorists in economics would attribute the lower earnings of older workers pri marily to lower productivity, perhaps related to skill obsolescence and employers’ reluctance to invest in the upgrading of those skills. This would seem reasonable, given the relatively short payoff time for such an invest ment. Second, equity theorists in sociology would argue that wages reflect not only productivity but also the work ers’ need for income and that declining wages at older ages describe a legitimate lifetime earnings profile. Work ers’ preferences for increased leisure (largely associated with declining financial need) may partly explain the earnings profiles of older workers found by Wanner and McDonald. Although their methodology accounts for re ductions in the number of weeks worked, by their own admission, they may have missed some of the hours effect, such as not incorporating older workers’ lower propensity to accept overtime work. The researchers prefer a third explanation: employers assume that older workers will accept lower levels of sal ary increases, or fewer of them, because older persons’ ability to find comparable alternative employment is quite low. Certainly, human capital theorists would agree that workers accumulate extensive firm-specific human capital for which a new employer would be unwilling to compen sate them. Stephen R. McConnell, in his assessment of age discrimination, also highlights this decline in leverage for older workers brought about by their high cost of job switching.43 19 MONTHLY LABOR REVIEW April 1989 • Barriers to Employment o f Older Workers Using the National Longitudinal survey to examine the wage decline for workers who were forced to look for a new job, David Shapiro and Stephen H. Sandell found little evidence of discrimination. In fact, they determined that about 90 percent of any loss in earnings in workers’ new jobs reflected a loss of their firm-specific human capi tal.44 While this is a real and important earnings loss for many workers, it cannot be said that such declines in earnings are the result of unfair practices by employers, who would not be expected to pay for skills, knowledge, or experience that are not transferable to a new job. It is interesting to examine workers’ own perceptions of discrimination. In the previously mentioned survey con ducted by the Gallup Organization in 1985, a sample of workers age 40 and older was asked whether they had experienced age discrimination.45 Only about 6 percent answered in the affirmative, mostly with the response that they had been denied a promotion or a chance for ad vancement because of their age. The perception of age discrimination increased with age; 4 percent of workers in their forties believed they had experienced age discrimina tion, compared with 10 percent of those age 63 and over. It is not clear whether the greater affirmative response for the older group represents increased discrimination with age (although it seems reasonable that this would be the case) or the greater number of years over which they could have experienced discrimination. A shortcoming of this survey, and most others, is that respondents are em ployed persons only; thus, those who may be unemployed or out of the labor force who have been victims of age discrimination are not included. These may be the groups of older persons who have been most affected by discrimi natory employment practices. Further insight into age bias comes from employers’ per ceptions of older workers. In a 1985 study, Benson Rosen and Thomas H. Jerdee found that many managers exhibited age discrimination in their personnel decisions.46 They asked 6,000 readers of Harvard Business Review (most of whom were in management positions) to make management decisions in seven hypothetical cases. In half of the respon dents’ questionnaires, the worker in question was a younger person; in the other half, an older one. Except for the age of the workers, the scenarios were identical. In the almost 1,600 returned survey forms, respondents consistently made different hiring, promotion, discipline, and training decisions based on the stated age of the worker in question. Yet, in a final set of questions, respondents indicated a very high level of support for nondiscriminatory business prac tices. Interestingly, respondents age 50 and over were consistently more supportive of the older workers than were younger respondents, from which the authors concluded that an older worker’s best prospect for fair treatment ap peared to be working for an older supervisor. The above research and other similar work suggest that age discrimination exists regarding older workers’ employment and advancement opportunities. Neverthe less, relatively few older workers state that they have been the victims of age discrimination. Few older workers search for a job, whereby they would be most exposed to discrimination. Also, experience on the job may provide many older workers with the skills and abilities that pre vent them from being marginal employees. In addition, the promotion expectations (or desires) of some workers may decline with age, often because of the desire to stay in a “comfort zone” toward the end of a career. W h i l e r e c e n t Federal policy has been directed toward extending worklives, substantial disincentives to work at older ages still exist. Changes in Social Security policies designed to increase work activity will not substantially alter the structure of the Social Security system and, as a result, may have only minor impacts on the labor force behavior of older persons. In addition, any changes that do occur may be overshadowed by decreases in work ac tivity resulting from greatly liberalized pension plan provisions. For those persons who wish to continue working at older ages, a scarcity of well-paying, part-time jobs may limit work activity. And, for some workers, age discrimi nation may provide barriers to employment. As the number of young workers continues to decline, however, it is possible that employers will begin to provide more attractive work options for older persons. □ -FOOTNOTES 'The concept of retirement is more complex for women. That is be cause women in their fifties and sixties today often had very little work experience throughout their lives. As a result, they often do not choose a retirement age based on their own work history or pension resources. Labor force participation rates for women ages 65 and over have fol lowed the same trend as those for men— they have declined from a high of about 11 percent in the early 1960’s to about 7 percent today. Partici pation rates for women ages 55 to 64 have changed little over the last two decades. “John A. Svahn and Mary Ross, “Social Security Amendments of 1983: Legislative History and Summary of Provisions,” Social Security Digitized for 20FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Bulletin, July 1983, pp. 3-4 8 . See Older Americans in the Workforce: Challenges and Situations (Washington, Bureau of National Affairs, Inc., 1987). Also see appendix: Text of the Age Discrimination in Em ployment Act of 1967, as amended. The 1986 amendments removed the upper limit (which had been age 70) in the law’s proscription against age discrimination. 3Susan Grad, Income o f the Population 55 and Over, 1986 (Social Security Administration, 1988), Publication No. 13-11871, pp. 1, 87. 4Svahn and Ross, “Social Security Amendments,” pp. 3-4 8 . 5For a detailed explanation of how benefits are derived, see the Social Security Handbook, 1988 (Social Security Administration, 1988), Publi cation No. 05-10135, ch. 7; see also Social Security Bulletin, Annual Statistical Supplement, 1987 (Social Security Administration, 1987). 6Gary S. Fields and Olivia S. Mitchell, “Restructuring Social Secu rity: How Will Retirement Ages Respond?” in Stephen H. Sandell, ed., The Problem Isn't Age (New York, Praeger Publishers, 1987), pp. 192-205. 7See, for example, Arden Hall and Terry R. Johnson, “The Determi nants of Planned Retirement Age,” Industrial and Labor Relations Review, January 1980, pp. 241-54; and Richard V. Burkhauser, “The Early Acceptance of Social Security: An Asset Maximization Ap proach,” Industrial and Labor Relations Review, July 1980, pp. 484-92. 8In 1982, workers were subject to an earnings test until age 72. Cur rently, benefits are not reduced for earnings after age 70. See Howard M. lams, “Jobs of Persons Working After Receiving Retired-Worker Bene fits,” Social Security Bulletin, November 1987, pp. 4-1 9 . ’Gary Burtless and Robert A. Moffitt, “The Joint Choice of Retire ment Age and Postretirement Hours of Work,” Journal o f Labor Economics, April 1985, pp. 209-36. 10Alan S. Blinder, Roger H. Gordon, and Donald E. Wise, “Reconsid ering the Work Disincentive Effects of Social Security,” National Tax Journal, December 1980, pp. 431-42. n Svahn and Ross, “Social Security Amendments,” pp. 3-48. 12Alan L. Gustman and Thomas L. Steinmeier, “The 1983 Social Security Reforms and Labor Supply Adjustments of Older Individuals in the Long Run,” Journal o f Labor Economics, April 1985, pp. 237-53. 13Fields and Mitchell, “Restructuring,” pp. 192-205. 14John R. Woods, “Retirement Age Women and Pensions: Findings From the New Beneficiary Survey,” Social Security Bulletin, December 1988, pp. 5-16. 15See Scott H. Beck, “Determinants of Labor Force Activity Among Retired Men,” Research on Aging, June 1985, pp. 251-80. 16Donald Bell and William Marclay, “Trends in retirement eligibility and pension benefits, 1974-83,” Monthly Labor Review, April 1987, pp. 18-25. 11Ibid., p. 19. 18Gary S. Fields and Olivia S. Mitchell, Retirement, Pensions, and Social Security (Cambridge, m a , The m i t Press, 1984), pp. 33-51. '’Laurence J. Kotlikoff and David A. Wise, The Incentive Effects o f Private Pension Plans (Cambridge, m a , National Bureau of Economic Research, Inc., 1984), Working Paper Series 1510. 20Laurence J. Kotlikoff and David A. Wise, Employee Retirement and a Firm's Pension Plan (Cambridge, MA, National Bureau of Eco nomic Research, Inc., 1987), Working Paper Series, 2323. 2'Patricia M. Moore, “Age-Related Changes in Retirement Policies and Plans,” Compensation and Benefits Management, Spring 1988, pp. 217-20. 22Employee Benefits in Medium and Large Firms, 1986, Bulletin 2281 (Bureau of Labor Statistics, 1987), pp. 53-76. 23Donald Bell and Diane Hill, “How Social Security Payments Affect Private Pensions,” Monthly Labor Review, May 1984, pp. 15-20. 24Bell and Marclay, “Trends in retirement eligibility,” p. 24. 26Phyllis H. Mutschler, James H. Schultz, and Thomas D. Leav itt, What Price Retirement?: A Study o f Early Retirement Incentive Programs (Washington, American Association of Retired Persons, 1984). 27Elizabeth L. Meier, Early Retirement Incentive Programs: Trends and Implications (Washington, American Association of Retired Per sons, Andrus Foundation, 1984). 28Hewitt Associates, Plan Design and Experience in Early Retirement Windows and Other Voluntary Separation Plans (Lincolnshire, IL, Hew itt Associates, 1986). 29Raymond C. Fay, The a d e a and Early Retirement Incentives, (Washington, Law Offices of Bell, Boyd, and Lloyd, undated). 30American Association of Retired Persons, Work and R etire ment: Employees Over 40 and Their Views (Washington, American Association of Retired Persons, 1986). ■"Mutschler and others, “What Price Retirement?” 32See Stephen R. McConnell and others, Alternative Work Options for Older Workers: A Feasibility Study (Los Angeles, CA, The Ethel Andrus Gerontology Center, 1980). 33Beck, “Determinants of Labor Force Activity,” p.276. 34Howard M. lams, “Jobs of Persons Working After Receiving Re tired-Worker Benefits,” Social Security Bulletin, November 1987, pp. 4-19. 35The Current Population Survey ( c p s ) is a monthly survey of about 55,000 households conducted by the Bureau of the Census for the Bu reau of Labor Statistics. 36See McConnell and others, Alternative Work Options-, also see Hilda Kahne, Reconceiving Part-Time Work: New Perspectives for Older Workers and Women (Totowa, n j , Rowman & Allanheld, 1985). 37Jim Jondrow, Frank Brechling, and Alan Marcus, “Older Workers in the Market for Part-Time Employment,” in Steven H. Sandell, ed., The Problem Isn't Age (New York, Praeger Publishers, 1987), pp. 84-99. 38Ibid, p. 96. 39Kahne, Reconceiving Part-Time Work. 40See Howard N Fullerton, Jr., “Labor force projections: 1986 to 2000,” Monthly Labor Review, September 1987, pp. 19-29. 4'See, for example, Lawrence Olson, Christopher Caton, and Martin Duffy, The Elderly and the Future Economy (Lexington, m a , Lexington Books, 1981). 42The National Longitudinal Survey of Labor Market Experience ( n l s ), a survey of several cohorts conducted by the Ohio State Univer sity, was specifically designed to measure many of the labor market problems experienced by older workers. The mature men’s cohort was first interviewed in 1966, when respondents were ages 45 to 59. See Richard A. Wanner and Lynn McDonald, “Ageism in the Labor Mar ket: Estimating Earnings Discrimination Against Older Workers,” Journal o f Gerontology, Vol. 38, No. 6, pp. 738-44. 43Stephen R. McConnell, “Age Discrimination in Employment,” in Herbert S. Parnes, ed., Policy Issues in Work and Retirement (Kalama zoo, m i , W. E. Upjohn Institute for Employment Research, 1983). 44David Shapiro and Steven H. Sandell, “Age Discrimination in Wages and Displaced Older Men,” Southern Economic Journal, July 1985, pp. 90-102. 45American Association of Retired Persons, Work and Retirement. 25James H. Stock and David A. Wise, The Pension Inducement to Retire: An Option Value Analysis (Cambridge, m a , National Bureau of Economic Research, Inc., 1988), Working Paper Series, 2660. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 46Benson Rosen and Thomas H. Jerdee, Older Employees: New Roles for Valued Resources (Homewood, i l , Dow Jones-Irwin, 1985). 21 Unemployment insurance in the United States and Europe, 1973-83 In general, comparisons show rising costs, changes in eligibility and benefits, possible disincentives to work, and low replacement ratios for the unemployed; some industrial countries have altered their unemployment insurance provisions with these problems in mind B e a t r ic e G. R eubens The unemployment insurance systems of Western Euro pean countries have been subjected to recent strong pressures because of higher unemployment rates and pro longed spells of unemployment. There has been concern that traditional unemployment insurance programs may not be able to cope with the current composition of unem ployment. This has led to the search for new approaches in some countries and efforts to curtail expenditures in others. This article compares the unemployment insurance programs of the United States and five western European countries—Austria, France, Germany, Great Britain, and Sweden. It discusses, among other subjects, the cost of the program, financing, the number of persons receiving bene fits, benefit levels, and replacement ratios. In addition, the article outlines the steps taken by the countries to curtail rising unemployment insurance costs, reports the diverse views on the effects of unemployment insurance benefits on work incentives, and raises some questions for which addi tional research is needed. This study covers the 1973-83 period; two Organization for Economic Cooperation and Development ( o e c d ) studies for other years are briefly dis cussed for comparison purposes. Beatrice G. Reubens, formerly a senior research associate at the Con servation of Human Resources, Columbia University, is an international economic consultant. 22 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Background Unemployment rates in most Western European coun tries were considerably lower than those in the United States through the 1950’s and 1960’s, rising with the onset of the oil crisis in 1973, dropping slightly for a few years, then increasing sharply in the early 1980’s, and remaining at high levels. While the U.S. unemployment rate has dropped since 1983, few European countries have shown much improvement. Along with the rise in unemploy ment rates, the average duration of unemployment also increased, although less in the United States than in most Western European countries. European employment has grown slowly since 1975, in contrast with substantial U.S. employment growth. The composition of unemployment also has changed, especially when compared with the pre-World War II period when male heads of household constituted the bulk of the labor force and were the focus of social concern. Structural unemployment, with its adverse effects on older workers, has reached new proportions in Europe, often overshadowing cyclical and frictional unemploy ment. Professional, white-collar, and skilled unemploy ment also has increased. Furthermore, unemployment has risen for young people, women, and a markedly enlarged minority population— groups given scant attention when unemployment insurance programs were first designed.1 Growth of unemployment insurance costs Unemployment insurance costs rose more sharply in the 1970’s than in the 1960’s. An o e c d study of unem ployment insurance costs in seven countries—the United States, Japan, Germany, Canada, France, Italy, and the United Kingdom— found that, on average, expenditures (in 1975 prices) almost doubled during the 1960’s and more than tripled in the 1970’s. When the timespan was divided into four periods (1960-64; 1965-69; 1970-74; and 1975-79), France, Germany, the United Kingdom, and the United States showed more periods with increases than with decreases in the average annual growth of un employment insurance expenditures. Three of these four countries experienced their highest rate of increase be tween 1970 and 1975; only the United Kingdom had its greatest rise between 1965 and 1970.2 Another o e c d analy sis for the 1960-75 period showed an average increase of 180 percent in unemployment insurance expenditures (in constant prices) in the same seven countries.3 The 180-percent increase found in the o e c d study for 1960-75 was exceeded in the six countries studied in this article during the period 1973-82. Four of the five Euro pean countries experienced greater cost increases (in 1973 prices) than did the United States, and all exceeded the United States in 1982 prices. Measured by the increase in expenditures per recipient (in 1973 prices), Austria led, followed by Germany, Sweden, and the United States. Only Great Britain spent less in 1982 per recipient than it had in 1973 (in 1973 prices). The relatively low position of the United States in regard to expenditures reflects its more favorable unemployment record, but the per beneficiary amounts also reflect a less generous approach than in four of five European countries. (See table 1.) By 1982, unemployment insurance expenditures as a percentage of the gross national product, while modest, were at least 2 to 3 times the 1973 level in four of the six countries; the rise was even greater in France and Ger many. (See table 2.) In one o e c d seven-country study, it was found that the average rise in unemployment insur ance expenditures as a share of gross domestic product (in 1975 prices) was greater in the 1970’s than in the 1960’s.4 In four of the six countries, unemployment insurance as a percentage of total expenditures on all public meas ures related to employment and training, including unem ployment benefits and allowances, rose considerably from 1973 to 1982. (See table 2.) In the United States, “pas sive” unemployment benefits dominate “active” training and employment programs, while the reverse is true of Sweden and Great Britain. Sweden has emphasized ac tive labor market programs that foster the adaptability and mobility of the labor force and improve the position of disadvantaged groups, areas, and industries, rather than unemployment insurance and other passive income replacement.5 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Table 1. Indexes of change in expenditures for unemployment insurance benefits over the 1973-82 period, six countries [1973=100] ______________________________________ 1982 prices 1973 prices (constant) Country Per recipient Total Total Austria................................... France................................... Germany............................... 681 2,567 1,292 401 968 861 343 — 143 Great Britain.......................... Sweden1................................. United States2........................ 852 786 543 245 333 278 51 3121 104 'Data are for 1974-83. includes programs for special groups (railroad workers, for example). Data for the United States have been computed according to the definitions of unem ployment insurance programs adopted for the six-country study by the International Institute of Management. Results may not fully agree with data published on unemployment compensation in the United States. 3Calculated from annual average daily benefits. Note : Dash indicates data not available. Gert Bruche, The Financing of Labour Market Policy in Austria (Berlin, International Institute of Management, 1984), tables 1 -3 ; Gert Bruche, The Financing of Labour Market Policy in France (Berlin, International Institute of Management, 1984), tables 1-2; Gert Bruche and Bernd Reissert, The Fi nancing of Labour Market Policy in the Federal Republic of Germany (Berlin, International Institute of Management, 1985), tables 1,2, and 5; Bernd Reissert, The Financing of Labour Market Policy in Great Britain (Berlin, International Institute of Management, 1985), tables 2 -5 , and 16; Gunther Schmid, The Financing of Labour Market Policy in Sweden (Berlin, International Institute of Management, 1984), tables 1,3, and 4; Eskil Wadensjo, The Financial Effects of Unemployment and Labour Market Policy Programs for Public Authorities in Sweden (Berlin, International Institute of Management, 1985), table A6; Bernd Reissert, The Financing of Labour Market Policy in the usa (Berlin, International Institute of Management, 1985), tables 1, 5, and 7; and the author's own calculations. Source : Unemployment insurance expenditures (in 1975 prices) generally increased as a percentage of total expenditures on income maintenance measures, according to one o e c d seven-country study. However, the share of expenditures remained lower in Western Europe, mainly because of the commitment to a more complex set of additional income maintenance programs with higher benefits than are found in North America. Thus, Canada spent between 8.43 and 17.35 percent of its income maintenance budget on unemployment insurance benefits during the four 5year periods of 1960-80, followed by the United States, with 4.81 to 9.92 percent. France, Germany, and the United Kingdom spent under 5 percent, and Italy, under 2 percent.6 Why costs rose. Expenditures on unemployment insur ance benefits change because of changes in (1) the levels, composition, and duration of unemployment; (2) the size of the labor force and the share covered by unemployment insurance; (3) coverage and eligibility rules and benefits; and (4) family circumstances and previous earnings of unemployed persons. The effects of these factors vary over time and by country. The o e c d analysis of seven large countries for the pe riod 1960-75 established that improvements in real benefit levels were the most important factor contributing to the increase in unemployment insurance expenditures. The study noted that changes in the numbers covered by unemployment insurance (growth of population, labor 23 MONTHLY LABOR REVIEW April 1989 • Unemployment Insurance in the U.S. and Abroad force, and unemployment) also strongly affected expendi tures, but found no influence from changes in eligibility for benefits.7 Another o e c d study of the same countries (France, Germany, the United Kingdom, the United States, Can ada, Italy, and Japan) for the period 1960 to 1980 found that benefits grew moderately and in line with wages in the 1960’s, except in Italy. After the oil crisis of 1973, the growth of benefits accelerated, exceeding that of wages. The growth slowed at the end of the 1970’s, when benefits dropped in real value in five of the countries, but not in Japan and France. The o e c d study also found that the ratio of unemployment insurance recipients to total un employed, after dropping slightly in the latter half of the 1960’s, except in Japan, rose sharply in the first half of the 1970’s, except in Germany, and then dropped again in the late 1970’s to early 1960’s levels or below. The following general points also emerged regarding unemployment insurance expenditures trends: • The behavior of individual factors has not been con stant over the period, and the contribution of each to unemployment insurance expenditures has changed. • Certain factors, such as the number of beneficiaries, are more affected than others by changes in the level of economic activity. Important lags in effect also occur. • Cyclical influences and long-term trends tend to inter act so that the influence of the underlying factors changes over time. • The slowdown in annual growth rates of unemploy ment insurance expenditures noticed in 1979-80 has been reversed by the rise in unemployment since 1981. Table 2. Expenditures for unemployment insurance benefits as a percentage of gross national product and of unemployment, employment, and other labor market programs, six countries, 1973-82 Unemployment, insurance benefits as a percentage o f— Country 1973 1982 1973 1975 1980 1982 Austria.................... France.................... Germany1 ............... .15 .20 .15 .43 1.40 1.13 37.0 18.6 20.4 38.8 34.2 43.0 39.1 40.8 36.8 43.4 41.4 47.0 Great Britain........... Sweden6.................. United States8......... .25 7.30 .35 .56 8.90 .81 234.1 715.1 42.1 336.7 13.8 70.2 430.9 13.8 55.2 521.7 24.0 69.6 'Excludes special Federal Government labor market programs and State and local measures. 2For budget year 1974-75. 3For budget year 1975-76. 4For budget year 1980 - 81. 5For budget year 1982-83. 6Excludes regional development and industrial policy programs. 7Data are for 1974. 8Data are for 1983. includes programs for special groups (railroad workers, for example). Data for the United States have been computed according to the definitions of unem ployment insurance programs adopted for the six-country study by the International Institute of Management. Results may not fully agree with data produced on unemployment compensation in the United States. Note : For sources, see table 1. 24 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis But the tightening of eligibility and payment criteria and slow or negative growth in the real value of benefits are containing expenditures. • Besides the unemployment rate, discretionary policy changes are of the greatest importance in explaining expenditure trends.8 Studies of individual countries, especially Germany, add to the picture, but do not contradict the above general findings.9 Policy responses In the first half of the 1980’s, many European countries and American States contained the growth in unemploy ment insurance costs through tightened eligibility criteria, little or negative growth in the amount and duration of benefits, and restructured programs to limit the unem ployment insurance portion of total income replacement programs for the unemployed.10 These actions were tied to the efforts of nations to cover rising unemployment insurance costs without excessive demands on financing sources. The main methods of augmenting the funds available to unemployment insurance systems are: increased contri butions from employers and workers; special assessments; use of income from reserve funds; drawing down reserve funds; borrowing; and an increased share of costs shifted to the government. The five European countries studied resorted to increased contribution rates. (See table 3.) Nevertheless, after 1973, the total intake from employer and employee contributions formed a declining share of unemployment insurance expenditures in Austria and Germany. France had a fluctuating share, while Sweden balanced a relative decrease in the share of direct em ployer contributions with a large rise in the share of employer indirect contributions. No calculation was made for Great Britain or the United States.11 Further increases in payroll taxes to support unemployment insurance would be unpopular in most European countries and are feared as an impediment to employment growth. When deficits continue despite these measures, govern ments provide subsidies, required by law in most cases. Governments also assume certain costs, such as all or part of administrative costs or continuation of contributions to old age, health, and other insurance on behalf of unem ployment insurance recipients. From 1973 to 1982, the government’s share of expenditures was highest in Swe den and lowest in Austria; the United States ranked fourth. (See table 4.) The government’s share decreased in Austria over the 1973-82 period, increased steadily in the United States, and fluctuated in the other countries.12 In most countries, government funding offers only lim ited relief. Restraints on expenditures appear to have been the main recourse. In the United States, the Federal Trea sury loaned $11.8 billion to State unemployment insur- Table 3. Rates of contribution to unemployment insurance by employers and employees, six countries, 1973-84 Employer (Percent of eligible payroll) Country Employee (Percent of eligible earnings) 1973 1975 1979 1984 1973 1975 1979 1984 Austria’ ........ France2 ....... Germany’ .... 1.00 .56 .85 1.00 1.92 1.00 1.05 2.76 1.50 2.20 4.08 2.30 1.00 .14 .85 1.00 .48 1.00 1.05 0.84 1.50 2.20 1.72 2.30 Great Britain3 Sweden........ United States _ 8.50 10.00 10.45 4.40 4.40 41.3 _ — (6) 5.50 6.50 9.00 (5) (7) (5) (7) (5) (7) (5) <7) (6) (6) (6) 'Contributions are for active labor market programs, as well as for unemploy ment insurance and unemployment allowance programs. 2Rates as of the end of the year. includes contributions for all social insurance programs (old age, health, disability, and maternity, for example). 4lncludes contributions for unemployment insurance and allowances. Data are for 1974 to 1982. From 1973 forward, data include tax for labor market training, previously under a separate payroll tax. 5Rates vary among funds. 6Tax varies among States. 7Most States do not tax employees. Note : Dash indicates data not available. Source : See table 1. ance trust funds following the 1981-82 recession. According to a recent General Accounting Office report, pressure by the Federal Government for repayment of the loans led to a tightening of eligibility requirements and/or a cutting of benefits in 44 States. Since 1976, the report declares, no more than two States in any given year have had sufficient funds to cope with a recession without seek ing Federal assistance. The report expressed concern that, in the event of another recession, State unemployment insurance systems would lack the financial resources to “stabilize the economy and mitigate the effects of income loss suffered by the unemployed.” These and other issues pertaining to the goals and functions of unemployment insurance are under discussion in many industrialized na tions and their international organizations. Because of sluggish employment growth, some Euro pean nations have extended the duration of unemploy ment benefits and instituted early retirement pensions for older workers, despite the increased costs. In addition, European countries have initiated programs that utilize unemployment insurance benefit monies to support em ployment-related activities beyond the job search. There are three major innovative uses of unemployment funds: (1) to compensate individuals working in regular jobs but on organized and approved short-time work, as in West Germany; (2) to permit fully unemployed persons al ready receiving unemployment benefits to continue to do so while undertaking an activity (such as training or edu cation) to improve their labor market position, or even while establishing a business as an entrepreneur; and (3) to support particular programs, such as early retirement, public training courses or allowances, private firm on-thejob training, or temporary employment, as well as give https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis employment subsidies to employers who hire unemploy ment benefit recipients. The rationale for funding such innovations is the presumed reduction of compensable unemployment that follows. How many receive benefits? The proportion of the labor force covered by unem ployment insurance systems has increased steadily since World War II.13 However, the percentage of unemployed persons receiving unemployment benefits is smaller than the share of the labor force covered by unemployment insurance programs. This occurs, in part, because those most likely to become unemployed have lower rates of unemployment insurance coverage and also because cov ered workers either fail to meet eligibility requirements or exhaust their benefits. The proportion of the unemployed receiving unemployment insurance benefits rose in many countries from 1973 to 1975, and then declined. In Aus tria, Germany, and Great Britain, the proportion of the labor force covered by unemployment insurance was lower in 1983 than in 1973, reflecting not only the further rise in unemployment in the 1980’s, but also the tighten ing of eligibility requirem ents. (See table 5.) This downward trend, not fully revealed by the 1983 data, contrasts with the 1973-75 period when the proportion of unemployed workers receiving benefits rose because many Table 4. Government share of unemployment insurance expenditures over the 1973-82 period, six countries [In percent] Country 1973 1975 1979 1980 1982 Austria’ .................... France..................... Germany’ ................ 8.4 29.1 0 6.1 24.8 40.8 26.6 39.6 0 6.5 25.8 8.5 4.9 34.9 21.0 Great Britain4 ........... Sweden.................... United States6.......... 14.0 73.5 7.0 15.0 539.8 15.0 18.0 550.9 11.0 18.0 549.4 17.0 13.0 540.4 18.0 ’ Expenditures are for active labor market programs as well as unemployment benefits and unemployment allowances. 2Data are for 1977. 3Data for 1979 and after are not entirely comparable to those for earlier years. 4lncludes expenditures for all social insurance programs (old age, health, disability, maternity, for example). Unemployment insurance accounted for 4 to 10 percent of all expenditures during the 1973-84 period. 5From 1975 forward, excludes part of government subsidy drawn from tax on employers imposed in 1974. includes advances from general fund for unemployment insurance trust fund expenditures on special groups (railroad workers, for example), and supplemen tal programs. Sources : Robert A. Hart, Unemployment Insurance and the Firm's Employ ment Strategy: A European and United States Comparison (Berlin, International Institute of Management, 1982), table 1; Axel Mittelstadt, Unemployment Bene fits and Related Payments in Seven Major Countries (Paris, oecd Economic Outlook, Occasional Studies, July 1975), table 2; Saul J. Blaustein and Isabel Craig, An International Review of Unemployment Insurance Schemes (Kalama zoo, mi, The W. E. Upjohn Institute for Employment, 1977), table 9; Gert Bruche, The Financing of Labour Market Policy in Austria, tables 4, 7; Gert Bruche, The Financing of Labour Market Policy in France, tables 4, 5; Gert Bruche, French Unemployment Insurance (Berlin, International Institute of Management, 1982), table 1; Gert Bruche and Bernd Reissert, The Financing of Labour Market Pol icy in the Federal Republic of Germany, tables 5, 6, 12; Gunther Schmid, The Financing of Labour Market Policy in Sweden, pp. 20-23, table 7; Eskil Wadensjo, The Financial Effect of Unemployment and Labour Market Policy Programs for Public Authorities in Sweden, table A2; Bernd Reissert, The Fi nancing of Labour Market Policy in the usa , table 3; and the author's own calculations. 25 MONTHLY LABOR REVIEW April 1989 • Unemployment Insurance in the U.S. and Abroad long-term employed persons became unemployed and be cause of policy changes in unemployment insurance, including extended coverage, new programs, and easing of eligibility rules. Whether the reduced share of unemployed workers re ceiving unemployment insurance benefits represents a deterioration in their economic position depends on the available alternative sources of income. Most Western Eu ropean countries have a national unemployment allow ance program which makes payments to unemployed workers who have exhausted their unemployment insur ance benefits or who do not qualify for such benefits. Usually, means-tested unemployment allowances may be paid for a stipulated period, or indefinitely, if employment is not obtained. In addition, the safety net includes a local government social welfare payment for which some un employed persons qualify. In Britain, between 1973 and 1983, the balance shifted from unemployment insurance to supplementary bene fits— the national, means-tested program for all low income persons. During the same period, the proportion of the unemployed who received neither unemployment insurance nor supplementary benefits shrank from almost 25 percent to 12.7 percent.14 The decline in the proportion of British unemployed workers without benefits from any national income re placement program is a sign of progress. Also, the shift from unemployment insurance to supplementary benefits is not necessarily an adverse condition. A 1978 study of a cohort of unemployed men found that family income re placement rates of men receiving supplementary benefits only were very close to those of men receiving unemploy ment insurance only.15 However, earned unemployment insurance benefits may yield higher psychic benefits than means-tested supplementary benefits. Germany showed a less favorable trend, although the proportion of the unemployed on unemployment insurance was higher than in Britain. From 1973 to 1983, the propor tion of the unemployed receiving unemployment allow ances climbed from 8 to 21 percent. Unlike the British case, the maximum German unemployment allowance payment is set at 10 percent below unemployment insurance bene fits. Many workers on unemployment allowances receive less than the statutory maximum because other resources, such as a spouse’s earnings, reduce the allowance. In April 1983, about one-third of Germany’s unemployment allow ance recipients were on reduced payments. Throughout the decade, about one-third of registered German unemployed workers received neither unemploy ment insurance nor unemployment allowance benefits.16 The number of unemployed recipients of public assistance grew dramatically in industrial cities in response to the restrictions placed on both unemployment insurance and unemployment allowances. The burden on localities in aiding the unemployed rose markedly after 1978.17 A stable percentage of unemployed workers without income provision implies a worse absolute position in the face of rising unemployment totals. Even in Britain, the absolute number of unemployed without income provi- Table 5. Number receiving unemployment insurance benefits and percent of unemployed receiving unemployment benefits, six countries, 1973-1983 (monthly average) (Numbers in thousands) Persons receiving benefits by country 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 — — — — 35 65.7 — — 67 63.5 75 59.2 — — — — — — — — — — 698 55 926 51 1,014 45 1,013 33.9 938 31.2 Austria: Number....................... Percent....................... 34 81.3 — — 35 68.5 — — France: Number....................... Percent....................... 128 32.4 152 30.5 225 35.4 — — — — — — Germany: Number....................... Percent....................... 154 56 352 60 707 66 615 58 557 54 516 55 448 454 51 51 Great Britain:1 Number....................... Percent....................... 210 39.2 292 44.6 553 49.0 — — 589 41.8 517 40.6 494 40.6 984 49.5 Sweden:2 ....................... Number....................... Percent....................... 8,625 — 41 8,718 50 8,128 47 8,161 42 10,597 45 11,036 48 10,666 47 14,485 52 20,018 56 23,594 60 2,558 49.6 6,116 77.1 4,974 67.2 3,683 52.7 2,686 43.3 2,592 42.2 3,837 50.2 3,410 41.2 4,795 44.9 4,660 43.5 United States:3 Number....................... Percent....................... 1,793 41.1 1Data relate to November of each year. 2Number of persons not available. Data are annual total days of unemployment and percent of days compensated by unemployment insurance benefits. includes all unemployment insurance programs. Note : Dashes indicate data not available. Gert Bruche, The Financing of Labour Market Policy in Austria (Ber lin, International Institute of Management, 1984), table 3; Unemployment Compen Sources : Digitized for26 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 33 61.5 — — sation and Related Employment Policy Measures in France (Paris, Organization for Economic Cooperation and Development, 1976), table 6; Gert Bruche and Bernd Reissert, The Financing of Labour Market Policy in the Federal Republic of Germany (Berlin, International Institute of Management, 1985), table 2; Bernd Reissert, The Financing of Labour Market Policy in Great Britain (Berlin, Interna tional Institute of Management, 1985), table 1; Eskil Wadensjo, The Financial Effects of Unemployment and Labour Market Policy Programs for Public Authori ties in Sweden (Berlin, International Institute of Management, 1985), table 3; Bernd Reissert, The Financing of Labour Market Policy in the usa (Berlin, Interna tional Institute of Management, 1985), table 5; and the author's own calculations. sion tripled (128,000 to 383,000) between 1973 and 1983, despite a reduced share of unprotected workers.18 Austrian data, while not entirely reliable, show a stable trend since 1975 in the proportion of unemployed workers with neither unemployment insurance nor unemployment allowance benefits. After 1973, the proportion of unem ployed in neither program rose from less than 10 percent to about 25 percent.19 The proportion of the Swedish unemployed workers covered by unemployment insurance funds (for the most part, the funds are organized by trade unions) has risen dramatically over the years, especially among women. In 1963, one-third of men age 16 to 74 were covered; by 1982 the proportion had risen to 60 percent. For women, the proportion increased from 7 percent in 1963 to 50 percent by 1982.20 During the period 1974-84, it is estimated that the proportion of Swedish unemployed workers who re ceived benefits from unemployment insurance funds rose from 41 percent to 69 percent, while the proportion receiving the government’s unemployment insurance benefit, payable to eligible nonmembers of funds, in creased from 10 to 18 percent. This left 13 percent of the unemployed dependent on the social welfare payments of local governments in 1984, down from one-half in 1974. Unemployed persons whose unemployment insurance or allowance has expired have the right to publicly created jobs; through these jobs, they acquire unemployment insurance eligibility once more. These “transitional measures,” introduced in the 1970’s and made a legal right in the 1980’s, are credited with producing the much smaller proportion of long-term unemployed workers in Sweden than is fo u n d in o th e r w e ste rn E u ro p e a n countries.21 The evidence for Great Britain, Sweden, and the United States indicates that for much of the 1973-83 period, fewer than half of the unemployed received unemploy ment insurance benefits. (See table 5.) In the United States, according to a recent General Accounting Office report, only 32 percent of unemployed civilian workers received unemployment benefits in 1986, compared to 55 percent in 1952. At the same time, it is not well estab lished how levels of payment from unemployment allowance and local welfare programs compare with un employment benefits. Replacement ratios How well off are those on unemployment insurance compared with their own earnings from full-time work? The definition and computation of appropriate replace ment ratios are complex, especially for comparative purposes. The first comparative efforts simply measured the percentage of average weekly earnings replaced by average weekly unemployment insurance benefits. More recently, a comprehensive concept of replacement ratios takes account of both net losses and net additions of in https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis come from all sources while unemployed. For example, net unemployment insurance benefits may drop if recipi ents are liable for income tax, Social Security contri butions, or other charges. However, the unemployed may receive assistance from other social programs, in addition to basic unemployment insurance. Net unemployment in surance benefits also may vary by family size. In some countries, benefit levels differ by region and occupational group. These and other factors can significantly affect the calculation of the replacement ratio. The United Nations Economic Commission for Europe examined replacement ratios from 1972 to 1982 in 17 European countries, Canada, and the United States. The results show that: • Unemployment insurance benefits usually were lower than previous take-home pay from employment in all countries over the entire period. • The replacement ratios varied significantly among countries, with average income losses during unem ployment ranging from 8 percent to more than 50 percent. • The percentage income loss was greater for a single man than for a married man in most countries, except Austria, Denmark, Norway, Switzerland, Spain, and the United States. • Replacement ratios for the majority of countries re mained unchanged or fell between 1972 and 1982, but rose markedly in France and Sweden (after 1975), Por tugal (during the early 1980’s), and less sharply in Italy. • A special analysis of Finland and the United Kingdom in the same study, using an alternative calculation based on the average earnings of typical unemployed workers while employed, instead of the actual last earn ings of the unemployed, found a sharp decline over time in replacement ratios.22 Another issue concerns net replacement ratios over longer periods, weighing all forms of replacement income, because unemployment may continue after unemployment insurance benefits are exhausted. An o e c d study assessed how the incomes of model families in five countries—Aus tralia, Canada, Germany, the United Kingdom, and the United States (represented by Michigan data only)— changed as the principal earner moved from full-time employment into prolonged unemployment.23 For a married couple with the earnings of an average production worker and no spousal income or children, the replacement ratio during the first year of unemployment ranged between 35.9 percent in the United States and 68.5 percent in Canada; for single people, the variation was greater. Replacement ratios varied by family size, and were as high as 90 percent or more in Austria and the United Kingdom for families with two children, whose single-earner family income previously was half the na27 MONTHLY LABOR REVIEW April 1989 • Unemployment Insurance in the U.S. and Abroad tional average. When average earnings were assumed, the replacement ratios ranged from 41 percent in the United States to 72 percent in Canada. In most countries, the continuation of the spouse’s earnings meant that family income fell less and that the replacement ratio was higher. In addition, the study found that in some countries, replacement ratios tend to decline over time as unemployment insurance benefits end and primary earners move from a nonmeans-tested pro gram to a means-tested program; the value of the con tribution of the second earner will tend to decline sharply, given that such earnings limit the means-tested benefit of the unemployed principal earner. The conclusion was that there is a wide disparity in income replacement during prolonged unemployment. This is so between countries for families of the same type at comparable earnings levels, and between families of different types at a range of earnings levels within the same country. In general, unemployment implies a sub stantial drop in net income, although there are exceptions. Replacement ratios during long-term unemployment are much lower than those during short-term unemployment and display much more variation. Do benefits affect work incentives? If workers lose only a small part of their disposable income when they become unemployed, they may delay their job search, perhaps waiting until their unemploy ment insurance benefits are about to expire. Unemploy ment insurance recipients with high replacement ratios may search for a job less actively than they would if they had lower replacement ratios. Finally, the level of replace ment income will influence the reservation wage, that is, the wage the unemployed are willing to accept on a new job. In a cross-national framework, no correlation appears between the level of replacement ratios in a country and the extent or depth of its belief, as expressed in popular, official, and academic opinions, that replacement ratios are too high and act as a work disincentive. In fact, countries with relatively high replacement ratios, as in Scandinavia, may be least vocal on the issue. Moreover, in countries where the issue has been raised, the volume of comment has not responded much to the downward trends in replacement ratios noted by the United Nations Economic Commission for Europe: . . . the fact that for the majority of countries considered the replacement ratio has either remained unchanged or has fallen since 1972 suggests that unemployment benefits have had little to do with the increase in unemployment since 1974, and espe cially with the large increase since 1979.24 The adverse effects of unemployment insurance bene fits on work incentives appear to concern the Englishspeaking countries far more than continental Europe. The Digitized for 28 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis United States, Great Britain, and Canada provide the bulk of academic contributions on this issue.25 Some multicountry studies have found that unemploy ment insurance benefits deter the search for a job and prolong unemployment.26 H. Grubel and M. A. Walker assembled studies on 10 countries, of which 7 showed that by lowering the cost of not looking for work, unemploy ment insurance benefits increased voluntary unemploy ment. Significant effects were found in the United States, Canada, Ireland, and the United Kingdom, but only lim ited evidence of induced unemployment was found in France, New Zealand, and Belgium. Germany and Italy