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U.S. Department of Labor In this issue Employment in d ay care Health insurance am ong families Fatalities of the self-em ployed Unemployment indicators Incom e inequality Textile and apparel em ploym ent https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis U.S. Department of Labor Robert B. Reich, Secretary Bureau of Labor Statistics Katharine G. Abraham, Commissioner 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) 606-5900. Subscription price per year—-$25 domestic; $31.25 foreign. Single copy—$7 domestic; $8.75 foreign. Subscription prices and distribution policies for the Monthly Labor Review (ISSN 0098-1818) and other Government publications are set by the Government Printing Office, an agency of the U.S. Congress. 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Gaddie Room 221 Federal Building 525 Griffin Street Dallas, TX 75202-5028 Phone: (214) 767-6970 Fax: (214) 767-3720 Region VII Iowa Kansas Missouri Nebraska August cover: "Happy Children," a 1973 cast bronze, by Chaim Gross. Photo courtesy o f the National Museum o f American Art, Smithsonian Institution Cover design by Melvin M oxley https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Region IX American Samoa Arizona California Guam Hawaii Nevada Trust Territory of the Pacific Islands Region VIII Colorado Montana North Dakota South Dakota Utah Wyoming Gunnar Engen Region X Alaska Idaho Oregon Washington Sam M. Hirabayashi 1100 Main St. Suite 600 Kansas City, MO 64105-2112 Phone: (816) 426-2481 Fax: (816) 426-6537 71 Stevenson Street P.O. Box 3766 San Francisco, CA 94119-3766 Phone: (415) 744-6600 Fax:(415)744-7138 M l Table of Contents ■ i j Federal Reserve Bank M st. Quis N T H L Y L A B O REVIEW A ugust 1995 R Volum e 118, N um ber 8 Family matters Editor-in-Chief Deborah P. Klein Boom in day care industry the result of many social changes Executive Editor Richard M. Devens, Jr. Five major factors are responsible for the rapid employment increase in this industry William Goodman Managing Editor Health insurance coverage for families with children Anna Huffman Hill Regardless of incomes, families without coverage are less likely to receive care than are partially insured families Geoffrey D. Paulin and Elizabeth Dietz Editors Brian I. Baker Leslie Brown Joyner Mary K. Rieg Stephen Singer Editorial Assistant Ernestine Patterson Leary Production Manager 3 13 Other articles Self employed individuals fatally injured at work 24 Individuals who work for themselves typically face higher risk of fatalities, compared with their wage and salary counterparts Martin E. Personick and Janice A. Windau Dennis L. Rucker International unemployment indicators, 1983-93 Production Assistants Catherine D. Bowman Phyllis L. Lott Edith W. Peters Catherine A. Stewart Contributors Michael H. Cimini Constance B. DiCesare Charles A. Muhl Polly A. Phipps https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 31 Sweden has the largest increase in labor underutilization when part-time work for economic reasons is taken into account Constance Sorrentino A surge in growing income inequality? 51 A reported surge in income inequality indicates that patterns of employment growth were consistent with greater income dispersion Paul Ryscavage Unraveling employment trends in textiles and apparel 62 These two closely related industries differ in the reasons for their job losses and the prognosis for their future Lauren A. Murray Departments Labor month in review Industrial relations Book reviews Current labor statistics 2 73 77 79 Labor Month in Review The August Review Chamovitz reviews Trade and Labor Stan dards: A Review of the Issues (edited by Gary Job, health, and family are cardinal sources o f well-being for working Americans. The broad demographic, social, and economic changes shaping the family’s involvement in economic life have been covered exten sively in the press, academic journals, and this Review. This month, we examine some more subtle effects of the forces affecting today’s working family. As William Goodman notes in our lead article, “The daily life of schoolchildren has changed dramatically in the last 20 years.” They are much less likely to be directly su pervised by relatives and much more likely to be watched by the employees of the rap idly growing day care industry. Goodman proceeds to weave together the five major factors that have led to a tripling of employ ment in the private day care industry since estimates of its employment were first pub lished by the Bureau in 1972: the growing number o f children, a rising percentage of mothers participating in the labor force, more public spending on child care, tax poli cies providing additional benefits to fami lies, and more widespread corporate and private initiatives to provide day care. In the June Review, we reported on the incidence of and access to health insurance as an employment benefit. In this issue, Geoffrey D. Paulin and Elizabeth M. Dietz rigorously explore the intricate interactions o f employment, income, and health insur ance coverage on health care spending in families with children. Perhaps the most interesting o f these analyses shows that the expenditure on drugs and other medi cal supplies is an important measure of those who “when they become ill ... be com e well faster.” In their econometric analysis, persons in fully and partially in sured families are much more likely to in cur such expenditures, even when all else is held constant. Other articles include Martin E. Personick and Janice A. Windau on fatal inju ries among the self-employed, an interna tional comparison of alternative measures of the underutilization of labor written by Constance Sorrentino, an evaluation of in come