showed no evidence of this effect.27 In Italy, flat-rate un employment benefits, financed by a payroll tax on employers, are very low and are used less often than an alternative system of benefits for temporary layoffs and short-time working.28 Great Britain has translated its academic findings into policy. Earnings-related unemployment insurance bene fits were abolished in 1982, leaving only the basic flat-rate benefit. British economists have developed optimal unem ployment insurance programs to minimize work dis incentives and have suggested reforms, some of which were implemented in the 1970’s.29 In contrast, discussions and public concern are rarer in the continental European countries, and especially in Scandinavia where replacement rates are relatively high.30 A recent German analysis contends that unemployment insurance protects the existing wage structure, the skills hierarchy, and working conditions on the job against the adverse effects of unemployment. This social function of unemployment insurance might be regarded less benignly in other countries. Also, reductions of unemployment in surance payments or restrictive definitions strengthen the employers’ bargaining position while undermining that of the unions.31 Many continental Europeans might agree with an o e c d multicountry report that declared: . . . [A] small but not negligible amount of additional unem ployment may be induced by the level of benefits, but these benefits are intended to raise social welfare, and the fact that people prolong their job search by an extra week or two may well improve the match between their skills and job opportuni ties and reduce labour turnover in the longer run.32 Only a few official representatives who attended the 1982 o e c d conference on income support policies men tioned that work disincentives or other distorting effects on the labor market resulted from unemployment insur ance benefits, instead pointing to factors other than replacement ratios that affect unemployment duration. They suggested that governments could more accurately test unemployment insurance recipients’ willingness to work by taking responsibility for effective placement ser vices and job offers.33 An earlier review of the academic literature had concluded that, although the phenomenon of insurance-induced unemployment exists, its impor tance should not be exaggerated, especially as a factor in the post-1979 rise in unemployment.34 Despite increased sophistication in recent economic studies on the work disincentives of unemployment insur ance benefits, many questions persist about the concepts, methodology, and data, including the way the replace ment ratio is derived and interpreted. For example, replacement ratios based on prior earnings— the usual measure for such studies— may be less relevant to reser vation wages than the comparison of disposable resources during unemployment with those on the proposed new job. Hypothetical, rather than actual, income data are faulted as are the limited number of worker or family types studied. The studies need a complete distribution of replacement ratios, rather than averages. While the most appropriate unit for measuring the replacement ratio may be the household, more information is needed about income sharing and the basis upon which work decisions are made within households. For most countries, it is misleading to compute replacement ratios only for recipi ents of unemployment insurance, omitting the unemployed receiving other income replacement. More insights are needed into the way unemployed persons think about their replacement ratios, their alternatives, and the time frame (weekly, monthly, annual) they use in looking for new employment. Such information might indicate that some theoretical models are inappropriate for predicting behavior. For policy purposes, it is important to know how the replacement ratio changes over time for particu lar unemployed individuals. Another question that needs to be treated is replacement ratios for the employed popu lation so that insights can be gained into the motivations for remaining in work when high replacement ratios are available for not working. A high replacement ratio may be a commentary on too low a wage while employed.35 Other questions about the labor supply also have been addressed. Studies have explored the effects of unemploy ment insurance on labor force participation and migration rates, and the aggregate unemployment rate. Studies have also inquired into the effects of unemployment insurance on the distribution of unemployment among various agesex groups, insured and uninsured workers, and registered versus unregistered unemployment.36 Another approach to the subject stresses that existing analyses are lopsided in concentrating on the effects of unemployment insurance on the supply of labor. The re duced form equation with deviations from the trend in output used to capture influences on the demand side is considered inappropriate for two reasons. First, the un derlying structure of the labor market is not explicitly outlined and, as a result, the structural parameters cannot be retrieved. Second, European academic studies ignore the possible effects of unemployment insurance programs on employment or unemployment via the demand for la https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis bor, as well as the potential of demand for confounding the estimation of a labor-supply response. Specifying a complete model of the labor market and using British data for the period between World Wars I and II, Alan Harrison and Robert A. Hart found that unemployment insurance influenced unemployment via the demand for labor, but did not influence the supply of labor or labor force participation.37 Hart found that un employment insurance affects the firm’s employment and layoff strategy in European countries as well as in the United States.38 This challenge to the most common ana lytic approach to work incentives and unemployment insurance benefits indicates that it will remain a lively issue. Conclusion Since 1973, many Western European countries have felt severe pressures on their unemployment insurance systems because of elevated unemployment rates, longer spells of unemployment, and a changed composition of the unemployed from the time when unemployment in surance was introduced. Unlike the United States, many of the European countries experienced a 5- to 10-fold increase in the number of recipients of unemployment insurance benefits from 1973 to 1983. Expenditures on unemployment insurance rose more sharply in the 1970’s and early 1980’s than they had in the 1960’s; the United States was less affected by cost pres sures than the five European countries studied in this article. In these and other industrialized countries, unem ployment insurance also accounted for a rising share of gross national product and of total expenditures on all public measures related to unemployment, employment training, and other labor market programs. Unemploy ment insurance accounted for a rising share of income maintenance program expenditures. In the 1970’s and 1980’s, many European countries sought to contain the growth in unemployment insurance costs through tighter eligibility criteria, little or no growth in the amount and duration of unemployment benefits, and restructuring of labor market programs to limit the unemployment insurance share of the various methods used to improve the position of the unemployed. In addi tion, unemployment insurance funds were augmented by increases in the contribution rates paid by employers and, in some cases, employees, as well as by drawing down reserve funds or by borrowing. Governments gave aid to a limited extent. Financing remains a problem for many unemployment insurance systems, especially in planning for possible recessions. Despite the financial crunch, some European countries have extended the duration of unemployment benefits for older unemployed workers, easing them into earlier retire ment and in the process reducing the labor supply. Programs also have been instituted to utilize unemploy29 MONTHLY LABOR REVIEW April 1989 • Unemployment Insurance in the U.S. and Abroad ment insurance monies to support employment-related activities of claimants beyond job search. The proportion of unemployed workers receiving un employment benefits tended to rise from 1973 to 1975 and then decline through 1983. Various forms of unemploy ment allowances and local social assistance filled the gap left by a declining role for unemployment insurance. At the same time, most countries reduced the proportion of the unemployed who were not served by any incomereplacement program. However, the absolute number of unemployed without any public support tended to in crease because of the sheer escalation in the numbers of unemployed workers. The adequacy of income replacement programs, their relation to previous income and reservation wages, and the impact on incentives to seek and obtain new jobs have been increasingly studied in individual countries and in cross-national perspective. Findings in one large study indicate that there is significant variation in the amount of income loss from country to country and that unemploy ment insurance benefits were lower than take-home pay from employment over the 1972-82 period. Replacement ratios in a majority of the countries declined from 1972 to 1982. Another study found that the wide disparity in 1High Unemployment: A Challenge fo r Income Support Policies (Paris, Organization for Economic Cooperation and Development, 1984), pp. 83-86. 2High Unemployment, pp. 193-94. 3“Social Expenditure: Erosion or Evolution?” OECD Observer, January 1984, pp. 3 -6 . 4French unemployment insurance expenditures as a share of gross domestic product showed the strongest growth, with considerable in creases in Germany and the United Kingdom. The United States, Canada, Italy, and Japan, however, showed decreases in the share of gross domestic product going to unemployment insurance benefits in the 1965-70 period. Only small changes occurred in the United States, Italy, and Japan in subsequent periods, but Canada tripled its percentage from 1965-70 to 1975-80. Canada ranked first in the share of gross domestic product going to unemployment insurance benefits in each period, but the other rankings shifted. In 1970-75, the percentages ranged from 1.4 to 0.18 among the seven countries, with the United States second, followed by the United Kingdom, Japan, Germany, Italy, and France. During the 1975-80 period, when the range was 1.74 per cent to 0.25 percent, France moved to third place after Canada and the United States, with Germany followed by the United Kingdom, Japan, and Italy. See High Unemployment, pp. 193-94. 5Research on Sweden suggests that active labor market programs are more fiscally sound policy than passive programs. The rise in the unem ployment insurance share of Sweden’s total labor market expenditures in 1982 reflects an increase in unemployment insurance costs as well as a new emphasis on the less expensive forms of active labor market policy, for example, placement rather than public works or public service jobs. See Inga Persson Tanimura, On the Costs o f Unemployment in Sweden (Berlin, International Institute of Management, 1979), Discussion Paper iim / lm p 79-16; Jan Johannesson, “Financing Active and Passive La bour Market Policy in Sweden” (Stockholm, unpublished paper, 1984); and Gunther Schmid, The Financing o f Labour Market Policy in Sweden (Berlin, International Institute of Management, 1985). Digitized for 30 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis income replacement during prolonged unemployment af fected families of the same type at comparable earnings levels among countries, as well as families of different types at a range of earnings within a country. In general, unemployment implies a substantial drop in net family income, especially in long-term unemployment, although there are exceptions. These exceptions, whose income during unemployment is higher, the same as, or only slightly lower than their last earnings or reservation wage, form the basis for the con cern about the disincentives to work inherent in unem ployment insurance; the concern is much stronger in the English-speaking industrial countries than in others. Many questions remain about the concepts, methodology, data, and conclusions in studies of the work disincentives of unemployment insurance. Others point to the need to study additional aspects of the impact of unemployment insurance— on the labor de mand, labor force participation rates, migration rates, the aggregate unemployment rate, unemployment rates of various age-sex groups, insured versus uninsured unem ployed workers, and registered versus unregistered unem ployed workers. It is fair to say that the last word on work incentives has not been said. □ 6High Unemployment, pp. 193-94. ’“Social Expenditure,” pp. 3 -6 . *High Unemployment, pp. 193-204. 9For example, see “Unemployment Compensation and Related Em ployment Policy Measures in Germany” (unpublished o ec d paper, 1976), pp. 11-27; and Gert Bruche and Bernd Reissert, The Financing o f Labour Market Policy in the Federal Republic o f Germany (Berlin, International Institute of Management, 1985), pp. 12-15, table 2. 10Gert Bruche, The Financing o f Labour Market Policy in France (Berlin, International Institute of Management, 1984), Discussion Paper iim / lm p 84—21b; Bernd Reissert, The Financing o f Labour Market Policy in Great Britain (Berlin, International Institute of Management, 1984), Discussion Paper iim / lm p 8 4 -2 1 c; High Unemployment; “Per centage of Jobless Lacking Benefits is Highest in 30 years,” The New York Times, Nov. 12, 1987; and “ g a o Warns on Jobless Insurance Reserves.” The New York Times, Sept. 27, 1988. n Gert Bruche, The Financing o f Labour Market Policy in Austria (Berlin, International Institute of Management, 1984), Discussion Paper iim / lm p 84-21d; Bruche, The Financing o f Labour Market Policy in France-, Bruche and Reissert, The Financing o f Labour Market Policy in the Federal Republic o f Germany, Bernd Reissert, The Financing o f Labour Market Policy in the USA (Berlin, International Institute of Management, 1985); and Eskil Wadensjo, The Financial Effects o f Un employment and Labour Market Policy Programs for Public Authorities in Sweden (Berlin, International Institute of Management, 1985). 12In most countries, administrative costs are included in the base for calculating the government’s share. The comparability of the data in table 4 is limited. Data for Austria and Germany refer to the govern ment’s subsidy to all labor market programs of the Austrian Unemploy ment Insurance Fund and the German Federal Employment Institute, while French data include government support of income maintenance for the unemployed other than conventional unemployment insurance programs. British government subsidies support all social insurance pro grams, but rising unemployment largely accounts for the increased government share in the budget years 1973-74 and 1980-81; the drop in the next three budget years reflects the increased share of employer and employee contributions in total intake. Noncomparability of the data does not fully explain the extent of government sharing in unem ployment insurance expenditures. Germany probably has had no Federal subsidy to the Federal Employment Institute for unemployment insurance, because unemployment insurance benefits are a first charge on the Federal Employment Institute Fund, taking precedence over discretionary expenditures or active labor market measures. In the few years when the Federal Employment Institute required a Federal sub sidy, it was not necessarily used to cover expenditures on unemployment insurance. The same would be the case in Austria. If the French data concerned only the government share for conventional unemployment insurance benefits, the proportion would probably drop to near the British or Austrian level. 13As a percentage of the civilian labor force, those covered by unem ployment insurance programs increased from 38.2 percent in 1960 to 59.4 percent in 1975 in France; from 38.0 percent in 1957 to 47.7 percent around 1980 in Italy; from 50.2 percent in 1950 to 87.7 percent in 1975 in Canada; and from 55.2 percent in 1950 to 89.5 percent around 1980 in the United States. In the United Kingdom, the coverage rate decreased from 88.9 percent in 1950 to 73.8 percent in 1974. See High Unemploy ment, p. 28. 14British urtemployment insurance recipients constituted 39 percent of the unemployed in 1973, but reached highs of nearly 50 percent in 1975 and again in 1980, and then fell to 31 percent in 1983. Means-tested supplementary benefits took up most of the slack. From 1973 to 1976, about one-third of the unemployed received supplementary benefits, rising to more than two-fifths at the end of the decade and more than half in 1982 and 1983. See Reissert, The Financing o f Labour Market Policy in Great Britain, table 1. !5M. White, Long Term Unemployment and Labour Markets (Lon don, Policy Studies Institute, 1983), Publicatton No. 622; and High Unemployment, pp. 121-33. 16Bruche and Reissert, The Financing o f Labour Market Policy in the Federal Republic o f Germany, p. 82, table 2. 17Between 1982 and 1983, three cities in the Ruhr reported a 70-percent increase in unemployed recipients of local public assistance. By 1983, 7 percent of the total expenditure was borne locally. Bruche and Reissert, Financing o f Labour Market Policy in the Federal Republic of Germany, p. 102, table 14. l8Reissert, The Financing o f Labour Market Policy in Great Britain, table 1. 19Bruche, The Financing o f Labour Market Policy in Austria, table 3. 20Anders Bjorklund and Bertil Holmlund, Arbetsloshetersattningen i Sverige-motiv, regler och effekter [Unemployment Programs in Sweden.] (Stockholm, Publication No. 151, Industriens Utredningsinstitut, 1983), table 3. 21Schmid, Financing Labour Market Policy in Sweden, pp. 10, 19; and Wadensjo, Financial Effects o f Unemployment and Labour Market Pro grams, Sweden, table 3. 22United Nations, Economic Bulletin for Europe (New York, Pergamon Press, September 1983), pp. 289-306. 23See L'Indemnisation du chômage en France et a l ’Etranger [Unem ployment Compensation in France and Abroad.] (Paris, Centre ¿’Etude des Revenus et des Coûts, 1982), Document No. 62; Employment Out look (Paris, Organization for Economie Cooperation and Development, September 1984), pp. 93-96; and High Unemployment, pp. 98-120. 24Economie Bulletin for Europe, September 1983, pp. 295. 25For British and Canadian examples, see A. B. Atkinson, “Unem ployment Benefits and Incentives,” in J. Creedy, ed., Economies of https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Unemployment in Great Britain (London, Butterworth, 1981); A. B. Atkinson and others, Unemployment Benefit Duration and Incentives: How Robust is the Evidence? (London, London School of Economics, 1982); D. K. Benjamin and L. A. Kochin, “Searching for an Explana tion of Unemployment in Inter-war Britain,” Journal o f Political Economy, June 1979; A.W. Dilnot and C.W. Morris, “Private Costs and Benefits of Unemployment: Measuring Replacement Rates,” Oxford Economic Papers, November 1983, supplement; S. F. Kaliski, “Real and Insurance-Induced Unemployment in Canada,” Canadian Journal o f Economics, 1975; S. F. Kaliski, “Unemployment and Unemployment Insurance: Testing Some Corollaries,” Canadian Journal o f Economics, 1976; C. Green and J. M. Cousineau, Unemployment in Canada: The Impact o f Unemployment Insurance (Ottawa, Economic Council of Can ada, 1976); H. Grubel and M. A. Walker, eds., Unemployment Benefits: Global Evidence o f Its Effects on Unemployment (Vancouver, bc , The Fraser Institute, 1978); R. Layard and S. J. Nickell, “The Causes of British Unemployment,” National Institute Economic Review, October 1985; D. R. Maki and Z. A. Spindler, “The Effect of Unemployment Compensation on the Rate of Unemployment in Great Britain,” Oxford Economic Papers, December 1975; W. Narendranathan, S. J. Nickell, and J. Stern, Unemployment Benefits Revisited (London, London School of Economics, 1983); S. J. Nickell, “The Effects of Unemployment and Related Benefits on the Duration of Unemployment,” Economic Jour nal, March 1979; Z. A. Spindler and D. R. Maki, “More on the Effects of Unemployment Compensation on the Rate of Unemployment in Great Britain,” Oxford Economic Papers, 1978. 26B. M. Walsh, Unemployment Insurance and the Labour Market: A Review o f Research Relating to Policy (Paris, Organization for Economic Cooperation and Development, 1981). 27Grubel and Walker, Unemployment Benefits. ^ “International: Unemployment Benefits in Twelve Countries,” Eu ropean Industrial Relations Review, October 1982, p. 12. 29The United Kingdom and Ireland set limits on replacement ratios at 85 percent; Canada reduced the rate of benefit; and Australia tightened eligibility criteria, widened the definitions of suitable jobs, and required more frequent registration by the unemployed. Some countries intro duced taxation of unemployment insurance benefits, but government financial stringency played a role, along with the aim of reducing work disincentives. See Walsh, Unemployment Insurance and the Labour Market-, Richard Disney and David Metcalf, “Financing Labour Market Policy in Great Britain” (Canterbury, England, University of Kent, unpublished). 30Bjorklund and Holmlund, Unemployment Insurance and the Labour Market, p. 108ff. 31Bruche and Reissert, The Financing o f Labour Market Policy in the Federal Republic o f Germany, p. 180. 32 Unemployment Compensation and Related Employment Policy Measures (Paris, Organization for Economic Cooperation and Develop ment, 1979). n High Unemployment, pp. 14, 81, 87-89, 95, 125, and 134-36. 34Walsh, Unemployment Insurance and the Labor Market, p. 61. iSHigh Unemployment, pp. 121-35. 36Walsh, Unemployment Insurance and the Labour Market, p. 61. 37Alan Harrison and Robert A. Hart, A Labour-Market Model o f Unemployment Insurance (Berlin, International Institute of Manage ment 1982), Discussion Paper iim / lm p 82-19. 38Robert A. Hart, Unemployment Insurance and the Firm's Employ ment Strategy: A European and United States Comparison (Berlin, International Institute of Management, 1982), Discussion Paper iim / lm p 82-11. 31 Multifactor productivity slips in the nonrubber footwear industry While output per employee hour rose modestly from 1958 to 1986, multifactor productivity for this industry declined on average, more so in the period before 1973 John D uke and L isa U sher For many years, the Bureau of Labor Statistics has published, a labor productivity measure for the footwear industry termed output per employee hour.1 Many fac tors influence movements in labor productivity, for example, technological change, changes in the skills and efforts of the work force, economies of scale, the amount of capital input per worker, and the amount of intermedi ate purchases input per worker. This article presents a supplementary productivity measure for the footwear in dustry— multifactor productivity— in which output is related to the combined inputs of labor, capital, and in termediate purchases. This measure differs from the traditional measure in that it accounts for the last two influences in the input measure and therefore does not reflect the impact of these influences in the productivity residual. From 1958 to 1986, output per employee hour in the footwear industry rose at an average rate of 0.6 percent per year, well below the 2.5-percent rate for manufacturing as a whole. Multifactor productivity actually declined over the period by an average 0.9 percent per year. The rise in John Duke and Lisa Usher are economists in the Office of Productivity and Technology, Bureau of Labor Statistics. 32 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis output per employee hour reflected changes in the contri bution of capital per hour, of intermediate purchases per hour, and of other sources (multifactor productivity). The development of the multifactor productivity measure indi cates that the low rate of growth in output per employee hour was caused not by declining amounts of capital or intermediate purchases available to labor over the period, but rather by the influence of other factors. The influence of capital, referred to here as the capital effect, is measured as the change in the capital-labor ratio multiplied by the share of capital income in the total output. The influence of intermediate purchases, referred to here as the intermediate purchases effect, is measured as the change in the interme diate purchases-labor ratio multiplied by the share of intermediate purchases in the total output. The capital ef fect showed an increase of 0.6 percent per year over the period 1958-86, while the intermediate purchases effect rose 0.9 percent. The decline in multifactor productivity was more than offset by these increases in the capital effect and intermediate purchases effect. Multifactor productiv ity suffered at least in part from a slow pace of development and diffusion of new technology in the industry. Underlying the 0.9-percent annual decrease in multi factor productivity was an output decline of 3.0 percent Chart 1. Output per employee hour rose In nonrubber footwear— despite multifactor productivity's fall— as capital and Intermediate purchases increased relative to labor □ Output per employee hour 1 9 5 8 -8 6 ID Multifactor productivity ■ Capital effect H Intermediate purchases effect 1 9 5 8 -7 3 1 9 7 3 -8 6 - 1 .5 - 1 .0 - 0 .5 0 .0 0 .5 1.0 1.5 Average annual percent change per year and a 2.1-percent average annual drop in com bined inputs. The decline in multifactor productivity slackened on average after 1973. (See table 1.) Although there have been year-to-year fluctuations, multifactor productivity fell at only a 0.5-percent rate after that year, compared with the 1.2-percent average rate of decrease prior to 1973. Output per employee hour also improved in the post-1973 period relative to the earlier period, but it was well below the manufacturing average for both periods. Trends in the individual inputs varied considerably over the 1958-86 period. (See table 2.) While labor input dropped at a rate of 3.5 percent per year, capital input rose a scant 0.1 percent per year, and intermediate purchases de clined at a 1.9-percent rate. Combined inputs, the weighted aggregate of these components, declined at a 2.1-percent rate per year. Thus, over the whole period, labor input showed the most rapid decline, followed by the lesser drop in intermediate purchases, while capital input showed a slight gain. Although the growth in output per employee hour was well below average in the footwear industry over the period 1958-86, there was no post-1973 slowdown, as there was for manufacturing as a whole and most other industries. Output per employee hour in the manufacturing sector fell off from a rate of 2.9 percent in the period 1958-73 to a rate https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis of 2.4 percent between 1973 and 1986. (It had declined to a rate of 1.6 percent in the period 1973-81, but began recov ering in the mid-1980’s.) For the footwear industry, output per employee hour actually accelerated somewhat from a rate of 0.6 percent in the earlier period to 0.9 percent in the post-1973 period.2 The relative contributions of the capital effect, the in termediate purchases effect, and multifactor productivity to changes in output per employee hour were not the same in the pre- and post-1973 periods. During the pre-1973 period, a 0.6-percent gain in output per employee hour was obtained from a 1.2-percent decline in multifactor productivity plus a 0.5-percent annual gain in the capital effect plus a 1.2-percent increase in the intermediate pur chases effect. (Rounding produces the one-tenth of a point discrepancy when the addends are summed.) In the pe riod 1973-86, a 0.9-percent average annual gain in output per employee hour was obtained from a 0.5-percent per year average drop in multifactor productivity plus a 0.8percent rise in the capital effect plus a 0.6-percent increase in the intermediate purchases effect. (See chart 1.) Thus, in both periods output per employee hour recorded an increase, despite a decline in multifactor productivity, as a result of increases in the amount of capital per worker hour and intermediate purchases per worker hour. 33 MONTHLY LABOR REVIEW April 1989 • Multifactor Productivity in Nonrubber Footwear For the period 1958-86 as a whole, the increase in the capital effect was 0.6 percent, resulting from a gain of 0.1 percent in capital input, while labor input was declining at a rate of 3.5 percent per year. Although the capital effect did not change much from the pre- to the post-1973 pe riod (0.5 percent and 0.8 percent), the changes in the components differed. In the period 1958-73, capital input grew at a rate of 1.6 percent per year, while labor input declined by 1.7 percent per year. In the period 1973-86, capital fell by 1.5 percent per year, but labor fell even faster at a 5.3-percent rate. The intermediate purchases effect showed a 0.9-percent gain over the period 1958-86. This increase resulted from a 1.9-percent decline per year in intermediate purchases, more than offset by a 3.5-percent average drop in hours. The intermediate purchases effect did fall off somewhat from a pre-1973 rate of 1.2 percent to a post-1973 rate of 0.6 percent. Underlying the pre-1973 growth was a 0.7percent increase in intermediate purchases and a 1.7percent drop in labor hours. The somewhat slower rate during 1973-86 resulted from a decline in intermediate purchases of 4.2 percent coming closer to matching a drop Table 1. Multifactor and related productivity indexes, 1958-86 [19 7 7 = 10 0 ] Year Multifactor productivity Output per employee hour Output per unit of capital Output per unit of intermediate purchases 1 9 5 8 ................... 1 9 5 9 ................... 1 1 3.0 1 19.0 8 6 .2 9 0 .7 1 50.0 1 6 5.6 123.1 1 2 8.3 1 9 6 0 ................... 1961 ................... 1 9 6 2 ................... 1 9 6 3 ................... 1 9 6 4 ................... 11 6.0 11 7.7 118.0 11 8.8 11 7.7 8 9 .4 9 0 .0 9 0 .7 94 .2 94 .0 1 56.3 15 9.4 1 59.7 1 5 3.3 1 5 3.7 1 2 5.2 1 2 7.5 12 7.4 12 7.2 12 4.7 1 9 6 5 ................... 1 9 6 6 ................... 1 9 6 7 ................... 1 9 6 8 ................... 1 9 6 9 ................... 115.1 1 15.9 1 0 5.8 1 08.3 1 0 1.6 9 3 .0 9 4 .6 9 2 .6 9 5 .9 8 9 .8 1 4 9.9 15 0.4 13 4.8 13 9.8 12 0.5 121.3 12 1.3 10 6.3 10 7.7 104.1 1 9 7 0 ................... 1971 ................... 1 9 7 2 ................... 1 9 7 3 ................... 1 9 7 4 ................... 10 3.7 1 02.8 1 01.5 1 01.0 9 7 .8 9 6 .6 98 .3 9 5 .9 9 4 .9 93 .8 11 8.7 11 4.7 11 5.6 106.1 9 8 .2 1 0 3.8 1 0 1.9 1 00.8 103.1 10 0.0 1 9 7 5 ................... 1 9 7 6 ................... 1 9 7 7 ................... 1 9 7 8 ................... 1 9 7 9 ................... 97.1 99 .4 1 00.0 1 01.6 10 6.5 97 .6 9 8 .2 10 0.0 1 01.8 99 .7 94 .3 1 01.8 1 0 0.0 10 0.0 9 8 .2 9 7 .6 99 .3 10 0.0 1 0 1.9 1 1 3.0 1 9 8 0 ................... 1981 ................... 1 9 8 2 ................... 1 9 8 3 ................... 1 9 8 4 ................... 9 9 .2 9 5 .6 10 0.3 9 9 .2 9 7 .6 9 8 .0 95 .0 1 06.0 104.1 10 5.0 9 4 .6 91.1 88.1 8 5 .2 7 7 .9 1 0 1 .0 9 7 .2 10 1.6 10 1.8 10 1.6 1 9 8 5 ................... 1 9 8 6 ................... 9 1 .4 9 1 .2 10 5.4 10 7.4 6 9 .4 6 4 .7 9 3 .5 9 4 .3 Average annual rates of change (percent) 1 9 5 8 - 8 6 ......... 1 9 5 8 - 7 3 ...... 1 9 7 3 - 8 6 ...... -0 .9 -1 .2 -.5 34FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 0.6 .6 .9 -3 .0 -2 .7 -3 .1 -1 .1 -1 .8 -.3 in labor of 5.3 percent than was the case in the earlier period. Technological change Technological change has come slowly to the footwear industry. Automation of the industry on a mass scale has been hampered by a number of factors, including the high cost of the necessary equipment and the small size of most of the firms in the industry. In addition, for years the industry lacked a uniform last-grading system needed to facilitate the making of shoes in a wide variety of shoe lengths and widths. With the advent of affordable comput ers and computer-aided design, it is now possible to design a shoe pattern and grade it for production in different sizes and widths within hours. However, frequent style changes are a fact of life for the footwear industry, and difficulty in adapting the production equipment to these changes is still a problem. Moreover, frequently changing styles do not allow for the long production runs required to make the purchase of the equipment feasible. Accordingly, most of the improvements in technology have been of an incremen tal nature involving improvements in existing machine designs, and even these improvements have not spread rap idly throughout the industry. As a result, the footwear industry has remained very labor intensive. Much of the technological change that occurred in the footwear industry during the late 1950’s and 1960’s was directed at reducing labor costs. This emphasis was strengthened as competition from low-cost imports rose. These imports benefit from low labor costs. For example, the introduction of injection molding made it possible to use liquid plastic to mold the upper material of the shoe onto the sole using no stitching and very little labor. Simi larly, the process of affixing preformed soles and heels to uppers using cement also saved time and labor costs. This process was accompanied by an increase in the use of pre molded “ unit bottom s” purchased from outside the industry, thus saving further on labor costs to the industry. Many of the technologies introduced during the 1970’s and 1980’s, along with the increased use of synthetic mate rials that coincided with the introduction of these new technologies, resulted in savings in both labor and interme diate purchases. Synthetic materials for shoe uppers, for example, were more uniform in weight and quality and could be cut in layers with automatic machinery. This saved time and labor costs and also reduced the amount of materials wastage. Similarly, the flow molding process, whereby designs are embossed onto a thermoplastic up per from a mold, reduced both labor and materials costs. The advent of computerized equipment has allowed even more savings: computer-controlled cutting and compu ter-controlled stitching, though not widespread in the industry, have tended to reduce the amount of labor time involved and the amount of damage done to materials. More recently, computer-aided design lets manufacturers respond rapidly to style changes by reducing the time Table 2. Output and input indexes, 1958-86 [1977=100] Year Output Combined inputs Employee hours Capital Intermediate purchases 1958........... 1959........... 134.9 148.4 119.4 124.7 156.5 163.7 89.9 89.6 109.6 115.6 1960........... 1961........... 1962........... 1963........... 1964........... 1965........... 1966........... 1967........... 1968........... 1969........... 141.0 142.0 144.2 140.3 143.4 143.9 148.3 138.6 147.4 132.1 121.6 120.7 122.1 118.1 121.9 125.0 128.0 131.0 136.0 129.9 157.8 157.8 159.0 149.0 152.6 154.8 156.8 149.7 153.7 147.1 90.2 89.1 90.3 91.5 93.3 96.0 98.6 102.8 105.4 109.6 112.6 111.4 113.1 110.3 114.9 118.6 122.3 130.3 136.9 126.8 1970........... 1971........... 1972........... 1973........... 1974........... 1975........... 1976........... 1977........... 1978........... 1979........... 130.1 122.6 121.5 114.0 105.8 98.2 101.7 100.0 99.5 94.0 125.5 119.2 119.7 112.9 108.2 101.2 102.3 100.0 97.9 88.3 134.7 124.7 126.6 120.2 112.8 100.7 103.5 100.0 97.7 94.3 109.6 106.9 105.1 107.4 107.8 104.2 99.9 100.0 99.5 95.7 125.4 120.3 120.5 110.6 105.8 100.6 102.4 100.0 97.6 83.2 1980........... 1981........... 1982........... 1983........... 1984........... 1985........... 1986........... 90.3 87.9 86.3 80.8 71.8 62.1 55.3 91.1 91.9 86.0 81.4 73.5 67.9 60.6 92.2 92.5 81.4 77.6 68.3 59.0 51.5 95.5 96.5 97.9 94.8 92.2 89.6 85.4 89.4 90.4 84.9 79.4 70.7 66.4 58.6 Average annual rates of change (percent) 1958-86 .... 1958-73 . 1973-86 . -3.0 -1.2 -4.5 -2.1 .0 -4.0 -3.5 -1.7 -5.3 0.1 1.6 -1.5 -1.9 .7 -4.2 involved in designing and grading patterns. Also, the process allows the operator to adjust the pattern to maxi mize the amount of usable material.3 Output Between 1958 and 1986, output of nonrubber footwear declined at an average annual rate of 3.0 percent. Al though the industry attained slightly higher levels of output in 1959 and 1966 relative to 1968, there was a general, though slight, upward trend in output between 1958 and 1968. After 1968, output declined in every year (except for a small gain in 1976), falling to less than onehalf the 1968 level in 1986. Since the late 1950’s, output of the U.S. footwear indus try has been adversely affected by a variety of factors. In particular, competition from foreign manufacturers has eroded the U.S. industry’s share of the total domestic con sumption of footwear. Moreover, despite large increases in disposable income in the United States, per capita consump tion of shoes has not increased substantially over the period. Imports of nonrubber footwear went from less than 27 mil lion pairs in 1960 to more than 940 million pairs in 1986, a 35-fold increase. The ratio of imports to U.S. consumption of nonrubber shoes rose from 4 percent in 1960 to 80 per cent in 1986, in quantity terms.4 In value terms, however, https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis imports account for a smaller proportion, almost 67 percent of U.S. consumption in 1986. These numbers reflect the continuing concentration of domestic production in a higher priced segment of the market. The product mix of U.S. production of footwear has also changed. While U.S. production of all types of foot wear has declined since the late 1950’s, the contraction in output has been especially severe in women’s and in miss es’ and children’s shoes. Output of women’s shoes fell about 70 percent between 1958 and 1986. Women’s shoes made up more than 46 percent of all nonrubber footwear produced domestically in 1958; by 1986, the proportion had fallen to 34 percent. Production of misses’ and chil dren’s shoes also declined dramatically, by about 87 percent between 1958 and 1986. The proportion of misses’ and children’s shoes to total nonrubber footwear fell from about 12 percent in 1958 to less than 4 percent in 1986. Although output of men’s shoes declined by almost 43 percent between 1958 and 1986, the rate at which produc tion of men’s shoes fell was slower than that for women’s or for misses’ and children’s shoes. As a result, the pro portion of men’s shoes produced rose from 17 percent of all nonrubber footwear in 1958 to 24 percent in 1986. Capital Over the period 1958-86 as a whole, the flow of serv ices from the capital stock in the industry rose slightly, by 0.1 percent per year on average. From 1958 to 1968, when output trended slightly upward, capital input increased at a 1.6-percent rate per year. From 1968 to 1986, when output was declining substantially, capital input fell, but at a much slower rate (-1.2 percent) than the drop in output. Capital rose almost steadily, though rather slowly, reaching a peak in 1970, 22 percent above the 1958 level. Capital input then declined almost every year thereafter. This pattern was similar to that of output, but capital rose more than output in the earlier period and fell more slowly than output in the latter period. Capital input includes the services in the production process yielded by the structures (mostly buildings) in which production takes place, the land on which the structures stand, the equipment used in producing out put (both in direct production activities and in support activities), and the inventories of finished goods, work in process, and materials and supplies that the firm holds. These categories of capital input— structures, land, equipment, and inventories— did not always move to gether. In the period 1958-68, when total capital grew at a 1.6-percent average annual rate, equipment grew at al most the same rate (1.4 percent), but structures and land rose more slowly (both at 0.3 percent), while inventories increased 2.2 percent per year. In the period 1968-86, when total capital fell by 1.2 percent per year, structures and land continued to increase slightly (by 0.2 percent per year), while inventories dropped by a substantial 2.1 35 MONTHLY LABOR REVIEW April 1989 • Multifactor Productivity in Nonrubber Footwear percent per year and equipment fell 0.9 percent per year. Labor Employment in the nonrubber footwear industry de clined from 227,000 workers in 1958 to 75,900 workers in 1986. Footwear employment has responded closely to changes in output throughout the period, declining only slightly during the early to mid-1960’s. Between 1958 and 1968, employment declined by 5.3 percent. From 1968 to 1986, however, employment fell 65 percent, or an average of 4.7 percent per year. In many industries, there is a lag between the time that demand rises or falls off and the time that employee hours are increased or reduced. This lag occurs because it is diffi cult for managers to predict how long changes in demand will last, and in many cases employers are reluctant to lay off skilled personnel because it can be costly to rehire them or train new personnel when demand rises again. As can be seen in table 3, in most years the declines (gains) in output after 1968 were matched quickly by reductions (increases) in employee hours. The reductions in employee hours oc curred because of both layoffs at existing plants and plant closures over the period. From 1967 to 1982, the number of footwear establishments declined from 1,083 to 751, a loss of more than 20 plants per year on average. Since 1982, plant closures have continued. Intermediate purchases Intermediate purchases consist of the raw materials, energy (purchased fuels and electricity), and purchased services used in the production of the industry’s output. Materials constitute more than 80 percent of the value of intermediate purchases for the nonrubber footwear indus try, and by far the largest component of materials for this industry is leather. Intermediate purchases declined at an average rate of 1.9 percent per year between 1958 and 1986. However, in the earlier part of the period, from 1958 to 1968, intermediate purchases rose at a relatively rapid 1.8-percent rate per year on average. In comparison, output increased at an average annual rate of only 0.3 percent during that period. From 1968 to 1973, interme diate purchases fell at an average annual rate of 3.5 percent per year, more closely in line with the rate at which output fell (-4.4 percent). As a result, the rate of decline in the productivity of intermediate purchases, that is, the ratio of output to intermediate purchases, which fell by 1.5 percent per year from 1958 to 1968, eased to a decrease of 0.9 percent per year between 1968 and 1973, and to 0.3 percent after 1973. Despite some year-to-year volatility in leather prices, the period 1958-68 was one of moderate price increases in intermediate purchases. Between 1958 and 1968, prices of intermediate purchases increased by about 0.9 percent per year on average. In contrast, the later period was characterized by much larger price increases in both 36FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Table 3. Annual percent changes in output and employee hours in the footwear industry, 1968-86 Year Output Employee hours 1968-69 ....................... 1969-70 ....................... 1970-71 ....................... 1971 -7 2 ....................... 1972-73 ....................... 1973-74 ....................... -10.4 -1.5 -5.8 -.9 -6.2 -7.2 -4.3 -8.4 -7.4 1.5 -5.1 -6.2 1974-75....................... 1975-76....................... 1976-77 ....................... 1977-78 ....................... 1978-79 ....................... 1979-80 ....................... -7.2 3.6 -1.7 -.5 -5.5 -3.9 -10.7 2.8 -3.4 -2.3 -3.5 -2.2 1980-81 ....................... 1981-82 ....................... 1982-83 ....................... 1983-84....................... 1984-85....................... 1985-86....................... -2.7 -1.8 -6.4 -11.1 -13.5 -11.0 .3 -12.0 -4.7 -12.0 -13.6 -12.7 leather and petrochemical-based inputs (affecting many synthetic materials). Between 1968 and 1986, intermedi ate purchases prices were increasing at an average annual rate of 7.7 percent. The more rapidly rising intermediate purchases prices after 1968 provided an incentive for manufacturers to find ways of conserving on intermediate purchases consump tion. For example, during the 1960’s footwear manu facturers shifted to using more synthetic materials. These synthetic materials, such as plastic, vinyl, and other poromeric materials, are more uniform in weight and quality and therefore allow less wastage. Tanners responded by supplying leathers that were more uniform than before, with the less desirable parts removed. Improvements in cutting, such as the use of laser technology, water-jet cut ting, and piecework systems, were introduced to reduce wastage also. Other technological changes, such as the nu merically controlled upper roughing machines used for roughing the leather, also reduced damage to materials. Summary Output per employee hour in the footwear industry over the period 1958-86 grew only 0.6 percent per year. This low rate of growth reflected increases in the amount of intermediate purchases and capital relative to labor, offset ting a decline of 0.9 percent per year in multifactor productivity. The decline in multifactor productivity was concentrated in the pre-1973 period; multifactor productiv ity declined at a slower rate on average during the post-1973 period. Output per employee hour did not slow down after 1973, but it was still well below the manufacturing average in both the pre- and post-1973 periods. Domestic production of footwear has fallen by more than half since the late 1960’s, as imports have risen rap idly since that time. Productivity growth in the industry has been hampered partly by a slow pace of technological change and a slow rate of adoption of whatever new tech nology has been introduced. □ -FOOTNOTES 'This labor productivity measure was introduced by the Bureau in July 1965 in Indexes o f Output per Man-hour 1949- 63. 2The conclusion that labor productivity in this industry experienced no slowdown in the 1970’s and early 1980’s holds regardless of the choice of initial and terminal years. With 1973 as the breakpoint, none of the growth rates ending in 1978 or later is significantly below any of the APPENDIX: 3For further examination of the changes in technology in the footwear industry, see Technology and Its Impact on Labor in Four Industries, Bulletin 2263 (Bureau of Labor Statistics, November 1986). ^Current Industrial Reports, Series MA 3 1 A, U.S. Department of Com merce, various issues. Multifactor productivity measurement Methodology and data definitions The following is a brief summary of the methods and data underlying the multifactor productivity measure for the footwear industry. A technical note, describing the procedures and data in more detail, is available from the authors at the Office of Productivity and Technology, Bureau of Labor Statistics, Washington, DC 20212. Output. The output measure for the footwear industry is based on the weighted change in the quantity of produc tion of eight types of shoes and slippers as reported in the Bureau of the Census’ Current Industrial Reports, series MA31A. The weights are computed as the share obtained by each type of shoe in the total value of production of all nonrubber footwear. For multifactor measures for individual industries, output is defined as total production, rather than the alternative of value added. For a value-added measure, intermediate inputs are subtracted from total production. Consequently, an important difference between the mul tifactor productivity measures that b l s publishes for individual industries and those for aggregate sectors of the economy is that the latter measures are constructed within a value-added framework. For the major sectors of the economy, intermediate transactions tend to cancel out; intermediate inputs are much more important in production at the industry level. Further, output in industry measures is defined as total production which “leaves” an industry in a given year in the form of shipments plus net changes in inventories of finished goods and work in process. Shipments to other establishments within the same industry are excluded be cause they represent double counting, which distorts the productivity measures. Labor. Employee-hour indexes, which represent the la bor input, measure the aggregate number of employee hours. These hours are the sum of production worker hours, from Censuses o f Manufactures and Annual Surveys o f Manufactures (U.S. Department of Commerce), and nonproduction worker hours, derived by multiplying the number of nonproduction workers from the Census publi cation by an estimate of nonproduction worker average https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis rates beginning in 1965 or earlier. annual hours. The labor input data are the same as those used in the published b l s output per hour series. Capital. A broad definition of capital input, including equipment, structures, land, and inventories, is used to measure the flow of services derived from the stock of physical assets. Financial assets are not included. For productivity measurement, the appropriate concept of capital is “productive” capital stock, which represents the stock used to produce the capital services employed in current production. To measure the productive stock, it is necessary, for each type of asset, to take account of the loss of efficiency of the asset as it ages. That is, assets of different vintages have to be aggregated. For the measures in this article, a concave form of the age/efficiency pat tern (slower declining efficiency during earlier years) is chosen. In combining the various types of capital stock, the weights applied are implicit rental prices of each type of asset. They reflect the implicit rate of return to capital, the rate of depreciation, capital gains, and taxes. (For an extensive discussion of capital measurement, see Trends in Multifactor Productivity, 1948-81, Bulletin 2178 (Bureau of Labor Statistics, 1983).) Intermediate purchases. Intermediate purchases pri marily include materials, fuels, electricity, and purchased business services. Materials measured in real terms refer to items consumed or put into production during the year. Freight charges and other direct charges incurred by the establishment in acquiring these materials are also in cluded. The data from which the intermediate inputs are derived include all purchased materials and fuels regard less of whether they were purchased by the individual establishment from other companies, transferred to it from other establishments of the same company, or with drawn from inventory during the year. An estimate of intraindustry transactions is removed from materials and fuels data. Annual estimates of the cost of services purchased from other business firms are also required for multifactor pro ductivity measurement in a total output framework. Some examples of such services are legal services, communica37 MONTHLY LABOR REVIEW April 1989 • Multifactor Productivity in Nonrubber Footwear tions services, and repair of machinery. An estimate of the constant-dollar cost of these services is included in the intermediate purchases input. wk PqQ W/ Capital, labor, and intermediate purchases income shares. Weights are needed to combine the indexes of the major inputs into a combined input measure. The weights for the footwear industry are derived in two steps: first, an estimate of income in current dollars for each input is derived, and then the income of each input is divided by the total income of all inputs. Conceptual framework The multifactor productivity measure presented here is computed by dividing an index of output by an index of combined inputs of capital, labor, and intermediate pur chases. The framework for measurement is a production function describing the relation of output and inputs and an index formula that is consistent with this production function. The general form of the production function underlying the multifactor productivity measures is postulated to be (V Qit) = Q(K(t), Lit), M(t), t), where Q(t) is total output, K(t) is input of capital services, L(t) is input of labor services, M(t) is input of intermedi ate purchases, and t is time. Differentiating equation (1) with respect to time, and with some algebraic manipulations, the sources-of-growth equation is, (2) Q — Q k L M — A + w k — +W i— + w,„ — , K L mM where A is the rate of change of multifactor productivity, wk is output elasticity (percentage change in output due to a 1-percent change in input) with respect to the capital input, h>, is output elasticity with respect to the labor input, and wm is output elasticity with respect to the inter mediate purchases input. (The dot over a variable indi cates the derivative of the variable with respect to time.) Equation (2) shows the rate of change of output as the sum of the rate of change of multifactor productivity and a weighted average of rates of change of capital, labor, and intermediate purchases inputs. Now, if competitive input markets are assumed, then each input is paid the value of its marginal product. The output elasticities in equation (2) can then be replaced by the factor income shares, 38FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis I\K P>L . and PqQ wm PmM PqQ where Pq is the price of output and Pk, Ph and Pm are the prices paid for the capital, labor, and intermediate pur chases inputs, respectively. Furthermore, if constant returns to scale are assumed, then wk + w, + wm = 1. Equation (2) can be rewritten as (3) K L M Q — -wk — -Wi — —w — K L mM Q In this expression, the growth of multifactor productivity can be seen as a measure of economic progress: it meas ures the increase in output over and above the gain due to increases in inputs. Equation (2) can also be transformed into a contribu tion equation which allows for an analysis of the change in output per employee hour. First, subtract L /L from both sides of equation (2). Because the weights sum to unity, apply the term (wk + wl + wm) to the L /L term inserted on the right-hand side. Next, gather terms with the same weight and derive the following equation: (4) Q L ,K - - - = wk( - - - ) + Q L yK L J wA M L - ~ ) +A M L The left side of equation (4) is the growth rate of output per employee hour. The terms in parentheses on the right side are, in order, the rates of change in the capital-labor ratio and the intermediate purchases-labor ratio. Thus, the rate of growth in output per employee hour can be decomposed into the weighted sum of changes in these ratios plus the change in multifactor productivity. Equations (2), (3), and (4) are Divisia indexes which require continuous data for computation. The b l s multi factor indexes are actually constructed according to a Tornqvist formula which represents a discrete approxima tion to the Divisia index. The rate of change in output or an input is calculated as the difference from one period to the next in the natural logarithms of the variables. For example, Q /Q is calculated as In Q(t) - In Q ( t- 1). In dexes are then constructed from the antilogarithms of this differential. The weights wk ,W/, and wm are calculated as the arithmetic averages of the respective shares in time periods t and t - 1. Major Agreements Expiring Next Month This list of selected collective bargaining agreements expiring in May is based on information collected by the Bureau’s Office of Compensation and Working Conditions. The list includes agreements covering 1,000 workers or more. Private industry is arranged in order of Standard Industrial Classification. Employer and location Industry or activity Labor organization1 Number of workers Private Mining......................................... Homestake Mining Co. (Lead, Sd) ......................................................... United Steelworkers........................ 1,125 Construction............................... Kanawa Valley Builders Association (Charlestown, wv, area).............. Associated General Contractors (Detroit, mi) ...................................... Associated General Contractors (Detroit, mi) ...................................... Associated General Contractors (Detroit, mi) ...................................... Associated General Contractors (Columbus, oh) ................................ Laborers........................................... Carpenters........................................ Laborers........................................... Operating Engineers........................ Laborers........................................... 1,000 6,000 1,650 7,500 1,700 Fox Valley Contractors Association (Illinois)....................................... Associated General Contractors (Eastern Massachusetts)................... Associated General Contractors (Alabama).......................................... Associated General Contractors (Central Illinois)................................ Michigan Road Builders Association (Michigan).................................. Carpenters........................................ Carpenters........................................ Various unions.................................. Laborers........................................... Laborers........................................... 1,100 4,200 2,000 6,000 2,000 Michigan Road Builders Association..................................................... Idaho Employers Bargaining Council (Southern Idaho)....................... Associated General Contractors (Western and Central Washington) .. Associated General Contractors (Western and Central Washington) .. Associated General Contractors (Seattle and Tacoma, wa, area)........ Associated General Contractors (Western Washington) ...................... Operating Engineers........................ Various unions.................................. Carpenters........................................ Laborers........................................... Operating Engineers........................ Teamsters ........................................ 2,500 3,450 7,000 4,500 3,200 1,100 Underground Contractors Association (Chicago, il) ............................ Associated General Contractors (Rhode Island)................................... National Electrical Contractors Association (White Plains, ny) ......... Painting and Decorating Contractors (Michigan) ................................ National Electrical Contractors Association (Southeastern Michigan). Laborers........................................... Carpenters........................................ Electrical Workers (ibew) ............... Painters............................................. Electrical Workers (ibew) ............... 1,600 1,500 1,500 1,300 3,500 Metropolitan Detroit Plumbing and Mechanical Contractors (Detroit, mi, area) National Electrical Contractors Association (Los Angeles, ca) ........... National Electrical Contractors Association (Colorado) ...................... Sheet Metal and Air Conditioning Contractors Association (Northwest Washington) Associated General Contractors (Columbus, oh) ................................ Plumbers and Pipe Fitters ............... 3,000 Electrical Workers (ibew) ............... Electrical Workers (ibew) ............... Sheet Metal Workers....................... 6,000 1,800 1,100 Carpenters........................................ 3,000 Seafarers........................................... Bakery, Confectionery and Tobacco Workers Teamsters ........................................ Bakery, Confectionery and Tobacco Workers 1,000 1,350 ...................................................... Clothing and Textile Workers......... 2,000 Paper and allied products........... Kimberly-Clark Corp. (Memphis, TN)................................................... Union Camp Corp. (Savannah, Ga) ....................................................... James River Corp. (Green Bay, wi).................................... .................. United Paperworkers....................... United Paperworkers....................... United Paperworkers....................... 1,250 1,000 1,000 Chemicals and allied products ... BASF Corp. (Enka, ......................................................................... United Textile Workers................... 1,000 PPG Industries, Inc............ .......... ......................................................... Owens-Coming Fiberglas Corp. (Aiken, sc) ........................................ Machinists ....................................... Teamsters ........................................ 1,050 1,250 Food and kindred products........ California and Hawaiian Sugar Co. (California).................................... Wholesale Bakers Group (California) ................................................... J. R. Simplot (Caldwell, id) .................................................................... Entenmann’s Inc. (Long Island, ny) ...................................................... Textile mill products................... Stone, clay, and glass products... Cone Mills Corp. (Greensboro, nc) nc) 1,300 1,250 See footnote at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 39 MONTHLY LABOR REVIEW April 1989 • Major Agreements Expiring Next Month Continued— Major Agreements Expiring Next Month Industry or activity Employer and location Labor organization' Number of workers Fabricated metal products......... Master Lock Co. (Milwaukee, w i)...................... Auto Workers ............................... 1,050 Electrical and electronic equipment Leviton Manufacturing Co. (Hillsgrove, Electrical Workers ( i b e w ............... 1,500 Public utilities.............................. AT&T Technologies (Interstate)............................... General Telephone Co. of the Southwest (Interstate)............... Connecticut Light and Power Co............................. Washington Gas Light Co. (Washington, D C , area) .................... Toledo Edison Co. (Toledo, o h ) ................... Communications Workers............... Communications Workers............... Electrical Workers ( i b e w ) ............................ Various unions.................................. Electrical Workers ( i b e w ) ............... 155,000 8,000 2,350 1,800 1,100 Retail trade.................................. Woodward & Lothrop, Inc. (Washington, d c , area)............... Nordstrom Inc. (Seattle, w a , area) ............... Allied Employers, Inc. (Puget Sound, w a , area)...................... Food and Commercial Workers....... Food and Commercial Workers....... Food and Commercial Workers....... 5,500 1,600 12,000 Services....................................... Nevada Resort Association (Las Vegas, Hotel Employees and Restaurant Employees Hotel Employees and Restaurant Employees Hotel Employees and Restaurant Employees 25,000 r i) n v ) Sacramento hotels and motels (Sacramento, .................................... ............ c a ) .................. Minneapolis hotels and motels .............................. ) 2,100 2,000 Public Medical services.......................... 'Affiliated with a f l - cio 40FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Michigan: University of Michigan nurses (Ann Arbor)................ American Nurses Association......... except where noted as independent (Ind.). A note on communications The Monthly Labor Review welcomes communications that supple ment, challenge, or expand on research published in its pages. To be considered for publication, communications should be factual and analytical, not polemical in tone. Communications should be addressed to the Editor-in-Chief, M onthly Labor Review, Bureau of Labor Statistics, U.S. Department of Labor, Washington, DC 20212. 1,100 Developments In Industrial Relations Meatpacking settlements Farmstead Foods employees in Cedar Rapids, i a , and Albert Lea, m n , accepted a 40-month contract proposal that was essentially the same as one they rejected 3 months earlier. According to the United Food and Com mercial Workers local union in Cedar Rapids, Farmstead was unable to significantly improve the offer because of intense competition from lower cost nonunion firms. The company also faced the possibility of competition from Quality Pork Processors of Dallas, t x , which was reopen ing a hog slaughtering line in a Geo. A Hormel & Co. plant in nearby Austin, m n , after negotiating wage and benefit terms with the union’s Local 9. The slaughtering line— but not pork processing— was closed in January 1988 because of high labor costs, according to Hormel. The Farmstead contract, covering 2,700 hog slaughter ing and processing employees, provided for three hourly wage increases of 10, 12, and 18 cents, bringing base pay to $9.10 in January 1992. The employees will also receive a lump-sum payment in December 1990 equal to 10 cents for each hour worked in 1989. Local 9’s settlement with Quality Pork Processing in cluded a company pledge to hire the employees it will need (variously estimated at 250 to 600) from a pool of 950 people who lost jobs when Hormel closed the hog slaughtering line. The agreement calls for an initial base wage rate of $7 an hour, rising to $9.10 in 1992. The wage rate drew criticism from leaders of the union’s locals at the two Farmstead plants. They contend that Quality Pork would have a cost advantage in buying hogs from farmers. However, Local 9 officials in Austin maintain that the combined wage-cost of the Quality Pork-Hormel operation would be comparable to that at Farmstead. Hormel, which buys carcasses from the Qual ity Pork slaughtering operation, pays its workers $10.20 an hour, rising to $10.70 by March 1990 under a contract with the union. Meatpackers such as Hormel provide “Developments in Industrial Relations” is prepared by George Ruben of the Division of Developments in Labor-Management Relations, Bureau of Labor Statistics, and is largely based on information from secondary sources. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis higher compensation for processing employees because profits are higher on such operations than on slaughtering. Meatpacking plant acts to curb injuries Cumulative trauma injuries, which have become of in creasing concern in a number of industries, were addressed in a program adopted by ib p Inc. and the Food and Com mercial Workers for the company’s flagship meatpacking plant in Dakota City, n e . A company official explained that other ib p plants were initially excluded so that the program could be tried in “a controlled environment, not helterskelter.” Some results might be seen in 6 months or so; other results might take 2 years. Cumulative trauma injuries (carpal tunnel syndrome, for example) usually result from repetitive motions, such as those performed by workers on slaughtering lines. The agreement calls for: • training certain workers as “ergonomics monitors” to identify injury-inducing jobs and recommend solutions (disputes, if any, between union and management re garding the solutions will be resolved by a joint committee); • training new employees in avoiding stressful work methods; • developing new work-station layouts to ease physical strain on employees; and • initiating a medical program to treat and rehabilitate injured employees. The 3-year agreement came less than 2 years after the Food and Commercial Workers began a campaign to pub licize alleged unsafe working conditions at the plant. Later, the Occupational Safety and Health Administra tion intensified enforcement activity in the meatpacking industry, culminating in a 1987 proposal to fine ib p $5.7 million for alleged safety and recordkeeping violations. In return for the company’s adopting the new safety pro gram, o s h a reduced the fine to $975,000. ConAgra to use robots in slaughterhouses ConAgra announced that it would install robots in some of its slaughterhouses by the end of 1989. A com pany official said that the goal is “to try to make this a 41 MONTHLY LABOR REVIEW April 1989 • Developments in Industrial Relations safer place to work” by eliminating some of the more difficult tasks employees must perform. A spokesperson for the Food and Commercial Workers said that any resulting loss of jobs was acceptable if the use of robots improves the quality of the remaining jobs and increases safety. Although ConAgra’s use of robots would be the first in animal slaughtering, Geo. A. Hormel & Co. already uses robots in producing processed meats. Danish pork houses also employ robots. California hotel and restaurant employees settle In Los Angeles, c a , 6,500 workers were covered by a settlement between the 16-member Hotel and Restaurant Employers Council and the Hotel Employees and Restau rant Employees union. The new contract, effective immediately and running to April 15, 1992, replaces one that was scheduled to expire March 1, 1989. The new contract provided for nontipped employees to receive a wage increase of 50 cents an hour retroactive to June 1, 1988, a 25-cent increase in March 1989, and 35-cent in creases in March of 1990 and 1991. For tipped employees, increases are 37, 15, 15, and 15 cents an hour on the corresponding dates. The agreement also provided for transferring persons who bus tables from the tipped category to the nontipped category, resulting in a pay increase; broadening the se niority preference provision to apply to work scheduling, shifts, days off, promotions, job transfers, and bumping rights; an employer-financed legal services plan; and an employer obligation of 5 cents per hour worked for a new program of the union’s choice. Coors employees reject union representation The latest occurrence in the long dispute between Adolph Coors Co. and organized labor was an election at the company’s Golden, co, brewery in which the employ ees decisively rejected representation by the Teamsters. The tally was 1,081 votes against union representation and 413 in favor. David Laughton, director of the union’s Brewery and Soft Drink Worker Conference, said the organizing cam paign was initiated in response to requests from Coors employees and “if we come back again, it will be in re sponse to their [future activity].” Laughton said he was satisfied with the fairness of the organizing contest and election and that organized labor would not resume its boycott of Coors’ products. In August 1987, the a f l - c i o and Coors had negoti ated an end to the 10-year-old boycott campaign in return for company assurances that Coors employees would be allowed “to freely choose union representation or refrain from doing so.” Following the Teamsters reaffiliation with the a f l - c i o later in the year, an arbitrator selected Digitized for 42FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis the Teamsters for the organizing role from among several competing member unions. The Coors employees had been represented by an a f l - c i o affiliated local union until 1977, when it was ousted in a representation election following a collective bargaining impasse. uaw organizes gm salaried workers The Auto Workers attained an organizing victory at General Motors Corp. ( g m ) when salaried employees at the company’s payroll check processing operation in Flint, m i , voted to be represented by the union. The tally was 32-28, with one eligible employee not voting. Despite several attempts in recent years, this was the union’s first win among salaried employees at Flint since 1972, when about 30 nurses at the Buick Motor Division voted for Auto Workers representation. A union representative said, “we’ve got a lot of other salaried (organizing) drives going, but this one was the toughest and most important of all, because we actually got into a salaried unit.” The union claimed that the organizing success at Flint was aided by g m ’s 1988 decision to increase health insurance deductibles, which angered employees. An administrator of the check processing unit said, “we are disappointed . . . but we do respect our employees’ right to be represented by a union.” Nationwide, fewer than 300 of g m ’s 108,000 salaried employees belong to the Auto Workers, according to the company. The union represents all of g m ’s 335,000 pro duction workers, except for 20,000 represented by the Electronic Workers and 4,000 represented by the Rubber Workers. Elsewhere in the industry, the Auto Workers represents production workers and some nonmanagement salaried employees at Chrysler Corp. and production workers at Ford Motor Co. Court upholds invalidation of containers rules The International Longshoremen’s Association ( i l a ) and Atlantic and Gulf Coast shippers, already facing daunting problems in their 1989 contract negotiations, faced another problem when the Supreme Court let stand a 1987 Federal Maritime Commission ruling invalidating their “Rules on Containers.” The rules, adopted in 1959, had reserved to i l a members the packing and unpacking of containerized cargo within 50 miles of a port where the union holds bargaining rights. In 1980 and 1985, the Su preme Court held that the container rules were valid work preservation measures consistent with labor law. The Court accepted the Maritime Commission’s 1987 ruling because it was limited to a finding that the negotiated rules imposed unwarranted costs on shippers. The container rules have been a cornerstone of the bargaining relationship since their inception, giving em ployers the right to automate operations in return for guaranteed work for employees and annual pay guaran tees they receive in most ports, financed by an employer payment for each container handled. Other issues to be addressed in a new contract to suc ceed the one scheduled to expire in September 1989 include increasing competition for cargo from non-iLA ports and reduced shipments of some types of cargo, par ticularly in the South. In the last round of bargaining, in 1986, the workers in the southern ports generally ac cepted wage cuts, while those in the northern ports won wage increases. Legal rulings • The Department of Labor ruled that special local union assessments to subsidize wage costs for unionized employers are not legal under the Copeland AntiKickback Act and the Davis Bacon Act. In issuing the ruling, the Department rejected the contention of the Associated Builders and Contractors that criminal prosecution was also warranted against the defendant, Local 595 of the International Brotherhood of Elec trical Workers, located in Oakland, CA. The trade association’s complaint arose from the local union’s practice of financially aiding employers with whom it had collective bargaining agreements to help them counter the labor cost advantages of nonunion firms. The aid, which was approved by a majority vote of the local’s members, emanated from an assessment on all members equal to 3 percent of their earnings. • General Motors Corp. ( g m ) settled charges that it had discriminated against black employees in pay and promotions. Under the consent accord, which did not include an admission of guilt by the company, g m will track the careers of black “salaried” employees to assure that they fare the same as do whites. Factors to be used in assessing the qualifications of the employees are total time with the company, time in the current job, years of education, area of study, and degrees earned and when the degree was obtained. If, after considering the factors, the percentage of promotions is substantially less among blacks than among whites, g m will be required to correct the imbalance. The aim is not to ensure promotions for specific employees, but to attain equality in three broad areas: clerical, engi neering, and manufacturing supervision. The plan applies to g m ’s nonexecutive salaried employees in Michigan, Ohio, and Indiana, or about 75 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis percent of its total salaried employees, 7,000 of whom are black. The plaintiffs’ attorney said that, unlike the typical plan which has rather rigid goals, this plan is better because it accommodates the legitimate objectives of management and employees without resorting to a “myriad of exceptions.” The plan provides for annual reviews of the results over a 5-year period, with provision for financial penal ties if g m does not conform to the formula, g m would not estimate the plan’s cost, but attorneys for the plain tiffs estimated as much as $53 million over the 5 years. • Chrysler Corp. agreed to pay $8.1 million to a group of nonunion salaried employees forced into retirement in the wake of the company’s financial crisis that began in 1979. Chrysler’s consent decrees with the Equal Employment Opportunity Commission, ending the long legal dispute, provide for payments totaling $2.9 mil lion to 82 employees who were involuntarily retired “at corporate option” and $5.1 million to 149 employees who signed “voluntary” retirement agreements that contained illegal conditions. The settlement came after Chrysler lost in proceedings before the Commission and on appeal to a Federal district court. In its defense, Chrysler presented a “failing company” justification for the retirements. • Nissan Motor Corp.’s distributor in the United States settled 45 -year-old charges by the Equal Employment Opportunity Commission that the unit had discrim inated against minorities, women, and older employees. While not adm itting any discrim ination, an official of the Japanese vehicle producer conceded that “there was room for improvement in the way we developed opportunities for protected employees, and, in that regard, we are specifically committed to implementing several changes in our practices.” Under the settlement, which did not involve Nissan’s manufacturing plant in Smyrna, t n , the company agreed to give managerial jobs to 68 current employees who were denied promotions between June 1981 and December 1987; pay a total of $605,600 to the 68 employees and others who took early retirement after not being “properly considered” for promotion; drop a requirement that employees have a college degree to be considered for promotion; advertise managerial job openings within the company more frequently; and require supervisors to attend classes on preventing discriminatory practices. 43 Book Reviews Numbers that work The U.S. Economy Demystified: What the Major Eco nomic Statistics Mean and Their Significance for Business. Rev. ed. By Albert T. Sommers with Lucie R. Blau. Lexington, m a , D. C. Heath and Co., 1988. 154 pp. $19.95, cloth; $13.95, paper. The purpose of this book is to increase the reader’s ability to understand the major data series on the U.S. economy and thereby to enable the reader “to develop confidence in his knowledge of current economic events, and to sense the probable range of future developments.” According to Albert T. Sommers, the book is intended, not for professional economists, but rather for business decision-makers, financial executives, and private inves tors “who seek a compact, digestible guide to the evidence on economic conditions.” Therefore, this volume presents no ground-breaking analysis (except, by definition, for the author’s discussion of housing-start data). What it does present is a lucid, edifying, and very readable explanation of the major macroeconomic data series. A large number of charts clarify the discussion, and a unique— and very useful— feature of the book is a set of calendars showing the approximate release dates of the important economic indicators. Another unique feature of the book is a list of the addresses and telephone numbers of the agencies that publish the major economic statistics. Sommers reports in his preface that the book has been adopted as a supplementary text in many economics courses. I heartily recommend the book for this purpose. While standard macro textbooks do a good job of present ing theory, they generally do not teach the student how to interpret the various statistics relating to the current busi ness environment. Sommers’ book fills this void nicely. I must note one irony in the book. Sommers comments that “in the years since 1984” the U.S. economy has re mained sluggish despite stimulative economic policy, but that this paradox “does not reflect defects in the statistical system.” However, recently revised gnp data show that the economy has not, in fact, been sluggish. Thus, the growth rate for 1985 has been revised from 3.0 to 3.4 percent and the rate for 1987 from 2.9 to 3.4 percent, largely because sales to consumers, government, and foreigners now appear to have been stronger than was apparent earlier. Thus, despite Sommers’ comment, the fault appears to lie not in our sales, but in the stats. Digitized for 44FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Sommers’ introduction says that the book is designed to help the reader understand the issues confronting the U.S. economy “in the remainder of this decade.” I infer from that statement that the author plans another revision in the early 1990’s. Another revision would be most wel come, not only because any discussion of statistical series and their meaning must be updated periodically, but also because the revision would afford the author an opportu nity to correct some flaws that mar an otherwise excellent work. The flaws are of two types. First, the book short changes the reader in its coverage of some important data series. For example, while acknowledging that the index of leading indicators “receives enormous attention from the press,” the author does not offer any discussion of the strengths and weaknesses of the index as a forecasting device. Employment data are similarly shortchanged; the discussion of the differences between the household and payroll measures of employment, for example, is con fined to a single sentence on page 80. The employment data warrant more attention, because they are the first of the comprehensive monthly indicators to appear, and they provide business analysts with the earliest assess ment of the economy’s performance in the previous month. Moreover, the differing behavior of the two em ployment series has been of great interest to businessconditions analysts during the current economic expansion. The book’s second flaw consists of a number of errors of fact and some statements of questionable analytical accuracy. Thus, on page 30, the author writes that “dura ble goods” in the national-income-and-product accounts are those with an expected life of “more than a year.” The standard is actually 3 years. On page 7, Sommers states, “In the automobile market and in the housing market the term of loans stopped rising several years ago.” In fact, Federal Reserve Board data show that the average term of a new-car loan at auto finance companies was 56 months in the spring of 1988, up from 50 months in 1986 and 48 months in 1984. On a more conceptual matter, Sommers implies on pages 92-93 that the Keynesian multiplier applies only to investment goods, and not to consumption goods. In fact, it applies to both. A most puzzling statement ap pears at the bottom of page 79: “It is often argued (with some justice) that unemployment compensation tends to elevate unemployment, but it is worth noting that on average more than half the unemployed are unemployed because they lost a job.” I am mystified by the “but” part of this sentence. Does Sommers mean that the high pro portion of job losers among the unemployed shows that unemployment insurance (ui) is not a factor in increasing unemployment? By and large, it is only job losers (as opposed to job leavers and idle labor force entrants and reentrants) who are eligible for ui, and so, if anything, the high proportion of job losers among the unemployed sup ports the hypothesis that ui increases unemployment. (According to that hypothesis, UI increases unemploy ment by lengthening the job search of job losers.) These flaws aside, the quality of Sommers’ work is cer tainly a business conditions economist’s best kind of unemployment insurance. —E dw ard I. Steinberg Economist AT&T Publications received Agriculture and natural resources Asefa, Sisay, ed., World Food and Agriculture: Economic Prob lems and Issues. Kalamazoo, Mi, W. E. Upjohn Institute for Employment Research, 1988, 144 pp. $15.95, cloth; $8.95, paper. Economic and social statistics Frumkin, Norman, Tracking America's Economy. Armonk, n y , M. E. Sharpe, Inc., 1988, 250 pp. $35, cloth; $14.95, paper. Greenwald, Mathew, “Bad News for the Baby Boom,” Ameri can Demographics, February 1989, pp. 34-37. Hall, Bronwyn H. and others, The r & d Master File Documenta tion. Cam bridge, m a , N ational Bureau of Econom ic Research, Inc., 1988, 49 pp. (Technical Working Paper Series, 72.) $2, paper. Kotlikoff, Laurence J., Estimating the Age-Productivity Profile Using Lifetime Earnings. Cambridge, m a , National Bureau of Economic Research, Inc., 1988, 26 pp. (Working Paper Series, 2788.) $2, paper. Raymondo, James C., “ How to Choose a Projection Tech nique,” Am erican Demographics, F ebruary 1989, pp. 38-39. Tracy, Joseph, Testing Strategic Bargaining Models Using Stock M arket Data. Cambridge, MA, National Bureau of Eco nomic Research, Inc., 1988, 35 pp. (Working Paper Series, 2754.) $2, paper. Waldrop, Judith, “ 2010,” American Demographics, February 1989, beginning on p. 18. International economics Katz, Lawrence F. and Lawrence H. Summers, Can Inter industry Wage Differentials Justify Strategic Trade Policy? Cambridge, m a , National Bureau of Economic Research Inc., 1988, 42 pp. (Working Paper Series, 2739.) $2, paper. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis McFetridge, Donald G., Trade Liberalization and the M ultina tionals. Ottawa, Economic Council of Canada, 1989, 66 pp., bibliography. Available from Canadian Government Pub lishing C enter, Supply and Services Canada, O ttaw a Canada K1A OS9. Mincer, Jacob and Yoshio Higuchi, Wage Structures and Labor Turnover in the United States and Japan. Reprinted from the Journal o f the Japanese and International Economies, Vol. 2, 1988, pp. 97-133. Cambridge, m a , National Bureau of Economic Research, Inc., 1988. ( n b er Reprint, 1101.) $2, paper. Labor force Cockburn, Cynthia, Machinery o f Dominance: Women, Men, and Technical Know-How. Boston, Northeastern University Press, 1988, 282 pp. $32.50. Cook, Alice H., “Public Policies to Help Dual-Earner Families Meet the Demand of the Work W orld,” Industrial and Labor Relations Review, January 1989, pp. 201-15. Freeman, Richard B., ed., Immigration, Trade, and the Labor Market. Cambridge, m a , National Bureau of Economic Re search, Inc., 1988, 38 pp., bibliography, ( n b er Summary Report.) $2, paper. Great Britain, Department of Employment, Employers' Labour Use Strategies: First Report on the 1987 Survey. By Douglas Wood and Patten Smith. London, Department of Employ ment, 1988, 75 pp. (Research Paper, 63.) Gustman, Alan L. and Thomas L. Steinmeier, A Model fo r Ana lyzing Youth Labor M arket Policies. Reprinted from the Journal o f Labor Economics, July 1988, pp. 376-96. Cam bridge, m a , National Bureau of Economic Research, Inc., 1988. ( n b er Reprint, 1097.) $2, paper. Howland, Marie, Plant Closings and Worker Displacement: The Regional Issues. Kalamazoo, m i , W. E. Upjohn Institute for Employment Research, 1988, 172 pp. $18.95, cloth; $11.95, paper. Indexed Bibliography on Alternative Work Schedules. New York, Catalyst, 1988, 36 pp. Johannesson, Jan, On the Composition and Outcome o f Swedish Labour M arket Policy, 1970-1988. Stockholm, Swedish Ministry of Labor, 1988, 41 pp. Konig, Heinz and Winfried Pohlmeier, “Employment, Labour Utilization and Procyclical Labour Productivity,” Kyklos, Vol. 41, 1988, Fasc. 4, pp. 551-72. Work Restructuring: “Introduction,” by Harry C. Katz; “Work Restructuring in the 1980’s: The View from Programs for Employment and Workplace Systems ( pew s ),” by Ann W. Martin; “The Japanese Auto Transplants: Challenges to Conventional Wisdom,” by John Paul MacDuffie; “Manag ing by Stress: The Dark Side of Team Concept,” by Mike Parker and Jane Slaughter; “Participative Consulting,” by Peter Lazes; “Participatory Action Research: Integrating Research and Technical Assistance in Industry,” by Wil liam Foote Whyte, i l r Report, Fall 1988, pp. 4 -3 3 . Management and organization theory Bittel, Lester R., The M cGraw-Hill 36-Hour M anagem ent Course. New York, M cG raw -H ill Publishing Co., 1989, 333 pp. $34.95, cloth; $19.95, paper. Juran, J. M., Juran on Leadership fo r Quality: An Executive Handbook. New York, The Free Press, 1989, 376 pp. $35. 45 MONTHLY LABOR REVIEW April 1989 • Book Reviews Wages and compensation Beadle, Carson E., The Future of Employee Benefits: More Mandates Ahead,” Compensation and Benefits Review, No vem ber-Decem ber 1988, pp. 36-44. Browne, M. Neil and Brian Powers, “Henry George and Com parable Worth: Hypothetical Markets as a Stimulus for Reforming the Labor M arket,” American Journal o f Eco nomics and Sociology, October 1988, pp. 461-72. Great Britain, Department of Employment, The Distribution o f Earnings, 1973 to 1986. By Mark Adams. London, Depart ment of Employment, Employment Market Research Unit, 1988, 31 pp. (Research Paper, 64.) Ohsfeldt, Robert L. “The Effect of a m a Membership on Physi cians Earnings, Industrial and Labor Relations Review October 1988, pp. 20-33. Putti, Joseph M. and Wong Kwei Cheong, “Flexible Wage Sys tems in Newly Industrialized Countries,” Compensation and Benefits Review, N ovem ber-D ecem ber 1988 nn 4 6 -5 5 . Zax, Jeffrey S., “Wages, Nonwage Compensation, and Munici pal Unions,” Industrial Relations, Fall 1988, pp. 301-17. Digitized 46 for FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Welfare programs and social insurance Rodgers, Harrell R., Jr., ed., Beyond Welfare: New Approaches to the Problem o f Poverty in America. Armonk, NY, M. E. Sharpe, Inc., 1988, 169 pp. $39.95, cloth; $14.95, paper. Worker training and development Carnevale, Anthony P., Leila J. Gainer, Ann S. Meltzer, Work place Basics: The Skills Employers Want. Alexandria, v a , American Society for Training and Development, 1988, 33 pp. $2, paper. Chusmir, Leonard H. and Victoria Franks, “Stress and the Woman Manager,” Training & Development Journal, Octo ber 1988, pp. 66-70. Sanders, Jo, Staying Poor: How the Job Training Partnership Act Fails Women. Metuchen, n j , The Scarecrow Press, Inc., 1988, 181 pp. $17.50, paper. Spain, Ministry of Labor and Social Security, Programmes Sup porting Job Creation and Types o f Contracts. M adrid, Ministry of Labor and Social Security, 1988, 39 pp. Current Labor Statistics Schedule of release dates for major statistical series .................................................................................................... 48 Notes on Current Labor Statistics............................................................................................................... 49 bls Comparative indicators 1. Labor market indicators ............................................................................ ................................................................................................... 2. Annual and quarterly percent changes in compensation, prices, and productivity....................................................... 3. Alternative measures of wage and compensation changes............................................................................................................................ 59 60 60 Labor force data 4. Employment status of the total population, data seasonally adjusted........................................................................................................ 5. Employment status of the civilian population, data seasonally adjusted ................................................................................................. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. Selected employment indicators, data seasonally adjusted.......................................................................................................................... Selected unemployment indicators, data seasonally adjusted..................................................................................................................... Unemployment rates by sex and age, data seasonally adjusted.................................................................................................................. Unemployed persons by reason for unemployment, data seasonally adjusted......................................................................................... Duration of unemployment, data seasonally adjusted.................................................................................................................................. Unemployment rates of civilian workers, by State........................................................................................................................................ Employment of workers by State ............................. Employment of workers by industry, data seasonally adjusted.................................................................................................................. Average weekly hours by industry, data seasonally adjusted...................................................................................................................... Average hourly earnings by industry, dataseasonally adjusted.................................................................................................................. Average hourly earnings by industry............................................................................................................................................................... Average weekly earnings by industry............................................................................................................................................................... Diffusion indexes of employment change, data seasonally adjusted.......................................................................................................... Annual data: Employment status of the noninstitutional population........................................................................................................ Annual data: Employment levels by industry ................................................................................................................................................ Annual data: Average hours and earnings levels by industry..................................................................................................................... 61 62 63 64 65 65 65 66 66 67 68 69 69 70 71 72 72 73 Labor compensation and collective bargaining data 22. 23. 24. 25. 26. 27. 28. 29. Employment Cost Index, compensation, by occupation and industry group........................................................................................... Employment Cost Index, wages and salaries, by occupation and industrygrou p ................................................................................... Employment Cost Index, private nonfarm workers, by bargaining status,region, and area size........................................................... Specified compensation and wage adjustments from contract settlements, and effective wage adjustments, situations covering 1,000 workers or more........................................................................................................................................................................ Average specified compensation and wage adjustments, bargaining situations covering 1,000 workers or m ore............................ Average effective wage adjustments, bargaining situations covering 1,000 workers or more............................................................... Specified compensation and wage adjustments, State and local government bargaining situations covering 1,000 workers or more .................................................................................................................................................................................................. Work stoppages involving 1,000 workers or m o r e ........................................................................................... ............................................ 74 75 76 77 77 78 78 78 Price data 30. Consumer Price Index: U.S. city average, by expenditure category and commodity and service groups ........................................... 31. Consumer Price Index: U.S. city average and local data, all item s............................................................................................................ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 79 82 47 MONTHLY LABOR REVIEW 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. April 1989 • Current Labor Statistics Annual data: Consumer Price Index, all items and major groups.............................................................................................................. Producer Price Indexes by stage of processing .............................................................................................................................................. Producer Price Indexes, by durability of product......................................................................................................................................... Annual data: Producer Price Indexes by stage of processing ..................................................................................................................... U.S. export price indexes by Standard International Trade Classification................................................................................................ U.S. import price indexes by Standard International Trade Classification.............................................................................................. U.S. export price indexes by end-use category................................................................................................................................................ U.S. import price indexes by end-use category.............................................................................................................................................. U.S. export price indexes by Standard Industrial Classification................................................................................................................. U.S. import price indexes by Standard Industrial Classification................................................................................................................. 83 84 85 85 86 87 88 88 88 89 Productivity data 42. Indexes of productivity, hourly compensation, and unit costs, data seasonally adjusted...................................................................... 43. Annual indexes of multifactor productivity............ . ...................................................................................................................................... 44. Annual indexes of productivity, hourly compensation, unit costs, and prices ........................................................................................ 89 90 91 International comparisons 45. Unemployment rates in nine countries, data seasonally adjusted .............................................................................................................. 46. Annual data: Employment status of civilian working-age population, ten countries............................................................................. 47. Annual indexes of productivity and related measures, twelve countries................................................................................................... 92 93 94 Injury and illness data 48. Annual data: Occupational injury and illness incidence rates.................................................................................................................... 95 Schedule of release dates for BLS statistical series S e rie s R e le a s e d a te Employment situation ........................ April 7 March Producer Price Indexes..................... April 14 March Consumer Price Index ....................... April 18 March Real earnings................................... April 18 March Major collective bargaining settlements................... April 25 1st quarter 3; 25-28 Employment Cost Index..................... April 25 1st quarter 1-3; 22-24 U.S. Import and Export Price Indexes................................ April 27 1st quarter Productivity and costs: Nonfarm business and manufacturing........................... Nonflnanclal corporations............... Digitized for48 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis P e rio d c o v e re d R e le a s e P e rio d R e le a s e d a te c o v e re d d a te P e rio d c o v e re d May 5 April June 2 May May 12 April June 9 May 2; 33-35 May 18 April June 16 May 2; 30-32 May 18 April June 16 May 14-17 May 25 April May 3 1st quarter June 22 May June 1 1st quarter M L R ta b le num ber 1; 4-21 36-41 2; 42-44 2; 42-44 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, collective bargaining settle ments, 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. 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 1977 = 100, the hourly rate expressed in 1977 dollars is $2 ($3/ 150 X 100 = $2). The $2 (or any other resulting values) are described as “real,” “constant,” or “ 1977” dollars. Additional Information 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 past experience. When new seasonal factors are computed each year, revisions may affect seasonally adjusted data for several preceding years. (Seasonally adjusted data appear in tables 1 -3 , 4 -1 0 , 13, 14, 15, 17, and 18.) Beginning in January 1980, the bls introduced two major modifications in the seasonal adjustment meth odology for labor force data. First, the data are seasonally adjusted with a procedure called x-11 arima , which was developed at Statistics Canada as an extension of the standard x -1 1 method previously used by bls. A detailed description of the procedure appears in The x-11 a r i m a Seasonal Adjustment Method by Estela Bee Dagum (Statistics Canada, Catalogue No. 12-564E, February 1980). The second change is that seasonal factors are calculated for use during the first 6 months of the year, rather than for the entire year, and then are calculated at midyear for the July-December period. However, revisions of historical data continue to be made only at the end of each calendar year. Seasonally adjusted labor force data in tables 1 and 4 -1 0 were revised in the February 1989 issue of the Review, to reflect experience through 1988. Annual revisions of the seasonally adjusted payroll data shown in tables 13 and 17 were made in the July 1988 Review using the x-11 arima seasonal adjustment methodology. New seasonal factors for productivity data in table 42 are usually introduced in the September issue. Seasonally adjusted indexes and percent changes from month to month and from 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 All Items 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 15—are adjusted to eliminate the effect of Data that supplement the tables in this section are published by the Bureau in a variety of sources. News releases provide the latest statistical information published by the Bureau; the major recurring releases are published according to the schedule preceding these general notes. More information about labor force, employment, and unem ployment data and the household and establishment surveys underlying the data are available in Employment and Earnings, a monthly publication of the Bureau. More data from the household survey are published in the data books—Revised Seasonally Adjusted Labor Force Statistics, Bulletin 2306, and Labor Force Statistics Derived From the Current Population Survey, Bulletin 2307. More data from the establish ment survey appear in two data books—Employment, Hours, and Earnings, United States, and Employment, Hours, and Earnings, States and Areas, and the supplements to these data books. More detailed information on employee compensation and collective bargaining settlements is published in the monthly periodical, Current Wage Developments. More detailed data on consumer and producer prices are published in the monthly periodicals, The c p i Detailed Report, and Producer Price Indexes. Detailed data on all of the series in this section are provided in the Handbook o f Labor Statistics, which is published biennally by the Bureau. BLS bulletins are issued covering productivity, injury and illness, and other data in this section. Finally, the Monthly Labor Review carries analytical articles on annual and longer term developments in labor force, employment, and unemployment; em ployee compensation and collective bargaining; prices; productivity; international comparisons; and injury and illness data. Symbols p = preliminary. To increase the timeliness of some series, preliminary figures are issued based on representative but incomplete returns. r = revised. Generally, this revision reflects the availability of later data but may also reflect other adjustments. n.e.c. = not elsewhere classified, n.e.s. = not elsewhere specified. 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-to-population ratio, and https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis unemployment rates for major demographic groups based on the Current Population (“household”) Survey are presented, while meas ures of employment and average weekly hours by major industry sector are given using nonagricultural 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. 49 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics Data on changes in compensation, prices, and productivity are presented in table 2. Measures of rates of change of compensation and wages from the Employment Cost Index program are provided for all civilian nonfarm workers (excluding Federal and household workers) and for all private nonfarm workers. Measures of changes in: consumer prices for all urban consumers; producer prices by stage of processing; and the 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. 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. For detailed descriptions of each data series, see b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988), as well as the additional bulletins, articles, and other publications noted in the separate sections of the Review's “Current Labor Statistics Notes.” Users may also wish to consult Major Programs, Bureau o f Labor Statistics, Report 718 (Bureau of Labor Statistics, 1985). EMPLOYMENT AND UNEMPLOYMENT DATA (Tables 1; 4 -2 1 ) Household survey 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 55,800 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 civilians 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. Members of the Armed Forces stationed in the United States are also included in the employed total. 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 because they were on layoff or waiting to start new jobs within the next 30 days are also counted among the unemployed. The overall unemployment rate represents the number unemployed as a percent of the labor force, including the resident Armed Forces. The civilian employment rate represents the number unemployed as a percent of the civilian labor force. The labor force consists of all employed or unemployed civilians plus members of the Armed Forces stationed in the United States. Persons not in the labor force are those not classified as employed or unemployed; this group includes persons who are retired, those engaged in their own housework, those not working while attending school, those unable to work because of long-term illness, those discouraged from seeking work because of personal or job-market factors, and those who are voluntarily idle. The 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, and members of the Armed Forces stationed in the United States. The labor force participation rate is the proportion of the noninstitutional population that is in the labor force. The employment- Digitized for 50 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis population ratio is total employment (including the resident Armed Forces) as a percent of the noninstitutional population. Notes on the data From time to time, and especially after a decennial census, adjust ments are made in the Current Population Survey figures to correct for estimating errors during the preceding years. These adjustments affect the comparability of historical data. A description of these adjustments and their effect on the various data series appear in the Explanatory Notes of Employment and Earnings. Data in tables 4 -1 0 are seasonally adjusted, based on the seasonal experience through December 1988. Additional sources of information For detailed explanations of the data, see b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). Historical unadjusted data from 1948 to 1987 are available in Labor Force Statistics Derived from the Current Population Survey, Bulletin 2307 (Bureau of Labor Statistics, 1988). Historical seasonally adjusted data appear in Labor Force Statistics Derived from the Current Population Survey: A Data book, Vol. II, Bulletin 2096 (Bureau of Labor Statistics, 1982), and Revised Seasonally Adjusted Labor Force Statistics, 1978-87, Bulletin 2306 (Bureau of Labor Statistics, 1988). A comprehensive discussion of the differences between household and establishment data on employment appears in Gloria P. Green, “Comparing employment estimates from household and payroll sur veys,” Monthly Labor Review, December 1969, pp. 9 -2 0 . 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 more than 300,000 establishments representing all industries except agriculture. 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 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 manufacturing include working supervisors and nonsupervisory workers closely associated with production opera tions. Those workers mentioned in tables 12-17 include production workers in manufacturing and mining; construction workers in con struction; and nonsupervisory workers in the following industries: transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. These groups account for about four-fifths of the total employment on private nonagricultural payrolls. Earnings are the payments production or nonsupervisory workers receive during the survey period, including premium pay 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 nonsu pervisory 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 6-month spans are seasonally adjusted, while those for the 12-month span are unadjusted. Data are centered within the span. The March 1989 Review introduced an expanded index on private nonagricultural employment based on 349 industries, and a new manufacturing index based on 143 industries. These indexes are useful for measuring the dispersion of economic gains or losses and are also economic indicators. Notes on the data Establishment data collected by the Bureau of Labor Statistics are periodically adjusted to comprehensive counts of employment (called “benchmarks”). The latest complete adjustment was made with the release of May 1988 data, published in the July 1988 issue of the Review. Consequently, data published in the Review prior to that issue are not necessarily comparable to current data. Unadjusted data have been revised back to April 1986; seasonally adjusted data have been revised back to January 1983. These revisions were published in the Supplement to Employment and Earnings (Bureau of Labor Statistics, 1988). Unadjusted data from April 1987 forward, and seasonally adjusted data from January 1984 forward are subject to revision in future benchmarks. In the establishment survey, estimates for the 2 most recent months are based on incomplete returns and are published as preliminary in the tables (13 to 18 in the Review). When all returns have been received, the https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis estimates are revised and published as final in the third month of their appearance. Thus, August data are published as preliminary in October and November and as final in December. For the same reason, quarterly establishment data (table 1) are preliminary for the first 2 months of publication and final in the third month. Thus, secondquarter data are published as preliminary in August and September and as final in October. Additional sources of information Detailed national data from the establishment survey are published monthly in the bls periodical, Employment and Earnings. Earlier comparable unadjusted and seasonally adjusted data are published in Employment, Hours, and Earnings, United States, 1909-84, Bulletin 1312-12 (Bureau of Labor Statistics 1985) and its annual supplement. For a detailed discussion of the methodology of the survey, see bls Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). A comprehensive discussion of the differences between household and establishment data on employment appears in Gloria P. Green, “Comparing employment estimates from household and payroll sur veys,” Monthly Labor Review, December 1969, pp. 9-2 0 . Unemployment data by State Description of the series Data presented in this section are obtained from two major sources— the Current Population Survey (cps) and the Local Area Unemploy ment Statistics (laus) program, which is conducted in cooperation with State employment security agencies. Monthly estimates of the labor force, employment, and unemploy ment 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 and the Public Works and Economic Development Act. 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 11 States— California, Florida, Illinois, Massachusetts, Michigan, New York, New Jersey, North Carolina, Ohio, Pennsylvania, and Texas— are obtained directly from the cps, because the size of the sample is large enough to meet bls standards of reliability. Data for the remaining 39 States and the District of Columbia are derived using standardized procedures established by bls. Once a year, estimates for the 11 States are revised to new population controls. For the remaining States and the District of Columbia, data are benchmarked to annual average cps levels. Additional sources of information Information on the concepts, definitions, and technical procedures used to develop labor force data for States and sub-State areas as well as additional data on sub-States are provided in the monthly Bureau of Labor Statistics periodical, Employment and Earnings, and the annual report, Geographic Profile o f Employment and Unemployment (Bureau of Labor Statistics). See also bls Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). 51 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics COMPENSATION AND WAGE DATA (Tables 1-3; 22-29) C o m pen sa t io n a n d w a g e data are gathered by the Bureau from business establishments, State and local governments, labor unions, collective bargaining agreements on file with the Bureau, and secondary sources. Employment Cost Index Description of the series The Employment Cost Index ( ec i ) 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 uses a fixed market basket of labor—similar in concept to the Consumer Price Index’s fixed market basket of goods and services— to measure change over time in employer costs of employing labor. The index is not seasonally adjusted. Statistical series on total compensation costs, on wages and salaries, and on benefit costs are available for private nonfarm workers excluding proprietors, the self-employed, and household workers. The total compensation costs and wages and salaries series are also available for State and local government workers and for the civilian nonfarm economy, which consists of private industry and State and local government workers combined. Federal workers are excluded. The Employment Cost Index probability sample consists of about 3,400 private nonfarm establishments providing about 18,000 occupa tional observations and 700 State and local government establishments providing 3,500 occupational observations selected to represent total employment in each sector. On average, each reporting unit provides wage and compensation information on five well-specified occupations. Data are collected each quarter for the pay period including the 12th day of March, June, September, and December. Beginning with June 1986 data, fixed employment weights from the 1980 Census of Population are used each quarter to calculate the indexes for civilian, private, and State and local governments. (Prior to June 1986, the employment weights are from the 1970 Census of Population.) These fixed weights, also used to derive all of the industry and occupation series indexes, ensure that changes in these indexes reflect only changes in compensation, not employment shifts among industries or occupations with different levels of wages and compensa tion. For the bargaining status, region, and m etrop olitan / nonmetropolitan area series, however, employment data by industry and occupation are not available from the census. Instead, the 1980 employment weights are reallocated within these series each quarter based on the current sample. Therefore, these indexes are not strictly comparable to those for the aggregate, industry, and occupation 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 payment-in-kind, free room and board, and tips. Digitized for 52FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Notes on the data The Employment Cost Index for changes in wages and salaries in the private nonfarm economy was published beginning in 1975. Changes in total compensation cost— wages and salaries and benefits combined— were published beginning in 1980. The series for 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 (June 1981 = 100) of the quarterly rates of change are presented in the March issue of the bls periodical, Current Wage Developments. Additional sources of information For a more detailed discussion of the Employment Cost Index, see the Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988), and the following Monthly Labor Review articles: “Employment Cost Index: a measure of change in the ‘price of labor’,” July 1975; “How benefits will be incorporated into the Employment Cost Index,” January 1978; “Estimation procedures for the Employment Cost Index,” May 1982; and “Introducing new weights for the Employment Cost Index,” June 1985. Data on the eci are also available in bls quarterly press releases issued in the month following the reference months of March, June, September, and December; and from the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). Collective bargaining settlements Description of the series Collective bargaining settlements data provide statistical measures of negotiated adjustments (increases, decreases, and freezes) in compensa tion (wage and benefit costs) and wages alone, quarterly for private industry and semiannually for State and local government. Compensa tion measures cover all collective bargaining situations involving 5,000 workers or more and wage measures cover all situations involving 1,000 workers or more. These data, covering private nonagricultural indus tries and State and local governments, are calculated using information obtained from bargaining agreements on file with the Bureau, parties to the agreements, and secondary sources, such as newspaper accounts. The data are not seasonally adjusted. Settlement data are measured in terms of future specified adjust ments: those that will occur within 12 months of the contract effective date—first-year—and all adjustments that will occur over the life of the contract expressed as an average annual rate. Adjustments are worker weighted. Both first-year and over-the-life measures exclude wage changes that may occur under cost-of-living clauses that are triggered by future movements in the Consumer Price Index. Effective wage adjustments measure all adjustments occurring in the reference period, regardless of the settlement date. Included are changes from settlements reached during the period, changes deferred from contracts negotiated in earlier periods, and changes under cost-of-living adjustment clauses. Each wage change is worker weighted. The changes are prorated over all workers under agreements during the reference period yielding the average adjustment. Definitions Wage rate changes are calculated by dividing newly negotiated wages by the average straight-time hourly wage rate plus shift premium at the time the agreement is reached. Compensation changes are calculated by dividing the change in the value of the newly negotiated wage and benefit package by existing average hourly compensation, which includes the cost of previously negotiated benefits, legally required social insurance programs, and average hourly earnings. Compensation changes are calculated by placing a value on the benefit portion of the settlements at the time they are reached. The cost estimates are based on the assumption that conditions existing at the time of settlement (for example, methods of financing pensions or composition of labor force) will remain constant. The data, therefore, are measures of negotiated changes and not of total changes of employer cost. Contract duration runs from the effective date of the agreement to the expiration date or first wage reopening date, if applicable. Average annual percent changes over the contract term take account of the compounding of successive changes. Notes on the data Comparisons of major collective bargaining settlements for State and local government with those for private industry should note differences in occupational mix, bargaining practices, and settlement characteris tics. Professional and white-collar employees, for example, make up a much larger proportion of the workers covered by government than by private industry settlements. Lump-sum payments and cost-of-living adjustment (co la ) clauses, on the other hand, are rare in government but common in private industry settlements. Also, State and local government bargaining frequently excludes items such as pension benefits and holidays, that are prescribed by law, while these items are typical bargaining issues in private industry. Additional sources of information For a more detailed discussion on the series, see the b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). Comprehen sive data are published in press releases issued quarterly (in January, April, July, and October) for private industry, and semiannually (in February and August) for State and local government. Historical data and additional detailed tabulations for the prior calendar year appear in the April issue of the b l s periodical, Current Wage Developments. 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 time lost because of stoppage. Data are largely from newspaper accounts and cover only establish ments directly involved in a stoppage. They do not measure the indirect or secondary effect of stoppages on other establishments whose employees are idle owing to material shortages or lack of service. Definitions Number of stoppages: The number of strikes and lockouts involving 1,000 workers or more and lasting a full shift or longer. Workers involved: The number of workers directly involved in the stoppage. Number of days idle: The aggregate number of workdays lost by workers involved in the stoppages. Days of idleness as a percent of estimated working time: Aggregate workdays lost as a percent of the aggregate number of standard workdays in the period multiplied by total employment in the period. Notes on the data This series is not comparable with the one terminated in 1981 that covered strikes involving six workers or more. Additional sources of information Data for each calendar year are reported in a bls press release issued in the first quarter of the following year. Monthly and historical data appear in the bls periodical, Current Wage Developments. Historical data appear in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). Other compensation data Other bls data on pay and benefits, not included in the Current Labor Statistics section of the Monthly Labor Review, appear in and consist of the following: Industry Wage Surveys provide data for specific occupations selected to represent an industry’s wage structure and the types of activities performed by its workers. The Bureau collects information on weekly work schedules, shift operations and pay differentials, paid holiday and vacation practices, and information on incidence of health, insurance, and retirement plans. Reports are issued throughout the year as the surveys are completed. Summaries of the data and special analyses also appear in the Monthly Labor Review. Area Wage Surveys annually provide data for selected office, clerical, professional, technical, maintenance, toolroom, powerplant, material movement, and custodial occupations common to a wide variety of industries in the areas (labor markets) surveyed. Reports are issued throughout the year as the surveys are completed. Summaries of the data and special analyses also appear in the Review. The National Survey o f Professional, Administrative, Technical, and Clerical Pay provides detailed information annually on salary levels and distributions for the types of jobs mentioned in the survey’s title in private employment. Although the definitions of the jobs surveyed reflect the duties and responsibilities in private industry, they are designed to match specific pay grades of Federal white-collar employees under the General Schedule pay system. Accordingly, this survey provides the legally required information for comparing the pay of salaried employees in the Federal civil service with pay in private industry. (See Federal Pay Comparability Act of 1970, 5 u.s.c. 5305.) Data are published in a bls news release issued in the summer and in a bulletin each fall; summaries and analytical articles also appear in the Review. Employee Benefits Survey provides nationwide information on the incidence and characteristics of employee benefit plans in medium and large establishments in the United States, excluding Alaska and Hawaii. Data are published in an annual bls news release and bulletin, as well as in special articles appearing in the Review. PRICE DATA (Tables 2; 30-41) P rice 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 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis base period (1982 = 100 for many Producer Price Indexes or 1982-84 - 100 for many Consumer Price Indexes, unless otherwise noted). 53 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics 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 1982-84 buying habits of about 80 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, short-term workers, the unemployed, retirees, and others not in the labor force. The c p i is based on prices of food, clothing, shelter, fuel, drugs, transportation fares, doctors’ and dentists’ fees, and other goods and services that people buy for day-to-day living. The quantity and quality of these items are kept essentially unchanged between major revisions so that only price changes will be measured. All taxes directly associated with the purchase and use of items are included in the index. Data collected from more than 21,000 retail establishments and 60,000 housing units in 91 urban areas across the country are used to develop the “U.S. city average.” Separate estimates for 27 major urban centers are presented in table 31. 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 measured for the c p i -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 c p i -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 C Pi-u and c p i -w were introduced with release of the January 1987 data. Additional sources of information For a discussion of the general method for computing the c p i , see b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). The recent change in the measurement of homeownership costs is discussed in Robert Gillingham and Walter Lane, “Changing the treatment of shelter costs for homeowners in the CPI,” Monthly Labor Review, July 1982, pp. 9 -1 4 . An overview of the recently introduced revised c p i , reflecting 1982-84 expenditure patterns, is contained in The Consumer Price Index: 1987 Revision, Report 736 (Bureau of Labor Statistics, 1987). Additional detailed c p i data and regular analyses of consumer price changes are provided in the c p i Detailed Report, a monthly publication of the Bureau. Historical data for the overall c p i and for selected groupings may be found in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). 54 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Producer P rice 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 3,100 commodities and about 75,000 quotations per month selected to represent the movement of prices of all commodities produced in the manufacturing, agriculture, forestry, fishing, mining, gas and electricity, and public utilities sectors. The stage of processing structure of Producer Price Indexes 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. 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 1987, 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 1982. The detailed data are aggregated to obtain indexes for stage-ofprocessing 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. Notes on the data Beginning with the January 1986 issue, the Review is no longer presenting tables of Producer Price Indexes for commodity groupings, special composite groups, or sic industries. However, these data will continue to be presented in the Bureau’s monthly publication Producer Price Indexes. The Bureau has completed the first major stage of its comprehensive overhaul of the theory, methods, and procedures used to construct the Producer Price Indexes. Changes include the replacement of judgment sampling with probability sampling techniques; expansion to systematic coverage of the net output of virtually all industries in the mining and manufacturing sectors; a shift from a commodity to an industry orientation; the exclusion of imports from, and the inclusion of exports in, the survey universe; and the respecification of commodities priced to conform to Bureau of the Census definitions. These and other changes have been phased in gradually since 1978. The result is a system of indexes that is easier to use in conjunction with data on wages, productivity, and employment and other series that are organized in terms of the Standard Industrial Classification and the Census product class designations. Additional sources of information For a discussion of the methodology for computing Producer Price Indexes, see b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). Additional detailed data and analyses of price changes are provided monthly in Producer Price Indexes. Selected historical data may be found in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). International Price Indexes Description of the series The BLS International Price Program produces quarterly export and import price indexes for nonmilitary goods traded between the United States and the rest of the world. The export price index provides a measure of price change for all products sold by U.S. residents to foreign buyers. (“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. With publication of an all-import index in February 1983 and an all-export index in February 1984, all U.S. merchandise imports and exports now are represented in these indexes. The reference period for the indexes is 1985= 100, unless otherwise indicated. 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 quarterly 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 2 weeks of the third month of each calendar quarter—March, June, September, and December. Survey respondents are asked to indicate all discounts, allowances, and rebates applicable to the reported prices, so that the price used in the calculation of the indexes is the actual price for which the product was bought or sold. In addition to general indexes of prices for U.S. exports and imports, indexes are also published for detailed product categories of exports and imports. These categories are defined by the 4- and 5-digit level of detail of the Standard Industrial Trade Classification System (su e). The calculation of indexes by s u e category facilitates the comparison of U.S. price trends and sector production with similar data for other countries. Detailed indexes are also computed and published on a Standard Industrial Classification (sic-based) basis, as well as by enduse class. Notes on the data The export and import price indexes are weighted indexes of the Laspeyres type. Price relatives are assigned equal importance within each weight category and are then aggregated to the sitc level. The values assigned to each weight category are based on trade value figures compiled by the Bureau of the Census. The trade weights currently used to compute both indexes relate to 1985. 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 quarterly questionnaire requests detailed descrip tions 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 the export price indexes, the preferred pricing basis is f.a.s. (free alongside ship) U.S. port of exportation. When firms report export prices f.o.b. (free on board), production point information is collected which enables the Bureau to calculate a shipment cost to the port of exportation. An attempt is made to collect two prices for imports. The first is the import price f.o.b. at the foreign port of exportation, which is consistent with the basis for valuation of imports in the national accounts. The second is the import price c.i.f. (cost, insurance, and freight) at the U.S. port of importation, which also includes the other costs associated with bringing the product to the U.S. border. It does not, however, include duty charges. For a given product, only one price basis series is used in the construction of an index. Beginning in 1988, the Bureau has also been publishing a series of indexes which represent the price of U.S. exports and imports in foreign currency terms. Additional sources of information For a discussion of the general method of computing International Price Indexes, see b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). Additional detailed data and analyses of international price develop ments are presented in the Bureau’s quarterly publication U.S. Import and Export Price Indexes and in occasional Monthly Labor Review articles prepared by bls analysts. Selected historical data may be found in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). For further information on the foreign currency indexes, see “bls publishes average exchange rate and foreign currency price indexes,” Monthly Labor Review, December 1987, pp. 47-49. PRODUCTIVITY DATA (Tables 2; 42 - 44) U.S. productivity and related data Corresponding indexes of hourly compensation, unit labor costs, unit nonlabor payments, and prices are also provided. Description of the series Definitions The productivity measures relate real physical output to real input. As such, they encompass a family of measures which include single factor productivity measures, such as output per unit of labor input (output per hour) 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. Output per hour of all persons (labor productivity) is the value of goods and services in constant prices produced per hour of labor input. Output per unit of capital services (capital productivity) is the value of goods and services in constant dollars produced per unit of capital services input. Multifactor productivity is output per unit of combined labor and capital inputs. Changes in this measure reflect changes in a number of factors which affect the production process such as changes in technology, shifts in the composition of the labor force, changes in https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 55 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics capacity utilization, research and development, skill and efforts of the work force, management, and so forth. Changes in the output per hour measures reflect the impact of these factors as well as the substitution of capital for labor. Compensation per hour is the wages and salaries of employees plus employers’ contributions for social insurance and private benefit plans, and the wages, salaries, and supplementary payments for the selfemployed (except for nonfmancial corporations in which there are no self-employed)—the sum divided by hours paid for. Real compensation per hour is compensation per hour deflated by 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 compensa tion 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 paid of payroll workers, selfemployed persons, and unpaid family workers. Capital services is 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. Labor and capital inputs combined are derived by combining changes in labor and capital inputs with weights which represent each compo nent’s share of total output. The indexes for capital services and combined units of labor and capital 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 Constant-dollar output for the business sector is equal to constantdollar gross national product but excludes the rental value of owner-occupied dwellings, the rest-of-world sector, the output of nonprofit institutions, the output of paid employees of private house holds, general government, and the statistical discrepancy. Output of the nonfarm business sector is equal to business sector output less farming. The measures are derived from data supplied by the Bureau of Economic Analysis, U.S. Department of Commerce, and the Federal Reserve Board. Quarterly manufacturing output indexes are adjusted by the Bureau of Labor Statistics to annual measures of manufacturing output (gross product originating) from the Bureau of Economic Analysis. Compensation and hours data are developed from data of the Bureau of Labor Statistics and the Bureau of Economic Analysis. The productivity and associated cost measures in tables 4 2 -4 4 describe the relationship between output in real terms and the labor time and capital services 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; capital investment; level of output; utilization of capacity, energy, and materials; the organization of production; managerial skill; and the characteristics and efforts of the work force. Additional sources of information Descriptions of methodology underlying the measurement of output per hour and multifactor productivity are found in the b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988). Historical data for selected industries are provided in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). INTERNATIONAL COMPARISONS (Tables 45-47) Labor force and unemployment Description of the series Tables 45 and 46 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 unemployment statistics (and, to a lesser extent, employment statistics) published by other industrial countries are not, in most cases, comparable to U.S. unemployment statistics. Therefore, the Bureau adjusts the figures for selected countries, where necessary, for all known major definitional differences. Although precise compara bility may not be achieved, these adjusted figures provide a better basis for international comparisons than the figures regularly published by each country. Definitions For the principal U.S. definitions of the labor force, employment, and unemployment, see the Notes section on EMPLOYMENT DATA: Household Survey Data. Notes on the data The adjusted statistics have been adapted to the age at which compulsory schooling ends in each country, rather than to the U.S. 56 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis standard of 16 years of age and over. Therefore, the adjusted statistics relate to the population age 16 and over in France, Sweden, and from 1973 onward, the United Kingdom; 15 and over in Canada, Australia, Japan, Germany, the Netherlands, and prior to 1973, the United Kingdom; and 14 and over in Italy. The institutional population is included in the denominator of the labor force participation rates and employment-population ratios for Japan and Germany; it is excluded for the United States and the other countries. In the U.S. labor force survey, persons on layoff who are awaiting recall to their job are classified as unemployed. European and Japanese layoff practices are quite different in nature from those in the United States; therefore, strict application of the U.S. definition has not been made on this point. For further information, see Monthly Labor Review, December 1981, pp. 8-11. The figures for one or more recent years for France, Germany, Italy, the Netherlands, and the United Kingdom are calculated using adjustment factors based on labor force surveys for earlier years and are considered preliminary. The recent-year measures for these countries are, therefore, subject to revision whenever data from more current labor force surveys become available. There are breaks in the date series for Germany (1983), Italy (1986), the Netherlands (1983), and Sweden (1987). For both Germany and the Netherlands, the breaks reflect the replacement of labor force survey results tabulated by the national statistical offices with those tabulated by the European Community Statistical Office ( e u r o s t a t ). The Dutch figures for 1983 onward also reflect the replacement of man-year employment data with data from the Dutch Survey of Employed Persons. The impact of the changes was to lower the adjusted unemployment rate by 0.3 percentage point for Germany and by about 2 percentage points for the Netherlands. For Italy, the break in series reflects more accurate enumeration of time of last job search. This resulted in a significant increase in the number of people reported as seeking work in the past 30 days. The impact was to increase the Italian unemployment rates approximating U.S. concepts by about 1 percentage point. Sweden introduced a new questionnaire. Questions regarding current availability were added and the period of active workseeking was reduced from 60 days to 4 weeks. These changes resulted in lowering Sweden’s unemployment rate by 0.5 percentage point. Additional sources of information For further information, see International Comparisons o f Unemploy ment, Bulletin 1979 (Bureau of Tabor Statistics, 1978), Appendix B, and unpublished Supplements to Appendix B, available on request. The statistics are also analyzed periodically in the Monthly Labor Review. The latest article appears in the April 1988 Review. Additional historical data, generally beginning with 1959, are published in the Handbook o f Labor Statistics and are available in unpublished statistical supplements to Bulletin 1979. Manufacturing productivity and labor costs Description of the series Table 47 presents comparative measures of manufacturing labor productivity, hourly compensation costs, and unit labor costs for the United States, Canada, Japan, and nine European countries. These measures are limited to trend comparisons—that is, intercountry series of changes over time— rather than level comparisons because reliable international comparisons of the levels of manufacturing output are unavailable. Definitions Output is constant value output (value added), generally taken from the national accounts of each country. While the national accounting methods for measuring real output differ considerably among the 12 countries, the use of different procedures does not, in itself, connote lack of comparability—rather, it reflects differences among countries in the availability and reliability of underlying data series. Hours refer to all employed persons including the self-employed in the United States and Canada; to all wage and salary employees in the other countries. The U.S. hours measure is hours paid; the hours measures for the other countries are hours worked. Compensation (labor cost) includes all payments in cash or kind made directly to employees plus employer expenditures for legally required insurance programs and contractual and private benefit plans. In addition, for some countries, compensation is adjusted for other significant taxes on payrolls or employment (or reduced to reflect subsidies), even if they are not for the direct benefit of workers, because such taxes are regarded as labor costs. However, compensation does not include all items of labor cost. The costs of recruitment, employee training, and plant facilities and services— such as cafeterias and medical clinics—are not covered because data are not available for most countries. Self-employed workers are included in the U.S. and Canadian compensation figures by assuming that their hourly compensation is equal to the average for wage and salary employees. Notes on the data For most of the countries, the measures refer to total manufacturing as defined by the International Standard Industrial Classification. However, the measures for France (beginning 1959), Italy (beginning 1970), and the United Kingdom (beginning 1971), refer to manufactur ing and mining less energy-related products and the figures for the Netherlands exclude petroleum refining from 1969 to 1976. For all countries, manufacturing includes the activities of government enterprises. The figures for one or more recent years are generally based on current indicators of manufacturing output, employment, hours, and hourly compensation and are considered preliminary until the national accounts and other statistics used for the long-term measures become available. Additional sources of information For additional information, see the b l s Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988), and periodic Monthly Labor Review articles. Historical data are provided in the Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985). The statistics are issued twice per year—in a news release (generally in May) and in a Monthly Labor Review article. OCCUPATIONAL INJURY AND ILLNESS DATA (Table 48) Description of the series The Annual Survey of Occupational Injuries and Illnesses is designed to collect data on injuries and illnesses based on records which employers in the following industries maintain under the Occupational Safety and Health Act of 1970: agriculture, forestry, and fishing; oil and gas extraction; construction; manufacturing; transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. Excluded from the survey are self-employed individuals, farmers with fewer than 11 employees, employers regulated by other Federal safety and health laws, and Federal, State, and local govern ment agencies. Because the survey is a Federal-State cooperative program and the data must meet the needs of participating State agencies, an indepen dent sample is selected for each State. The sample is selected to https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis represent all private industries in the States and territories. The sample size for the survey is dependent upon (1) the characteristics for which estimates are needed; (2) the industries for which estimates are desired; (3) the characteristics of the population being sampled; (4) the target reliability of the estimates; and (5) the survey design employed. While there are many characteristics upon which the sample design could be based, the total recorded case incidence rate is used because it is one of the most important characteristics and the least variable; therefore, it requires the smallest sample size. The survey is based on stratified random sampling with a Neyman allocation and a ratio estimator. The characteristics used to stratify the establishments are the Standard Industrial Classification (sic) code and size of employment. 57 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics Definitions Recordable occupational injuries and illnesses are: (1) occupational deaths, regardless of the time between injury and death, or the length of the illness; or (2) nonfatal occupational illnesses; or (3) nonfatal occupational injuries which 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, amputation, and so forth, which results from a work accident or from exposure involving a single incident in the work environment. Occupational illness is an abnormal condition or disorder, other than one resulting from an occupational injury, caused by exposure to environmental 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 cases are cases which involve days away from work, or days of restricted work activity, or both. Lost workday cases involving restricted work activity are those cases which result in restricted work activity only. Lost workdays away from work are the number of workdays (consecutive or not) on which the employee would have worked but could not because of occupational injury or illness. Lost workdays—restricted work activity are the number of workdays (consecutive or not) on which, because of injury or illness: (1) the employee was assigned to another job on a temporary basis; or (2) the employee worked at a permanent job less than full time; or (3) the employee worked at a permanently assigned job but could not perform all duties normally connected with it. 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 even though able to work. Incidence rates represent the number of injuries and/or illnesses or lost workdays per 100 full-time workers. Notes on the data Estimates are made for industries and employment-size classes and for severity classification: fatalities, lost workday cases, and nonfatal cases without lost workdays. Lost workday cases are separated into 58 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis those where the employee would have worked but could not and those in which work activity was restricted. Estimates of the number of cases and the number of days lost are made for both categories. Most of the estimates are in the form of incidence rates, defined as the number of injuries and illnesses, or lost workdays, per 100 full-time employees. For this purpose, 200,000 employee hours represent 100 employee years (2,000 hours per employee). Only a few of the available measures are included in the Handbook o f Labor Statistics. Full detail is presented in the annual bulletin, Occupational Injuries and Illnesses in the United States, by Industry. Comparable data for individual States are available from the bls Office of Safety, Health, and Working Conditions. Mining and railroad data are furnished to BLS by the Mine Safety and Health Administration and the Federal Railroad Administration, respectively. Data from these organizations are included in BLS and State publications. Federal employee experience is compiled and published by the Occupational Safety and Health Administration. Data on State and local government employees are collected by about half of the States and territories; these data are not compiled nationally. Additional sources of information The Supplementary Data System provides detailed information describing various factors associated with work-related injuries and illnesses. These data are obtained from information reported by employers to State workers’ compensation agencies. The Work Injury Report program examines selected types of accidents through an employee survey which focuses on the circumstances surrounding the injury. These data are not included in the Handbook o f Labor Statistics but are available from the bls Office of Safety, Health, and Working Conditions. The definitions of occupational injuries and illnesses and lost workdays are from Recordkeeping Requirements under the Occupa tional Safety and Health Act o f 1970. For additional data, see Occupational Injuries and Illnesses in the United States, by Industry, annual Bureau of Labor Statistics bulletin; bls Handbook o f Methods, Bulletin 2285 (Bureau of Labor Statistics, 1988); Handbook o f Labor Statistics, Bulletin 2217 (Bureau of Labor Statistics, 1985), pp. 411-14; annual reports in the Monthly Labor Review; and annual U.S. Department of Labor press releases. 1. Labor market indicators 1987 Selected indicators 1987 1988 1988 I II III IV I II III IV Employment data Employment status of the civilian noninstitutionalized population (household survey):1 Labor force participation rate................................................... Employment-population ratio.................................................... Unemployment rate ................................................................. Men..................................................................................... 16 to 24 years ................................................................... 25 years and over.............................................................. Women .............................................................................. 16 to 24 years ................................................................... 25 years and over.............................................................. Unemployment rate, 15 weeks and over................................ 65.6 61.5 6.2 6.2 12.6 4.8 6.2 11.7 4.8 1.7 65.9 62.3 5.5 5.5 11.4 4.2 5.6 10.6 4.3 1.3 65.4 61.1 6.6 6.6 13.3 5.1 6.6 12.5 5.0 1.8 65.6 61.5 6.3 6.4 13.1 4.9 6.2 11.7 4.7 1.7 65.6 61.7 6.0 6.0 12.2 4.6 6.0 11.4 4.7 1.6 65.7 61.9 5.9 5.8 11.9 4.4 6.0 11.2 4.6 1.5 65.8 62.1 5.7 5.6 11.8 4.3 5.8 11.0 4.5 1.4 65.8 62.2 5.5 5.4 11.2 4.2 5.6 10.7 4.3 1.3 65.9 62.3 5.5 5.4 11.4 4.1 5.6 10.5 4.4 1.3 66.1 62.5 5.3 5.4 11.3 4.1 5.3 10.3 4.2 1.2 Total ......................................................................................... Private sector ......................................................................... Goods-producing..................................................................... Manufacturing....................................................................... Service-producing ................................................................... 102,310 85,295 24,784 19,065 77,525 106,039 88,653 25,565 19,539 80,475 101,024 84,130 24,523 18,895 76,500 101,841 84,869 24,644 18,965 77,196 102,669 85,643 24,847 19,112 77,782 103,683 86,518 25,116 19,290 78,567 104,670 87,406 25,260 19,388 79,410 105,609 88,263 25,498 19,498 80,111 106,478 89,063 25,648 19,567 80,830 107,344 89,812 25,827 19,701 81,517 Average hours: Private sector ......................................................................... Manufacturing .................................................................... Overtime........................................................................... 34.8 41.0 3.7 34.8 41.1 3.9 34.8 41.0 3.6 34.7 40.9 3.7 34.7 40.9 3.8 34.8 41.1 3.9 34.7 41.0 3.8 34.8 41.1 3.9 34.7 41.1 3.9 34.8 41.1 3.9 Percent change in the ECI, compensation: All workers (excluding farm, household, and Federal workers) ..... Private industry workers ......................................................... Goods-producing2 ............................................................... Service-producing2 .............................................................. State and local government workers....................................... 3.6 3.3 3.1 3.7 4.4 5.0 4.9 4.4 5.1 5.6 .9 1.0 .5 1.3 .8 .7 .7 .7 .7 .3 1.2 1.0 .8 1.0 2.3 .8 .7 1.0 .5 .9 1.4 1.5 1.8 1.3 1.3 1.1 1.2 1.1 1.4 .3 1.3 1.0 .6 1.2 2.7 1.0 1.0 .8 1.2 1.1 Workers by bargaining status (private industry): Union.......................................................................... Nonunion ............................................................ 2.8 3.6 3.9 5.1 .5 1.1 .5 .7 .6 1.1 1.1 .6 1.6 1.5 1.0 1.3 .7 1.1 .5 1.2 Employment nonagricultural (payroll data), in thousands:1 Employment Cost Index 1 Quarterly data seasonally adjusted. 2 Goods-producing industries include mining, construction, and manufacturing. Service- https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis producing industries include all other private sector industries. 59 MONTHLY LABOR REVIEW 2. April 1989 • Current Labor Statistics: Comparative Indicators Annual and quarterly percent changes in compensation, prices, and productivity 1988 1987 Selected measures 1987 1988 III II I II I IV IV III Compensation data 1, 2 Employment Cost Index-compensation (wages, salaries, benefits): Civilian nonfarm .............................................................. Private nonfarm ............................................................. Employment Cost Index-wages and salaries Civilian nonfarm .............................................................. Private nonfarm ............................................................. 3.6 3.3 5.0 4.9 0.9 1.0 0.7 .7 1.2 1.0 0.8 .7 1.4 1.5 1.1 1.2 1.3 1.0 1.0 1.0 3.5 3.3 4.3 4.1 1.0 1.0 .5 .7 1.3 1.0 .7 .6 1.0 1.0 .9 1.1 1.3 1.0 1.0 1.0 Price data1 Consumer Price Index (All urban consumers): All items..... 4.4 4.4 1.4 1.2 1.3 .3 1.0 1.3 1.5 .6 Producer Price Index: Finished goods............................................................... Finished consumer goods.............................................. Capital equipment ......................................................... Intermediate materials, supplies, components .................. Crude materials.............................................................. 2.2 2.6 1.3 5.4 8.9 4.0 4.0 3.5 5.7 2.8 .8 .9 .1 1.3 4.2 1.2 1.6 .3 1.9 5.3 .2 .3 -.2 1.2 .6 .1 -.2 1.1 .9 -1.4 .5 .4 .7 1.1 -.3 1.3 1.4 .6 2.6 4.0 .8 1.0 .4 1.2 -1.2 1.3 1.1 1.7 .7 .3 Productivity data3 Output per hour of all persons: Business sector............................................................. Nonfarm business sector............................................... Nonfinancial corporations 4............................................. .8 .8 1.5 1.0 1.4 1.2 .3 .0 -1.0 .6 .9 -.1 3.9 3.7 4.7 2.7 3.2 3.1 3.5 3.4 4.3 -3.4 -2.4 -1.6 -2.0 .1 1.7 2.0 -.8 Quarterly percent changes reflect annual rates of change in quarterly In dexes. The data are seasonally adjusted. 4 Output per hour of all employees. - Data not available. 1 Annual changes are December-to-December change. 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 Annual rates of change are computed by comparing annual averages. 3. Alternative measures of wage and compensation changes Four quarters ended- Quarterly average III Average hourly compensation:1 All persons, business sector............................................................ All employees, nonfarm business sector.......................................... Employment Cost Index-compensation: Civilian nonfarm 2 ........................................................................... Private nonfarm ........................................................................... Nonunion................................................................................... State and local governments........................................................ Employment Cost Index-wages and salaries: Civilian nonfarm2 ............................................................................ Private nonfarm ........................................................................... Nonunion................................................................................... State and local governments......................................................... Total effective wage adjustments3......................................................... From current settlements................................................................ From prior settlements.................................................................... From cost-of-living provision............................................................ Negotiated wage adjustments from settlements:3 First-year adjustments .................................................................... Annual rate over life of contract................................... •................. Negotiated wage and benefit adjustments from settlements:4 First-year adjustment...................................................................... Annual rate over life of contract...................................................... III II I IV III IV II I III IV 4.6 4.5 6.2 6.4 3.7 3.5 4.8 4.2 6.2 5.7 4.7 5.6 3.9 3.7 4.2 4.1 4.5 4.4 4.8 4.6 5.2 5.0 4.8 4.8 1.2 1.0 .6 1.1 2.3 .8 .7 1.1 .6 .9 1.4 1.5 1.6 1.5 1.3 1.1 1.2 1.0 1.3 .3 1.3 1.0 .7 1.1 2.7 1.0 1.0 .5 1.2 1.1 3.4 3.3 2.0 3.7 4.2 3.6 3.3 2.8 3.6 4.4 4.1 3.9 3.9 4.0 4.9 4.6 4.5 4.3 4.5 5.0 4.7 4.5 4.5 4.5 5.4 5.0 4.9 3.9 5.1 5.6 1.3 1.0 .6 1.1 2.3 .9 .2 .6 .1 .7 .6 1.1 .5 .9 .8 .3 .3 .2 1.0 1.0 .4 1.0 .9 .4 .1 .3 .1 .9 1.1 .8 1.2 .3 .9 .3 .5 .1 1.3 1.0 .7 1.0 2.6 .8 .2 .4 .2 1.0 1.0 .4 1.1 1.0 .5 .1 .2 .2 3.4 3.3 1.7 3.8 4.1 2.6 .4 1.7 .4 3.5 3.3 2.6 3.6 4.2 3.1 .7 1.8 .5 3.5 3.3 2.6 3.5 4.4 3.2 .8 1.8 .5 3.9 3.7 2.9 4.0 4.4 3.0 1.0 1.6 .5 3.9 3.7 2.9 3.9 4.7 2.9 1.0 1.4 .5 4.3 4.1 2.2 4.5 4.8 2.6 .7 1.3 .6 2.1 2.0 2.4 1.8 2.1 2.3 2.6 2.2 2.7 2.8 2.7 2.3 2.0 2.2 2.2 2.1 2.4 2.2 2.4 2.0 2.5 2.2 2.6 2.4 2.5 2.1 3.4 2.4 1.8 1.8 3.1 2.4 3.4 3.2 3.8 2.2 2.7 2.6 3.0 2.6 3.1 2.5 3.0 2.3 3.1 2.5 3.1 2.5 1 Seasonally adjusted. 2 Excludes Federal and household workers. 3 Limited to major collective bargaining units of 1,000 workers or more. The 60 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis IV 1988 1987 1988 1987 Components most recent data are preliminary. 4 Limited to major collective bargaining units of 5,000 workers or more. The most recent data are preliminary. 4. Employment status of the total population, by sex, monthly data seasonally adjusted (Numbers in thousands) Annual average 1988 1989 Employment status 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. TOTAL Noninstitutional population 1, 2 ...... Labor force2............................... Participation rate 3.............. Total employed 2..................... Employment-population ratio 4 ................................ Resident Armed Forces 1 ...... Civilian employed .................. Agriculture .......................... Nonagricultural industries.... Unemployed............................ Unemployment rate 5.......... Not in labor force ...................... 184,490 186,322 185,705 185,847 185,964 186,088 186,247 186,402 186,522 186,666 186,801 186,949 187,098 187,340 187,461 121,602 123,378 122,901 122,672 123,060 122,917 123,209 123,331 123,692 123,688 123,778 124,215 124,259 125,124 124,865 65.9 66.2 66.2 66.0 66.2 66.1 66.2 66.2 66.3 66.3 66.3 66.4 66.4 66.8 66.6 114,177 116,677 116,009 115,865 116,392 116,117 116,686 116,707 116,895 117,074 117,260 117,652 117,705 118,407 118,537 61.9 62.6 62.5 62.3 62.6 62.4 62.7 62.6 62.7 62.7 62.8 62.9 62.9 63.2 63.2 1,737 1,709 1,736 1,736 1,732 1,714 1,685 1,673 1,692 1,704 1,687 1,705 1,696 1,696 1,684 112,440 114,968 114,273 114,129 114,660 114,403 115,001 115,034 115,203 115,370 115,573 115,947 116,009 116,711 116,853 3,208 3,169 3,181 3,200 3,187 3,110 3,121 3,060 3,142 3,176 3,238 3,238 3,193 3,300 3,223 109,232 111,800 111,073 110,948 111,473 111,293 111,880 111,974 112,061 112,194 112,335 112,709 112,816 113,411 113,630 7,425 6,701 6,892 6,807 6,668 6,800 6,624 6,523 6,797 6,614 6,518 6,563 6,554 6,716 6,328 6.1 5.4 5.6 5.5 5.4 5.5 5.3 5.4 5.5 5.3 5.3 5.3 5.3 5.4 5.1 62,888 62,944 62,804 63,175 62,904 63,171 63,038 63,071 62,830 62,978 63,023 62,734 62,839 62,216 62,596 Men, 16 years and over Noninstitutional population 1, 2 ...... Labor force2............................... Participation rate 3.............. Total employed 2..................... Employment-population ratio 4 ................................ Resident Armed Forces 1 ...... Civilian employed.................. Unemployed............................ Unemployment rate 5 .......... 88,476 67,784 76.6 63,684 89,404 68,474 76.6 64,820 89,099 68,289 76.6 64,587 89,168 68,194 76.5 64,417 89,225 68,462 76.7 64,866 89,287 68,409 76.6 64,672 89,367 68,436 76.6 64,894 89,445 68,461 76.5 64,941 89,504 68,685 76.7 64,931 89,577 68,604 76.6 65,015 89,637 68,569 76.5 64,976 89,716 68,686 76.6 65,074 89,792 68,638 76.4 65,055 89,914 69,032 76.8 65,322 89,973 69,113 76.8 65,572 72.0 1,577 62,107 4,101 6.1 72.5 1,547 63,273 3,655 5.3 72.5 1,577 63,010 3,702 5.4 72.2 1,573 62,844 3,777 5.5 72.7 1,569 63,297 3,596 5.3 72.4 1,553 63,119 3,737 5.5 72.6 1,523 63,371 3,542 5.2 72.6 1,512 63,429 3,520 5.1 72.5 1,529 63,402 3,754 5.5 72.6 1,540 63,475 3,589 5.2 72.5 1,526 63,450 3,593 5.2 72.5 1,542 63,532 3,612 5.3 72.5 1,534 63,521 3,583 5.2 72.6 1,532 63,790 3,710 5.4 72.9 1,521 64,051 3,540 5.1 96,013 53,818 56.1 50,494 96,918 54,904 56.6 51,858 96,606 54,612 56.5 51,422 96,679 54,478 56.3 51,448 96,739 54,598 56.4 51,526 96,801 54,508 56.3 51,445 96,880 54,773 56.5 51,792 96,957 54,870 56.6 51,766 97,018 55,007 56.7 51,964 97,089 55,084 56.7 52,059 97,164 55,209 56.8 52,284 97,234 55,529 57.1 52,578 97,306 55,621 57.2 52,650 97,427 56,091 57.6 53,085 97,488 55,752 57.2 52,965 52.6 160 50,334 3,324 6.2 53.5 162 51,696 3,046 5.5 53.2 159 51,263 3,190 5.8 53.2 163 51,285 3,030 5.6 53.3 163 51,363 3,072 5.6 53.1 161 51,284 3,063 5.6 53.5 162 51,630 2,981 5.4 53.4 161 51,605 3,104 5.7 53.6 163 51,801 3,043 5.5 53.6 164 51,895 3,025 5.5 53.8 161 52,123 2,925 5.3 54.1 163 52,415 2,951 5.3 54.1 162 52,488 2,971 5.3 54.5 164 52,921 3,006 5.4 54.3 163 52,802 2,787 5.0 Women, 16 years and over Noninstitutional population 1, 2 ...... Labor force2............................... Participation rate 3............... Total employed2 ...................... Employment-population ratio 4 ................................ Resident Armed Forces 1 ...... Civilian employed.................. Unemployed............................ Unemployment rate 5 .......... 1 The population and Armed Forces figures are not adjusted for seasonal variation. 2 Includes members of the Armed Forces stationed in the United States. 3 Labor force as a percent of the noninstitutional population. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis __________I_____| _ _ L 4 Total employed as a percent of the noninstitutional population. 5 Unemployment as a percent of the labor force (including the resident Armed Forces). 61 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Employment Data 5. Employment status of the civilian population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted (Numbers in thousands) 1987 1988 1989 1988 Annual average Employment status Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. TOTAL Civilian noninstitutlonal Civilian labor force..................... Participation rate ................ Employed............................... Employment-population ratio2 ................................ Unemployed............................ Unemployment rate............. Not in labor force ...................... 182,753 184,613 183,969 184,111 184,232 184,374 184,562 184,729 184,830 184,962 185,114 185,244 185,402 185,644 185,777 119,865 121,669 121,165 120,936 121,328 121,203 121,524 121,658 122,000 121,984 122,091 122,510 122,563 123,428 123,181 66.5 66.3 66.1 66.0 66.1 66.0 66.0 65.8 65.9 65.7 65.9 65.7 65.9 65.9 65.6 112,440 114,968 114,273 114,129 114,660 114,403 115,001 115,034 115,203 115,370 115,573 115,947 116,009 116,711 116,853 61.5 7,425 6.2 62,888 62.3 6,701 5.5 62,944 62.1 6,892 5.7 62,804 62.0 6,807 5.6 63,175 62.2 6,668 5.5 62,904 62.0 6,800 5.6 63,171 62.3 6,523 5.4 63,038 62.3 6,624 5.4 63,071 62.3 6,797 5.6 62,830 62.4 6,614 5.4 62,978 62.4 6,518 5.3 63,023 62.6 6,563 5.4 62,734 62.6 6,554 5.3 62,839 62.9 6,716 5.4 62,216 62.9 6,328 5.1 62,596 79,565 62,095 78.0 58,726 80,553 62,768 77.9 59,781 80,203 62,614 78.1 59,561 80,260 62,532 77.9 59,468 80,326 62,774 78.1 59,833 80,402 62,721 78.0 59,656 80,526 62,669 77.8 59,780 80,608 62,729 77.8 59,897 80,669 62,916 78.0 59,839 80,751 62,884 77.9 59,979 80,851 62,915 77.8 60,004 80,924 62,995 77.8 59,999 81,001 63,002 77.8 60,049 81,162 63,358 78.1 60,420 81,256 63,490 78.1 60,636 73.8 2,329 56,397 3,369 5.4 74.2 2,271 57,510 2,987 4.8 74.3 2,279 57,282 3,053 4.9 74.1 2,258 57,210 3,064 4.9 74.5 2,259 57,574 2,941 4.7 74.2 2,238 57,418 3,065 4.9 74.2 2,231 57,549 2,889 4.6 74.3 2,252 57,645 2,832 4.5 74.2 2,273 57,566 3,077 4.9 74.3 2,249 57,730 2,905 4.6 74.2 2,315 57,689 2,911 4.6 74.1 2,313 57,686 2,996 4.8 74.1 2,292 57,757 2,953 4.7 74.4 2,277 58,143 2,938 4.6 74.6 2,320 58,316 2,853 4.5 88,583 49,783 56.2 47,074 89,532 50,870 56.8 48,383 89,178 50,530 56.7 47,934 89,261 50,510 56.6 48,060 89,307 50,591 56.6 48,120 89,382 50,532 56.5 48,040 89,502 50,690 56.6 48,205 89,588 50,807 56.7 48,242 89,670 50,959 56.8 48,492 89,735 50,991 56.8 48,535 89,807 51,201 57.0 48,788 89,887 51,558 57.4 49,113 89,954 51,587 57.3 49,165 90,072 51,998 57.7 49,543 90,153 51,821 57.5 49,514 53.1 622 46,453 2,709 5.4 54.0 625 47,757 2,487 4.9 53.8 638 47,296 2,596 5.1 53.8 641 47,419 2,450 4.9 53.9 653 47,467 2,471 4.9 53.7 604 47,436 2,492 4.9 53.9 626 47,579 2,485 4.9 53.8 549 47,693 2,565 5.0 54.1 609 47,883 2,467 4.8 54.1 638 47,897 2,456 4.8 54.3 640 48,148 2,413 4.7 54.6 640 48,473 2,445 4.7 54.7 646 48,519 2,422 4.7 55.0 715 48,827 2,455 4.7 54.9 666 48,849 2,306 4.5 14,606 7,988 54.7 6,640 14,527 8,031 55.3 6,805 14,588 8,021 55.0 6,778 14,591 7,894 54.1 6,601 14,598 7,963 54.5 6,707 14,590 7,950 54.5 6,707 14,534 8,165 56.2 7,016 14,533 8,122 55.9 6,895 14,491 8,125 56.1 6,872 14,477 8,109 56.0 6,856 14,456 7,975 55.2 6,781 14,433 7,957 55.1 6,835 14,447 7,974 55.2 6,795 14,410 8,071 56.0 6,748 14,367 7,871 54.8 6,703 45.5 258 6,382 1,347 16.9 46.8 273 6,532 1,226 15.3 46.5 283 6,495 1,243 15.5 45.2 282 6,319 1,293 16.4 45.9 275 6,432 1,256 15.8 46.0 268 6,439 1,243 15.6 48.3 264 6,752 1,149 14.1 47.4 259 6,636 1,227 15.1 47.4 260 6,612 1,253 15.4 47.4 289 6,567 1,253 15.5 46.9 283 6,498 1,194 15.0 47.4 285 6,550 1,122 14.1 47.0 255 6,540 1,179 14.8 46.8 307 6,441 1,323 16.4 46.7 237 6,466 1,168 14.8 Men, 20 years and over Civilian noninstitutional population1................................. Civilian labor force..................... Participation rate ................ Employed ............................... Employment-population Agriculture............................ Nonagricultural industries....... Unemployed............................ Unemployment rate............. Women, 20 years ond over Civilian noninstitutional population1................................. Civilian labor force..................... Participation rate ................ Employed ................................ Employment-population ratio2 ................................ Agriculture............................ Nonagricultural industries....... Unemployed............................ Unemployment rate............. Both sexes, 16 to 19 years Civilian noninstitutional population1................................ Civilian labor force..................... Participation rate ................ Employed................................ Employment-population ratio2 ................................ Agriculture............................ Nonagricultural industries....... Unemployed............................ Unemployment rate............. White Civilian noninstitutional population1................................ Civilian labor force..................... Participation rate ................ Employed................................ Employment-population ratio2 ................................ Unemployed............................ Unemployment rate............. 156,958 158,194 157,773 157,868 157,943 158,034 158,166 158,279 158,340 158,422 158,524 158,603 158,705 158,865 158,947 103,290 104,756 104,404 104,172 104,517 104,433 104,716 104,651 105,013 105,036 105,051 105,395 105,411 106,106 105,798 66.6 66.8 66.4 66.5 66.3 66.3 66.3 66.1 66.2 66.2 66.1 66.2 66.0 65.8 66.2 99,907 100,058 100,199 100,543 100,567 101,183 101,278 97,789 99,812 99,350 99,252 99,663 99,508 99,902 99,761 62.3 5,501 5.3 63.1 4,944 4.7 63.0 5,054 4.8 62.9 4,920 4.7 63.1 4,854 4.6 63.0 4,925 4.7 63.2 4,814 4.6 63.0 4,890 4.7 63.1 5,106 4.9 63.2 4,978 4.7 63.2 4,852 4.6 63.4 4,852 4.6 63.4 4,844 4.6 63.7 4,923 4.6 63.7 4,521 4.3 20,352 12,993 63.8 11,309 20,692 13,205 63.8 11,658 20,569 13,138 63.9 11,504 20,596 13,100 63.6 11,461 20,622 13,101 63.5 11,534 20,650 13,102 63.4 11,514 20,683 13,066 63.2 11,543 20,715 13,283 64.1 11,761 20,736 13,236 63.8 11,733 20,762 13,201 63.6 11,758 20,786 13,290 63.9 11,807 20,811 13,330 64.1 11,831 20,842 13,405 64.3 11,856 20,877 13,477 64.6 11,860 20,905 13,476 64.5 11,873 55.6 1,684 13.0 56.3 1,547 11.7 55.9 1,634 12.4 55.6 1,639 12.5 55.9 1,567 12.0 55.8 1,588 12.1 55.8 1,523 11.7 56.8 1,522 11.5 56.6 1,503 11.4 56.6 1,443 10.9 56.8 1,483 11.2 56.8 1,499 11.2 56.9 1,549 11.6 56.8 1,617 12.0 56.8 1,603 11.9 Black Civilian noninstitutional population1................................ Civilian labor force..................... Participation rate ................ Employed ................................ Employment-population ratio2 ................................. Unemployed........................... Unemployment rate............. See footnotes at end of table. Digitized for 62 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 5. Continued— Employment status of the civilian population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted (Numbers in thousands) Annual average 1988 1989 Employment status 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. 12,867 8,641 66.4 7,790 13,325 8,982 67.4 8,250 13,153 8,987 68.3 8,241 13,192 8,818 66.8 8,088 13,230 8,823 66.7 8,030 13,268 8,910 67.2 8,128 13,306 9,009 67.7 8,222 13,344 8,997 67.4 8,265 13,381 8,963 67.0 8,214 13,419 9,061 67.5 8,378 13,458 9,075 67.4 8,368 13,495 9,148 67.8 8,419 13,533 9,133 67.5 8,441 13,564 9,205 67.9 8,434 13,606 9,219 67.8 8,596 60.5 751 8.8 61.9 732 8.2 62.7 746 8.3 61.3 730 8.3 60.7 793 9.0 61.3 782 8.8 61.8 787 8.7 61.9 732 8.1 61.4 749 8.4 62.4 683 7.5 62.2 707 7.8 62.4 729 8.0 62.4 692 7.6 62.2 771 8.4 63.2 624 6.8 Hispanic origin Civilian noninstitutional population1................................ Civilian labor force..................... Participation rate ................ Employed ................................ Employment-population ratio2 ................................ Unemployed............................ Unemployment rate............. 1 The population figures are not seasonally adjusted. 2 Civilian employment as a percent of the civilian noninstitutional population. NOTE: Detail for the above race and Hispanic-origin groups will not sum to totals 6. because data for the “other races” groups are not presented and Hispanics are included in both the white and black population groups. Selected employment indicators, monthly data seasonally adjusted (In thousands) Annual average 1988 1989 Selected categories 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. CHARACTERISTIC Civilian employed, 16 years and over......................................... 112,440 114,968 114,273 114,129 114,660 114,403 115,001 115,034 115,203 115,370 115,573 115,947 Men...................................... 62,107 63,273 63,010 62,844 63,297 63,119 63,371 63,429 63,402 63,475 63,450 63,532 Women ................................. 50,334 51,696 51,263 51,285 51,363 51,284 51,630 51,605 51,801 51,895 52,123 52,415 Married men, spouse present .. 40,265 40,472 40,488 40,486 40,494 40,317 40,493 40,518 40,511 40,513 40,504 40,407 Married women, spouse present ................................ 28,107 28,756 28,620 28,713 28,772 28,632 28,678 28,669 28,809 28,836 28,890 28,995 Women who maintain families . 6,151 6,060 6,211 6,158 6,091 6,000 6,130 6,170 6,280 6,253 6,344 6,375 116,009 116,711 116,853 63,521 33,790 64,051 52,488 02,921 52,802 40,483 40,925 40,928 29,053 6,399 29,589 6,416 29,412 6,385 1,698 1,349 149 1,684 1,387 189 1,645 1,419 150 MAJOR INDUSTRY AND CLASS OF WORKER Agriculture: Wage and salary workers ....... Self-employed workers........... Unpaid family workers............ Nonagricultural industries: Wage and salary workers ....... Private industries................. Private households............ Other................................ Self-employed workers........... Unpaid family workers............ 1,632 1,423 153 1,621 1,398 150 1,640 1,410 123 1,610 1,416 146 1,632 1,390 152 1,574 1,365 155 1,583 1,375 161 1,572 1,362 149 1,607 1,411 158 1,612 1,421 137 1,661 1,405 177 1,672 1,450 125 100,771 103,021 102,498 102,339 102,562 102,145 102,953 103,189 103,207 103,501 103,733 103,770 103,904 104,510 104,797 16,800 17,114 16,961 16,952 17,012 16,946 17,049 17,031 17,111 17,145 17,240 17,387 17,423 17,393 17,311 83,970 85,907 85,537 85,387 85,550 85,199 85,904 86,158 86,096 86^356 86,493 86,383 86,481 87,117 87,486 1,208 1,153 1,167 1,167 1,114 1,152 1,146 1,132 1,128 1,119 1,152 1,209 1,210 1,196 1,135 82,762 84,754 84,370 84,220 84,436 84,047 84,758 85,026 84,968 85,237 85,341 85,174 85,271 85,921 86,350 8,201 8,519 8,338 8,395 8,567 8,816 8,536 8,531 8,508 8,570 8,479 8,619 8,602 8,718 8,517 260 260 232 250 272 301 297 251 241 230 232 300 266 298 285 PERSONS AT WORK PART TIME1 All Industries: Part time for economic reasons . Slack work ............................ Could only find part-time work Voluntary part time ................... Nonagricultural industries: Part time for economic reasons . Slack work ............................ Could only find part-time work Voluntary part time ................... 5,401 2,385 2,672 14,395 5,206 2,350 2,487 14,963 5,369 2,408 2,591 14,619 5,331 2,448 2,548 14,654 5,212 2,264 2,519 14,949 4,878 2,267 2,353 14,813 5,302 2,346 2,586 14,612 5,341 2,471 2,538 15,026 5,192 2,315 2,473 14,999 5,097 2,266 2,389 15,270 4,963 2,220 2,399 15,161 5,061 2,279 2,375 15,446 5,321 2,549 2,410 15,363 5,097 2,302 2,352 15,401 4,981 2,303 2,333 15,126 5,122 2,201 2,587 13,928 4,965 2,199 2,408 14,509 5,101 2,258 2,477 14,172 5,087 2,265 2,482 14,203 4,953 2,131 2,426 14,441 4,676 2,136 2,276 14,376 5,073 2,183 2,504 14,180 5,102 2,334 2,493 14,606 4,972 2,171 2,408 14,564 4,862 2,102 2,317 14,819 4,727 2,095 2,319 14,679 4,819 2,116 2,288 14,986 5,033 2,377 2,307 14,928 4,837 2,144 2,283 14,970 4,697 2,105 2,272 14,688 1 Excludes persons “with a job but not at work” during the survey period for such reasons as vacation, illness, or industrial disputes. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 63 MONTHLY LABOR REVIEW 7. April 1989 • Current Labor Statistics: Employment Data Selected unemployment indicators, monthly data seasonally adjusted (Unemployment rates) 1939 1988 Annual average Selected categories July Aug. Sept. Oct. Nov. Dec. Jan. Feb. 1987 1988 Feb. Mar. Apr. May June Total, all civilian workers...................................... Both sexes, 16 to 19 years............................. Men, 20 years and over................................. Women, 20 years and over............................. 6.2 16.9 5.4 5.4 5.5 15.3 4.8 4.9 5.7 15.5 4.9 5.1 5.6 16.4 4.9 4.9 5.5 15.8 4.7 4.9 5.6 15.6 4.9 4.9 5.4 14.1 4.6 4.9 5.4 15.1 4.5 5.0 5.6 15.4 4.9 4.8 5.4 15.5 4.6 4.8 5.3 15.0 4.6 4.7 5.4 14.1 4.8 4.7 5.3 14.8 4.7 4.7 5.4 16.4 4.6 4.7 5.1 14.8 4.5 4.5 White, total.................................................... Both sexes, 16 to 19 years.......................... Men, 16 to 19 years................................ Women, 16 to 19 years........................... Men, 20 years and over ............................... Women, 20 years and over.......................... 5.3 14.4 15.5 13.4 4.8 4.6 4.7 13.1 13.9 12.3 4.1 4.1 4.8 12.5 12.5 12.6 4.2 4.4 4.7 14.1 15.5 12.6 4.2 3.9 4.6 13.9 14.4 13.3 4.0 4.0 4.7 13.2 14.0 12.3 4.2 4.1 4.6 12.3 13.2 11.4 4.0 4.1 4.7 12.9 14.3 11.4 3.9 4.3 4.9 13.7 13.9 13.5 4.3 4.1 4.7 13.4 14.5 12.3 4.1 4.1 4.6 12.9 14.4 11.3 4.1 4.0 4.6 11.9 12.6 11.3 4.2 4.0 4.6 12.6 13.4 11.8 4.1 3.9 4.6 14.1 16.4 11.7 4.0 3.9 4.3 12.1 14.0 10.2 3.8 3.6 Both sexes, 16 to 19 years.......................... Men, 16 to 19 years ................................ Women, 16 to 19 years........................... Men, 20 years and over ............................... Women, 20 years and over.......................... 13.0 34.7 34.4 34.9 11.1 11.6 11.7 32.4 32.7 32.0 10.1 10.4 12.4 36.8 39.9 33.8 10.9 10.5 12.5 35.8 37.8 33.9 11.0 10.8 12.0 30.8 27.9 33.9 10.4 10.9 12.1 33.9 33.2 34.8 10.4 10.6 11.7 30.6 31.5 29.6 9.9 10.6 11.5 31.7 31.2 32.4 9.6 10.3 11.4 32.1 32.1 32.0 9.7 10.0 10.9 31.9 31.9 31.9 9.1 9.7 11.2 30.9 32.8 28.6 9.6 9.8 11.2 31.1 32.1 29.9 9.8 9.8 11.6 29.6 29.8 29.3 10.0 10.5 12.0 34.5 36.7 32.0 10.4 10.4 11.9 32.4 33.1 31.6 10.5 10.3 Hispanic origin, total....................................... 8.8 8.2 8.3 8.3 9.0 8.8 8.7 8.1 8.4 7.5 7.8 8.0 7.6 8.4 6.8 Married men, spouse present.......................... Married women, spouse present..................... Women who maintain families......................... Full-time workers ............................................ Part-time workers ........................................... Unemployed 15 weeks and over..................... Labor force time lost1 ..................................... 3.9 4.3 9.2 5.8 8.4 1.7 7.1 3.3 3.9 8.1 5.2 7.6 1.3 6.3 3.4 4.0 8.3 5.3 7.9 1.4 6.6 3.4 4.0 7.5 5.3 7.8 1.4 6.5 3.1 3.8 8.5 5.1 7.5 1.3 6.2 3.3 3.9 8.4 5.2 7.7 1.3 6.4 3.2 3.9 7.9 5.0 7.7 1.3 6.3 3.1 4.0 8.5 5.0 8.0 1.3 6.4 3.4 4.0 7.5 5.3 7.4 1.3 6.4 3.1 3.8 8.1 5.1 7.4 1.3 6.3 3.1 3.7 7.9 5.0 7.4 1.3 6.1 3.3 3.8 7.7 5.0 7.1 1.2 6.2 3.1 3.7 8.2 5.1 7.0 1.2 6.3 3.1 3.6 8.0 5.0 7.9 1.2 6.2 3.1 3.4 8.0 4.8 7.3 1.1 5.9 6.2 10.0 11.6 6.0 5.8 6.3 4.5 6.9 4.9 3.5 10.5 5.5 7.9 10.6 5.3 5.0 5.7 3.9 6.2 4.5 2.8 10.6 5.7 7.8 10.9 5.6 5.7 5.4 3.8 6.3 4.6 2.9 10.5 5.6 8.2 10.6 5.2 5.1 5.4 4.1 6.7 4.3 2.9 11.0 5.4 8.1 10.6 5.3 4.8 5.9 3.8 5.9 4.3 3.0 11.0 5.6 9.4 10.5 5.3 4.9 5.9 4.2 6.3 4.6 2.9 12.4 5.4 6.8 10.3 4.9 4.5 5.5 4.1 6.0 4.6 2.9 10.0 5.4 5.4 10.4 5.2 4.9 5.6 3.6 6.2 4.5 3.0 11.0 5.6 7.0 10.7 5.5 5.0 6.3 3.8 6.4 4.4 2.9 11.0 5.4 8.6 9.6 5.4 5.2 5.8 3.8 6.2 4.4 2.7 10.8 5.4 8.8 10.0 5.3 5.0 5.7 3.5 6.0 4.5 2.6 10.2 5.5 8.9 10.6 5.1 4.9 5.3 4.0 6.2 4.6 2.5 9.3 5.4 7.7 10.4 5.2 5.0 5.5 3.8 6.3 4.1 2.7 8.8 5.6 6.1 10.4 5.3 5.0 5.7 3.8 6.3 4.7 2.7 9.5 5.1 8.0 10.0 4.9 4.4 5.5 3.9 5.6 4.3 2.7 8.9 CHARACTERISTIC INDUSTRY Nonagricultural private wage and salary workers .... Mining............................................................ Construction .................................................. Manufacturing ................................................ Durable goods............................................. Nondurable goods....................................... Transportation and public utilities .................... Wholesale and retail trade.............................. Finance and service industries........................ Government workers ........................................... Agricultural wage and salary workers ................... 1 Aggregate hours lost by the unemployed and persons on part time for economic reasons as a percent of potentially available labor force hours. 64 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 8. Unemployment rates by sex and age, monthly data seasonally adjusted (Civilian workers) Annual average Sex and age 1988 1987 9. 1989 1988 Apr. Mar. Feb. June May Sept. Aug. July Nov. Oct. Feb. Jan. Dec. 6.2 12.2 16.9 19.1 15.2 9.7 4.8 5.0 3.3 5.5 11.0 15.3 17.4 13.8 8.7 4.3 4.5 3.1 5.7 11.1 15.5 17.7 14.1 8.7 4.4 4.7 3.2 5.6 11.6 16.4 17.7 15.3 9.0 4.2 4.5 2.9 5.5 11.2 15.8 17.7 14.1 8.7 4.2 4.4 3.0 5.6 11.2 15.6 16.7 14.8 8.8 4.3 4.5 3.3 5.4 10.5 14.1 15.9 13.3 8.5 4.2 4.4 3.0 5.4 10.9 15.1 17.5 13.1 8.5 4.2 4.4 3.1 5.6 11.0 15.4 18.5 13.7 8.4 4.4 4.5 3.2 5.4 10.9 15.5 19.6 12.8 8.4 4.2 4.4 2.9 5.3 10.9 15.0 17.2 13.3 8.6 4.1 4.3 2.8 5.4 10.6 14.1 15.8 12.9 8.7 4.2 4.4 2.8 5.3 10.9 14.8 16.6 13.3 8.7 4.1 4.3 3.0 5.4 11.9 16.4 18.3 15.4 9.3 4.1 4.2 3.1 5.1 10.5 14.8 18.2 12.7 8.1 4.0 4.2 3.1 6.2 12.6 17.8 20.2 16.0 9.9 4.8 5.0 3.5 5.5 11.4 16.0 18.2 14.6 8.9 4.2 4.4 3.3 5.5 11.4 15.8 17.6 14.9 9.0 4.3 4.5 3.4 5.7 11.9 17.4 18.6 16.6 9.0 4.3 4.5 3.4 5.4 11.2 15.9 17.6 14.7 8.7 4.1 4.3 3.2 5.6 11.5 16.3 17.4 15.3 8.9 4.3 4.4 3.5 5.3 11.0 15.4 17.5 14.3 8.5 4.1 4.2 3.2 5.3 11.3 16.3 18.1 14.4 8.5 4.0 4.2 3.2 5.6 11.4 16.0 17.7 14.5 8.9 4.4 4.5 3.4 5.4 11.3 16.4 20.8 13.5 8.5 4.1 4.3 2.9 5.4 11.8 16.5 18.5 15.0 9.2 4.0 4.2 3.0 5.4 10.9 14.8 17.3 13.0 8.8 4.2 4.4 3.2 5.3 11.1 15.4 17.3 13.5 8.7 4.1 4.3 3.3 5.5 12.8 18.6 20.6 17.9 9.6 4.0 4.2 3.0 5.2 11.1 16.7 19.6 15.1 8.1 4.0 4.1 3.4 6.2 11.7 15.9 18.0 14.3 9.4 4.8 5.1 3.0 5.6 10.6 14.4 16.6 12.9 8.5 4.3 4.6 2.8 5.9 10.9 15.1 17.7 13.3 8.5 4.6 4.9 3.0 5.6 11.2 15.2 16.7 14.0 9.0 4.1 4.5 2.4 5.6 11.1 15.6 17.7 13.5 8.6 4.3 4.6 2.8 5.6 10.9 15.0 16.0 14.2 8.6 4.4 4.6 3.1 5.5 10.0 12.6 14.1 12.1 8.6 4.3 4.6 2.8 5.7 10.5 13.8 16.8 11.6 8.6 4.4 4.7 2.9 5.5 10.4 14.8 19.2 12.8 8.0 4.3 4.6 2.8 5.5 10.5 14.5 18.2 12.0 8.2 4.3 4.5 2.9 5.3 9.9 13.3 15.8 11.6 7.9 4.2 4.5 2.4 5.3 10.3 13.3 14.1 12.8 8.6 4.2 4.4 2.4 5.4 10.7 14.2 15.8 13.1 8.7 4.1 4.4 2.6 5.4 10.9 14.0 15.9 12.7 9.1 4.1 4.3 3.1 5.0 9.7 12.8 16.8 10.0 8.0 3.9 4.2 2.5 Unemployed persons by reason for unemployment, monthly data seasonally adjusted (Numbers in thousands) On layoff.......................................................... Other job losers................................................ New entrants ...................................................... Apr. Mar. Feb. 1988 1987 1989 1988 Annual average Reason tor unemployment June May Nov. Oct. Sept. Aug. July Jan. Dec. Feb. 3,066 819 2,247 998 1,725 799 3,121 827 2,294 985 1,835 780 2,876 774 2,102 985 1,740 765 3,566 943 2,623 965 1,974 920 3,092 851 2,241 983 1,809 816 3,182 877 2,305 969 1,916 855 3,131 882 2,249 1,059 1,792 871 2,968 844 2,124 985 1,804 886 3,201 806 2,395 942 1,804 811 3,070 861 2,209 953 1,747 800 3,085 853 2,232 923 1,883 799 3,112 880 2,232 986 1,843 800 3,079 833 2,246 985 1,767 761 2,951 844 2,107 984 1,747 747 3,031 814 2,217 963 1,766 799 48.0 12.7 35.3 13.0 26.6 12.4 46.1 12.7 33.4 14.7 27.0 12.2 46.0 12.7 33.3 14.0 27.7 12.4 45.7 12.9 32.8 15.5 26.1 12.7 44.7 12.7 32.0 14.8 27.2 13.3 47.4 11.9 35.4 13.9 26.7 12.0 46.7 13.1 33.6 14.5 26.6 12.2 46.1 12.8 33.4 13.8 28.1 11.9 46.2 13.1 33.1 14.6 27.3 11.9 46.7 12.6 34.1 14.9 26.8 11.5 45.9 13.1 32.8 15.3 27.2 11.6 46.2 12.4 33.8 14.7 26.9 12.2 46.5 12.4 34.1 15.1 26.2 12.1 46.4 12.3 34.1 14.7 27.3 11.6 45.2 12.2 33.0 15.5 27.3 12.0 3.0 .8 1.6 .8 2.5 .8 1.5 .7 2.6 .8 1.6 .7 2.6 .9 1.5 .7 2.4 .8 1.5 .7 2.6 .8 1.5 .7 2.5 .8 1.4 .7 2.5 .8 1.5 .7 2.6 .8 1.5 .7 2.5 .8 1.4 .6 2.4 .8 1.4 .6 2.5 .8 1.4 .7 2.5 .8 1.4 .7 2.5 .8 1.5 .6 2.3 .8 1.4 .6 PERCENT OF UNEMPLOYED On layoff........................................................ Other job losers............................................. New entrants ................................................... PERCENT OF CIVILIAN LABOR FORCE Job leavers........................................................ Reentrants ......................................................... New entrants ...................................................... 10. Duration of unemployment, monthly data seasonally adjusted (Numbers in thousands) 1989 1988 Annual average Weeks of unemployment 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. 3,246 2,196 1,983 943 27 weeks and over........... ......................... 1,040 3,084 2,007 1,610 801 809 3,097 2,093 1,732 842 890 3,057 2,060 1,693 851 842 3,093 1,969 1,582 756 826 3,072 2,068 1,614 789 825 3,093 1,910 1,543 749 794 2,985 2,041 1,619 826 793 3,158 1,956 1,636 831 805 3,116 1,896 1,568 775 793 3,059 1,835 1,554 788 766 3,117 1,935 1,502 787 715 3,029 2,039 1,495 758 737 3,181 2,081 1,512 757 755 3,247 1,865 1,304 665 639 14.5 6.5 13.5 5.9 14.1 6.3 13.8 6.4 13.5 5.8 13.8 5.9 13.2 5.9 13.5 6.2 13.5 5.9 13.5 5.7 13.4 5.7 12.6 5.6 12.8 5.8 12.7 5.7 12.1 5.3 1987 Mean duration in weeks................................ Median duration in weeks.............................. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 65 MONTHLY LABOR REVIEW 11. April 1989 • Current Labor Statistics: Employment Data Unemployment rates of civilian workers by State, data not seasonally adjusted Jan. 1988 Jan. 1989 8.0 10.9 5.7 9.3 5.6 8.5 10.4 5.8 7.9 5.4 Florida.......................................................... 7.8 3.7 4.5 6.1 5.0 7.3 3.7 3.4 5.3 5.9 Hawaii........................................................... Idaho ............................................................ Illinois ........................................................... Indiana......................................................... 6.4 3.9 9.2 7.4 6.6 5.6 3.5 7.1 6.4 5.1 7.1 5.6 9.5 12.2 4.9 5.2 8.1 11.8 4.6 State Alabama....................................................... Arizona......................................................... Arkansas...................................................... California...................................................... Colorado ...................................................... Jan. 1988 Jan. 1989 9.5 5.2 7.2 3.3 7.3 3.5 5.9 2.9 New Jersey ................................................ 4.5 8.9 50 5.1 7.0 4.6 7.1 56 4.4 5.7 Ohio ............................................................ 7.1 7.6 7.1 6.2 4.0 6.9 66 6.1 5.0 3.2 6.1 4.7 7.0 8.4 6.7 4.6 48 65 7.6 4.4 State Nevada ....................................................... New Hampshire.......................................... Oregon........................................................ Pennsylvania............................................... Rhode Island............................................... South Carolina............................................ Kentucky...................................................... Maine........................................................... 5.5 Texas .......................................................... Utah ............................................................ Vermont...................................................... 5.2 10.7 6.1 4.0 3.8 7.8 5.1 10.7 9.4 6.8 6.5 3.8 Mississippi................................................ NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the 12. 4.1 43 3.3 13 8 7.1 43 68 84 4.6 8.9 80 8.2 database, Employment of workers on nonagricultural payrolls by State, data not seasonally adjusted (In thousands) State Alaska ..................................................... Arkansas .................................................. Delaware................................................. District of Columbia.................................. Georgia ................................................... Idaho ....................................................... Illinois...................................................... Iowa........................................................ Louisiana................................................. Maryland................................................. Massachusetts......................................... Minnesota................................................ Jan. 1988 Dec. 1988 1,516.9 195.2 1,397.6 829.4 11,767.3 1,567.2 207.1 1,434.8 873.1 12,378.3 1,404.8 1,642.9 317.4 654.7 4,954.3 1,444.9 1,709.2 338.0 682.2 5,257.1 2,806.8 465.4 330.0 4,958.9 2,317.0 2,949.9 490.1 357.2 5,136.7 2,450.1 1,105.9 1,001.9 1,336.6 1,476.2 497.1 1,185.6 1,052.2 1,395.4 T517.0 530.1 2,022.1 3,034.7 3,706.5 1,951.2 870.6 2,171.3 270.2 2,139.4 3,182.3 3,890.2 2,059.2 910.2 2,269.6 280.8 Jan. 1989p p = preliminary NOTE: Some data in this table may differ from data published elsewhere Digitized for66 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis State 1,548.7 199.2 Nevada .................................................. 1,411.0 858.9 12,194.9 New Mexico ............................................ 1,420.2 1,671.1 333.9 670.9 5,220.1 Oklahoma............................................... 2,924.4 Oregon................................................... 483.0 348.2 5,082.8 2,413.1 South Dakota.......................................... 1,158.3 1,030.0 1,373.2 Utah .......................................... 1,497.5 514.9 Virginia................................................... 2,078.5 Washington ............................................. 3,100.2 West Virginia........................................... 3,806.9 2,011.4 897.4 2,219.4 273.9 Jan. 1988 Dec. 1988 Jan. 1989p 665.4 509.5 514.1 705.4 556.2 543.3 692 8 549.9 530 4 3,544.1 525.5 7,977.0 2,884.5 248.1 3 700 0 549.6 8,335 9 3,030.8 259.0 3 611 2 539.0 8 116 0 2 984 9 253.1 4,546 1 T 106.3 1,101.5 4,891 6 444.4 4,781 8 1J45.1 1,183.3 5 106 8 464 4 4 671 4 1J25.5 1,157.8 4 993 7 448.7 1 393 4 253.5 2,011.0 6,501 6 636 9 1 479 4 265.5 2 073 1 6 755 0 682.7 1 457 9 258.0 2 045 3 6 697 4 661.8 248 9 2,683.6 1,855.0 590.0 2,072.6 264 3 2,860.7 1,984.5 616.9 2,185.0 259 3 2,804.7 1,955.4 602.4 2,139.5 177.7 792 1 40.6 177 9 836 6 41.5 174 6 823 7 40.6 because of the continual updating of the database. 13. Employment of workers on nonagiricultural payrolls by industry, monthly data seasonally adjusted (In thousands) 1988 Feb. t o t a l ...................................... 102,310 PRIVATE SECTOR ..................... 85,295 106,039 88,653 104,729 87,475 Oil and gas extraction ............... 24,784 721 405 25,565 733 417 25,271 731 415 General building contractors...... 4,998 1,326 5,293 1,396 Production workers ................... 19,065 12,995 Production workers ................... 1987 GOODS-PRODUCING Mining ........................................... Lumber and wood products ........ Furniture and fixtures................. Stone, clay, and glass products ... Primary metal industries ............. Blast furnaces and basic steel products................................... Fabricated metal products.......... Machinery, except electrical........ Electrical and electronic equipment................................. Transportation equipment........... Motor vehicles and equipment .... Instruments and related products Miscellaneous manufacturing industries ................................. 1989 1988 Annual average Industry Mar. Apr. May June July 106,057 106,271 88,678 88,941 Aug. Sept. Oct. 106,425 106,737 106,973 89,066 89,205 89,481 Jan. Feb. 107,419 107,641 89,855 90,100 108,056 90,515 108,345 90,739 Nov. Dec. 105,020 105,281 87,700 87,973 105,489 88,139 25,330 733 419 25,435 737 421 25,466 739 425 25,592 740 425 25,663 740 424 25,639 739 423 25,648 734 419 25,743 729 413 25,849 722 406 25,889 719 402 26,044 716 399 26,012 714 398 5,150 1,377 5,192 1,383 5,238 1,400 5,237 1,394 5,308 1,412 5,330 1,400 5,340 1,401 5,365 1,404 5,366 1,393 5,413 1,406 5,430 1,414 5,535 1,440 5,513 1,435 19,539 13,338 19,390 13,249 19,405 13,251 19,460 13,280 19,490 13,302 19,544 13,341 19,593 13,382 19,560 13,352 19,549 13,332 19,648 13,412 19,714 13,465 19,740 13,481 19,793 13,524 19,785 13,524 11,218 7,453 11,516 7,677 11,404 7,599 11,411 7,598 11,459 7,632 11,477 7,649 11,515 11,566 7,6764 7,720 11,547 7,705 11,537 7,689 11,595 7,733 11,637 7,765 11,651 7,776 11,688 7,806 11,674 7,801 740 518 582 749 758 538 587 782 756 535 584 770 755 534 585 772 758 535 587 773 757 537 585 776 757 537 587 781 756 541 589 789 753 537 586 785 753 538 585 787 760 540 588 794 767 541 590 796 771 540 592 794 776 540 592 796 770 542 593 794 269 1,407 281 1,455 280 1,438 281 1,439 281 1,444 281 1,448 281 1,457 282 1,464 281 1,458 280 1,460 282 1,469 282 1,474 280 1,479 281 1,487 281 1,490 2,023 2,138 2,091 2,099 2,111 2,121 2,134 2,151 2,156 2,159 2,173 2,185 2,190 2,196 2,203 2,115 2,048 851 709 2,120 2,047 850 713 2,122 2,052 857 715 2,126 2,044 855 718 2,124 2,032 849 716 2,126 2,045 859 719 2,130 2,050 860 721 2,123 2,051 858 726 2,120 2,066 871 729 2,115 2,050 857 729 381 382 387 384 383 381 383 385 386 388 8,077 5,700 8,089 5,705 8,105 5,718 8,111 5,723 2,084 2,048 865 696 2,120 2,042 850 713 2,112 2,031 837 705 2,115 2,025 835 705 2,117 2,045 848 706 370 383 382 382 383 7,847 5,543 8,023 5,662 7,986 5,650 7,994 5,653 8,001 5,648 8,013 5,653 8,029 5,665 8,027 5,662 8,013 5,647 8,012 5,643 8,053 5,679 Food and kindred products........ Tobacco manufactures .............. Textile mill products ................... Apparel and other textile products................................... Paper and allied products .......... 1,624 54 725 1,645 53 726 1,649 54 732 1,647 54 729 1,648 54 727 1,643 52 728 1,645 53 727 1,631 52 726 1,630 52 719 1,632 51 722 1,654 52 722 1,661 63 723 1,656 53 722 1,664 52 725 1,658 52 724 1,100 679 1,097 689 1,104 686 1,106 687 1,100 687 1,100 689 1,097 691 1,096 692 1,089 691 1,087 688 1,086 691 1,093 691 1,096 692 1,096 691 1,100 691 Printing and publishing............... Chemicals and allied products.... Petroleum and coal products...... Rubber and mise, plastics products................................... Leather and leather products ..... 1,507 1,026 165 1,565 1,063 167 1,544 1,049 165 1,548 1,052 164 1,554 1,056 165 1,559 1,060 166 1,565 1,065 167 1,567 1,067 167 1,572 1,070 167 1,575 1,069 168 1,581 1,071 169 1,583 1,073 169 1,592 1,076 168 1,597 1,081 167 1,599 1,082 168 823 144 873 146 856 147 860 147 864 146 870 146 873 146 882 147 878 145 874 146 882 145 887 144 890 144 887 145 892 145 77,525 80,475 79,458 79,690 79,846 80,023 80,465 80,608 80,786 81,089 81,230 81,570 81,752 82,012 82,333 5,385 3,166 5,584 3,336 5,513 3,272 5,530 3,285 5,543 3,298 5,556 3,308 5,582 3,332 5,598 3,345 5,605 3,351 5,618 3,366 5,631 3,380 5,658 3,407 5,670 3,422 5,711 3,453 5,723 3,465 2,218 2,248 2,241 2,245 2,245 2,248 2,250 2,253 2,254 2,252 2,251 2,251 2,248 2,258 2,258 6,115 3,635 2,480 6,148 3,660 2,488 6,174 3,681 2,493 6,192 3,696 2,496 6,219 3,714 2,505 6,246 3,736 2,510 6,275 3,758 2,517 6,301 3,779 2,522 6,332 3,796 2,536 6,362 3,815 2,547 Production workers..................... SERVICE-PRODUCING Transportation and public Transportation........................... Communication and public utilities...................................... 5,872 3,449 2,423 6,156 3,666 2,490 6,035 3,573 2,462 6,061 3,591 2,470 6,089 3,610 2,479 18,509 2,432 2,957 19,206 2,540 3,089 19,045 2,561 3,029 19,050 2,543 3,044 19,093 2,546 3,049 19,130 2,541 3,053 19,205 2,549 3,080 19,261 2,545 3,097 19,279 2,539 3,106 19,291 2,533 3,110 19,327 2,520 3,143 19,401 2,533 3,157 19,429 2,544 3,177 19,557 2,580 3,195 19,631 2,600 3,202 2,004 6,127 2,079 6,360 2,047 6,291 2,055 6,319 2,064 6,326 2,070 6,336 2,076 6,352 2,088 6,369 2,095 6,377 2,095 6,384 2,103 6,415 2,106 6,440 2,106 6,449 2,108 6,466 2,115 6,493 Real estate................................ 6,549 3,275 2,022 1,252 6,679 3,305 2,075 1,299 6,636 3,305 2,053 1,278 6,651 3,306 2,060 1,285 6,650 3,302 2,065 1,283 6,656 3,299 2,067 1,290 6,679 3,304 2,074 1,301 6,684 3,300 2,077 1,307 6,689 3,298 2,081 1,310 6,692 3,300 2,083 1,309 6,708 3,308 2,089 1,311 6,725 3,314 2,092 1,319 6,741 3,325 2,101 1,315 6,732 3,320 2,095 1,317 6,743 3,325 2,099 1,319 Health services .......................... 24,196 5,172 6,828 25,464 5,478 7,228 24,975 5,385 7,056 25,078 5,405 7,088 25,163 5,420 7,126 25,216 5,443 7,153 25,472 5,480 7,203 25,561 5,500 7,238 25,662 5,512 7,271 25,737 5,538 7,323 25,826 5,553 7,365 25,947 5,563 7,414 26,070 5,605 7,466 26,139 5,578 7,497 26,268 5,619 7,544 Local........................................ 17,015 2,943 3,963 10,109 17,387 2,971 4,051 10,365 17,254 2,972 4,014 10,268 17,320 2,970 4,031 10,319 17,308 2,963 4,041 10,304 17,350 2,957 4,050 10,343 17,379 2,951 4,049 10,379 17,330 2,951 4,059 10,320 17,359 2,956 4,070 10,333 17,532 2,989 4,086 10,457 17,492 2,989 4,070 10,433 17,564 2,989 4,074 10,501 17,541 2,990 4,071 10,480 17,541 2,973 4,061 10,507 17,606 2,975 4,079 10,552 Durable goods........................... Nondurable goods..................... General merchandise stores....... Food stores............................... Automotive dealers and service Eating and drinking places......... Finance, insurance, and real = preliminary NOTE: See notes on the data for a description of the most recent benchmark revision. ” https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 67 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Employment Data 14. Average weekly hours of production or nonsupervisory workers on private nonagricultural payrolls by industry, monthly data seasonally adjusted Industry Annual average 1987 1988 1988 Feb. Mar. Apr. May June July 1989 Aug. Sept. Oct. Nov. Dec. Jan.p Feb.p PRIVATE SECTOR .......................................... 34.8 34.8 34.8 34.6 34.9 34.7 34.7 34.9 34.6 34.7 34.9 34.8 34.7 34.8 34.7 MANUFACTURING................................................ 41.0 3.7 41.1 3.9 41.0 3.7 40.9 3.7 41.2 3.9 41.0 3.9 41.1 3.9 41.1 3.9 41.0 3.9 41.2 3.9 41.2 4.0 41.2 3.9 40.8 3.9 41.0 3.9 41.0 3.9 Overtime hours........................................... Lumber and wood products............................. Furniture and fixtures...................................... Stone, clay, and glass products....................... Primary metal industries .................................. Blast furnaces and basic steel products......... Fabricated metal products ............................... 41.5 3.8 40.6 40.0 42.3 43.1 43.4 41.5 41.8 4.1 40.3 39.4 42.3 43.6 44.0 41.8 41.5 3.8 40.3 39.5 42.3 43.1 43.8 41.6 41.5 3.8 40.1 39.3 42.3 43.3 43.7 41.6 42.0 4.2 40.6 39.5 42.5 43.5 43.8 42.0 41.8 4.2 40.1 39.5 42.3 43.6 43.9 41.9 41.8 4.1 40.2 39.4 42.4 43.6 44.3 42.0 41.8 4.0 40.5 39.7 42.1 43.4 44.0 41.7 41.6 4.1 40.0 39.0 42.1 43.5 44.0 41.8 41.9 4.0 39.9 39.6 42.3 44.0 44.6 42.0 41.9 4.2 40.7 39.4 42.5 43.8 44.3 41.9 41.9 4.2 40.3 39.4 42.6 43.7 44.0 42.2 41.5 4.1 40.3 39.2 42.4 43.4 43.7 41.7 41.8 4.1 40.3 40.0 42.6 43.7 43.9 41.8 41.6 4.0 39.6 39.6 41.8 43.3 43.7 41.7 Machinery except electrical ............................. Electrical and electronic equipment.................. Transportation equipment................................ Motor vehicles and equipment....................... Instruments and related products ..................... Miscellaneous manufacturing........................... 42.2 40.9 42.0 42.2 41.4 39.4 42.6 41.0 42.7 43.5 41.5 39.2 42.6 40.9 42.0 42.3 41.3 39.3 42.5 40.9 42.1 42.3 41.4 39.2 42.8 41.2 43.0 44.1 41.8 39.4 42.6 41.0 43.0 44.0 41.4 39.2 42.5 41.1 43.0 44.2 41.3 39.3 43.0 41.0 42.6 42.5 41.8 39.2 42.4 40.8 42.7 43.6 41.5 39.2 42.7 41.0 43.3 44.5 41.6 39.2 42.6 41.0 43.3 44.2 41.9 39.1 42.5 41.0 43.3 44.6 41.6 39.2 42.3 40.7 42.4 43.0 41.0 38.9 42.4 40.7 42.7 43.4 41.7 39.5 42.4 40.7 42.8 43.6 41.7 39.6 Nondurable goods.............................................. Overtime hours........................................... Food and kindred products.............................. Textile mill products........................................ Apparel and other textile products.................... Paper and allied products ................................ 40.2 3.6 40.2 41.8 37.0 43.4 40.2 3.7 40.4 41.1 36.9 43.2 40.2 3.6 40.3 41.6 37.0 43.3 40.1 3.6 40.1 41.2 37.0 43.2 40.3 3.6 40.1 41.6 37.4 43.3 40.0 3.6 40.1 40.8 36.8 43.3 40.1 3.6 40.3 40.7 36.9 43.2 40.2 3.7 40.5 41.1 36.9 43.2 40.1 3.6 40.4 41.1 36.8 43.2 40.2 3.7 40.3 41.1 37.1 43.3 40.2 3.8 40.6 41.0 36.8 43.2 40.2 3.6 40.6 41.0 37.0 43.1 39.9 3.6 40.3 40.5 36.6 43.1 40.1 3.6 40.1 40.8 37.0 43.1 40.1 3.7 40.2 40.7 37.0 43.3 Printing and publishing..................................... Chemicals and allied products.......................... Rubber and miscellaneous plastics products.... Leather and leather products .......................... 38.0 42.3 41.6 38.2 38.0 42.3 41.6 37.5 38.1 42.4 41.6 37.8 38.1 42.5 41.7 37.9 38.2 42.1 42.0 37.3 37.7 42.0 41.7 37.3 38.0 42.4 41.6 36.9 38.0 42.3 41.6 37.0 38.0 42.1 41.5 37.6 38.1 42.1 41.6 37.5 38.0 42.5 41.5 37.9 37.8 42.4 41.7 37.3 37.7 42.3 41.2 37.7 38.0 42.5 41.6 38.3 37.9 42.5 41.6 38.6 TRANSPORTATION AND PUBLIC UTILITIES 39.2 39.3 39.1 38.8 39.5 39.4 39.3 39.5 39.3 39.4 39.4 39.2 39.4 39.5 39.3 WHOLESALE TRADE........................................... 37.5 37.4 38.2 38.1 38.3 38.0 37.9 38.2 37.8 38.1 38.1 38.0 38.0 38.2 38.1 RETAIL TRADE .................................................... 29.2 29.1 29.1 29.0 29.2 29.0 29.1 29.3 29.0 28.9 29.2 29.0 29.2 29.2 29.1 SERVICES ............................................................. 32.5 32.6 32.7 32.4 32.7 32.5 32.5 32.7 32.4 32.6 32.8 32.6 32.6 32.8 32.5 Overtime hours........................................... Durable goods.................................................... p = preliminary NOTE: See “ Notes on the data” for a description of the most recent Digitized for68 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis benchmark adjustment. 15. Average hourly earnings of production or nonsupervisory workers on private nonagricultural payrolls by industry, seasonally adjusted __________________ ________________ PRIVATE SECTOR (in current dollars)1 ......... 1989 1988 Annual average Industry 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan.p $8.98 $9.29 $9.13 $9.16 $9.23 $9.27 $9.27 $9.32 $9.32 $9.37 $9.43 $9.42 $9.45 $9.50 $9.51 13.13 10.32 9.86 12.50 10.19 6.43 9.43 9.14 13.17 10.35 9.88 12.43 10.16 6.46 9.33 9.18 4.82 Finance, insurance, and real estate ............. Services....................................................... 12.69 9.91 9.48 12.03 9.59 6.11 8.73 8.48 12.97 10.17 9.71 12.32 9.92 6.31 9.10 8.90 12.82 10.03 9.59 12.19 9.72 6.20 8.91 8.72 12.90 10.05 9.61 12.21 9.76 6.22 8.90 8.75 12.93 10.11 9.65 12.29 9.88 6.25 8.99 8.81 12.91 10.15 9.69 12.35 9.88 6.28 9.08 8.88 12.93 10.18 9.72 12.33 9.86 6.29 9.00 8.86 13.03 10.17 9.71 12.37 9.97 6.33 9.10 8.92 12.99 10.20 9.74 12.39 9.93 6.32 9.09 8.93 13.04 10.26 9.78 12.37 10.01 6.34 9.18 8.99 13.03 10.28 9.81 12.43 10.13 6.37 9.36 9.06 13.01 10.29 9.83 12.37 10.04 6.42 9.26 9.04 13.09 10.31 9.84 12.36 10.08 6.42 9.37 9.09 PRIVATE SECTOR (in constant (1977) dollars)1 4.86 4.84 4.84 4.83 4.85 4.85 4.84 4.84 4.82 4.83 4.84 4.82 4.82 Manufacturing.............................................. Excluding overtime................................... Transportation and public utilities................ 1 Includes mining, not shown separately. - Data not available. Feb.P - p = preliminary. NOTE: See “ Notes on the data” for a description of the most recent benchmark revision. 16. Average hourly earnings of production or nonsupervisory workers on private nonagricultural payrolls by industry Industry Annual average 1987 1988 1989 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. JanT Feb.P $9.46 $9.46 $9.54 $9.54 PRIVATE SECTOR................................................ $8.98 $9.29 $9.17 $9.18 $9.23 $9.26 $9.23 $9.25 $9.24 $9.40 $9.45 12.52 12.69 12.71 12.59 12.60 12.54 12.55 12.66 12.62 12.75 12.72 12.83 12.97 13.11 13.03 13.04 13.16 13.21 13.16 MINING.................................................................. CONSTRUCTION.................................................. 12.69 12.97 12.82 12.87 12.88 12.87 12.85 12.91 12.95 13.13 13.13 MANUFACTURING................................................ 9.91 10.17 10.05 10.07 10.12 10.14 10.16 10.16 10.12 10.25 10.24 10.30 10.37 10.37 10.37 10.90 8.75 8.04 10.58 12.27 14.07 10.43 10.90 8.70 8.07 10.60 12.27 13.99 10.44 10.90 8.69 8.06 10.60 12.23 13.96 10.44 10.43 8.40 7.67 10.25 11.94 13.78 10.00 10.70 8.60 7.92 10.48 12.15 13.98 10.24 10.58 8.53 7.74 10.33 12.03 13.89 10.13 10.59 8.45 7.76 10.36 12.07 13.89 10.14 10.65 8.50 7.81 10.41 12.11 13.94 10.22 10.67 8.54 7.87 10.45 12.13 13.96 10.23 10.69 8.60 7.91 10.48 12.15 13.96 10.26 10.67 8.65 7.97 10.54 12.22 14.09 10.18 10.64 8.58 8.00 10.46 12.11 13.96 10.20 10.78 8.67 8.07 10.55 12.25 14.08 10.32 10.78 8.76 8.04 10.58 12.20 14.04 10.32 10.85 8.68 8.00 10.61 12.23 14.01 10.35 Machinery, except electrical ............................ 10.70 Electrical and electronic equipment.................. 9.88 Transportation equipment................................. 12.95 Motor vehicles and equipment....................... 13.55 Instruments and related products .................... 9.71 Miscellaneous manufacturing........................... 7.75 10.97 10.13 13.36 14.07 9.95 7.98 10.82 10.02 13.17 13.85 9.92 7.90 10.84 10.04 13.20 13.93 9.88 7.91 10.88 10.09 13.28 14.09 9.89 7.92 10.90 10.12 13.31 14.10 9.87 7.94 10.93 10.15 13.35 14.16 9.88 7.93 10.94 10.13 13.23 13.86 9.93 7.94 10.93 10.15 13.26 13.90 9.91 7.93 11.05 10.19 13.49 14.17 9.97 7.99 11.07 10.16 13.49 14.16 10.05 8.07 11.17 10.24 13.60 14.25 10.05 8.09 11.20 10.29 13.65 14.31 10.10 8.17 11.16 10.27 13.63 14.29 10.17 8.22 11.20 10.25 13.61 14.26 10.24 8.20 9.18 Food and kindred products.............................. 8.94 14.03 Tobacco manufactures.................................... Textile mill products........................................ 7.17 Apparel and other textile products.................... 5.93 Paper and allied products................................ 11.43 9.42 9.11 14.56 7.37 6.10 11.64 9.31 9.06 14.01 7.30 6.02 11.50 9.33 9.07 14.42 7.31 6.03 11.52 9.37 9.14 14.98 7.35 6.04 11.60 9.38 9.15 15.24 7.31 6.05 11.64 9.39 9.12 15.78 7.33 6.08 11.65 9.45 9.13 15.66 7.31 6.02 11.71 9.40 9.04 14.84 7.37 6.07 11.63 9.50 9.12 13.98 7.43 6.19 11.70 9.48 9.04 13.92 7.45 6.20 11.67 9.53 9.16 14.43 7.47 6.23 11.72 9.60 9.26 14.18 7.52 6.27 11.79 9.62 9.28 14.33 7.59 6.29 11.77 9.62 9.30 14.71 7.60 6.28 11.80 Printing and publishing..................................... 10.28 Chemicals and allied products.......................... 12.37 Petroleum and coal products........................... 14.59 Rubber and miscellaneous plastics products.... 8.91 Leather and leather products .......................... 6.08 10.53 12.67 15.05 9.11 6.28 10.40 12.55 14.96 9.00 6.19 10.45 12.53 14.98 9.00 6.23 10.40 12.57 15.00 9.04 6.29 10.43 12.59 14.93 9.04 6.27 10.43 12.60 15.04 9.07 6.27 10.49 12.70 14.99 9.11 6.20 10.55 12.63 14.91 9.14 6.23 10.70 12.76 15.08 9.18 6.31 10.68 12.79 15.22 9.20 6.34 10.68 12.87 15.25 9.22 6.42 10.71 12.91 15.28 9.27 6.45 10.73 12.84 15.30 9.32 6.49 10.69 12.92 15.34 9.29 6.53 TRANSPORTATION AND PUBLIC UTILITIES.... 12.03 12.32 12.23 12.19 12.27 12.28 12.27 12.33 12.35 12.41 12.43 12.46 12.43 12.51 12.48 Lumber and wood products............................. Furniture and fixtures...................................... Stone, clay, and glass products....................... Primary metal industries .................................. Blast furnaces and basic steel products........ Fabricated metal products ............................... Nondurable goods ............................................... WHOLESALE TRADE........................................... 9.59 9.92 9.78 9.78 9.88 9.87 9.85 9.93 9.88 10.01 10.08 10.05 10.12 10.22 10.22 6.24 6.26 6.28 6.26 6.28 6.26 6.37 6.38 6.43 6.42 6.47 6.49 RETAIL TRADE .................................................... 6.11 6.31 6.23 FINANCE, INSURANCE, AND REAL ESTATE.... 8.73 9.10 9.02 8.97 9.03 9.09 8.98 9.03 9.04 9.14 9.29 9.27 9.32 9.48 9.45 SERVICES ............................................................. 8.48 8.90 8.81 8.80 8.82 8.84 8.78 8.79 8.79 8.98 9.07 9.10 9.15 9.24 9.27 p = preliminary NOTE: See “ Notes on the data” for a description of the most recent https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis benchmark revision. 69 MONTHLY LABOR REVIEW 17. April 1989 • Current Labor Statistics: Employment Data Average weekly earnings of production or nonsupervisory workers on private nonagricultural payrolls by industry Annual average 1988 1989 Industry 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan.p Feb.p PRIVATE SECTOR Current dollars.............................................. $312.50 $323.29 $316.37 $315.79 $320.28 $320.40 $322.13 $324.68 $323.40 $327.12 $329.81 $328.26 $330.15 $329.13 $327.22 Seasonally adjusted.................................... 317.72 316.94 322.13 321.67 321.67 325.27 322.47 325.14 329.11 327.82 327.92 330.60 330.00 Constant (1977) dollars ................................ 169.28 168.29 168.01 167.08 168.57 167.92 168.13 168.75 167.30 168.10 168.96 167.99 168.70 167.41 MINING.................................................................. 530.85 536.79 531.28 527.52 539.28 529.19 533.38 535.52 530.04 538.05 543.14 537.58 553.82 549.31 CONSTRUCTION.................................................. 479.68 491.56 462.80 481.34 488.15 491.63 497.30 497.04 499.87 504.19 512.07 491.61 489.55 480.84 476.39 Current dollars............................................... Constant (1977) dollars.................................. 406.31 220.10 417.99 409.04 217.59 217.23 411.86 414.92 217.92 218.38 414.73 217.36 418.59 218.47 413.51 214.92 412.90 213.61 423.33 217.54 422.91 216.66 427.45 431.39 218.76 220.43 Durable goods ..................................................... Lumber and wood products............................. Furniture and fixtures...................................... Stone, clay, and glass products....................... Primary metal industries .................................. Blast furnaces and basic steel products......... Fabricated metal products ............................... 432.85 341.04 306.80 433.58 514.61 598.05 415.00 447.26 346.58 312.05 443.30 529.74 615.12 428.03 436.95 440.54 444.11 444.94 448.98 339.49 337.16 345.10 345.87 351.74 301.09 302.64 305.37 307.72 311.65 426.63 435.12 442.43 447.26 448.54 519.70 523.84 526.79 527.66 530.96 609.77 606.99 613.36 612.84 621.22 418.37 421.82 426.17 426.59 431.95 439.60 348.60 310.03 446.90 525.46 619.96 417.38 439.43 452.76 452.76 457.87 345.77 348.53 358.28 347.20 314.40 323.61 322.40 318.40 444.55 451.54 454.94 451.99 521.94 539.00 531.92 536.90 608.66 629.38 616.36 616.44 423.30 433.44 433.44 439.88 Machinery, except electrical ............................ Electrical and electronic equipment.................. Transportation equipment................................. Motor vehicles and equipment....................... Instruments and related products..................... Miscellaneous manufacturing........................... 542.05 MANUFACTURING Nondurable goods............................................... Food and kindred products.............................. Tobacco manufactures.................................... Textile mill products........................................ Apparel and other textile products.................... Paper and allied products ................................ 425.17 216.26 422.06 - 462.16 454.53 353.50 344.52 325.62 316.34 446.48 439.90 541.11 537.43 621.89 614.16 445.36 436.39 451.26 339.78 314.34 432.48 530.78 610.05 432.22 451.54 467.32 459.85 462.87 463.49 462.16 465.62 462.76 459.06 471.84 470.48 478.08 404.09 415.33 406.81 410.64 411.67 411.88 417.17 409.25 412.09 417.79 416.56 423.94 543.90 570.47 553.14 561.00 569.71 572.33 574.05 551.69 554.27 580.07 581.42 592.96 571.81 612.05 587.24 598.99 621.37 624.63 625.87 576.58 587.97 624.90 623.04 635.55 401.99 412.93 408.70 411.01 410.44 406.64 409.03 408.12 408.29 414.75 419.09 422.10 305.35 312.82 307.31 310.07 309.67 309.66 311.65 305.69 309.27 314.01 319.57 321.17 486.08 430.12 595.14 636.80 424.20 324.35 474.30 420.04 586.09 625.90 424.09 323.05 473.76 414.10 582.51 623.16 425.98 321.44 369.04 378.68 370.54 373.20 359.39 368.04 358.78 359.17 547.17 579.49 540.79 566.71 299.71 302.91 301.49 299.71 219.41 225.09 220.93 223.11 496.06 502.85 494.50 494.21 373.86 361.03 576.73 301.35 222.27 498.80 374.26 366.92 601.98 297.52 222.64 501.68 377.48 367.54 628.04 300.53 226.18 502.12 383.84 381.91 371.20 367.35 543.11 551.63 308.15 307.80 230.84 230.48 508.46 507.40 395.20 529.20 666.00 391.13 528.78 658.41 392.17 396.52 403.01 534.24 533.40 527.93 678.30 679.05 664.99 376.06 235.75 378.22 237.63 377.06 377.88 384.75 368.85 368.83 373.01 613.87 595.08 575.98 295.32 304.38 307.60 220.33 223.98 229.03 502.36 498.93 511.29 382.04 368.83 574.90 306.94 229.40 505.31 385.97 374.64 581.53 309.26 232.38 508.65 388.80 378.73 565.78 309.07 232.62 518.76 411.95 539.75 674.08 406.91 541.02 680.33 406.91 548.26 674.05 411.26 404.52 401.94 553.84 545.70 547.81 676.90 662.49 664.22 373.51 231.26 377.48 381.89 234.87 236.63 382.72 240.29 386.32 240.11 389.34 247.04 Printing and publishing..................................... Chemicals and allied products.......................... Petroleum and coal products........................... Rubber and miscellaneous plastics products........................................... Leather and leather products .......................... 390.64 523.25 641.96 400.14 393.12 399.19 535.94 530.87 532.53 668.22 647.77 654.63 370.66 232.26 378.98 372.60 235.50 227.79 375.30 377.87 233.00 232.73 TRANSPORTATION AND PUBLIC UTILITIES............................................................. 471.58 484.18 475.75 470.53 480.98 481.38 484.67 490.73 490.30 490.20 490.99 489.68 490.99 489.14 487.97 WHOLESALE TRADE........................................... 365.38 377.95 370.66 370.66 377.42 375.06 375.29 380.32 375.44 381.38 385.06 381.90 386.58 388.36 386.32 RETAIL TRADE.................................................... 178.41 183.62 177.56 178.46 180.91 181.49 184.04 188.40 186.55 184.73 185.66 185.18 190.03 184.40 184.97 FINANCE, INSURANCE, AND REAL ESTATE ............................................................... 316.90 326.69 328.33 321.13 326.89 325.42 321.48 326.89 322.73 327.21 334.44 330.94 333.66 343.18 338.31 SERVICES ............................................................. 275.60 290.14 287.21 284.24 287.53 286.42 287.11 290.07 291.85 296.59 295.75 297.38 - Data not available. p = preliminary https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 288.31 388.64 384.61 245.97 245.53 301.22 300.35 NOTE: See "Notes on the data” for a description of the most recent benchmark revision. 18. Diffusion indexes of employment change, seasonally adjusted (In percent) Jan. Feb. Mar. Apr. and year Over 1-month span: 1987 .................................................. 1988 ............................................................... 1989 ............................................................... May June July Aug. Sept. Oct. Nov. Dec. Private nonagricultural payrolls, 3 19 industri 3 S 57.4 60.3 64.8 58.3 64.6 57.3 59.9 64.0 ” 64.6 63.0 61.3 58.9 61.6 66.6 68.6 62.3 60.6 56.2 62.3 54.0 67.6 62.5 63.9 68.9 65.0 61.7 69.3 69.1 69.8 69.8 71.5 68.8 72.5 61.9 72.1 62.6 73.4 68.3 74.5 71.9 68.2 74.4 72.5 72.2 75.2 69.1 76.9 68.8 77.4 74.5 78.5 71.1 74.2 72.6 74.4 72.6 75.6 76.6 75.6 ” 77.2 75.6 77.4 78.4 77.8 76.5 79.1 - 78.7 77.8 “ 80.5 “ ' Over 3-month span: 1987 ....................................................... 1988 ............................................................... 1989 ............................................................... 61.3 70.6 69.1 62.2 68.8 “ 67.3 68.3 ” 68.9 67.2 " Over 6-month span: 1987 ........................................................ 1988 ............................................................... 1989 ............................................................... 69.2 72.2 66.3 71.5 “ 66.3 70.8 “ 70.1 74.2 ' Over 12-month span: 1987 ............................................................... 1988 ............................................................... 1989 ............................................................... 68.1 77.2 70.3 78.1 “ 71.1 74.2 ” 74.1 73.9 “ ' Manufacturing payrolls, 143 industries Over 1-month span: 1987 ............................................................... 1988 ............................................................... 1989 ............................................................... 46.8 58.2 61.0 52.5 55.7 51.8 53.9 55.7 “ 56.4 60.6 “ 55.7 61.3 67.7 60.3 56.0 44.0 64.2 46.8 64.2 61.7 64.2 68.1 61.0 57.4 68.4 68.8 69.5 61.3 73.8 52.1 70.2 53.5 74.1 65.6 74.5 70.9 67.0 70.9 69.1 66.0 74.5 63.8 75.5 62.1 76.6 68.8 79.4 66.0 74.1 66.7 72.7 69.9 72.3 - 73.0 72.0 ” 73.8 70.9 75.2 72.3 75.2 69.9 75.9 - 75.9 “ 75.2 ” 79.1 ” 58.9 57.4 " Over 3-month span: 1987 ............................................................... 1988 ............................................................... 1989 ............................................................... 50.7 66.0 62.1 50.7 61.0 “ 58.5 62.8 63.8 64.5 ” 63.5 66.7 " Over 6-month span: 1987 ............................................................... 1988 ............................................................... 1989 ............................................................... 58.5 68.4 ” 57.1 67.0 ” 57.1 66.0 “ 66.7 70.9 " Over 12-month span: 1987 ............................................................... 1988 ............................................................... 1989 ............................................................... 59.6 74.1 “ 63.5 72.3 64.5 68.8 “ - Data not available. NOTE: Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 68.8 70.6 “ employment. Data for the 2 most recent months shown in each span are prelimi nary. See the “ Definitions” in this section. See “ Notes on the data” for a descrip tion of the most recent benchmark revision. MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Employment Data 19. Annual data: Employment status ol the noninstitutional population (Numbers in thousands) Employment status 1980 1981 1982 1983 1984 1985 1986 1987 1988 Noninstitutional population................................. 169,349 171,775 173,939 175,891 178,080 179,912 182,293 184,490 186,322 Labor force: Total (number).............................................. Percent of population.................................... 108,544 64.1 110,315 64.2 111,872 64.3 113,226 64.4 115,241 64.7 117,167 65.1 119,540 65.6 121,602 65.9 123,378 66.2 100,907 59.6 1,604 102,042 59.4 1,645 101,194 58.2 1,668 102,510 58.3 1,676 106,702 59.9 1,697 108,856 60.5 1,706 111,303 61.1 1,706 114,177 61.9 1,737 116,677 62.6 1,709 99,303 3,364 95,938 100,397 3,368 97,030 99,526 3,401 96,125 100,834 3,383 97,450 105,005 3,321 101,685 107,150 3,179 103,971 109,597 3,163 106,434 112,440 3,208 109,232 114,968 3,169 111,800 Unemployed: Total (number)........................................ Percent of labor force............................. 7,637 7.0 8,273 7.5 10,678 9.5 10,717 9.5 8,539 7.4 8,312 7.1 8,237 6.9 7,425 6.1 6,701 5.4 Not in labor force (number) ............................. 60,806 61,460 62,067 62,665 62,839 62,744 62,752 62,888 62,944 Employed: Total (number) ......................................... Percent of population ............................... Resident Armed Forces.......................... Civilian Total .................................................. Agriculture........................................ Nonagricultural industries................... NOTE: See “ Notes on the data” for a description of the most recent benchmark revision. 20. Annual data: Employment levels by industry (Numbers in thousands) Industry 1980 1981 1982 1983 1984 1985 Total employment.............................................................. Private sector................................................................... Goods-producing........................................................... Mining...................................................................... Construction ............................................................. Manufacturing........................................................... 90,406 74,166 25,658 1,027 4,346 20,285 91,156 75,126 25,497 1,139 4,188 20,170 89,566 73,729 23,813 1,128 3,905 18,781 90,200 74,330 23,334 952 3,948 18,434 94,496 78,472 24,727 966 4,383 19,378 97,519 81,125 24,859 927 4,673 19,260 99,525 102,310 106,039 82,832 85,295 88,653 24,558 24,784 25,565 777 721 733 4,816 4,998 5,293 18,965 19,065 19,539 Service-producing.......................................................... Transportation and public utilities................................ Wholesale trade ........................................................ Retail trade ............................................................... Finance, insurance, and real estate............................ Services.................................................................... 64,748 5,146 5,275 15,035 5,160 17,890 65,659 5,165 5,358 15,189 5,298 18,619 65,753 5,082 5,278 15,179 5,341 19,036 66,866 4,954 5,268 15,613 5,468 19,694 69,769 5,159 5,555 16,545 5,689 20,797 72,660 5,238 5,717 17,356 5,955 22,000 74,967 5,255 5,753 17,930 6,283 23,053 77,525 5,385 5,872 18,509 6,549 24,196 80,475 5,584 6,156 19,206 6,679 25,464 Government............................................................. Federal................................................................ State.................................................................... Local................................................................... 16,241 2,866 3,610 9,765 16,031 2,772 3,640 9,619 15,837 2,739 3,640 9,458 15,869 2,774 3,662 9,434 16,024 2,807 3,734 9,482 16,394 2,875 3,832 9,687 16,693 2,899 3,893 9,901 17,015 2,943 3,963 10,109 17,387 2,971 4,051 10,365 NOTE: See “ Notes on the data” for a description of the most recent benchmark revision. 72FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1986 1987 1988 21. Annual data: Average hours and earnings of production or nonsupervisory workers on nonagricultural payrolls, by industry Industry Private sector Average weekly hours.......................... Average hourly earnings (in dollars)...... Average weekly earnings (in dollars) .... Mining Average weekly hours .................... Average hourly earnings (in dollars) .. Average weekly earnings (in dollars). Construction Average weekly hours .................... Average hourly earnings (in dollars) .. Average weekly earnings (in dollars) Manufacturing Average weekly hours .................... Average hourly earnings (in dollars) . Average weekly earnings (in dollars) Transportation and public utilities Average weekly hours .................... Average hourly earnings (in dollars) . Average weekly earnings (in dollars) Wholesale trade Average weekly hours .................... Average hourly earnings (in dollars) . Average weekly earnings (in dollars) Retail trade Average weekly hours .................... Average hourly earnings (in dollars) . Average weekly earnings (in dollars) Finance, insurance, and real estate Average weekly hours .................... Average hourly earnings (in dollars) . Average weekly earnings (in dollars) Services Average weekly hours ................... Average hourly earnings (in dollars) Average weekly earnings (in dollars) https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1980 1981 1982 1983 1984 1985 1986 1987 1988 35.3 6.66 235.10 35.2 7.25 255.20 34.8 7.68 267.26 35.0 8.02 280.70 35.2 8.32 292.86 34.9 8.57 299.09 34.8 8.76 304.85 34.8 8.98 312.50 34.8 9.29 323.29 43.3 9.17 397.06 43.7 10.04 438.75 42.7 10.77 459.88 42.5 11.28 479.40 43.3 11.63 503.58 43.4 11.98 519.93 42.2 12.46 525.81 42.4 12.52 530.85 42.3 12.69 536.79 37.0 9.94 367.78 36.9 10.82 399.26 36.7 11.63 426.82 37.1 11.94 442.97 37.8 12.13 458.51 37.7 12.32 464.46 37.4 12.48 466.75 37.8 12.69 479.68 37.9 12.97 491.56 39.7 7.27 288.62 39.8 7.99 318.00 38.9 8.49 330.26 40.1 8.83 354.08 40.7 9.19 374.03 40.5 9.54 386.37 40.7 9.73 396.01 41.0 9.91 406.31 41.1 10.17 417.99 39.6 8.87 351.25 39.4 9.70 382.18 39.0 10.32 402.48 39.0 10.79 420.81 39.4 11.12 438.13 39.5 11.40 450.30 39.2 11.70 458.64 39.2 12.03 471.58 39.3 12.32 484.18 38.5 6.96 267.96 38.5 7.56 291.06 38.3 8.09 309.85 38.5 8.55 329.18 38.5 8.89 342.27 38.4 9.16 351.74 38.3 9.35 358.11 38.1 9.59 365.38 38.1 9.92 377.95 30.2 4.88 147.38 30.1 5.25 158.03 29.9 5.48 163.85 29.8 5.74 171.05 29.8 5.85 174.33 29.4 5.94 174.64 29.2 6.03 176.08 29.2 6.11 178.41 29.1 6.31 183.62 36.2 5.79 209.60 36.3 6.31 229.05 36.2 6.78 245.44 36.2 7.29 263.90 36.5 7.63 278.50 36.4 7.94 289.02 36.4 8.36 304.30 36.3 8.73 316.90 35.9 9.10 326.69 32.6 5.85 190.71 32.6 6.41 208.97 32.6 6.92 225.59 32.7 7.31 239.04 32.6 7.59 247.43 32.5 7.90 256.75 32.5 8.18 265.85 32.5 8.48 275.60 32.6 8.90 290.14 MONTHLY LABOR REVIEW 22. April 1989 • Current Labor Statistics: Compensation & Industrial Relations Employment Cost Index, compensation,1 by occupation and industry group (June 1981=100) 1986 1987 1988 Percent change Series 3 months ended 12 months ended Dec. Mar. June Sept. Dec. Mar. June Sept. Dec. 133.8 135.0 135.9 137.5 138.6 140.6 142.1 144.0 145.5 1.0 5.0 136.9 128.4 136.6 138.5 129.1 138.0 139.3 130.1 138.5 141.2 131.3 139.9 142.2 132.5 140.8 144.2 134.7 142.9 145.7 136.2 144.3 147.9 137.2 147.2 149.7 138.2 148.5 1.2 .7 .9 5.3 4.3 5.5 129.5 130.1 136.5 143.6 130.2 130.7 138.1 145.2 “ “ 144.1 136.9 131.1 131.5 138.9 145.8 “ 132.2 132.7 140.8 149.2 146.4 139.6 133.5 134.1 141.7 150.6 148.1 140.5 135.8 136.8 143.6 152.8 150.3 142.3 137.3 138.1 145.1 153.8 151.2 143.9 138.2 139.0 147.6 157.7 154.0 146.1 139.3 140.1 149.2 159.7 154.4 147.7 .8 .8 1.1 1.3 1.3 1.3 .3 1.1 4.3 4.5 5.3 6.0 5.7 5.9 4.3 5.1 Dec 1988 Civilian workers 2 ....................... Workers, by occupational group: White-collar workers .............. Blue-collar workers................ Service occupations.............. Workers, by Industry division: Goods-producing.................... Manufacturing ....................... Service-producing................... Services............................... Health services................... Hospitals............................ Public administration 3 ........... Nonmanufacturing.................... Private industry workers.................................................. Workers, by occupational group: White-collar workers................................................... Professional specialty and technical occupations....... Executive, administrative, and managerial occupations Sales occupations..................................................... Administrative support occupations, including clerical.................................................................... Blue-collar workers..................................................... Precision production, craft, and repair occupation....... Machine operators, assemblers, and inspectors......... Transportation and material moving occupations......... Handlers, equipment cleaners, helpers, and laborers ... Service occupations................................................... Workers, by industry division: Goods-producing......................................................... Construction.............................................................. Manufacturing............................................................. Durables................................................................... Nondurables.............................................................. Service-producing ........................................................ Transportation and public utilities................................. Transportation........................................................... Public utilities............................................................ Wholesale and retail trade.......................................... Wholesale trade........................................................ Retail trade .............................................................. Finance, insurance, and real estate............................. Service...................................................................... Health services......................................................... Hospitals................................................................. Nonmanufacturing State and local government workers W orkers, by occupational group: W hite-collar w o rk e rs............................. Blue-collar w o rk e rs............................... W orkers, by Industry division: S e r v ic e s .................... ......................... Hospitals and other serv ice s'* ........ Health s e r v ic e s ................................. S c h o o ls ................................................ Elem entary and s e c o n d a ry ........... Public administration3 ........................... ---- * * • 141.6 135.4 131.6 132.9 133.8 135.1 136.0 138.1 139.8 141.2 142.6 1.0 4.9 134.3 136.1 “ “ 137.0 - 138.5 ” 139.3 “ 141.2 “ 143.0 “ 144.6 - 146.3 1.2 .6 1.3 2.4 5.0 4.9 4.1 6.8 130.6 135.9 131.8 136.7 134.1 138.6 _ 135.6 140.1 _ _ 136.5 142.2 137.6 143.9 .7 .8 .7 1.1 .3 .7 1.2 5.0 4.4 3.8 5.2 4.7 4.5 5.3 135.6 136.8 140.2 " 137.1 138.1 142.1 - 137.9 139.0 143.8 - 139.0 140.1 145.5 - .8 .8 .8 .7 1.1 1.2 .0 -.3 .4 .8 .5 1.0 3.5 1.1 1.4 1.5 4.4 4.2 4.5 4.5 4.4 5.1 2.8 3.5 2.1 5.2 4.2 5.7 6.5 5.7 6.0 6.1 138.9 140.8 142.4 143.9 1.1 5.0 " 127.8 “ “ “ 133.5 ~ “ 134.7 " 129.5 “ 135.2 129.2 130.1 “ 133.5 ~ ” ” “ “ “ “ “ 129.9 130.7 * “ 135.3 “ “ “ “ “ 130.8 131.5 136.3 “ 131.9 132.7 137.7 “ 133.2 134.1 138.4 - 132.4 134.1 135.1 136.4 137.1 128.4 - 144.7 145.9 146.3 149.7 151.1 153.1 153.6 157.8 159.6 1.1 5.6 147.2 140.8 147,5 141.3 151,2 143.3 152.7 144.3 154.8 145.9 155.2 145.9 159.6 148.4 161.8 149.1 1.4 .5 6.0 3.3 146,6 141,1 148.4 150.3 141.6 147,3 142.5 148.9 150.5 147.6 143.3 149,1 150,7 144,1 144,7 151.8 145.1 154.1 156.5 146.4 153.1 146.3 155.5 157.8 148,1 155.2 150.3 156.8 158.9 150.3 155.6 150.4 157.3 159.4 151,2 160.5 153.2 163.1 165.4 154,0 163.0 155.2 165.7 168.3 154.4 1.6 1.3 .8 1.8 1.8 .3 6.5 6.1 4.6 6.6 6.7 4.3 3 Consist of legislative, judicial, administrative, and regulatory 4 Includes, (or exam ple, library, social, and health services. - Data not available. activities. r-w. nvwi »Tvirwv/ luwouiou im hip tmpiuymeni U081 iriUBX Digitized for 74 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis - 146,0 139,5 consists of w ages, salaries, and employer cost of em ployee benefits. C o n sist of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers, 3 144.7 137.8 23. Employment Cost Index, wages and salaries, by occupation and industry group (June 1981=100) Series Dec. Mar. June Percent change 1988 1987 1986 Sept. Dec. Mar. June Sept. Dec. 3 months ended 12 months ended Dec. 988 Civilian workers 1 ....................... 131.5 132.8 133.5 135.2 136.1 137.4 138.7 140.5 141.9 1.0 4.3 Workers, by occupational group: White-collar workers .............. Blue-collar workers................ Service occupations.............. 135.0 125.6 132.8 136.6 126.2 134.2 137.3 127.1 134.7 139.4 128.3 136.0 140.2 129.4 136.6 141.5 130.4 138.0 143.0 131.6 139.3 145.2 132.5 141.8 146.8 133.4 142.9 1.1 .7 .8 4.7 3.1 4.6 127.0 127.9 134.2 141.1 127.8 128.7 135.8 142.7 128.5 129.5 136.5 143.4 129.8 130.8 138.5 146.8 131.0 132.2 139.2 148.2 132.2 133.3 140.5 149.5 134.1 135.1 144.2 154.0 135.1 136.2 145.8 155.7 149.4 144.1 .7 .8 1.1 1.1 1.3 1.3 .3 1.0 3.1 3.0 4.7 5.1 5.5 5.7 3.9 4.6 Workers, by industry division Goods-producing.................... Manufacturing ....................... Service-producing................... Services ............................. Health services.................. Hospitals........................... Public administration 2 ........ Nonmanufacturing ................. Private industry workers.......................................... Workers, by occupational group: White-collar workers........................................... Professional specialty and technical occupations Executive, administrative, and managerial occupations................................................... Sales occupations............................................ Administrative support occupations, including clerical........................................................... Blue-collar workers............................................. Precision production, craft, and repair occupations.................................................. Machine operators, assemblers, and inspectors . Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers......................................................... Service occupations........................................... Workers, by industry division: Goods-producing................................................. Construction ...................................................... Manufacturing.................................................... Durables......................................................... Nondurables.................................................... Service-producing................................................ Transportation and public utilities..................... Transportation................................................ Public utilities................................................. Wholesale and retail trade............................... Wholesale trade ........................................... Retail trade.................................................. Finance, insurance, and real estate.................. Services......................................................... Health services............................................. Hospitals...................................................... Nonmanufacturing............................................. State and local government workers Workers, by occupational group White-collar workers...................... Blue-collar workers........................ Workers, by industry division Services ....................................... Hospitals and other services 3 ..... Health services......................... Schools...................................... Elementary and secondary ....... Public administration 2................... 138.1 133.0 140.5 134.5 141.0 135.2 142.6 137.1 143.8 137.8 145.5 139.0 133.4 134.4 141.9 150.4 _ 146.4 140.5 129.5 130.8 131.7 133.0 133.8 135.1 136.6 137.9 139.3 1.0 4.1 144.0 148.9 1.1 .5 4.7 4.4 1.3 2.2 3.7 6.6 _ _ - - - 148.9 142.7 132.7 136.4 134.6 138.4 135.4 139.1 137.0 141.2 137.6 142.6 139.0 144.0 140.8 145.8 142.4 148.1 133.5 124.9 135.6 126.7 136.4 127.1 138.6 127.0 139.2 126.1 139.9 127.5 141.3 130.8 142.5 131.5 144.4 134.4 132.7 134.3 135.5 137.1 138.1 140.2 141.2 143.2 144.1 .6 4.3 .8 3.1 125.1 125.6 126.6 127.7 128.9 129.9 131.1 131.9 132.9 127.4 124.9 120.1 127.9 125.5 120.5 128.8 126.7 121.5 130.2 127.5 122.3 131.1 129.2 122.9 132.1 129.9 123.7 133.4 131.2 125.4 134.0 131.9 126.7 134.9 133.3 126.9 .7 1.1 .2 2.9 3.2 3.3 121.4 130.1 121.9 131.4 122.6 131.9 123.7 132.6 125.0 133.2 126.7 134.5 127.5 135.8 128.4 137.6 129.3 139.1 .7 1.1 3.4 4.4 126.8 120.8 127.9 127.2 129.3 131.6 127.5 127.5 121.7 128.7 127.7 130.5 133.4 128.1 128.3 122.7 129.5 128.7 131.0 134.3 129.3 129.6 123.8 130.8 129.7 132.8 135.7 130.0 130.8 124.7 132.2 131.1 134.1 136.2 130.2 132.0 125.9 133.3 132.1 135.6 137.5 131.3 _ 133.2 127.6 134.4 133.1 136.7 139.3 132.5 133.9 128.6 135.1 133.7 137.6 141.0 133.5 134.9 129.4 136.2 134.6 139.1 142.6 133.4 - 131.9 139.0 129.2 132.9 148.6 _ 134.6 141.7 131.7 134.9 149.8 _ - .7 .6 .8 .7 1.1 1.1 -.1 -.4 .4 .7 .3 .8 3.7 1.0 1.3 1.4 3.1 3.8 3.0 2.7 3.7 4.7 2.5 2.5 2.6 4.7 3.7 5.2 6.3 5.0 5.7 5.9 126.9 133.1 124.5 130.0 139.5 - 127.9 134.8 125.2 133.5 141.8 - 129.9 137.2 127.1 131.5 142.8 - _ 130.6 137.8 127.8 131.8 145.9 - _ _ 130.7 138.5 127.7 131.6 147.1 - _ _ - - - 136.0 143.2 133.2 134.9 152.9 - 136.9 143.6 134.3 139.9 154.4 - - - - 130.4 131.9 132.8 134.2 134.8 136.0 137.8 139.4 140.8 1.0 4.5 141.4 142.5 142.8 146.1 147.4 148.7 149.1 153.0 154.5 1.0 4.8 154.9 143.5 156.8 144.1 1.2 .4 5.0 3.2 155.6 147.4 158.0 159.7 148.9 157.6 148.7 160.3 162.1 149.4 1.3 .9 1.0 1.5 1.5 .3 5.4 4.6 4.8 5.6 5.7 3.S 142.8 135.1 143.9 136.3 144.1 136.9 147.7 139.0 149.3 139.6 150.5 141.1 150.8 141.1 143.3 137.3 143.9 138.6 144.2 139.4 148.2 141.2 149.5 142.2 145.1 146.4 138.1 145.5 146.5 140.5 145.6 146.6 141.0 150.3 152.0 142.6 151.8 153.4 143.8 150.7 144.5 152.6 154.0 145.5 151.1 144.7 153.0 154.3 146.4 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. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis _ _ _ _ _ 3 Includes, for example, library, social and health services. - Data not available. MONTHLY LABOR REVIEW 24. April 1989 • Current Labor Statistics: Compensation & Industrial Relations Employment Cost Index, private nonfarm workers, by bargaining status, region, and area size (June 1981=100) 1986 1987 1988 Percent change Series Dec. Mar. June Sept. Dec. Mar. June Sept. Dec. 3 months ended 12 months ended Dec. 1988 'COMPENSATION Workers, by bargaining status1 Union ............................................................................ Goods-producing........................................................... Service-producing.......................................................... Manufacturing ............................................................... Nonmanufacturing ......................................................... 129.8 127.5 133.4 127.9 131.5 130.5 128.0 134.4 128.0 132.6 131.2 128.7 135.2 128.7 133.5 132.0 129.5 135.9 129.5 134.3 133.4 131.3 136.7 131.5 135.1 135.6 134.1 138.0 135.0 136.2 136.9 135.3 139.4 136.2 137.5 137.9 136.2 140.5 137.0 138.6 138.6 137.2 140.9 138.2 138.9 0.5 .7 .3 .9 .2 3.9 4.5 3.1 5.1 2.8 Nonunion......................................................................... Goods-producing........................................................... Service-producing.......................................................... Manufacturing............................................................... Nonmanufacturing......................................................... 132.1 130.0 133.4 131.4 132.5 133.6 130.8 135.3 132.2 134.3 134.6 131.8 136.4 133.2 135.3 136.1 133.1 137.9 134.6 136.8 136.9 134.1 138.6 135.6 137.5 138.9 136.2 140.5 137.8 139.4 140.7 137.8 142.5 139.2 141.5 142.2 138.7 144.4 140.1 143.2 143.9 139.9 146.3 141.3 145.0 1.2 .9 1.3 .9 1.3 5.1 4.3 5.6 4.2 5.5 135.2 131.4 128.1 132.8 137.4 132.1 129.1 134.1 138.6 133.2 130.2 134.2 140.3 134.2 131.2 135.8 141.9 135.4 131.7 136.3 143.7 137.1 134.4 138.3 145.9 139.3 135.5 139.5 147.8 140.4 136.7 140.6 150.4 141.3 138.0 141.5 1.8 .6 1.0 .6 6.0 4.4 4.8 3.8 132.2 127.9 133.5 129.0 134.4 130.2 135.8 131.3 136.7 132.0 138.9 133.6 140.5 135.5 142.0 136.2 143.6 136.8 1.1 .4 5.0 3.6 Union .................................................................. Goods-producing........................................................... Service-producing.......................................................... Manufacturing .................................................... Nonmanufacturing ............................................... 127.2 124.8 130.9 125.5 128.7 127.7 125.0 131.7 125.6 129.5 128.3 125.8 132.2 126.2 130.1 129.1 126.5 132.9 127.0 130.8 130.5 128.5 133.6 129.3 131.5 131.0 128.7 134.4 129.6 132.1 132.0 129.7 135.4 130.4 133.3 132.9 130.4 136.7 131.0 134.5 133.4 131.2 136.8 132.1 134.6 .4 .6 .1 .8 .1 2.2 2.1 2.4 2.2 2.4 Nonunion............................................... Goods-producing.......................................................... Service-producing.................................................. Manufacturing .......................................................... Nonmanufacturing .............................................. 130.3 127.8 131.7 129.5 130.6 131.8 128.8 133.6 130.6 132.4 132.8 129.6 134.6 131.5 133.4 134.3 131.1 136.2 133.0 134.9 135.0 132.1 136.7 133.9 135.4 136.4 133.6 138.0 135.5 136.8 138.1 135.0 140.0 136.7 138.8 139.5 135.7 141.8 137.4 140.4 141.1 136.8 143.6 138.6 142.2 1.1 .8 1.3 .9 1.3 4.5 3.6 5.0 3.5 5.0 133.1 129.4 126.2 130.1 135.4 130.1 127.4 131.2 136.6 131.1 128.5 131.1 138.3 132.1 129.6 133.1 139.7 133.0 129.9 133.5 140.9 134.0 131.3 134.9 142.9 136.1 132.1 136.0 144.6 137.1 133.3 137.4 147.3 137.8 134.5 138.1 1.9 .5 .9 .5 5.4 3.6 3.5 3.4 130.2 125.6 131.6 126.6 132.4 127.8 133.7 129.1 134.6 129.8 135.8 130.9 137.3 133.0 138.7 133.5 140.2 133.7 1.1 4.2 3.0 Workers, by region 1 Northeast................................................................... South .............................................................................. Midwest (formerly North Central)....................................... West................................................................................ Workers, by area size 1 Metropolitan areas........................................................... Other areas................................................................ WAGES AND SALARIES Workers, by bargaining status 1 Workers, by region 1 Northeast................................................ South ..................................................... Midwest (formerly North Central)....................... West..................................................... Workers, by area size1 Metropolitan areas............................................ Other areas....................................... The indexes are calculated differently from those for the occupation and industry groups. For a detailed description of the index calculation, see the 76FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis •1 M o n th ly L a b o r R e v ie w Technical Note, “ Estimation procedures for the Employment Cost Index,” May 1982. 25. S p e c ifie d c o m p e n s a t io n a n d w a g e a d ju s tm e n ts fr o m c o n t r a c t s e t t le m e n t s , a n d e f f e c t iv e w a g e a d ju s tm e n ts , p r iv a te Quarterly average Annual average 1988 1987 Measure 1986 Specified adjustments: Total compensation ' adjustments, covering 5,000 workers or more: 1987 I II III IV I IV; III If settlements Wage adjustments, settlements covering 1,000 workers or more: Effective adjustments: Deferred from settlements reached in earlier 1.1 1.6 3.0 2.6 1.1 2.1 4.1 3.9 2.5 2.1 3.4 2.4 1.8 1.8 3.1 2.4 3.4 3.2 3.8 2.2 1.2 1.8 2.2 2.1 .8 1.6 2.6 2.9 2.1 2.0 2.4 1.8 2.1 2.3 2.6 2.2 2.7 2.8 2.7 2.3 2.3 .5 3.1 .7 .4 (4) 1.0 .2 .9 .2 .8 .3 .4 .1 .9 .3 .8 .2 .5 .1 1.7 .2 1.8 .5 .3 .1 7 .2 .6 .1 .3 .2 .3 .1 .5 .1 .4 .2 .2 .2 3 Because of rounding, total may not equal sum of parts. Between -0.05 and 0.05 percent. 1 Compensation includes wages, salaries, and employers’ cost of employee benefits when contract is negotiated. 2 Adjustments are the net result of increases, decreases, and no changes in com pensation or wages. = preliminary. 26. Average specified compensation and wage adjustments, major collective bargaining settlements in private industry situations covering 1,000 workers or more during 4-quarter periods (in percent)____________________ Average for four quarters ending1988 1987 Measure IV III II I I ivp HIP ip Specified total compensation adjustments, settlements covering 5,000 workers or more, all industries: 1.2 1.7 1.8 2.1 2.7 2.6 3.0 2.6 3.1 2.5 3.0 2.3 3.1 2.5 3.1 2.5 1.2 2.0 .8 1.8 1.8 1.8 1.5 1.8 1.3 2.0 1.7 2.1 2.0 2.1 2.0 2.2 1.7 2.5 2.2 2.3 2.1 2.1 1.5 2.5 2.4 2.2 2.5 2.2 1.4 2.7 2.4 2.4 2.4 2.0 1.5 2.5 2.5 2.4 2.6 2.2 1.5 2.8 2.6 2.4 2.7 2.4 1.8 2.8 -1.5 1.3 -3.5 (2) .8 -.6 -.8 1.3 -2.7 .3 .8 -.2 1.1 2.1 -.1 1.0 1.0 1.2 2.1 2.4 1.3 1.3 1.0 2.1 2.4 2.4 2.4 1.5 1.0 2.7 2.5 2.5 2.5 1.6 1.3 2.5 2.5 2.4 3.0 1.9 1.4 3.1 2.2 2.1 2.5 2.1 1.8 2.6 2.2 2.2 2.1 2.4 2.2 2.5 2.3 2.1 2.3 2.6 2.2 2.7 2.4 2.1 2.6 2.8 2.4 2.9 2.3 1.9 2.4 2.7 2.7 2.7 2.3 1.6 2.5 2.7 2.4 2.7 2.3 2.2 2.4 2.4 1.9 2.6 2.4 2.4 2.5 2.4 1.8 2.7 2.8 2.9 2.7 2.5 1.7 2.8 2.4 1.6 2.4 2.5 1.4 2.6 2.7 3.7 2.7 2.9 3.8 2.9 2.9 2.6 .0 2.6 2.7 .0 2.7 2.1 .0 2.1 2.4 .0 2.4 2.2 .0 2.2 2.6 .0 2.6 Specified wage adjustments, settlements covering 1,000 workers or more: All industries Annual rate over life of contract .................................................. Manufacturing Nonmanufacturing Construction Contracts without COLA clauses............................................... 1 Data do not meet publication standards. 2 Between -0.05 and 0.05 percent. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 2.9 3.0 (1) (1) (’) () 3.2 (’) 0 p = preliminary. (1) (1) 3.1 (1) l) (’) 0 .0 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Compensation & Industrial Relations 27. Average effective wage adjustments, private industry collective bargaining situations covering 1,000 workers or more during 4-quarter periods (in percent) Average for four quarters endingEffective wage adjustment 1987 1988 II III IV I IP lllp IVP 2.2 .3 1.6 .3 2.6 .4 1.7 .4 3.1 .7 1.8 .5 3.2 .8 1.8 .5 3.0 1.0 1.6 .5 2.9 1.0 1.4 .5 2.6 .7 13 .6 2.8 .9 3.5 1.8 3.2 1.8 3.3 2.3 3.6 2.9 3.3 2.6 3.8 2.9 3.3 2.7 3.7 2.9 3.3 2.3 3.5 2.9 3.0 2.5 3.3 3.1 3.0 For all workers:1 Total................................................... From settlements reached in period .............................. Deferred from settlements reached in earlier period ........ From cost-of-living-adjustments clauses....................................... For workers receiving changes: Total....................................................... From settlements reached in period .................... Deferred from settlements reached in earlier period..................... From cost-of-living-adjustments clauses................................. 1 Because of rounding, total may not equal sum of parts. 2.7 = preliminary. p 28. Specified compensation and wage adjustments from contract settlements, and effective wage adjustments, State and local government collective bargaining situations covering 1,000 workers or more (in percent) Annual average Measure 1986 1987 1988p 6.2 6.0 4.9 4.8 5.4 5.3 5.7 5.7 4.9 5.1 5.1 5.3 5.5 2.4 3.0 (4) 4.9 2.7 2.2 (4) 4.7 2.3 2.4 (4) Specified adjustments: Total compensation 1 adjustments, 2 settlements covering 5,000 workers or more: First year of contract....................................................................................... Annual rate over life of contract ...................................................................... Wage adjustments, settlements covering 1,000 workers or more: First year of contract ............................................................. Annual rate over life of contract ............................................. Effective adjustments: Total effective wage adjustment 3 ............................. From settlements reached in period........................ Deferred from settlements reached in earlier periods From cost-of-living-adjustment clauses.................... 1 Compensation includes wages, salaries, and employers’ cost of employee benefits when contract is negotiated. 2 Adjustments are the net result of increases, decreases, and no changes in compensation or wages. 29. 3 Because of rounding, total may not equal sum of parts. 4 Less than 0.05 percent. p = preliminary. Work stoppages involving 1,000 workers or more Annua totals 1988 Measure 1987 Number of stoppages: Beginning in period................... In effect during period.............. Workers involved: Beginning in period (in thousands).............................. In effect during period (in thousands).............................. Days idle: Number (in thousands).............. Percent of estimated working time1 ...................................... 1988 Feb. Mar. Apr. May July 1989 Aug. Sept. Oct. Nov. Dec. Jan.p Feb.p 46 51 40 43 5 8 3 11 0 7 5 11 7 15 174.4 118.0 17.5 17.9 .0 14.5 13.6 21.0 11.7 4.0 8.6 2.3 .0 7.4 0 377.7 121.4 21.1 39.0 23.9 31.4 34.8 47.4 46.9 34.0 25.9 10.6 2.5 9.9 7.7 4,455.6 4,381.0 236.6 505.0 331.7 344.5 490.5 725.9 713.1 510.0 293.2 77.9 52.5 .02 .02 .01 .02 .02 .02 .02 .03 .03 .02 .01 (2) (2) 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’ measure of strike idleness," M o n th ly L a b o r R e v ie w , October 1968, 78FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis June 4 14 7 18 pp. 54-56. 2 (_ess than 0.005 percent, p = preliminary, 2 14 1 5 3 9 0 1 3 4 0 2 152.7 137.8 .01 ______J .01 30. Consumer Price Indexes for Ail 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 1989 1988 Annual average 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. 1987 113.6 340.4 118.3 354.3 116.0 347.4 116.5 349.0 117.1 350.8 117.5 352.0 118.0 353.5 118.5 354.9 119.0 356.6 119.8 358.9 120.2 360.1 120.3 360.5 120.5 360.9 121.1 362.7 121.6 364.1 Food and beverages................... Food........................................ Food at home........................ Cereals and bakery products . Meats, poultry, fish, and eggs Dairy products..................... Fruits and vegetables........... Other foods at home............ Sugar and sweets.............. Fats and oils..................... Nonalcoholic beverages..... Other prepared foods........ Food away from home ........... Alcoholic beverages.... ............. 113.5 113.5 111.9 114.8 110.5 105.9 119.1 110.5 118.2 118.2 116.6 122.1 114.3 108.4 128.1 113.1 114.0 113.1 107.5 118.0 115.8 115.7 113.9 118.7 116.0 115.9 113.9 118.9 117.1 117.0 115.1 120.3 110.6 111.2 107.3 124.7 107.2 123.0 116.7 116.6 114.6 119.8 111.5 107.1 126.0 117.6 118.8 117.6 118.8 115.8 117.3 120.8 122.1 114.6 116.5 107.2 107.6 126.1 129.0 112.4 113.1 113.3 114.0 111.5 112.6 107.1 107.2 117.1 118.3 121.5 122.1 118.7 119.2 119.4 120.1 119.4 120.2 118.1 119.0 124.0 124.7 117.3 117.4 108.2 108.9 129.9 133.2 113.6 114.0 114.8 115.6 114.9 115.9 107.0 107.4 118.7 119.1 122.5 123.0 119.3 119.6 120.3 120.3 119.0 125.6 116.8 109.9 131.7 114.8 116.0 117.1 108.1 119.9 123.4 119.8 120.2 120.6 120.2 120.7 118.7 119.1 125.9 126.6 116.4 116.1 110.6 111.4 129.5 131.0 114.9 115.3 115.9 116.7 117.1 118.5 108.2 107.8 120.1 120.7 123.7 124.1 119.9 119.9 122.0 122.2 121.2 127.9 118.5 112.6 134.8 116.6 117.2 119.6 109.6 121.9 124.7 120.3 122.7 122.9 122.0 128.9 118.2 113.4 137.1 117.8 117.8 120.5 111.3 123.0 125.2 121.1 Housing................................................. Shelter................................................. Renters’ costs (12/82=100).............. Rent, residential............................... Other renters’ costs......................... Homeowners’ costs (12/82=100)....... Owners’ equivalent rent (12/82 = 100) Household insurance (12/82 = 100) .... Maintenance and repairs.................... Maintenance and repair services ...... Maintenance and repair commodities . Fuel and other utilities........................... Fuels ................................................. Fuel oil, coal, and bottled gas.......... Gas (piped) and electricity............... Other utilities and public services........ Household furnishings and operations... Housefurnishings................................ Housekeeping supplies....................... Housekeeping services....................... 114.2 121.3 128.1 123.1 127.4 124.8 124.8 124.0 119.1 127.4 134.7 127.8 139.2 131.0 131.1 129.7 114.5 117.9 110.1 106.0 100.8 76.9 108.1 122.4 109.8 105.5 115.2 115.0 119.5 119.9 128.2 128.4 135.6 134.7 128.4 129.1 141.3 135.5 131.8 132.6 131.9 132.7 130.1 130.2 115.0 115.3 118.1 118.1 110.8 111.7 106.1 106.4 100.9 101.0 75.9 76.3 108.3 108.5 122.6 123.3 109.7 110.1 105.3 105.7 114.8 115.5 115.1 115.5 119.9 128.8 134.8 129.4 134.8 133.1 133.1 130.4 115.0 117.6 111.6 105.4 98.6 74.6 105.8 124.5 110.3 105.9 115.6 115.5 119.9 129.1 134.2 129.8 131.1 133.8 133.9 130.2 115.4 118.2 111.7 104.3 96.8 75.0 103.7 124.4 110.6 106.1 116.5 115.7 120.2 129.3 134.1 130.1 130.0 134.0 134.1 130.6 115.8 118.4 112.4 105.0 97.4 76.8 104.1 125.5 110.6 105.9 117.0 115.9 120.7 129.8 135.2 130.5 132.7 134.4 134.5 130.9 116.1 118.7 112.8 106.0 98.7 80.5 105.1 125.9 110.9 106.0 117.5 116.6 121.1 130.3 136.3 130.9 136.2 134.7 134.8 131.2 117.1 119.9 113.4 105.9 98.6 81.4 104.9 126.0 110.9 105.9 117.7 116.8 Apparel and upkeep................. Apparel commodities............. Men's and boys’ apparel...... Women’s and girls’ apparel .. Infants’ and toddlers' apparel Footwear............................ Other apparel commodities ... Apparel services.................... 110.6 112.7 110.8 111.9 109.8 116.2 108.2 116.5 123.4 112.6 110.7 111.6 109.9 118.2 107.4 116.2 124.0 117.8 116.2 115.2 118.1 119.0 112.2 117.4 124.4 120.7 119.3 117.6 121.9 118.1 115.9 119.4 125.5 119.9 118.4 118.2 120.2 117.2 114.5 119.5 126.3 118.0 116.3 117.3 116.5 117.3 113.5 119.1 126.7 115.3 113.3 115.1 111.6 115.6 112.2 119.2 127.3 115.3 113.3 114.2 111.4 118.8 112.7 120.4 127.8 CONSUMER PRICE INDEX FOR ALL URBAN CONSUMERS: All items.................. All items (1967=100) 111.0 111.8 112.0 112.2 112.6 112.1 112.3 110.3 107.8 116.6 120.7 118.0 112.1 107.4 127.1 112.3 112.5 111.2 109.5 107.7 116.1 119.7 116.8 110.3 107.7 116.3 118.5 116.6 127.1 125.0 133.6 131.3 127.8 126.3 134.8 130.4 131.1 129.0 131.1 129.0 129.0 127.1 111.8 114.7 114.3 114.8 117.9 117.9 107.8 110.4 109.5 103.0 104.4 102.8 96.0 98.0 97.3 80.9 78.1 77.9 103.8 104.6 101.9 122.9 121.8 120.1 107.1 109.4 107.7 103.6 105.1 103.7 111.5 114.7 113.2 110.6 114.3 111.6 117.0 125.6 132.9 126.4 136.6 129.2 129.2 127.8 113.3 116.4 109.2 102.7 95.8 80.5 101.7 121.7 108.3 104.7 112.9 111.7 117.3 125.8 132.9 126.6 136.0 129.4 129.5 128.2 115.3 119.4 109.7 122.3 109.1 104.9 113.8 114.7 118.6 126.6 133.7 127.3 137.0 130.4 130.4 128.9 114.7 118.1 110.1 105.9 100.8 79.1 102.6 107.8 122.3 122.6 109.3 109.6 104.9 105.3 114.1 114.7 114.8 114.8 105.1 108.0 119.6 115.4 113.7 113.4 114.9 116.4 109.9 116.0 123.7 110.2 108.3 109.1 107.8 111.4 105.8 113.1 122.0 114.3 112.7 111.6 115.3 114.0 107.3 113.6 122.2 117.0 115.5 112.9 119.6 117.1 109.4 114.6 116.3 114.8 113.6 117.3 117.7 109.7 114.9 122.8 114.6 112.9 112.5 114.1 116.5 109.2 114.6 123.1 Transportation............................................. Private transportation................................. New vehicles........................................... New cars.............................................. Used cars............................................... Motor fuel............................................... Gasoline.............................................. Maintenance and repair........................... Other private transportation..................... Other private transportation commodities Other private transportation services..... Public transportation................................. 105.4 104.2 114.4 114.6 113.1 80.2 80.1 114.8 120.8 96.9 125.6 121.1 108.7 107.6 116.5 116.9 118.0 80.9 80.8 119.7 127.9 98.9 133.9 123,3 106.8 105.7 116.0 116,2 116.0 78,3 78.1 117,7 125,0 98,1 130,8 120,8 106.5 105.4 115.7 116.0 116.1 77.5 77.3 118.5 124.9 98.3 130.3 121.4 107.2 108.1 106.0 107.0 115.6 115.9 115.9 116.3 116.6 117.0 81.4 79.4 81.3 79.2 118.8 119.3 125.0 126.3 98.9 98.2 130.5 132.0 122.4 122.4 108.5 107.4 116.1 116.5 117.6 81.4 81.3 119.7 127.2 98.8 133.1 123.2 108.9 107.8 116.1 116.5 117.9 82.3 82.3 120.0 127.5 98.2 133.7 123.7 109.6 108.6 115.9 116.3 119.2 84.1 84.2 120.3 128.7 99.2 134,8 123.7 109.7 108.6 116.2 116.8 119.4 83.1 83.1 120.9 129.3 99.7 135.5 124.0 110.0 109.0 117.2 117.7 119.9 81.6 81.6 121.1 131.0 99.3 137.7 124.2 110.7 109.6 118.4 118.7 119.7 81.5 81.4 121.5 132.1 99.4 139,1 125.3 110.8 109.6 119.0 119.1 120.2 80.3 80.3 121.5 132.5 100,3 139.3 126.5 111.1 109.8 119.4 119.5 120.5 79.6 79.4 122.4 133.5 101.0 140.4 127,5 111.6 110.3 119.5 119.6 120.5 80.3 80.1 123.3 134.3 101,2 141.4 128.1 Medical care........................... Medical care commodities..... Medical care services............ Professional services.......... Hospital and related services 130,1 131.0 130.0 138.6 139.9 126.8 131.0 137.5 143.9 135.5 136,1 136.3 134.6 139.0 136.3 137,0 136.1 135.4 140.0 136.9 138.1 138.6 136.0 140.7 137.5 139.0 137.2 136.4 141.8 138.2 139.4 137.9 137.5 142.1 139.3 140.5 139.0 138,4 144.3 139.9 141,1 139.6 138.7 145.9 140.4 142.0 140.1 139.2 148.9 141.2 143.2 140.8 139.8 148.5 141.8 143.3 141.5 140.4 149.7 142.3 144.2 141.9 140.8 150.8 143.8 145.0 143.5 142.2 152.9 145.2 145,8 145.1 143.5 155.1 Entertainment..................... Entertainment commodities Entertainment services..... 115.3 110.5 122.0 120.3 115.0 127.7 118.3 112.9 126.7 119.0 113.4 126.5 119.6 114.2 127.0 119.7 114.5 126.9 120.1 114.8 127.3 120.5 115.3 127.7 120.7 115.4 128.1 121.3 116.0 128.6 121.8 116.3 129.4 122.2 117.2 129.3 122.8 117.5 130.0 123.8 118.1 131.6 124.3 118.4 132.3 Other goods and services............................ Tobacco products...................................... Personal care............................................ Toilet goods and personal care appliances Personal care services............................ Personal and educational expenses............ School books and supplies...................... Personal and educational services........... 128.5 133.6 115.1 113.9 116.2 138.5 138.1 138.7 137.0 145.8 119.4 118.1 120.7 147.9 148.1 148.0 134.2 142.2 117.8 116.4 119.1 144.7 146.3 144.8 134.6 142.8 118.1 116.8 119.2 145.0 146.2 145.1 134.8 142.9 118.5 117.4 119.5 145.2 146.3 145.3 135.1 143.2 118.7 117.2 135,5 143.5 119.C 117.5 120.4 146.C 146.5 146.2 136.5 147.5 119.2 117.5 120.5 146.C 146.5 146.5 137,5 148.6 119.0 117.2 121.0 147.8 146.9 148.1 140.0 148.9 120.3 118.7 121.9 151.6 151.1 152.1 140.6 149.3 121.C 119.6 122.C 152.^ 152.C 152.' 141.0 149.7 121.8 120.7 122.7 152.7 152.1 152.6 141,3 149.S 122.4 121.6 123.1 153.C 152.2 153.2 143.4 157.C 122.8 121.7 123.6 154.C 153.C 154.2 144.1 158.5 123.2 121.9 124.4 154.4 155.0 154.6 108.1 107.5 113.8 117.0 114.1 108.9 109.1 110.4 112.1 121.8 118.6 138.3 120.2 117.4 102.8 95.7 80.2 101.6 122.6 107.5 117.0 121.0 118.2 117.7 126.2 133.1 126.9 135.7 129.9 130.0 128.2 114.3 117.8 109.8 103.5 96.5 80.0 120.1 145.5 146.4 145.6 - See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 79 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Price Data 30. 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 1988 1989 1987 1988 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. All items....................................... Commodities.................................. Food and beverages ................................ Commodities less food and beverages............ Nondurables less food and beverages ................ Apparel commodities.......................................... Nondurables less food, beverages, and apparel ........ Durables...................................... 113.6 107.' 113.5 104.C 101.' 108.5 99.5 108.2 118.3 111.5 118.2 107.3 105.2 113.7 103.2 110.4 116.C 109.1 115.8 105.0 101.9 108.3 101.0 109.4 116.5 109.8 116.0 105.9 103.4 112.7 101.0 109.5 117.1 110.7 116.7 106.9 105.0 115.5 102.0 109.7 117.5 111.1 117.1 107.2 105.4 114.8 103.0 109.9 118.0 111.1 117.6 107.1 104.9 112.9 103.2 110.2 118.5 111.5 118.8 107.0 104.7 110.8 104.0 110.3 119.C 111.9 119.4 107.3 105.2 110.7 104.8 110.3 119.8 113.C 120.1 108.5 107.1 116.2 104.9 110.6 120.2 113.5 120.3 109.2 107.8 119.3 104.5 111.1 120.3 113.5 120.2 109.4 107.7 118.4 104.6 111.8 120.5 113.5 120.6 109.0 106.9 116.3 104.5 112.2 121.1 113.9 122 0 108 9 106.4 113 3 105.3 112.5 121.6 114 3 122 7 109 1 106 9 113 3 106.1 112.4 Services..................................... Rent of shelter (12/82 = 100)...................... Household services less rent of’ shelter (12/82=100)... Transportation services........................................ Medical care services..................................... Other services .............................. 120.2 125.9 113.1 121.9 130.0 125.7 125.7 132.0 115.3 128.0 138.3 132.6 123.4 129.8 113.1 125.2 135.3 130.2 123.8 130.4 113.0 125.4 136.1 130.7 124.1 130.6 113.7 125.8 136.6 131.0 124.6 131.0 114.3 126.7 137.2 131.1 125.5 131.5 116.6 127.6 137.9 131.6 126.1 132.3 116.9 128.1 139.0 131.9 126.7 133.1 117.0 128.8 139.6 132.8 127.3 133.4 117.4 129.3 140.1 134.9 127.6 133.8 116.6 130.6 140.8 135.5 127.8 134.1 115.6 131.6 141.5 135.7 128.1 134.3 116.2 132.1 141.9 136.2 128.9 134 8 117.0 133.0 143.5 137.3 129 4 135 4 116 9 133.9 145.1 137.8 Special indexes: All items less food......................... All items less shelter ........................... All items less homeowners' costs (12/82=100)........ All items less medical care.................................................... Commodities less food.......................................................... Nondurables less food .......................................................... Nondurables less food and apparel ....................................... Nondurables........................................ Services less rent of’ shelter (12/82 = 100)...... Services less medical care.................................................... Energy........................................... All items less energy ..................... All items less food and energy .............................................. Commodities less food and energy........................................ Energy commodities ................................. Services less energy...................... 113.6 118.3 116.0 116.6 117.2 117.6 118.1 118.4 111.6 115.9 113.5 114.0 114.7 115.2 115.7 116.1 115.1 119.5 117.1 117.7 118.4 118.8 119.3 119.8 112.6 117.0 114.8 115.3 115.9 116.3 116.8 117.2 104.3 107.7 105.4 106.3 107.3 107.6 107.4 107.4 101.8 105.8 102.7 104.1 105.6 106.0 105.5 105.4 100.3 104.0 101.9 101.9 102.9 103.8 104.0 104.8 107.5 111.8 109.0 109.8 111.0 111.4 111.4 111.9 123.1 128.3 125.8 126.0 126.5 127.1 128.4 128.9 119.1 124.3 122.1 122.4 122.8 123.2 124.1 124.7 88.6 89.3 87.0 86.5 87.3 88.7 91.0 91.4 117.2 122.3 120.0 120.6 121.2 121.5 121.8 122.3 118.2 123.4 121.1 121.9 122.4 122.7 123.0 123.3 111.8 115.8 113.3 114.6 115.5 115.5 115.4 115.2 80.2 80.8 78.8 78.0 79.7 81.4 81.4 81.9 122.0 127.9 125.7 126.1 126.5 126.9 127.4 128.0 118.9 119.7 120.2 120.3 120.4 120.8 116.5 117.5 117.9 118.0 118.1 118 7 120.3 121.1 121.5 121.5 121.6 122.3 117.8 118.6 118.9 119.0 119.1 119.7 107.7 108.9 109.5 109.7 109.4 109.2 105.9 107.7 108.3 108.2 107.5 107.1 105.5 105.6 105.2 105.4 105.3 106.0 112.4 113.7 114.2 114.1 1139 114 3 129.4 130.3 130.5 130.6 131.1 132.1 125.3 125.9 126.2 126.3 126.6 127.3 92.3 91.9 89.9 88.9 88.7 89.0 122.8 123.8 124.4 124.7 124.8 125.5 123.8 124.7 125.5 125.8 126.0 126.4 115.2 116.9 118.0 118.2 118.0 117.9 83.4 82.5 81.0 80.9 80.1 79.9 128.8 129.3 129.9 130.3 130.6 131.4 121.3 119.2 122.9 120 1 109 5 107 6 106.8 114 9 132 7 127.8 89.3 126.0 126.9 118 1 80.6 132.0 Purchasing power of the consumer dollar: 1982-84 = $1.00.................... 1967 = $1.00.................................... 88.0 29.4 84.6 28.2 86.2 28.8 85.8 28.7 85.4 28.5 85.1 28.4 84.7 28.3 84.4 28.2 84.0 28.0 83.5 27.9 83.2 27.8 83.1 27.7 83.0 27.7 82.6 27.6 82.3 27.5 112.5 335.0 117.0 348.4 114.7 341.6 115.1 343.0 115.7 344.7 116.2 346.1 116.7 347.6 117.2 349.1 117.7 350.7 118.5 353.0 118.9 354.2 119.0 354.6 119.2 355.0 119.7 356.7 120.2 358.0 113.3 113.3 111.7 114.8 110.4 105.7 118.8 110.4 110.9 107.9 107.5 113.6 116.9 113.9 117.9 117.9 116.2 122.2 114.1 108.1 127.6 113.0 113.9 113.0 107.7 117.8 121.6 118.3 115.5 115.4 113.5 118.8 110.5 107.0 124.0 111.7 112.1 109.5 107.9 115.8 119.6 116.6 115.7 116.3 116.8 115.6 116.2 116.7 113.5 114.2 114.7 118.9 119.9 120.4 111.1 111.4 112.0 106.9 106.9 107.2 122.2 125.2 126.4 111.9 112.0 112.2 112.4 112.2 112.4 110.3 110.2 111.0 108.0 107.9 107.7 116.0 116.4 116.8 120.0 120.6 120.9 117.3 117.9 118.0 117.4 117.3 115.5 120.8 114.5 107.0 125.5 112.3 113.1 111.4 107.3 116.9 121.4 118.4 118.5 118.5 116.9 122.1 116.3 107.3 128.4 113.0 113.9 112.5 107.4 118.1 122.0 118.9 119.1 119.8 120.0 119.2 119.9 120.1 117.8 118.7 118.7 124.1 124.8 125.7 117.1 117.3 116.6 107.9 108.6 109.7 129.6 132.8 131.4 113.5 113.9 114.7 114.8 115.6 115.9 114.8 115.8 117.0 107.2 107.6 108.3 118.5 118.8 119.7 122.3 122.8 123.2 118.9 119.2 119.5 119.9 119.9 118.4 126.0 116.1 110.4 129.1 114.8 115.7 117.0 108.4 119.9 123.5 119.5 120.3 120.4 118.8 126.7 115.8 111.2 130.8 115.1 116.7 118.3 107.8 120.5 124.0 119.5 121.7 121.9 120.8 128.0 118.3 112.4 134.3 116.5 117.3 119.5 109.8 121.7 124.6 119.8 122.4 122.6 121.7 129.0 118.0 113.3 136.8 117.7 117.8 120 4 111.4 122.8 125.1 120.8 112.8 118.8 114.6 122.9 128.2 113.8 113.7 114.1 111.3 114.7 106.0 102.7 97.1 77.6 103.6 120.1 106.7 103.1 111.8 110.9 116.8 124.3 119.2 127.5 135.2 119.5 119.5 118.2 114.0 117.7 108.3 104.1 97.7 77.9 104.4 122.9 108.9 104.5 115.1 115.0 115.0 115.4 115.6 122.4 122.9 123.0 117.3 118.4 118.4 126.1 126.2 126.3 130.0 136.9 136.1 117.6 117.8 118.0 117.6 117.8 118.0 116.7 117.2 117.3 113.6 112.8 114.7 117.6 116.6 119.8 107.5 107.1 107.5 102.5 102.3 102.5 95.6 95.4 95.4 80.6 80.2 79.9 101.6 101.4 101.4 121.8 121.7 122.3 107.2 107.8 108.7 103.1 104.1 104.2 113.6 113.4 114.3 111.8 111.9 115.6 116.0 123.4 118.6 126.6 136.2 118.4 118.5 117.3 113.7 117.6 107.9 103.0 96.1 79.7 102.2 122.5 108.8 104.2 114.5 115.7 116.9 123.9 119.3 126.9 138.8 118.8 118.8 118.0 113.9 117.9 107.9 105.5 100.5 78.9 107.5 122.2 109.1 104.6 115.1 115.7 117.4 117.8 118.2 118.2 124.5 125.3 125.6 126.0 120.0 120.7 120.2 120.4 127.5 128.0 128.7 129.0 140.8 143.0 136.1 135.1 119.4 120.2 120.9 121.3 119.5 120.2 120.9 121.4 118.6 119.0 119.1 119.3 113.8 114.2 114.4 114.1 117.6 118.0 117.7 117.0 108.0 108.3 109.1 109.2 105.6 105.8 106.1 105.1 100.5 100.6 100.8 98.3 76.7 76.2 75.9 74.6 107.8 108.0 108.2 105.5 122.4 122.5 123.3 124.7 109.4 109.1 109.6 109.9 104.9 104.5 105.1 105.4 115.5 115.1 115.8 116.1 115.9 116.0 116.3 116.3 118.3 126.4 120.1 129.4 131.4 122.0 122.1 119.2 114.6 117.6 109.7 104.1 96.6 75.0 103.5 124.6 110.2 105.6 116.9 116.4 118.5 126.5 120.0 129.7 129.2 122.2 122.2 119.6 115.2 117.8 110.6 104.8 97.2 76.7 103.9 125.6 110.2 105.4 117.4 116.5 119.0 126.9 120.7 130.1 131.8 122.5 122.5 119.9 115.6 118.3 110.9 105.7 98 4 80.3 104.8 126.2 110.4 105.5 117.9 116.9 119.3 127.4 121.5 130.4 135.2 122 8 122 8 120 0 116.7 119 5 111.8 105.7 98 3 81.0 104.6 126 3 110.4 105.4 118.1 117.0 110.4 114.9 110.0 115.7 114.1 112.4 119.5 117.6 114.8 114.7 CONSUMER PRICE INDEX FOR URBAN WAGE EARNERS AND CLERICAL WORKERS: All items .............................. Ml items (1967=100) .................. Food and beverages .......................... Food at home ......................... Cereals and bakery products............................................. Meats, poultry, fish, and eggs............................................ Dairy products............................. Fruits and vegetables........................................................ Other foods at home........................................................ Sugar and sweets.......................................................... Fats and oils............................. Nonalcoholic beverages.................................................. Other prepared foods..................................................... Food away from home ........................................................ Alcoholic beverages..................... Housing .......................... Shelter.................................... Renters’ costs (12/84=100)........ Rent, residential.............................. Other renters’ costs ................ Homeowners’ costs (12/84 = 100)....................................... Owners’ equivalent rent (12/84=100)............................... Household insurance (12/84 = 100)................................... Maintenance and repairs................ Maintenance and repair services ...................................... Maintenance and repair commodities................................ Fuel and other utilities.......................... Fuel oil, coal, and bottled gas ........................................... Gas (piped) and electricity..................... Other utilities and public services........................................ Household furnishings and operations.................................... Housefurnishings........................... Housekeeping supplies........................................................ Housekeeping services....................... Apparel and upkeep................................. See footnotes at end of table. 80FRASER Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 113.9 116.3 112.2 117.2 120.1 30. 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 Jan. Feb. 116.0 116.5 116.2 120.3 114.0 117.8 125.8 113.0 114.4 111.3 118.5 112.8 112.8 113.1 119.0 126.8 109.4 109.4 109.8 110.3 110.4 108.6 108.6 109.0 109.5 109.5 115.5 115.8 116.9 118.1 118.8 116.0 116.4 117.5 118.5 118.9 119.0 119.2 119.8 119.5 120.1 80.4 81.5 81.6 83.1 84.3 80.4 81.5 81.6 83.2 84.3 121.5 121.5 121.3 120.5 121.0 126.5 127.2 128.9 130.0 130.4 99.9 99.0 98.8 99.3 98.8 132.5 133.2 135.5 136.8 137.1 125.4 124.3 123.0 123.1 123.5 110.7 109.7 119.2 119.3 120.3 79.6 79.5 122.4 131.4 100.5 138.2 126.1 111.2 142.2 142.2 142.2 140.6 148.9 142.8 143.1 142.7 141.0 150.0 144.2 143.9 144.2 142.4 151.9 145.6 144.7 145.8 143.7 154.2 121.7 117.3 129.0 122.2 117.6 129.7 123.1 118.1 131.3 123.6 118.4 131.9 139.9 149.5 120.9 119.9 140.3 149.9 121.7 122.0 122.7 152.0 150.9 152.3 140.6 150.2 122.3 121.5 123.0 152.3 151.1 152.7 143.0 156.9 122.7 121.7 123.6 153.3 152.0 153.7 143.7 158.2 123.0 121.9 124.2 153.7 153.9 154.0 119.0 113.1 119.9 108.9 107.1 118.1 104.3 110.4 119.2 113.0 120.3 108.6 106.3 116.0 104.1 110.7 119.7 113.5 121.7 108.4 105.9 113.0 104.9 120.2 113.9 122.4 108.7 106.3 111.0 111.0 126.9 121.4 106.2 130.9 142.2 134.5 127.2 121.5 106.8 131.2 142.7 135.0 127.9 121.9 107.5 132.2 144.2 136.1 128.4 122.4 107.4 133.1 145.8 136.5 118.8 117.3 112.2 112.3 117.7 117.8 109.0 109.2 107.8 107.6 104.9 105.1 113.8 113.7 117.6 117.6 125.2 125.3 88.4 89.3 123.1 123.4 124.0 124.3 116.9 117.1 81.2 81.2 129.1 129.5 118.8 117.4 112.4 117.9 108.9 106.9 104.9 113.5 118.1 125.6 119.6 118.5 113.4 118.9 109.0 107.0 106.4 114.6 119.5 126.7 123.6 124.4 117.0 80.3 129.8 119.2 118.0 113.0 118.5 108.8 106.5 105.6 114.0 119.0 126.3 88.3 124.2 124.8 116.9 79.9 130.5 84.0 28.2 83.9 28.2 83.5 28.0 83.2 27.9 July Aug. 110.6 110.5 111.5 109.5 118.6 108.7 115.2 122.7 111.0 Sept. Oct. Mar. Apr May 112.4 114.9 111.1 112.2 113.3 106.4 114.9 116.0 107.7 121.5 112.8 121.6 118.8 119.1 109.6 113.9 114.3 113.0 116.7 119.7 109.9 114.0 122.0 122.2 108.3 107.5 116.2 116.6 117.9 80.9 80.8 119.8 125.8 98.6 131.7 122.5 106.4 105.6 115.7 116.0 116.0 78.3 78.1 117.8 123.2 98.0 128.5 120.4 106.2 106.8 107.8 105.3 105.9 107.0 115.3 115.3 115.6 115.7 115.7 116.0 116.1 116.6 116.9 81.4 79.4 7"’.5 81.3 79.2 77.3 118.6 118.9 119.4 123.1 123.0 124.3 98.6 97.9 98.1 128.2 128.3 129.7 120.8 121.7 121.8 130.2 130.2 130.3 129.0 131.1 139.0 139.0 139.0 137.7 143.3 135.8 135.4 135.8 134.7 138.4 136.5 136.1 136.6 135.5 139.3 137.1 137.2 137.1 136.1 140.1 137.8 138.0 137.7 136.6 141.2 138.5 138.3 138.5 137.7 141.5 139.6 139.4 139.6 138.5 143.8 140.3 140.0 140.3 138.9 145.4 140.8 141.0 140.8 139.3 146.3 141.7 142.1 141.6 139.9 147.8 114.8 110.6 121.8 119.7 115.1 127.2 117.6 112.9 125.2 118.2 113.5 126.0 118.9 114.2 126.5 119.0 114.6 126.3 119.4 114.9 126.8 119.8 115.4 127.2 120.1 120.6 121.2 115.5 127.6 116.0 128.1 116.5 128.9 127.8 133.7 115.0 113.9 116.1 138.2 137.9 . 138.4 136.5 146.0 119.3 118.0 120.5 147.4 147.1 147.7 133.6 142.3 117.5 116.2 118.9 144.3 145.3 144.5 134.0 143.0 117.7 116.5 119.0 144.6 145.2 144.8 134.2 134.5 143.1 143.4 118.1 118.5 117.0 117.1 119.3 119.9 144.7 145.2 145.4 145.4 144.9 145.4 135.0 143.8 118.8 117.4 136.3 147.9 119.1 117.8 120.4 146.0 145.6 146.3 137.2 148.9 119.0 117.4 120.7 147.4 146.0 147.8 139.3 149.2 120.3 118.8 121.9 151.1 150.0 151.5 . . . . . . 112.5 107.3 113.3 103.6 100.8 108.8 99.2 . 106.6 117.0 111.0 117.9 106.8 104.6 113.4 102.9 108.9 114.7 108.7 115.5 104.5 101.4 108.3 100.5 107.9 115.1 109.3 115.7 105.3 102.7 112.4 100.4 108.0 115.7 116.7 110.7 117.4 106.5 104.3 117.2 117.7 112.6 110.6 101.6 102.6 102.8 108.1 108.4 108.7 103.7 108.8 119.1 107.0 104.9 110.5 104.7 108.8 118.5 112.5 119.8 108.1 106.6 115.8 104.7 109.1 118.9 113.0 116.3 106.3 104.3 114.9 116.2 110.5 116.8 106.7 104.8 114.3 Services..................................................................... Rent of shelter (12/84=100).................................... Household services less rent of shelter (12/84=100) Transportation services............................................ Medical care services.............................................. Other services ........................................................ . 119.4 . 114.0 . 104.0 . 120.8 .. 130.3 .. 124.7 124.7 119.4 105.9 127.1 139.0 131.4 122.5 117.5 103.9 124.4 135.8 129.0 122.8 123.1 118.2 104.4 124.8 137.1 129.8 123.6 118.5 104.9 125.8 137.7 130.0 124.5 119.0 107.2 126.6 138.5 130.5 125.1 119.6 107.4 127.1 139.6 130.8 125.7 120.3 107.6 127.8 140.3 131.6 126.3 120.7 108.0 128.4 140.8 133.6 126.7 Special indexes: All items less food ........................................... All items less shelter ....................................... All items less homeowners’ costs (12/84=100). All items less medical care............................... Commodities less food..................................... Nondurables less food .................................... Nondurables less food and apparel .................. Nondurables................................................... Services less rent of shelter (12/84=100)....... Services less medical care.............................. Energy............................................................ All items less energy ....................................... All items less food and energy ........................ Commodities less food and energy.................. Energy commodities ....................................... Services less energy........................................ .. 112.2 .. 111.0 .. 106.4 .. 111.5 .. 103.9 .. 101.4 .. 100.0 .. 107.2 .. 110.8 .. 118.2 88.C .. 116.C ... 116.8 ... 110.8 80.8 ... 121.2 116.7 115.2 110.4 115.8 107.2 105.3 103.7 111.5 115.6 123.3 88.6 121.0 121.9 114.7 80.9 127.0 114.4 115.' 116.0 114.4 109.7 115.0 107.0 105.4 103.4 117.3 115.9 111.0 111.1 111.6 114.4 116.1 123.6 90.7 120 120.8 120.2 121.1 114.3 79.7 125.6 114.4 81.5 126.0 121.7 114.2 82.1 127.1 122.2 113 77 125 115.7 123.1 90.3 120.5 121.4 114.3 81.4 126.5 114.3 83.8 127.8 118.1 116.8 111.9 117.3 108.4 107.2 105.3 113.4 117.3 124.9 91.3 122.4 123.1 115.8 82.7 128.4 118.6 117.2 115.6 106.9 105.0 103.6 116.8 115.4 110.7 116.0 107.0 105.1 104.5 85 119.: 115.5 113.9 109.2 114.6 106.6 104.9 102.5 110.5 113.9 121.7 86.7 119.9 116.5 115.0 108 113 104 113. 108. 114. 105 103, Purchasing power of the consumer dollar: 1982-84=$1.00................................... 1967=$1.00........................................ 89.( 29. 85.5 28.7 87.2 29.3 86.4 29.0 86.1 ...j 85.7 28.8 85.3 28.6 84.9 28.5 84.4 28.3 84.1 28.2 1987 1988 108.8 108.5 110.3 114.0 105.5 107.4 119.2 113.4 112.8 114.5 118.6 110.4 114.9 123.0 Transportation .............................................. Private transportation.................................. New vehicles............................................ New cars............................................... Used cars................................................ Motor fuel................................................ Gasoline................................................ Maintenance and repair............................ Other private transportation...................... Other private transportation commodities Other private transportation services...... Public transportation.................................. 105.1 104.1 114.0 114.3 113.1 80.3 80.2 115.1 119.0 96.7 123.4 120.4 Medical care ............................. Medical care commodities...... Medical care services............. Professional services........... Hospital and related services Entertainment..................... Entertainment commodities Entertainment services...... Apparel commodities.............. Men’s and boys’ apparel....... Women’s and girls’ apparel ... Infants’ and toddlers’ apparel Footwear............................. Other apparel commodities... Apparel services..................... Other goods and services............................. Tobacco products...................................... Personal care............................................. Toilet goods and personal care appliances . Personal care services............................. Personal and educational expenses............. School books and supplies....................... Personal and educational services............ All items................................................................... Commodities.......................................................... Food and beverages ............................................ Commodities less food and beverages.................. Nondurables less food and beverages ............... Apparel commodities....................................... Nondurables less food, beverages, and apparel Durables............................................................ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Feb. 112.0 112. 102 . 101 . 108. 113, 121 86 118 119 112 78 124.8 118.0 103.8 124.5 136.6 129 101 . 109. 113 121 , 110.1 122.2 88.1 28.9 112.6 112.1 113.5 118.8 109.6 113.5 122.4 108.2 108.6 107.3 107.7 115.8 115.8 116.2 116.2 117.5 117.8 82.3 81.4 82.3 81.3 119.8 120.1 125.4 125.2 97.9 98.5 130.8 131.3 122.3 123.0 120.2 145.8 145.6 146.0 110.2 111.1 118.5 106.6 104.3 121.0 109.5 120.4 108.0 114.9 123.3 111.6 111.1 116.6 107.3 105.6 105.3 112.3 116.6 124.3 91.8 121.5 115.8 114.4 117.6 121.5 112.7 116.2 123.7 118.9 116.9 121.5 118.1 117.5 119.9 120.6 120.1 116.3 117.9 124.7 115.0 118.2 125.4 151.7 150.8 152.0 120.0 108.7 107.2 118.9 104.1 109.7 121.1 107.2 129.9 141.6 134.2 120.6 88.1 117.8 126.4 113.4 110.7 121.8 110.3 119.3 119.5 120.4 80.3 80.2 123.3 132.2 100.7 139.2 126.8 112.8 105.6 88.6 124.7 125.3 117.1 80.6 131.1 _ 81 MONTHLY LABOR REVIEW 31. April 1989 • Current Labor Statistics: Price Data Consumer Price Index: U.S. city average and available local area data: all items (1982-84 = 100, unless otherwise indicated) Urban Wage Earners All Urban Consumers Area1 U.S. city average................. Pricing schedule2 1989 1988 1988 1989 Feb. Mar. Oct. Nov. Dec. Jan. Feb. Feb. Mar. Oct. Nov. Dec. Jan. Feb. M 116.0 116.5 120.2 120.3 120.5 121.1 121.6 114.7 115.1 118.9 119.0 119.2 119.7 120.2 M 119.2 119.6 124.1 124.4 124.5 125.4 125.8 118.1 118.4 122.9 123.2 123.3 124.1 124.5 M 119.9 120.4 124.9 125.1 125.3 126.1 126.5 118.0 118.5 122.9 123.1 123.2 124.0 124.3 Region and area size3 Northeast urban.................... Size A - More than 1,200,000 .......................... Size B - 500,000 to 1,200,000 .......................... Size C - 50,000 to 500,000 ............................. North Central urban .............. Size A - More than 1,200,000 .......................... Size B - 360,000 to 1,200,000 .......................... Size C - 50,000 to 360,000 ............................. Size D - Nonmetro politan (less than 50,0000 ..................... South urban.......................... Size A - More than 1,200,000 .......................... Size B - 450,000 to 1,200,000 .......................... Size C - 50,000 to 450,000 ............................. Size D - Nonmetro politan (less than 50,000)...................... West urban.......................... Size A - More than 1,250,000 .......................... Size B - 330,000 to 1,250,000 .......................... Size C - 50,000 to 330,000 ............................. Size classes: A (12/86)........................... B ...................................... C ...................................... D ...................................... M 117.0 117.5 122.5 122.9 122.2 123.1 123.9 116.0 116.4 121.2 121.6 121.0 121.9 122.7 M M 117.2 113.7 117.2 114.3 121.7 118.1 122.7 118.1 123.3 118.2 124.4 118.7 124.3 119.3 119.8 111.8 119.8 112.3 124.2 116.1 125.1 116.2 125.7 116.3 126.8 116.8 126.7 117.3 M 114.7 115.1 119.1 119.1 119.2 119.8 120.4 112.1 112.5 116.4 116.5 116.6 117.1 117.7 M 113.5 114.2 118.2 118.0 118.2 118.3 118.6 111.1 111.8 115.7 115.7 115.8 116.0 116.2 118.4 118.2 118.8 119.5 112.3 113.4 116.5 117.3 117.1 117.7 118.4 115.1 119.2 110.2 113.8 110.6 114.2 113.9 117.7 113.9 117.8 113.8 118.0 114.3 118.3 114.8 118.7 M 113.4 114.6 117.7 M M 110.5 114.4 111.1 114.8 114.2 118.2 114.1 118.3 114.0 118.5 114.5 118.9 M 115.2 115.5 118.9 118.9 119.2 119.7 120.1 114.4 114.7 118.1 118.0 118.4 118.8 119.3 M 115.1 115.8 119.5 119.6 119.7 119.9 120.3 113.0 113.6 117.5 117.7 117.8 117.9 118.2 M 113.4 114.0 117.1 117.4 117.6 117.8 118.0 113.8 114.3 117.7 117.9 118.1 118.4 118.6 M M 112.7 116.9 112.7 117.5 116.0 120.7 116.3 120.7 116.3 120.9 116.9 121.7 117.4 122.3 113.4 115.6 113.4 116.2 116.8 119.4 117.0 119.4 117.0 119.6 117.7 120.3 118.1 120.9 M 118.2 118.9 122.2 122.3 122.5 123.3 123.7 115.6 116.2 119.6 119.6 119.7 120.5 121.0 . 119.3 _ _ 115.7 116.0 _ _ 119.4 _ _ M 115.6 115.9 _ M 115.9 116.2 119.4 119.0 119.0 119.8 120.5 115.3 115.6 118.7 118.4 118.4 119.3 119.9 M 105.3 M 115.2 M 114.6 M 113.1 105.7 115.8 115.1 113.5 109.2 119.7 118.5 116.8 109.2 119.7 118.9 117.0 109.4 119.8 119.1 116.8 110.0 120.1 119.6 117.5 110.5 120.8 120.0 118.0 105.2 113.8 114.9 113.4 105.6 114.3 115.4 113.7 109.1 118.3 118.9 117.1 109.1 118.4 119.3 117.3 109.3 118.5 119.4 117.1 109.9 118.8 120.0 117.8 110.3 119.3 120.4 118.3 M 116.6 116.9 121.6 121.0 121.3 121.5 122.2 112.9 113.2 117.8 117.4 117.7 117.9 118.4 M 119.7 120.6 124.0 124.1 124.2 124.6 125.5 116.6 117.5 121.0 120.9 121.1 121.4 122.3 M 121.1 M 119.3 121.5 119.6 126.2 124.6 125.9 125.3 126.0 125.6 127.0 125.7 127.6 125.4 119.3 119.0 119.7 119.5 124.3 124.4 124.1 125.0 124.1 125.2 125.1 125.5 125.5 125.4 M 117.9 119.1 122.3 122.2 124.0 117.0 117,7 122.1 115.1 115.1 114,2 119.2 _ _ 117,5 120.1 112.7 117.9 Selected local areas Chicago, ILNorthwestern IN ................ Los Angeles-Long Beach, Anaheim, CA...................... New York, NYNortheastern N J ................ Philadelphia, PA-NJ............. San FranciscoOakland, C A ...................... Baltimore, M D...................... Boston, M A ......................... Cleveland, OH...................... Miami, FL ........................... St. Louis, MO-IL.................. Washington, DC-MD-VA , , , , 1 1 1 1 1 1 _ - Dallas—Ft. Worth, TX ........... Detroit, M l........................... Houston, TX ........................ Pittsburgh, PA...................... 2 2 2 2 114,0 113,7 108.0 113.3 _ " 122.6 124.0 - 121.2 127.4 118,0 118.3 118.3 123.2 - 121.3 129.0 118.9 120.0 118.4 124,3 117.9 118.6 111,1 116.3 _ " 117.2 118.3 111.3 116.7 _ 1 Area is the Consolidated Metropolitan Statistical Area (CMSA), ex clusive of farms and military, Area definitions are those established by the Office of Management and Budget in 1983, except for BostonLawrence-Salem, MA-NH Area (excludes Monroe County); and Milwau kee, Wl Area (Includes only the Milwaukee MSA). Definitions do not In clude revisions made since 1983. 8 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. Digitized for82 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis _ " 117.9 121.3 121.1 121.5 122.8 122.9 - 117.3 121.8 110.2 114,3 113.8 118,5 _ - 120.8 127.4 113.0 117.2 117.8 122.6 _ - 120.9 128.9 113.8 118.8 118.0 123.7 - 113.8 110.9 108.1 108.9 . " 117.7 115.6 111.4 111.7 . - 117,0 115.7 111.4 112,2 . ” 117,2 117.3 112.9 113.4 3 Regions are defined as the four Census regions, - Data not available. NOTE; Local area CPI indexes are byproducts of the national CPI program, Because each local Index Is a small subset of the national In dex, It has a smaller sample size and Is, therefore, subject to substan tially more sampling and other measurement error than the national In dex. As a result, local area Indexes show greater volatility than the na tional Index, although their long-term trends are quite similar. Therefore, the Bureau of Labor Statistics strongly urges users to consider adopting the national average CPI for use In escalator clauses. 32. Annual data: Consumer Price Index, U.S. city average, all items and major groups (1982-84 = 100) Series 1980 1981 1982 1983 1984 1985 1986 1987 1988 Consumer Price Index for All Urban Consumers: All items: 82.4 13.5 90.9 10.3 96.5 6.2 99.6 3.2 103.9 4.3 107.6 3.6 109.6 1.9 113.6 3.6 118.3 4.1 86.7 8.5 93.5 7.8 97.3 4.1 99.5 2.3 103.2 3.7 105.6 2.3 109.1 3.3 113.5 4.0 118.2 4.1 81.1 15.7 90.4 11.5 96.9 7.2 99.5 2.7 103.6 4.1 107.7 4.0 110.9 3.0 114.2 3.0 1185 3.8 90.9 7.1 95.3 4.8 97.8 2.6 100.2 2.5 102.1 1.9 105.0 2.8 105.9 .9 110.6 4.4 115.4 43 83.1 17.9 93.2 12.2 97.0 4.1 99.3 2.4 103.7 4.4 106.4 2.6 102.3 -3.9 105.4 30 108 7 31 74.9 11.0 82.9 10.7 92.5 11.6 100.6 8.8 106.8 6.2 113.5 6.3 122.0 7.5 130.1 6.6 138.6 65 83.6 9.0 90.1 7.8 96.0 6.5 100.1 4.3 103.8 3.7 107.9 3.9 111.6 3.4 115.3 33 120 3 43 75.2 9.1 82.6 9.8 91.1 10.3 101.1 11.0 107.9 6.7 114.5 6.1 121 4 6.0 128.5 5.8 137.0 6.6 82.9 13.4 91.4 10.3 96.9 6.0 99.8 3.0 103.3 3.5 106.9 3.5 108.6 1.6 112.5 3.6 117.0 4.0 Food and beverages: Housing: Apparel and upkeep: Transportation: Medical care: Entertainment: Other goods and services: Consumer Price Index for Urban Wage Earners and Clerical Workers: All items: https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis MONTHLY LABOR REVIEW 33. April 1989 • Current Labor Statistics: Price Data Producer Price Indexes, by stage of processing (1982 = 100) Annual average 1988 1989 Grouping Finished goods ......................................... Finished consumer goods ..................... Finished consumer foods.................... Finished consumer goods excluding foods ................................................ Nondurable goods less food .............. Durable goods .................................. Capital equipment.................................. Intermediate materials, supplies, and components............................................... Materials and components for manufacturing ...................................... Materials for food manufacturing.......... Materials for nondurable manufacturing . Materials for durable manufacturing...... Components for manufacturing............. Materials and components for construction.......................................... Processed fuels and lubricants............... Containers............................................. Supplies................................................. Crude materials for further processing ... Foodstuffs and feedstuffs ..................... Crude nonfood materials....................... 1987 1988 Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. 105.4 103.6 109.5 108.0 106.2 112.6 106.3 104.4 110.1 107.0 105.1 110.3 107.5 105.7 111.2 107.7 105.9 112.3 108.6 107.0 113.6 108.7 107.1 113.6 108.6 107.0 115.1 109.4 107.6 114.6 109.7 107.9 114.9 110.0 108.2 115.1 111.0 109.3 116.5 111.7 110.2 117.3 100.7 94.9 111.5 111.7 103.1 97.3 113.7 114.3 101.5 95.6 112.6 113.2 102.6 97.0 112.8 113.6 103.0 97.4 113.1 113.8 102.8 97.1 113.2 113.9 103.8 98.3 113.6 114.2 103.9 98.4 113.8 114.5 103.0 97.6 112.8 114.3 104.1 97.7 116.4 116.0 104.5 98.4 115.8 116.0 104.8 98.8 116.0 116.3 105.8 99.9 116.6 117.0 106.6 101.0 116.7 117.4 101.5 107.1 104.7 105.6 106.3 107.4 108.2 108.4 108.7 108.6 109.0 109.5 110.5 110.9 105.3 100.8 102.2 106.2 108.8 113.2 105.9 112.9 118.8 112.3 110.5 101.6 109.6 114.7 111.1 111.6 102.6 110.9 116.8 111.5 112.3 104.0 111.7 117.7 111.9 112.9 106.9 112.2 118.5 112.1 114.0 109.9 113.8 119.3 112.4 114.3 108.9 114.5 119.7 112.8 114.9 109.5 115.2 120.3 113.2 115.5 108.3 116.0 121.8 113.5 116.2 107.4 116.8 123.5 113.8 116.8 108.3 117.5 124.4 114.1 117.8 109.9 118.9 125.3 114.9 118.2 109.8 119.7 125.3 115.2 109.8 73.3 114.5 107.7 116.1 71.3 120.1 113.7 114.4 69.6 117.4 111.1 115.0 70.5 118.4 111.7 115.4 71.5 119.5 112.3 115.8 73.9 120.0 113.8 116.5 73.6 120.5 115.2 116.7 73.5 121.3 115.1 117.1 72.6 122.3 115.6 117.5 69.7 122.4 116.0 118.2 69.5 122.7 116.2 118.8 70.3 122.7 116.1 119.3 71.5 123.0 117.1 119.8 72.0 124.1 117.4 93.7 96.2 87.9 95.9 106.0 85.5 94.1 99.8 86.4 95.6 101.1 88.0 97.2 104.7 88.2 97.9 108.6 87.0 97.3 110.1 85.1 96.9 110.4 84.4 96.7 112.0 83.0 95.9 111.9 81.9 94.0 107.7 81.4 97.0 109.5 85.1 101.0 112.4 89.5 101.0 111.0 90.3 104.0 61.8 112.3 112.5 113.3 106.5 59.8 115.8 116.3 117.0 105.1 58.2 114.1 114.4 115.7 105.9 60.9 114.3 114.6 115.9 106.2 61.6 114.8 115.2 116.2 106.1 60.3 115.3 115.8 116.4 106.9 61.3 116.2 116.9 117.1 107.1 61.1 116.4 117.0 117.4 106.4 58.8 116.7 117.5 117.2 107.7 58.7 117.7 118.3 118.8 108.0 59.8 117.8 118.4 118.9 108.3 59.3 118.2 118.9 119.4 109.1 60.9 119.1 119.9 120.0 109.8 61.9 119.8 120.6 120.6 Special groupings Finished goods, excluding foods............... Finished energy goods ............................. Finished goods less energy...................... Finished consumer goods less energy....... Finished goods less food and energy ........ Finished consumer goods less food and energy.................................................... Consumer nondurable goods less food and energy.................................................... 114.2 118.5 117.1 117.3 117.6 117.9 118.8 119.1 118.9 120.5 120.5 121.2 121.8 122.6 116.3 122.0 120.4 120.6 120.9 121.3 122.7 123.0 123.3 123.6 124.0 125.0 125.8 126.9 Intermediate materials less foods and feeds...................................................... Intermediate foods and feeds.................... Intermediate energy goods ....................... Intermediate goods less energy................ Intermediate materials less foods and energy............................................. 101.7 99.2 73.0 107.3 107.0 109.5 71.0 114.6 104.8 102.0 69.3 112.1 105.7 103.4 70.2 113.0 106.4 104.8 71.2 113.6 107.2 111.8 73.5 114.4 107.8 116.6 73.3 115.5 108.1 114.5 73.1 115.7 108.3 115.5 72.3 116.3 108.3 114.7 69.4 116.8 108.8 113.3 69.2 117.4 109.3 112.8 70.0 117.8 110.2 115.2 71.2 118.7 110.8 113.8 71.6 119.1 107.8 115.2 112.9 113.8 114.4 114.9 115.7 116.1 116.7 117.3 118.0 118.6 119.4 119.9 Crude energy materials............................. Crude materials less energy .................. Crude nonfood materials less energy......... 75.0 100.9 115.7 67.8 112.5 132.7 68.7 108.1 133.4 70.6 109.0 133.1 71.4 111.1 131.3 70.0 114.0 131.2 67.3 115.5 132.9 66.1 116.0 133.9 64.7 117.1 133.4 63.3 117.0 133.4 62.6 114.1 134.0 66.7 115.6 134.9 71.2 118.5 137.7 72.0 117.7 138.5 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 34. Producer Price indexes, by durability of product (1982 = 100) Dec. 115.2 102.7 116.4 116.7 102.2 102.1 117.1 102.9 117.9 104.6 118.2 105.2 110.0 110.1 114.4 105.6 114.5 105.6 110.5 115.6 105.4 111.0 116.0 106.0 111.3 116.3 106.3 112.3 117.0 107.6 112.8 117.3 108.3 97.2 150.6 94.7 97.5 149.5 95.0 96.5 150.1 93.9 94.7 151.8 92.1 96.9 153.8 94.2 99.8 158.4 97.0 100.1 Apr. May June July Aug. 113.3 98.8 113.8 99.8 114.1 114.4 114.8 115.1 100.8 101.8 102.6 102.6 108.6 113.5 103.7 109.0 113.7 104.3 109.8 114.1 105.4 95.6 143.1 93.3 97.5 144.2 95.3 97.8 149.3 95.3 114.7 Total manufactures Durable.............. Nondurable ........ 104.4 109.6 99.2 109.1 114.0 104.1 107.1 101.7 107.9 113.2 102.7 Total raw or slightly processed goods Durable......................................... Nondurable ............ ....................... 94.2 122.6 95.9 147.4 93.5 93.8 146.2 91.4 94.9 146.1 92.5 35. Nov. Mar. 109.9 97.5 101.1 112.6 Feb. Oct. Jan. 1988 Total durable goods.... Total nondurable goods 92.9 1989 1988 Annual average Grouping Sept. 159.0 97.3 Annual data: Producer Price Indexes, by stage of processing (1982=100) Index Finished goods: Intermediate materials, supplies, and components: Materials and components for Materials and components for construction .... Crude materials for further processing: https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1979 1980 1981 1982 1983 1984 1985 1986 1987 77.6 77.5 77.5 88.0 88.6 85.8 96.1 96.6 94.6 100.0 100.0 100.0 101.6 101.3 102.8 103.7 103.3 105.2 104.7 103.8 107.5 103.2 101.4 109.7 105.4 103.6 111.7 78.4 90.3 98.6 100.0 100.6 103.1 102.7 99.1 101.5 80.9 84.2 61.6 79.4 80.2 91.7 91.3 85.0 89.1 89.9 98.7 97.9 100.6 96.7 96.9 100.0 100.0 100.0 100.0 100.0 101.2 102.8 95.4 100.4 101.8 104.1 105.6 95.7 105.9 104.1 103.3 107.3 92.8 109.0 104.4 102.2 108.1 72.7 110.3 105.6 105.3 109.8 73.3 114.5 107.7 85.9 100.0 69.6 57.3 95.3 104.6 84.6 69.4 103.0 103.9 101.8 84.8 100.0 100.0 100.0 100.0 101.3 101.8 100.7 105.1 103.5 104.7 102.2 105.1 95.8 94.8 96.9 102.7 87.7 93.2 81.6 92.2 93.7 96.2 87.9 84.1 85 MONTHLY LABOR REVIEW 36. April 1989 • Current Labor Statistics: Price Data U.S. export price indexes by Standard International Trade Classification (1985 = 100, unless otherwise indicated) Category 1974 SITO 1986 1987 1988 June Sept. June Sept. Dec. Mar. June Sept. Dec. 99.1 97.9 99.0 99.9 102.2 102.8 104.9 106.5 109.5 111.7 111.5 ALL COMMODITIES ....... Dec. Mar. F o o d ................ Meat and meat preparations........... Fish and crustaceans............. Grain and grain preparations............... Vegetables and fru it.................. Animal feeds, excluding unmilled cereals. . Miscellaneous food products ... 0 01 03 04 05 08 09 97.1 105.2 108.6 89.0 108.6 114.8 97.0 86.0 111.3 111.9 66.3 114.6 123.9 98.7 90.1 114.5 115.9 72.5 117.5 119.7 99.9 87.3 115.0 117.1 68.3 115.3 117.0 100.1 89.9 121.2 125.8 71.0 112.4 123.8 100.6 86.7 118.8 131.1 67.8 101.1 123.1 100.3 94.6 116.8 138.5 77.4 100.5 145.2 100.3 95.2 122.8 140.9 79.8 97.5 134.6 102.3 103.4 131.0 145.0 87.2 104.3 158.1 102.8 118.7 137.0 175.9 108.5 109.9 161.0 105.2 114.2 130 0 174.0 102 0 110 2 156 9 104.9 Beverages and tobacco (6/83 = 100) Tobacco and tobacco products . . . 1 12 97.4 97.1 97.3 97.0 102.6 102.6 102.6 102.6 105.0 105.0 105.5 105.5 107.0 107.0 109.6 109.8 110.6 110.7 112.0 112.1 111 7 111.8 Crude materials.................. Raw hides and s k in s ....... Oilseeds.................. Crude rubber................ Wood.......................... Pulp and waste paper . . . . Textile fibers................ Crude minerals...................... Metal ores and metal scrap . . . . 2 21 22 23 24 25 26 27 28 102.2 117.1 98.1 99.9 101.2 116.4 98.0 98.4 98.0 99.6 108.3 97.5 99.6 102.9 129.0 73.0 98.0 100.4 102.4 115.9 95.2 98.9 107.9 129.4 90.9 96.8 96.8 105.7 131.9 90.4 99.9 111.2 144.2 97.8 94.4 98.8 114.5 149.6 101.6 101.0 116.2 149.9 112.4 94.0 107.0 118.7 147.7 95.1 102.8 141.7 153.0 116.5 91.6 117.4 125.2 157.1 109.6 105.3 146.0 160.4 111.6 91.6 125.9 130.0 171.4 115.6 104.5 150.2 171.2 107.5 92.8 131.8 139.9 166.8 143.0 106.1 149.6 179.5 109.9 94.2 146.0 140.8 156.7 154.7 109.1 150.0 181.7 100.8 94.8 145.0 136.0 137.4 135.7 111.0 148.5 182.9 103.6 94.8 150.3 Fuels and related products......... Coal and coke................ Crude petroleum and petroleum products 3 32 33 76.8 94.0 77.4 93.5 77.8 92.0 81.3 92.6 - 82.8 88.2 - 84.6 91.0 - 82.5 89.8 100.0 79.3 90.6 90.8 82.1 92.0 97.2 79.5 92.9 89.2 79.3 93 4 88.1 Fats and o ils .................... Animal oils and fa ts ............... Fixed vegetable oils and fats......... 4 41 42 62.3 70.6 62.2 60.2 79.9 64.6 81.1 67.3 86.7 71.9 86.7 71.2 88.7 75.4 101.3 85.7 101.6 93.7 104.3 99.1 95.7 87.1 Chemicals and related products....... Organic chemicals.................... Dyeing, tanning, and coloring materials....... Medicinal and pharmaceutical products (12/85 = 100) . Essential oils, polish, and cleaning preparations....... Fertilizers, manufactured......... Artificial resins, plastics and cellulose. .. Chemical materials and products, n.e.s. 5 51 53 54 55 56 57 58 98.0 93.1 99.4 101.4 105.2 93.0 99.5 101.8 95.7 91.6 101.1 101.2 104.5 85.1 98.2 97.6 95.2 92.4 101.4 100.8 104.2 77.4 99.5 97.3 99.6 101.9 103.6 101.0 105.5 85.6 104.8 97.5 106.7 118.4 104.2 101.4 105.7 91.6 111.9 97.7 107.7 116.1 105.5 102.2 107.3 100.9 116.4 97.1 112.9 123.5 108.5 105.4 108.4 106.5 124.8 98.2 117.9 135.1 109.1 109.3 111.2 110.6 129.4 100.3 121.6 144.6 110.1 106.3 113.6 109.8 137.5 101.7 124.9 153.3 111.5 105.9 120.2 116.4 138.2 104.1 125.4 150.8 113.0 107.3 122.4 119.9 132.3 105.1 Intermediate manufactured products Leather and furskins........... Rubber manufactures......... Paper and paperboard products.................. Textiles ........................... Non-metallic mineral manufactures (9/85 = 100) Iron and stee l...................... Nonferrous metals .................. Metal manufactures, n.e.s............ 6 61 62 64 65 66 67 68 69 102.5 103.8 100.1 104.7 102.9 102.4 100.2 103.1 100.8 103.8 104.2 100.5 109.1 101.9 104.7 102.3 105.3 100.8 104.2 107.8 100.9 110.8 101.8 108.0 101.9 102.6 100.8 106.4 123.6 102.0 114.7 103.3 106.8 102.9 106.6 101.5 107.9 126.9 102.5 117.0 103.7 108.7 102.9 113.0 101.3 110.3 128.7 103.9 120.1 104.1 110.4 100.7 123.0 102.3 111.2 118.0 104.1 122.4 105.2 111.3 102.9 124.4 103.4 114.4 125.7 105.2 126.2 106.5 113.4 106.1 134.0 104.5 117.7 125.1 108.8 129.0 107.9 114.1 110.8 143.5 107.6 119.6 128.6 109.4 130.2 108.6 115.6 111.4 149.1 109.9 120.8 125.0 109.7 131.2 112.7 117.0 112.1 150.4 110.9 Machinery and transport equipment, excluding military and commercial a ircra ft.................... Power generating machinery and equipment . Machinery specialized for particular industries. Metalworking machinery............... General industrial machines and parts, n.e.s. Office machines and automatic data processing equipment Telecommunications, sound recording and reproducing equipment Electrical machinery and equipment............... Road vehicles and parts .................... Other transport equipment, excluding military and commercial aviation ................................... 7 71 72 73 74 75 76 77 78 100.8 102.4 100.3 102.0 101.6 99.0 98.9 99.2 101.7 101.0 102.5 100.4 103.0 102.5 98.8 99.7 99.7 101.9 101.6 103.7 100.6 104.2 103.3 98.2 101.3 100.3 103.3 101.7 104.6 100.0 105.8 104.2 96.0 101.9 101.7 103.1 101.8 103.7 100.1 106.7 104.5 96.1 101.4 102.1 103.5 102.1 104.8 100.5 107.8 104.6 95.7 101.4 102.5 103.8 102.4 105.2 100.9 108.2 105.4 95.5 101.9 101.8 104.6 103.2 107.0 102.1 109.3 106.7 95.8 102.8 103.1 104.5 104.0 108.4 103.6 110.8 108.1 95.7 104.6 103.4 104.9 104.5 108.5 104.7 111.0 109.3 96.8 104.1 103.2 105.4 105.5 109.3 106.0 114.5 110.4 96.3 105.1 103.6 107.1 79 103.1 102.8 103.5 104.5 105.5 105.8 106.6 107.4 109.6 109.7 111.8 8 82 103.5 103.4 103.8 104.6 105.2 105.4 105.6 _ 106.9 _ 108.1 108.9 110.5 Miscellaneous manufactured articles....... Furniture and parts.......................... Professional, scientific, and controlling instruments and apparatus .......................................... Photographic apparatus and supplies, optical goods, watches, and clocks ................................. Miscellaneous manufactured articles, n.e.s......... ~ - https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis - - _ _ 87 103.1 103.0 103.5 104.4 105.5 106.3 107.1 110.0 111.1 112.5 114.0 88 102.6 102.4 102.1 102.7 102.5 99.0 97.9 97.6 100.1 99.4 99.9 - - - - - - - - - 89 ' Data not available. - - 37. U.S. import price indexes by Standard International Trade Classification (1985=100, unless otherwise indicated) Category Dec. ALL COMMODITIES (9/82-100)......................................................... All commodities, excluding fuels......................................................... 1968 1987 1986 1974 SITC Mar. June Sept. Dec. Mar. June Sept. Dec. 115.3 126.1 117.1 129.1 102.3 110.9 106.5 113.7 110.0 116.5 110.9 117.5 112.5 120.8 113.8 123.7 116.8 126.7 Food and live animals Meat and meat preparations............................................................. Dairy products and eggs .................................................................. Fish and crustaceans....................................................................... Bakery goods, pasta products, grain, and grain preparations................................................................................... Fruits and vegetables....................................................................... Sugar, sugar preparations, and honey............................................... Coffee, tea, cocoa........................................................................... 0 01 02 03 109.1 109.2 113.8 119.1 105.2 105.0 119.3 121.8 108.3 108.0 122.3 126.0 109.1 114.4 121.7 130.4 112.5 113.4 125.1 131.0 114.1 111.5 125.6 132.5 114.0 107.0 125.0 129.3 112.7 111.2 122.2 125.9 113.9 108.7 125.8 126.6 04 05 06 07 118.8 104.3 106.5 104.9 122.3 101.9 107.4 89.9 126.2 110.1 109.6 87.0 124.8 110.0 109.0 85.1 130.7 116.2 107.0 90.6 135.8 115.4 109.6 94.3 139.8 120.3 110.0 93.3 136.9 123.7 112.1 87.4 142.8 126.4 110.7 90.1 Beverages and tobacco ..................................................................... Beverages....................................................................................... 1 11 106.8 109.5 107.8 112.1 112.8 114.2 112.2 114.8 113.5 116.2 116.0 118.7 116.2 120.0 115.3 118.9 116.0 119.8 Crude fertilizers and crude minerals................................................. Metalliferous ores and metal scrap................................................... Crude animal and vegetable materials, n.e.s...................................... 2 23 24 25 26 ' 27 28 29 109.1 98.4 104.8 116.9 102.9 98.6 118.3 111.9 115.1 98.4 113.5 127.0 110.9 98.2 122.8 113.0 116.2 103.7 110.2 132.0 118.4 99.6 124.5 109.0 120.3 110.7 117.4 133.4 128.1 99.2 128.7 107.6 122.1 120.1 108.8 141.0 135.2 99.9 137.9 118.3 129.2 121.7 112.4 151.0 137.8 100.4 151.2 135.8 137.8 151.1 111.4 160.5 145.5 101.0 167.6 148.2 135.4 133.3 109.7 169.6 141.9 97.2 172.2 122.0 142.9 121.5 107.4 174.7 145.6 100.2 205.3 138.1 Fuels and related products............................................................... Crude petroleum and petroleum products.......................................... 3 33 55.9 55.0 67.4 67.4 74.1 74.4 74.3 75.2 67.2 67.8 60.6 60.4 63.4 63.6 57.7 57.7 53.2 52.7 Fixed vegetable oils and fats (9/87 = 100) ........................................ 4 42 83.4 - 82.9 - 87.9 - 96.4 100.0 102.1 105.7 106.4 111.1 111.2 116.1 114.0 119.2 112.6 117.6 Chemicals and related products ........................................................ Organic chemicals........................................................................... Inorganic chemicals.......................................................................... Medicinal and pharmaceutical products............................................ Essential oils and perfumes............................................................. Manufactured fertilizers.................................................................... Artificial resins and plastics and cellulose ......................................... Chemical materials and products, n.e.s.............................................. 5 51 52 54 55 56 58 59 99.0 87.5 94.6 113.6 106.9 89.9 110.3 112.7 102.6 96.1 90.5 120.1 117.6 92.9 110.0 115.1 104.8 99.8 89.8 123.4 117.8 94.6 114.7 117.7 105.6 98.2 89.8 124.3 119.2 109.3 114.4 120.6 110.1 103.0 90.1 126.3 123.0 133.6 117.6 124.8 114.2 105.8 92.0 135.3 125.7 133.7 121.6 138.7 116.4 107.3 92.3 140.3 126.2 136.3 124.3 148.5 119.2 111.3 93.0 145.4 127.5 136.5 127.6 153.4 122.0 115.2 95.2 146.5 130.5 139.3 129.4 156.5 Intermediate manufactured products ................................................. Leather and furskins ........................................................................ Rubber manufactures, n.e.s............................................................... Cork and wood manufactures........................................................... Paper and paperboard products....................................................... 6 61 62 63 64 65 66 67 68 69 106.7 107.2 101.8 117.4 104.9 107.9 117.9 100.9 101.5 108.3 108.6 110.9 104.3 118.0 104.8 110.4 120.5 102.7 102.5 112.1 112.5 116.6 104.6 124.3 104.9 111.8 126.7 106.6 112.4 112.7 116.3 117.8 103.2 128.3 110.3 114.6 130.4 109.4 120.9 114.6 119.8 124.4 104.6 128.2 112.3 118.6 133.4 114.0 125.8 117.8 124.4 131.8 106.0 133.8 117.2 120.0 137.4 120.0 132.7 121.1 132.2 137.0 107.7 138.2 118.3 120.6 142.5 127.2 159.7 126.9 132.3 136.6 109.1 136.1 119.5 119.1 139.7 129.9 158.9 127.5 135.5 134.9 111.1 134.1 119.9 120.1 144.2 130.2 171.0 130.9 7 114.4 134.3 130.2 130.1 114.8 110.2 115.1 120.6 123.1 “ 142.1 135.5 137.0 118,3 112.1 118.2 122.6 125.4 123.0 120.9 120.9 108,9 108.9 109.8 116.1 119.9 “ 136.1 128.1 130.8 114,0 110.3 115.8 120.5 119.9 72 73 74 75 76 77 78 117.5 ” 130.4 126.4 127.9 110.0 110.5 112.4 118.6 146.8 139.9 140.4 118.1 112.8 122.2 125.5 127.3 “ 149.8 142.4 143.7 119.5 113.8 124,2 127.6 126.7 ” 143.7 139.7 139.6 118.7 113.9 125.9 127.1 129.9 “ 149.5 144,2 144,1 119.1 115.8 129.2 130.8 8 81 82 83 84 85 110,3 110,8 112.3 87,5 102.8 112,3 114.5 111.6 114,8 98.1 106,4 114,8 117.8 117,0 119.8 99.8 109.2 119.8 118,5 116,2 119.0 98,2 111,9 119,0 121.8 121,0 124.3 103,0 112.3 124,3 124.2 123.4 125.4 105.8 115.6 125.4 125.7 126.9 129.6 107,3 114,9 129,6 124.2 124,5 128,0 111,3 116,7 128.0 126.4 125,5 129.2 115.2 117.2 129.2 87 122,5 131.3 135.9 132,7 138,7 140,0 142.5 135.8 141.8 88 89 119,0 ” 123,7 ” 126,0 122,1 127.3 129.2 129,3 125.4 130.5 Crude rubber (including synthetic and reclaimed)............................... Pulp and waste paper...................................................................... Nonmetallic mineral manufactures, n.e.s............................................ Nonferrous metals........................................................................... Metal manufactures......................................................................... Machinery and transport equipment ................................................. Machinery (Including SITC 71-77).................................................... Machinery specialized for particular industries................................... Metalworking machinery...................... ............................................ General industrial machinery and parts, n.e.s..................................... Office machines and automatic data processing equipment............... Telecommunications, sound recording and reproducing apparatus..... Electrical machinery and equipment.................................................. Road vehicles and parts................................................................... Miscellaneous manufactured articles................................................. Plumbing, heating, and lighting fixtures............................................. Furniture and parts.......................................................................... Travel goods, handbags, and similar goods (8/85-100) ................. Clothing............................................................................................ Footwear.................................................................. ......... ............. Professional, scientific, and controlling Instruments and apparatus,,,,................................................................................... Photographic apparatus and supplies, optical goods, watches, and ClOCKS ... .......................................... . Miscellaneous manufactured articles, n.e.s......... ............................... ' ' - Data not available, https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 87 MONTHLY LABOR REVIEW 38. April 1989 • Current Labor Statistics: Price Data U.S. export price indexes by end-use category (1985 = 100 unless otherwise indicated) Category Foods, feeds, and beverages .................................................. Industrial supplies and materials............................................... Capital goods.......................................................................... Automotive.............................................................................. Consumer goods..................................................................... Consumer nondurables, manufactured, except rugs.................. Consumer durables, manufactured......................................... Agricultural (9/88 = 100)........................................................ All exports, excluding agricultural (9/88 = 100)........................ Per centage of 1980 trade value 16.294 30.696 21.327 9.368 30.186 7.483 7.467 3.965 3.501 1986 Dec. 1987 Mar. June 90.2 96.3 100.8 103.5 105.2 104.3 104.9 101.4 103.4 105.9 105.4 105.5 101.1 - 87.4 1988 Sept. Dec. Mar. June Sept. 101.6 91.5 106.1 88.0 109.1 101.8 103.6 106.3 104.3 106.6 111.8 102.1 104.0 106.9 104.6 107.3 104.5 108.0 106.3 107.9 110.1 110.6 107.4 110.4 108.7 110.4 96.6 110.1 98.5 114.2 103.4 104.3 118.3 104.3 104.8 - - - - - _ “ “ ” - - - 124.5 118.7 104.9 105.3 111.3 109.3 110.7 108.8 - Dec. 117.3 118.8 105.7 106.8 112.9 109.7 112.6 102.8 - - Data not available. 39. U.S. import price indexes by end-use category (1985 = 100) Category All imports, excluding petroleum (6/88 = 100)........................... Foods, feeds, and beverages................................................. Industrial supplies and materials........................................... Petroleum and petroleum products, excluding natural gas . Industrial supplies and materials, excluding petroleum . . . . Capital goods, except automotive........................................ Automotive vehicles, parts and engines............................... Consumer goods except automotive..................................... Nondurables, manufactured .............................................. Durables, manufactured................................................... Per centage of 1980 trade value 7.477 31.108 19.205 9.391 9.814 13.164 11.750 14.250 5.507 8.743 1986 Dec. 1987 Mar. June 1988 Sept. Dec. Mar. June Sept. Dec. _ _ _ _ _ _ 108.4 81.6 54.7 114.2 114.6 110.5 105.2 88.4 67.2 107.8 93.5 74.1 122.2 118.4 116.9 109.0 95.3 74.7 121.9 118.4 118.2 112.1 93.7 67.6 126.6 120.6 121.4 113.7 92.7 60.3 - - - - 128.6 123.7 124.2 131.0 125.8 126.3 129.0 126.0 125.0 132.2 129.1 127.5 - 118.7 116.5 114.2 102.7 113.7 97.8 63.5 102.1 112.7 95.2 57.5 - - - - - - - - - “ - - " - - - - - Sept. Dec. - Data not available. 40. U.S. export price indexes by Standard Industrial Classification 1 (1985 = 100) 1986 1987 1988 Industry group Dec. Manufacturing: Food and kindred products............................................ Lumber and wood products, except furniture.................. Furniture and fixtures.................................................... Paper and allied products ............................................. Chemicals and allied products .................................. Petroleum and coal products......................................... Primary metal products................................................. Machinery, except electrical .......................................... Electrical machinery...................................................... Transportation equipment.............................................. Scientific instalments; optical goods; clocks................... 1 SIC - based classification. 88 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 100.2 108.8 104.1 104.9 95.8 67.6 106.9 100.1 100.8 106.0 105.3 104.5 113.9 94.9 52.8 Mar. 102.0 112.8 108.0 109.3 100.5 73.5 110.6 99.6 101.9 106.2 105.8 June 107.4 116.2 108.6 112.3 107.6 80.5 117.2 99.4 102.1 106.7 106.8 Sept. 107.1 138.9 108.7 115.5 108.7 81.4 122.3 99.4 102.5 106.9 106.6 Dec. 116.3 142.5 111.2 119.3 113.8 78.8 126.6 99.7 102.2 107.8 107.1 Mar. 120.8 146.1 112.5 124.6 118.4 73.0 126.9 100.6 102.9 108.1 109.2 June 125.1 145.4 112.9 129.8 122.3 77.8 133.8 101.3 103.7 109.1 110.8 128.9 146.1 112.9 133.1 125.4 73.7 133.5 102.2 103.5 109.4 112.0 123.5 143.9 115.6 135.9 125.7 75.1 134.2 102.7 103.8 111.1 113.4 41. U.S. import price indexes by Standard Industrial Classification (1985 = 100) 1988 1987 1986 Industry group Manufacturing: Food and kindred products.................................................. Textile mill products............................................................ Apparel and related products .............................................. Lumber and wood products, except furniture........................ Furniture and fixtures.......................................................... Paper and allied products ................................................... Chemicals and allied products............................................. Petroleum refining and allied products................................. Rubber and miscellaneous plastics products........................ Leather and leather products .............................................. Stone, clay, glass, and concrete products............................ Primary metal products........................................................ Fabricated metal products................................................... Machinery, except electrical................................................. Electrical machinery............................................................ Transportation equipment.................................................... Scientific instruments; optical goods; clocks......................... Miscellaneous manufactured commodities ........................... 1 SIC June Mar. Dec. 103.8 114.1 107.0 114.8 116.1 105.1 105.7 103.0 110.6 103.0 109.0 111.6 102.6 100.0 103.3 120.2 110.6 121.6 107.9 106.4 115.8 101.3 111.7 118.9 107.0 117.3 122.4 109.3 102.7 116.7 123.4 109.4 119.9 128.8 115.1 112.2 110.6 108.4 119.4 112.3 120.3 118.3 110.9 107.2 138.4 112.3 113.3 129.6 115.2 119.8 127.8 106.3 116.1 109.4 115.0 117.0 105.9 106.2 136.4 113.6 113.3 130.0 110.4 117.5 127.4 110.7 124.3 113.4 115.4 118.9 113.6 112.2 127.4 115.7 118.4 133.9 110.2 122.1 122.5 128.8 121.4 132.5 118.1 Mar. Dec. Sept. 114.4 128.9 115.8 120.3 124.0 121.3 121.3 119.2 119.0 124.6 141.5 137.0 133.3 138.2 116.1 129.5 137.0 133.1 114.0 127.4 116.6 119.5 122.2 119.1 116.8 114.5 117.2 120.0 120.8 138.2 122.6 123.2 133.9 112.5 124.6 134.0 123.8 127.3 135.9 114.7 127.3 135.8 127.7 Sept. June Dec. 115.0 127.0 117.0 118.6 124.8 123.8 123.5 110.8 117.7 123.7 140.5 136.2 133.0 135.0 116.7 129.3 132.2 130.6 based classification. 42. Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted (1977 = 100) Quarterly Indexes Item II Business: Output per hour of all persons.......................... Compensation per hour..................................... Real compensation per hour............................. Unit labor costs ................................................ Unit nonlabor payments.................................... Implicit price deflator ........................................ 1987 1986 III IV 110.0 109.8 184.0 186.2 101.1 101.6 102.1 110.4 182.0 I II 1988 III IV 170.8 168.7 170.1 111.7 191.1 101.3 171.1 171.5 171.2 194.0 101.9 173.5 168.9 171.9 173.5 170.0 172.3 109.9 192.9 101.4 175.6 170.9 174.0 194.6 101.3 175.7 171.6 174.2 110.6 101.1 164.9 165.2 165.0 167.3 166.6 167.0 169.6 163.7 167.5 108.4 181.2 100.7 167.1 166.6 167.0 108.0 183.1 169.5 168.1 169.0 107.8 185.4 101.7 172.1 164.9 169.5 107.8 186.4 100.9 172.9 167.2 170.9 108.6 187.9 100.5 173.0 169.8 171.9 109.6 190.0 100.7 173.3 173.0 173.2 109.3 178.5 99.2 166.7 163.3 176.9 132.7 161.4 162.6 109.6 180.2 99.5 168.4 164.3 180.3 133.6 164.0 164.2 110.1 168.8 165.1 179.6 129.7 162.1 164.1 182.9 99.0 169.9 166.2 180.8 128.5 162.5 164.9 110.9 184.3 98.6 170.3 166.1 182.6 129.8 164.1 165.4 186.1 98.7 170.2 165.9 183.0 136.4 166.6 166.1 188.5 99.0 172.0 168.1 183.6 128.3 164.2 166.7 127.2 182.0 128.0 183.6 101.4 143.4 128.8 185.3 101.7 143.8 130.0 185.9 100.7 143.1 131.7 186.3 99.7 141.4 132.8 187.2 99.3 141.0 133.2 188.2 98.9 141.3 Nonfarm business: Output per hour of all persons.......................... Compensation per hour..................................... Real compensation per hour............................. Unit labor costs ................................................ Unit nonlabor payments .................................... Implicit price deflator ........................................ 101.2 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 ........................................ 110.3 182.2 100.0 II III IV 111.8 112.8 111.8 112.3 111.8 195.8 198.1 201.1 203.4 101.9 102.0 102.4 102.4 109.9 187.3 101.4 170.5 165.6 168.7 189.0 I 112.2 112.2 177.1 170.4 174.7 179.0 172.7 176.8 110.8 110.1 196.6 101.3 178.6 171.8 176.2 110.7 199.4 101.5 180.2 173.9 178.0 113.3 189.9 98.9 171.5 167.5 183.4 132.5 165.6 166.9 112.9 191.9 98.8 173.8 170.0 185.1 132.6 166.7 168.8 112.7 194.5 99.0 176.4 172.6 187.8 129.6 167.4 170.8 134.3 190.7 99.3 142.1 135.5 192.1 99.0 141.8 137.2 194.4 99.0 141.6 182.0 173.5 179.0 110.7 202.2 101.8 182.6 176.8 180.6 - - Manufacturing: Output per hour of all persons.......................... Compensation per hour..................................... Real compensation per hour............................. Unit labor costs ................................................ Data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 101.1 143.2 137.9 197.0 99.2 142.9 115.4 127.1 117.5 116.8 128.0 125.2 130.5 109.0 121.4 123.8 144.2 140.8 136.5 138.2 119.2 132.8 137.7 133.7 MONTHLY LABOR REVIEW 43. April 1989 • Current Labor Statistics: Productivity Data Annual Indexes of multifactor productivity and related measures, selected years (1977 = 100) Item 1960 1970 1973 1977 1979 1981 1982 1983 1984 1985 1986 1987 Private business Productivity: Output per hour of all persons........................ Output per unit of capital services................... Multifactor productivity.................................... Output.............................................................. Inputs: Hours of all persons....................................... Capital services ............................................. Combined units of labor and capital Input........ Capital per hour of all persons.......................... 105.6 92.7 100.9 119.2 107.9 92.9 102.4 124.3 110.3 93.0 103.9 128.7 111.2 106.7 124.4 112.9 128.6 118.1 113.9 115.2 133.8 121.4 116.1 116.7 138.5 123.9 118.7 120.0 106.2 91.0 100.7 124.0 108.3 90.8 110.1 104.7 91.3 99.9 119.3 102.0 109.1 91.5 102.7 133.2 107.4 126.1 113.5 117.4 114.0 130.6 119.4 114.6 116.8 136.3 123.1 116.7 118.5 141.3 125.8 119.3 122.0 109.4 105.7 123.3 111.4 116.6 101.4 99.5 100.9 108.1 103.6 89.0 99.7 104.8 105.9 81.6 99.2 98.4 112.0 118.1 95.5 123.6 97.3 116.4 131.9 117.5 122.0 127.7 98.4 119.5 124.7 123.6 130.1 106.5 108.6 107.1 101.9 101.1 92.9 120.5 99.2 129.8 93.5 99.5 123.0 104.8 123.7 98.7 125.4 104.8 127.1 97.7 126.8 104.4 129.8 98.6 127.6 105.3 129.4 99.5 99.7 99.6 107.9 100.6 100.3 92.3 97.6 108.9 95.2 105.4 108.4 108.2 108.3 99.8 108.2 117.9 111.5 108.9 110.7 115.8 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.2 98.9 99.1 107.9 99.6 91.0 96.7 108.4 99.1 85.1 94.1 104.8 108.8 109.1 108.9 100.3 108.8 119.1 100.0 93.4 112.0 100.0 100.0 98.0 100.0 96.3 100.0 103.1 86.0 100.0 100.0 98.3 100.0 83.4 88.4 102.7 93.1 80.2 82.2 53.3 70.5 64.9 90.8 78.1 70.7 104.9 81.2 54.4 89.2 103.5 93.8 79.9 96.4 106.3 99.7 92.9 77.0 51.9 67.1 67.4 89.6 77.2 85.2 96.3 87.3 93.2 90.7 62.2 103.0 72.0 52.5 80.8 99.1 85.3 78.6 84.4 51.0 72.9 60.4 97.3 79.3 92.1 81.5 86.1 86.1 103.0 88.3 97.6 109.9 100.0 100.0 100.0 100.0 100.0 96.9 88.0 100.0 100.0 93.7 100.0 90.8 67.3 103.7 78.5 55.3 95.9 105.6 99.2 93.0 86.6 105.2 121.8 112.6 116.6 93.7 104.7 133.4 142.4 127.4 118.6 Private nonfarm business Productivity: Output per hour of all persons........................ Output per unit of capital services................... Multifactor productivity.................................... Output............................................................. Inputs: Hours of all persons....................................... Capital services............................................. Combined units of labor and capital input........ Capital per hour of all persons.......................... 86.2 112.2 102.5 87.3 97.0 128.3 145.5 129.6 119.2 Manufacturing Productivity: Output per hour of all persons........................ Output per unit of capital services................... Multifactor productivity.................................... Output............................................................. Inputs: Hours of all persons....................................... Capital services............................................. Combined units of labor and capital Inputs...... Capital per hour of all persons.......................... 90 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 117.8 105.1 116.5 86.7 105.0 104.7 120.8 99.7 129.3 112.1 102.0 44. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years (1977=100) Item 1960 1970 1973 1977 1979 1981 1982 1983 1984 1985 1986 67.6 33.6 68.9 49.7 46.4 48.5 88.4 57.8 90.3 65.4 59.4 63.2 95.9 70.9 96.8 73.9 72.5 73.4 100.0 100.0 100.0 100.0 100.0 100.0 99.6 119.1 99.4 119.5 112.5 117.0 100.7 143.7 95.8 142.7 134.6 139.8 100.3 154.9 97.3 154.5 136.6 148.1 103.0 161.4 98.2 156.7 146.4 153.0 105.5 167.9 97.9 159.1 156.5 158.2 107.7 175.5 98.8 162.9 160.9 162.2 110.1 111.0 112.1 183.1 190.4 199.5 101.2 101.5 102.2 71.0 35.3 72.3 49.7 46.3 48.5 89.3 58.2 90.9 65.2 60.0 63.4 96.4 71.2 97.2 73.9 69.3 72.3 100.0 100.0 100.0 100.0 100.0 100.0 99.3 118.9 99.2 119.7 110.5 116.5 99.8 143.6 95.8 144.0 133.5 140.3 99.2 154.8 97.2 156.0 136.5 149.2 102.5 161.5 98.3 157.6 148.3 154.3 104.6 167.8 97.9 160.4 156.3 159.0 106.1 174.9 98.5 164.9 161.9 163.8 73.4 36.9 75.5 49.4 50.2 47.0 59.8 51.5 50.7 91.1 59.2 92.5 64.8 65.0 64.2 52.3 60.1 63.3 97.5 71.6 97.7 72.7 73.4 70.7 65.6 68.9 71.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 99.8 118.7 99.1 118.2 119.0 115.8 94.5 108.4 115.4 99.6 143.3 95.5 147.7 143.8 159.1 98.1 137.8 141.7 100.4 154.3 96.9 159.5 153.8 176.4 78.5 142.1 149.8 103.5 159.9 97.3 159.5 154.5 174.3 110.9 152.1 153.7 106.0 165.8 96.7 160.8 156.5 173.6 136.5 160.6 157.9 62.2 36.5 74.8 58.7 60.0 59.1 80.8 57.4 89.6 71.0 64.1 69.0 93.4 100.0 68.8 100.0 93.9 100.0 73.7 100.0 70.7 100.0 72.8 100.0 101.4 118.6 99.0 117.0 98.9 111.7 103.6 145.2 96.8 140.1 105.9 157.5 98.9 148.7 114.0 138.6 112.0 118.1 168.0 98.0 142.2 138.6 141.2 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 ................................................ Unit nonlabor payments.................................... Implicit price deflator ........................................ Data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 111.8 131.8 162.4 98.8 145.0 128.5 140.2 1987 1988 166.3 165.0 165.8 171.5 168.7 170.5 177.9 171.7 175.7 108.2 182.3 109.0 189.4 168.6 166.4 167.8 173.8 170.2 172.5 110.5 198.2 101.5 179.3 173.6 177.3 107.7 172.5 97.1 164.1 160.2 175.8 133.0 160.8 160.4 109.7 179.5 99.2 167.3 163.6 178.4 132.4 162.3 163.2 111.3 185.5 98.9 170.6 166.6 182.5 130.8 164.4 165.8 112.7 193.2 99.0 175.3 171.5 186.9 129.8 166.9 169.9 123.6 176.4 99.3 142.7 130.4 139.1 127.7 183.0 132.0 186.9 99.7 141.7 139.2 141.0 136.2 193.6 99.2 142.1 100.8 101.0 101.2 143.3 136.3 141.3 - “ MONTHLY LABOR REVIEW 92 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis April 1989 • Current Labor Statistics: International Comparisons Data 45. Unemployment rates, approximating U.S. concepts, in nine countries, quarterly data seasonally adjusted 1988 1987 Annual average Country 1987 1988 IV III II I II IV III Total labor force basis United States................................. Canada .......................................... Australia ........................................ Japan ............................................. France ........................................... Germany........................................ Italy 2 .......................................... Sweden’’ ........................................ United Kingdom.............................. 6.1 8.8 8.1 2.9 10.6 6.8 7.7 1.9 5.4 7.7 7.2 2.5 6.2 9.0 8.1 10.3 7.0 7.8 10.7 7.0 7.7 1.9 10.5 1.6 3.0 10.2 8.3 United States................................. Canada .......................................... Australia ........................................ Japan ............................................. 6.2 8.9 8.1 5.5 7.8 7.2 2.5 6.3 9.0 France ........................................... Germany........................................ Italy1, 2 ........................................... Sweden3 ........................................ United Kingdom.............................. 10.8 10.5 7.1 7.9 10.9 7.1 7.8 1.9 5.9 8.6 8.0 2.8 10.6 7.0 7.8 1.9 10.0 7.9 2.7 5.6 7.8 7.5 2.7 5.4 7.6 7.5 2.5 5.4 7.8 6.9 10.3 7.0 7.9 1.7 9.4 10.3 7.0 7.8 1.7 9.0 10.3 7.0 7.8 10.4 7.0 7.8 10.2 6.8 5.9 5.7 7.8 7.6 2.7 5.5 7.7 7.6 2.5 5.5 7.8 7.0 5.3 7.7 10.6 10.5 7.2 7.9 5.8 8.1 1.6 8.6 2.6 1.6 8.0 5.3 7.7 6.8 2.4 7.8 1.4 7.5 Civilian labor force basis 2.9 6.9 7.9 1.9 10.3 1.6 8.3 1 Quarterly rates are for the first month of the quarter. 2 Many Italians reported as unemployed did not actively seek work in the past 30 days, and they have been ex cluded for comparability with U.S. concepts. Inclusion of such persons would about double the Italian unemployment rate In 1985 and earlier years and increase It to 11-12 per cent for 1986 onward. 8.2 3.0 10.6 6.0 8.6 8.0 2.8 10.8 7.2 8.0 1.9 10.0 8.1 8.0 2.7 10.6 7.1 8.1 1.7 9.5 7.1 7.9 1.7 9.0 1.6 8.6 2.6 10.6 7.1 8.0 1.6 8.0 6.8 2.4 10.4 7.0 7.9 1.4 7.6 3 Break In series beginning In 1987. The 1986 rate based on the new series was 2.2 percent. NOTE: Quarterly figures for France, Germany, and the United Kingdom are calculated by applying annual adjust ment factors to current published data and therefore should be viewed as less precise indicators of unemployment under U.S. concepts than the annual figures. 46. Annual data: Employment status of the civilian working-age population, approximating U.S. concepts, 10 countries (Numbers in thousands) Employment status and country 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 Labor force United States................................................... Canada ............................................................ Australia........................................................... Japan ............................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 104,962 106,940 108,670 110,204 111,550 113,544 115,461 11,231 11,573 11,904 11,958 12,183 12,399 12,639 6,519 6,693 6,810 6,910 6,997 7,133 7,272 55,210 55,740 56,320 56,980 58,110 58,480 58,820 22,660 22,800 22,950 23,160 23,140 23,300 23,360 26,250 26,520 26,650 26,700 26,650 26,770 26,970 20,850 21,120 21,320 21,410 21,590 21,670 21,800 5,100 5,520 5,310 5,570 5,600 5,620 5,710 4,262 4,312 4,327 4,350 4,369 4,385 4,418 26,350 26,520 26,590 26,740 26,790 27,180 27,370 117,834 119,865 121,669 12,870 13,121 13,275 7,562 7,736 7,949 59,410 60,050 60,860 23,450 23,520 27,110 27,290 27,440 22,280 22,340 5,760 5,810 4,443 4,480 4,530 27,540 27,760 - Participation rate1 United States................................................... Canada ............................................................ Australia........................................................... Japan ............................................................... France .............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 63.7 63.4 61.6 62.7 57.5 53.3 48.0 49.0 66.6 62.6 63.8 64.1 62.1 62.6 57.2 53.2 48.2 50.2 66.9 62.5 63.9 64.8 61.9 62.6 57.1 52.9 48.3 51.4 64.0 64.1 61.7 62.7 57.1 52.6 47.7 51.2 62.2 62.3 66.8 66.8 64.0 64.4 61.4 63.1 56.6 52.3 47.5 50.9 66.7 62.1 64.4 64.8 61.5 62.7 56.6 52.4 47.3 50.5 66.6 62.6 64.8 65.2 61.8 62.3 56.3 52.6 47.2 50.7 66.9 62.7 65.3 65.7 63.0 62.1 56.1 52.8 48.2 50.5 67.1 62.7 65.6 66.2 63.0 61.9 55.8 53.1 48.2 50.3 67.4 63.0 65.9 66.7 63.4 61.9 - 67.7 - Employed United States................................................... Canada ............................................................ Australia........................................................... Japan ............................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 98,824 10,395 6,111 54,040 21,300 25,470 19,930 4,830 4,174 24,940 99,303 100,397 10,708 11,006 6,284 6,416 54,600 55,060 21,330 21,200 25,750 25,560 20,200 20,280 4,980 5,010 4,226 4,219 24,670 23,800 99,526 100,834 105,005 107,150 109,597 112,440 114,968 10,644 10,734 11,000 11,311 11,634 11,955 12,244 6,415 6,300 6,490 6,670 6,952 7,107 7,373 55,620 56,550 56,870 57,260 57,740 58,320 59,310 21,240 21,170 20,980 20,920 20,960 20,970 25,140 24,750 24,800 24,960 25,220 25,400 25,490 20,250 20,320 20,390 20,490 20,610 20,590 4,980 4,890 4,930 5,110 5,200 5,270 4,213 4,218 4,249 4,293 4,326 4,396 4,458 23,710 23,600 24,000 24,310 24,450 24,910 - Employment-population ratio2 United States................................................... Canada ............................................................ Australia........................................................... Japan ............................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 59.9 58.7 57.8 61.4 54.0 51.7 45.9 46.4 65.3 59.2 59.2 59.3 58.3 61.3 53.5 51.7 46.1 47.0 65.6 58.1 59.0 59.9 58.4 61.2 52.8 50.8 45.9 46.6 65.1 55.7 57.8 57.0 57.3 61.2 52.3 49.6 45.2 45.8 64.7 55.3 57.9 56.7 55.3 61.4 51.8 48.6 44.7 44.5 64.4 54.7 59.5 57.4 56.0 61.0 51.0 48.5 44.5 44.3 64.5 55.3 60.1 58.4 56.6 60.6 50.4 48.7 44.4 45.3 65.0 55.7 60.7 59.4 57.9 60.4 50.2 49.2 44.6 45.6 65.4 55.7 61.5 60.3 57.9 60.1 49.7 49.4 44.4 45.6 56.6 66.2 66.7 - 6,137 836 408 1,170 1,360 780 920 270 7,637 865 409 1,140 1,470 770 920 330 1,850 10,678 1,314 495 1,360 1,920 1,560 1,160 590 137 3,030 10,717 1,448 697 1,560 1,970 1,900 1,270 710 151 3,190 8,539 1,399 642 1,610 2,320 1,970 1,280 690 136 3,180 8,312 1,328 602 1,560 2,440 1,420 8,273 898 394 1,260 1,750 1,090 1,040 510 108 2,790 1,310 600 125 3,060 8,237 1,236 610 1,670 2,490 1,890 1,680 560 117 3,090 7,425 1,167 629 1,730 2,550 1,890 1,760 540 84 2,850 6,701 1,031 575 1,550 1,950 _ _ 72 - 7.6 7.5 5.8 11.0 9.6 11.9 7.5 11.3 9.0 7.2 10.5 8.3 7.0 9.6 6.2 8.9 8.1 2.9 10.8 7.0 7.5 9.7 6.9 7.9 9.3 1.9 10.3 5.5 7.8 7.2 2.5 10.5 7.1 7.9 - 62.3 61.6 58.8 60.4 - Unemployed United States................................................... Canada ............................................................ Australia........................................................... Japan ............................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 88 86 2,010 Unemployment rate United States................................................... Canada ............................................................ Australia........................................................... Japan .............................................................. France .............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Sweden............................................................ United Kingdom................................................ 5.8 7.4 6.3 2.1 6.0 3.0 4.4 5.3 7.1 7.5 6.1 2.0 6.4 2.9 4.4 2.1 6.2 2.0 5.4 7.0 Labor force as a percent of the civilian working-age population. Employment as a percent of the civilian working-age population. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 2.2 7.6 4.1 4.9 9.2 2.5 10.5 9.7 7.2 2.4 8.3 5.8 5.4 10.6 3.1 11.3 10.0 2.7 8.5 7.1 5.9 12.7 - 11.9 Data not available. 2.8 10.0 7.4 5.9 12.3 3.1 11.7 2.6 10.4 7.5 6.0 10.5 2.8 11.2 8.1 2.8 10.6 2.6 11.2 1.6 8.3 MONTHLY LABOR REVIEW 47. April 1989 • Current Labor Statistics: International Comparisons Data Annual indexes of manufacturing productivity and related measures, 12 countries (1977 = 100) Item and country United States................................................... Canada ............................................................ Japan .............................................................. Belgium............................................................ Denmark.......................................................... France............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Norway............................................................. Sweden............................................................ United Kingdom................................................ 1977 62.2 50.7 23.2 33.0 37.2 37.4 40.3 35.4 32.4 54.3 42.3 55.9 80.8 75.6 64.8 60.4 65.6 71.4 71.2 72.7 64.3 81.3 80.7 80.4 93.4 90.3 83.1 78.8 83.3 83.8 84.0 90.9 81.5 94.4 94.8 95.5 97.1 94.8 94.3 95.3 98.2 94.4 96.4 98.9 95.8 100.4 101.7 99.1 100.0 101.5 101.4 103.6 105.9 112.0 100.0 101.1 98.2 102.9 98.3 105.4 100.0 108.0 122.7 127.2 135.0 142.3 100.0 106.1 119.2 127.6 135.2 148.2 100.0 101.5 112.3 114.2 114.6 120.2 100.0 104.6 110.6 113.9 122.0 125.1 100.0 103.1 108.6 111.0 112.6 119.2 100.0 103.0 116.9 124.8 129.6 138.6 100.0 106.4 113.9 116.9 119.4 127.5 100.0 101.2 107.4 108.0 109.2 117.2 100.0 102.8 112.7 113.2 116.5 125.5 100.0 101.5 101.9 107.0 113.5 123.2 52.5 41.3 19.2 41.9 49.2 36.5 50.0 36.4 44.8 54.8 52.6 71.2 78.6 73.5 69.9 78.6 82.0 75.5 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 102.1 100.0 100.0 106.1 100.0 98.2 106.0 104.6 106.7 101.4 99.7 102.3 78.0 84.4 86.5 92.5 95.0 96.3 93.5 91.9 96.4 95.9 90.5 96.1 90.5 95.8 99.2 100.3 104.8 84.4 81.4 82.7 127.1 132.4 97.6 123.8 97.3 97.2 107.9 130.2 125.1 105.7 121.7 107.4 131.2 106.4 114.6 118.1 103.1 103.6 110.7 122.3 115.2 107.9 114.4 99.6 117.6 105.1 105.7 109.8 100.0 95.9 101.8 100.0 100.6 100.0 104.6 100.0 101.4 100.0 100.0 101.3 101.6 100.0 99.0 100.0 103.3 100.0 101.7 100.0 100.0 104.3 99.0 100.0 104.4 103.4 98.8 95.5 98.3 97.8 98.7 98.8 96.6 96.5 94.6 99.1 101.7 105.5 89.6 98.0 94.6 98.1 98.7 93.6 92.6 92.3 90.1 82.8 93.4 90.3 94.6 92.2 91.2 91.3 88.9 80.6 15.0 18.8 8.4 12.5 15.8 14.7 15.2 57.4 47.9 33.9 34.9 36.3 36.3 48.0 26.1 39.0 37.9 38.5 31.4 60.0 55.1 53.5 56.1 51.9 67.5 43.7 60.5 54.5 54.2 47.9 92.1 90.3 90.7 89.5 90.4 87.8 91.2 84.2 91.9 100.0 108.2 100.0 107.6 100.0 106.6 100.0 107.8 100.0 110.2 100.0 113.0 100.0 107.8 100.0 114.5 100.0 108.4 88.8 100.0 110.0 91.5 100.0 111.4 88.4 100.0 116.7 132.4 131.3 120.7 130.3 135.9 148.5 125.6 160.2 123.6 128.0 133.6 168.6 145.2 151.1 129.8 144.5 149.7 172.0 134.5 198.4 129.1 142.8 148.1 193.4 58.7 54.2 38.4 41.7 33.8 40.2 46.6 23.7 38.5 29.2 34.8 27.2 71.0 63.4 52.3 57.8 55.4 50.8 67.4 36.0 60.7 46.6 47.7 39.1 73.7 66.5 66.4 67.9 67.4 62.0 80.3 48.1 74.3 57.8 57.2 50.2 94.9 95.3 96.2 93.9 92.1 93.0 94.6 85.1 96.0 88.5 90.0 89.2 58.7 59.4 28.5 30.0 29.5 40.3 25.9 33.7 25.1 71.0 64.5 39.1 41.7 44.4 45.2 42.9 50.6 41.2 34.7 41.1 53.7 73.7 70.6 65.6 62.7 67.2 94.9 102.7 86.9 87.2 91.5 95.8 87.3 90.5 89.1 86.4 92.3 92.2 86.6 102.8 101.0 138.4 124.4 127.3 Compensation per hour United States................................................... Canada ............................................................ Japan .............................................................. Belgium............................................................ Denmark.......................................................... France............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Norway............................................................. Sweden............................................................ United Kingdom................................................ 36.5 27.5 8.9 13.8 12.6 68.8 93.1 96.5 94.8 99.7 99.6 95.6 98.0 97.9 99.0 Unit labor costs: National currency basis United States................................................... Canada ............................................................ Japan .............................................................. Belgium............................................................ Denmark.......................................................... France .............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Norway............................................................. Sweden............................................................ United Kingdom................................................ Unit labor costs: U.S. dollar basis United States................................................... Canada ............................................................ Japan ............................................................... Belgium............................................................ Denmark .......................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Nonway............................................................. Sweden............................................................ United Kingdom................................................ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1983 1976 Total hours United States................................................... Canada ............................................................ Japan .............................................................. Belgium............................................................ Denmark................................................—....... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Norway............................................................. Sweden............................................................ United Kingdom................................................ 1982 1973 Output United States................................................... Canada ............................................................ Japan .............................................................. Belgium............................................................ Denmark.......................................................... France.............................................................. Germany.......................................................... Italy.................................................................. Netherlands...................................................... Norway............................................................. Sweden............................................................ United Kingdom................................................ 1981 1970 Output per hour 21.8 30.1 43.7 68.6 70.4 73.1 65.6 53.5 58.7 70.5 1978 1980 1960 103.2 103.6 124.1 106.8 104.8 107.4 129.8 105.7 106.6 102.9 104.9 115.1 106.7 98.6 98.4 93.6 137.3 1984 1985 1986 1987 118.1 114.4 152.5 154.3 119.6 127.6 123.7 147.8 140.5 124.1 131.0 130.0 123.6 117.3 161.1 159.0 117.6 131.0 128.4 151.7 145.5 126.8 136.1 134.7 127.7 117.7 163.8 165.3 113.5 134.9 128.4 152.9 144.8 125.9 136.0 138.3 132.0 120.5 170.5 170.3 114.9 139.2 130.3 157.8 145.5 134.9 141.8 147.8 122.0 124.7 121.9 178.0 130.1 128.5 184.1 123.1 120.5 103.3 118.7 108.3 119.2 104.7 99.6 148.2 114.8 115.6 103.8 103.6 114.3 107.0 97.2 105.2 88.9 117.5 112.5 165.4 117.5 99.5 98.3 108.5 76.1 85.9 76.2 93.5 94.5 104.2 77.5 96.2 83.0 86.9 82.5 83.9 82.9 83.9 72.2 157.5 167.0 136.6 150.7 162.9 204.0 141.0 238.3 137.5 156.0 158.9 211.7 121.0 102.6 118.8 177.0 119.9 123.0 101.5 106.4 119.0 113.3 102.7 111.5 92.6 116.7 106.5 115.3 95.2 118.1 106.9 114.7 95.4 98.7 80.5 80.6 82.8 85.1 71.2 109.8 75.4 104.6 77.5 85.7 80.3 80.2 84.0 84.7 70.7 97.7 103.6 108.7 73.8 109.2 75.7 86.3 82.3 81.5 84.9 84.3 69.0 98.6 106.6 108.0 72.3 104.9 74.2 85.7 83.2 81.6 80.3 84.0 162.4 177.2 140.7 159.8 174.2 225.1 148.3 282.9 144.0 173.5 173.3 226.6 168.0 185.6 144.9 173.1 184.1 245.0 155.5 316.5 150.0 188.3 189.7 242.3 176.4 194.4 151.4 183.6 196.2 265.4 164.6 348.0 157.4 204.3 212.4 258.8 183.0 203.5 158.8 190.8 202.7 277.2 171.7 359.4 162.2 224.2 228.7 277.9 186.9 214.0 161.1 194.5 226.3 285.7 178.6 380.5 166.5 262.6 244.8 297.6 100.0 106.6 130.6 140.1 148.7 100.0 106.5 133.7 146.7 170.0 100.0 98.7 98.4 102.0 101.2 100.0 101.6 109.3 113.2 111.5 100.0 108.6 121.0 131.1 142.2 100.0 108.0 134.3 151.0 167.2 100.0 104.5 115.7 121.2 125.2 100.0 111.2 137.0 158.9 184.0 100.0 101.8 108.5 110.4 115.2 100.0 108.7 119.1 132.2 142.9 100.0 108.4 118.6 130.9 136.3 100.0 115.0 165.5 180.7 186.5 145.0 168.1 98.9 107.8 144.9 179.9 124.4 204.1 113.0 148.0 138.1 184.0 142.2 162.3 95.0 142.7 165.7 94.0 115.5 166.8 202.7 128.3 229.4 108.1 161.1 156.1 192.1 143.3 172.8 97.0 115.5 178.7 205.4 133.7 235.1 141.7 177.5 94.5 114.2 197.0 205.2 137.1 241.2 114.4 194.7 172.6 201.3 100.0 106.6 130.6 100.0 99.3 121.5 100.0 126.8 116.8 100.0 115.8 134.2 100.0 118.4 129.0 100.0 117.9 156.4 100.0 121.0 147.9 100.0 115.6 141.4 100.0 115.7 134.1 100.0 110.4 128.4 100.0 107.2 125.3 100.0 126.4 220.6 145.0 144.9 111.5 75.6 95.1 116.1 113.1 118.6 97.1 107.9 80.4 159.8 142.2 133.2 107.2 69.6 89.3 108.1 142.7 128.9 105.6 69.7 94.5 107.6 81.6 99.0 78.2 142.8 106.1 80.0 99.8 81.1 142.9 143.3 132.1 154.2 92.6 132.5 145.8 143.0 139.2 101.8 101.8 102.8 97.7 97.3 100.6 110.1 104.6 106.6 115.4 106.6 99.5 104.0 91.7 110.1 108.3 104.0 102.4 113.4 105.0 96.8 100.6 100.1 86.2 86.4 101.1 104.3 101.2 102.0 140.1 130.0 123.8 109.6 110.3 136.4 124.9 123.2 108.9 122.5 115.4 209.6 92.9 95.2 101.7 81.4 94.5 85.2 91.0 87.5 88.0 88.6 148.7 146.3 108.8 87.2 102.3 124.9 119.7 119.9 105.8 117.8 96.9 186.9 101.2 80.4 86.1 112.2 153.9 192.0 125.8 214.1 106.8 151.8 144.8 186.4 122.0 123.9 102.1 110.0 110.8 111.6 121.8 125.8 131.2 101.2 111.0 102.6 101.2 112.0 178.1 168.2 200.9 112.2 128.1 105.4 169.0 100.6 68.0 141.7 142.3 175.0 109.6 172.7 167.8 177.0 164.2 138.6 153.7 121.5 189.2 48. Occupational injury and illness incidence rates by industry, United States Incidence rates per 100 full-time workers2 Industry and type of case1 1979 1980 1981 1982 1983 1984 1985 1986 1987 PRIVATE SECTOR3 Total cases........... Lost workday cases Lost workdays....... 8.7 4.0 65.2 8.3 3.8 61.7 7.7 3.5 58.7 7.6 3.4 58.5 11.7 5.7 83.7 11.9 5.8 82.7 12.3 5.9 82.8 11.8 5.9 86.0 11.9 6.1 12.0 6.1 90.8 11.4 11.2 11.6 6.2 150.5 6.5 163.6 146.4 10.5 5.4 137.3 15.7 6.5 117.0 15.1 6.3 113.1 14.6 6.8 111.2 15.5 6.5 113.0 15.1 107.1 112.0 113.0 16.6 6.7 123.1 16.3 6.3 117.6 14.9 106.0 15.1 5.8 113.1 16.0 6.9 124.3 15.5 6.7 118.9 15.2 14.7 119.3 118.6 13.3 5.9 90.2 11.5 5.1 82.0 10.2 5.4 86.7 4.4 75.0 175.9 18.6 9.5 171.8 17.6 9.0 158.4 16.9 8.3 153.3 17.6 7.1 99.6 16.0 15.1 97.6 91.9 13.9 5.5 85.6 15.0 7.1 128.1 122.2 15.2 7.1 128.3 14.4 6.7 121.3 101.6 18.5 Agriculture, forestry, and fishing3 Total cases............................................................. Lost workday cases................................................ Lost workdays........................................................ Mining Total cases....................................... Lost workday cases.......................... Lost workdays................................... 8.0 9.5 4.3 67.7 6.8 7.9 3.6 64.9 7.9 3.6 65.8 11.2 11.2 90.7 11.4 5.7 91.3 5.6 93.6 5.7 94.1 8.4 4.5 125.1 9.7 5.3 160.2 8.4 4.8 145.3 7.4 4.1 125.9 8.5 4.9 144.0 14.8 6.3 118.2 15.5 6.9 128.1 15.2 14.7 128.9 15.2 6.9 134.5 14.4 15.4 6.9 121.3 15.2 14.9 120.4 122.7 14.2 6.5 134.0 122.4 14.9 6.4 131.7 14.5 6.3 127.3 14.7 6.3 132.9 14.5 6.4 139.1 14.8 6.4 119.0 15.8 7.1 130.1 15.4 7.0 133.3 15.6 7.2 140.4 15.0 7.1 135.7 10.0 10.6 4.7 77.9 10.4 4.6 80.2 10.6 4.3 73.5 4.7 85.2 11.9 5.3 95.5 18.3 9.2 163.5 19.6 9.9 172.0 18.5 9.3 171.4 18.9 9.7 177.2 18.9 9.6 176.5 14.1 5.7 83.0 15.3 6.4 101.5 15.0 6.3 100.4 15.2 6.3 103.0 15.4 6.7 103.6 3.7 63.4 8.3 3.8 69.9 Construction Total cases............................................ Lost workday cases................................ Lost workdays........................................ General building contractors: Total cases............................................ Lost workday cases................................ Lost workdays........................................ Heavy construction contractors: Total cases............................................ Lost workday cases................................ Lost workdays........................................ Special trade contractors: Total cases............................................ Lost workday cases ................................ Lost workdays........................................ 16.2 6.8 120.4 16.3 Manufacturing Total cases........... Lost workday cases Lost workdays....... Durable goods Lumber and wood products: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Furniture and fixtures: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Stone, clay, and glass products: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Primary metal industries: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Fabricated metal products: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Machinery, except electrical: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Electric and electronic equipment: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Transportation equipment: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Instruments and related products: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... Miscellaneous manufacturing industries: Total cases.............................................. Lost workday cases................................. Lost workdays.......................................... See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 20.7 10.8 16.8 8.0 133.7 17.3 8.1 134.7 12.2 6.6 6.1 6.0 6.6 6.2 14.1 6.9 6.0 115.7 14.1 5.9 6.2 13.0 6.2 15.4 6.2 13.1 6.6 120.8 13.6 13.9 6.7 127.8 13.6 6.5 126.0 14.9 7.1 135.8 12.4 5.4 12.4 5.4 103.4 13.3 12.6 13.6 115.3 5.7 113.8 125.5 17.0 7.4 145.8 15.3 6.4 102.5 15.1 6.1 118.4 96.5 16.1 6.7 104.9 14.7 5.9 83.6 13.7 5.5 81.3 12.9 5.1 74.9 10.7 4.2 66.0 9.8 3.6 58.1 10.7 4.1 65.8 8.6 8.0 3.3 51.8 6.5 2.7 42.2 6.3 3.4 51.9 7.4 3.1 48.4 2.6 6.8 2.8 41.4 45.0 9.8 4.6 78.1 9.2 4.0 72.2 8.4 3.6 64.5 68.8 11.6 10.6 4.9 82.4 6.1 9.3 4.2 16.3 6.9 115.5 4.2 69.3 10.7 4.2 72.0 11.3 4.4 72.7 6.4 2.7 45.7 6.4 2.7 49.8 7.2 3.1 55.9 9.0 3.9 71.6 9.6 4.1 79.1 13.5 5.7 105.7 5.2 5.3 2.3 42.2 5.8 2.4 43.9 10.2 10.7 4.6 81.5 110.1 10.8 7.2 6.8 2.7 41.8 6.5 2.7 39.2 5.6 2.3 37.0 2.1 2.2 2.2 35.6 37.5 37.9 11.7 4.7 67.7 10.9 4.4 67.9 10.7 4.4 68.3 9.9 4.1 69.9 9.9 4.0 66.3 10.5 4.3 70.2 9.7 4.2 73.2 5.2 5.4 6.1 17.0 7.2 121.9 40.0 2.8 6.6 6.0 112.0 17.5 7.5 109.9 5.5 85.9 6.8 6.8 135.8 6.1 112.2 19.9 8.7 124.2 8.0 6.8 16.0 6.8 4.3 70.9 MONTHLY LABOR REVIEW April 1989 • Current Labor Statistics: Injury and Illness Data 48. Continued— Occupational injury and illness incidence rates by industry, United States Incidence rates per 100 full-time workers2 Industry and type of case1 1979 1982 1981 1980 1983 1984 1986 1985 1987 Nondurable goods Food and kindred products: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... Tobacco manufacturing: Total cases........................................................................................ Lost workday cases ........................................................................... Lost workdays.................................................................................... Textile mill products: Total cases........................................................................................ Lost workday cases ........................................................................... Lost workdays.................................................................................... Apparel and other textile products: Lost workday cases........................................................................... Lost workdays.................................................................................... Paper and allied products: Lost workday cases........................................................................... Lost workdays.................................................................................... Printing and publishing: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... Chemicals and allied products: Total cases........................................................................................ Lost workday cases............................................-.............................. Lost workdays.................................................................................... Petroleum and coal products: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... Rjbber and miscellaneous plastics products: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.......... ......................................................................... Leaiher and leather products: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... Transportation and public utilities Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays .................................................................................. 8.1 8.2 3.8 45.8 3.9 56.8 7.2 3.2 44.6 6.5 3.0 42.8 9.3 4.2 64.8 9.7 3.4 61.3 9.1 3.3 62.8 8.8 3.2 59.2 6.5 6.4 6.3 34.1 13.5 8.6 8.0 16.7 16.5 17.7 131.6 138.0 137.8 153.7 7.7 3.2 51.7 7.3 3.0 51.7 6.7 2.5 45.6 2.5 46.4 7.5 3.0 57.4 7.8 3.1 59.3 9.0 3.6 65.9 6.7 6.7 2.7 49.4 7.4 3.1 59.5 16.7 8.1 8.1 8.0 8.0 53.8 51.4 3.0 54.0 2.2 6.0 2.1 34.9 35.0 36.4 6.4 2.4 40.6 6.7 2.5 40.9 11.6 10.6 10.0 108.4 12.7 5.8 112.3 5.4 103.6 4.9 99.1 10.4 4.7 93.8 4.7 94.6 10.5 4.7 99.5 5.8 122.3 7.1 3.1 45.1 6.9 3.1 46.5 6.7 3.0 47.4 6.6 2.8 45.7 2.9 44.6 6.5 2.9 46.0 6.3 2.9 49.2 6.5 2.9 50.8 6.7 3.1 55.1 7.7 3.5 54.9 6.8 6.6 3.1 50.3 3.0 48.1 5.7 2.5 39.4 5.5 2.5 42.3 5.3 2.4 40.8 5.1 2.3 38.8 6.3 2.7 49.4 7.0 3.1 58.8 7.7 3.6 62.0 7.2 3.5 59.1 6.7 2.9 51.2 5.3 2.5 46.4 5.5 2.4 46.8 5.1 2.4 53.5 5.1 2.4 49.9 7.1 3.2 67.5 7.3 3.1 65.9 17.1 14.6 7.2 117.4 12.7 13.0 100.9 101.4 13.6 6.4 104.3 13.4 6.3 107.4 14.0 127.1 15.5 7.4 118.6 118.2 15.9 7.6 130.8 11.5 4.9 76.2 11.7 5.0 82.7 11.5 5.1 82.6 9.9 4.5 86.5 4.4 87.3 10.5 4.7 94.4 10.3 4.6 88.3 10.5 4.8 83.4 12.4 5.8 114.5 10.0 9.4 5.5 104.5 9.0 5.3 8.2 8.8 8.6 100.6 8.5 4.9 96.7 4.7 94.9 5.2 105.1 5.0 107.1 8.2 4.8 102.1 8.4 4.9 108.1 7.4 3.2 48.7 7.3 3.1 45.3 7.2 3.1 45.5 7.2 3.1 47.8 7.4 3.3 50.5 7.4 3.2 50.7 7.7 3.3 54.0 7.7 3.4 56.1 2.2 6.0 8.2 5.9 107.0 8.0 3.4 49.0 2.2 7.6 6.0 4.5 90.3 6.6 6.2 10.0 2.6 44.1 10.2 6.6 12.8 8.8 8.2 4.1 59.1 3.9 58.2 7.7 3.6 54.7 7.1 3.4 52.1 7.0 3.2 50.6 7.2 3.5 55.5 7.2 3.5 59.8 7.2 3.6 62.5 7.4 3.7 64.0 7.7 3.1 44.7 7.1 2.9 44.5 7.1 2.9 41.1 7.2 2.9 42.6 7.3 3.0 46.7 7.5 3.2 48.4 7.5 3.1 47.0 7.8 3.2 50.5 7.8 3.3 52.9 1.9 2.0 2.0 2.0 .8 12.2 .8 11.6 1.9 .9 13.6 2.0 .9 13.2 2.0 .9 12.8 2.0 .9 13.3 .9 15.4 .9 17.1 .9 14.3 5.5 2.5 38.1 5.2 2.3 35.8 5.0 2.3 35.9 4.9 2.3 35.8 5.1 2.4 37.0 5.2 2.5 41.1 5.4 45.4 5.3 2.5 43.0 5.5 2.7 45.8 2.1 N = EH = 2.6 number of injuries and illnesses or lost workdays; total hours worked by all employees during calendar year; 2 0 0 ,0 0 0 = base for 100 full-time equivalent workers (working 40 hours per week, 50 weeks per year.) (N /E H ) X 2 0 0 ,0 0 0 96 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 8.6 7.4 1 Total cases include fatalities. 2 The incidence rate represent the number of injuries and illnesses or lost work days per 100 full-time workers and were calculated as: where: 8.6 2.8 Services Total cases........................................................................................ Lost workday cases.............................................. ............................. Lost workdays................................................................................... 16.7 2.8 Finance, insurance, and real estate Total cases........................................................................................ Lost workday cases ........................................................................... Lost workdays.................................................................................... 129.3 18.7 9.0 136.8 Wholesale and retail trade Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... Wholesale trade: Total cases........................................................................................ Lost workday cases ........................................................................... Lost workdays.................................................................................... Retail trade: Total cases........................................................................................ Lost workday cases........................................................................... Lost workdays.................................................................................... 130.7 16.5 7.9 131.2 17.8 19.9 9.5 141.8 3 Excludes farms with fewer than 11 employees since 1976. / Sound > Economics Twelve issues of the Monthly Labor Review for only $20. Analytical articles. Developments in Industrial Relations. Major Agreements Expiring. 48 tables of Current Labor Statistics, Research Summaries. Book Reviews, and much more. , Use the coupon below A to place your order for 1 or 2 years. S< https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Send subscription orders to: O rd er form Please start___ subscriptions to the Monthly Labor Review for □ one year, $20 or. Q two years, $40. Total cost________ □ Enclosed is a check or money order payable to Supenntendent of Documents D Charge to GPO Deposit Account No___________________ Order No-------------- □ Charge to Credit card n o . Name Company name Address City, State. Zip code D Expiration date. 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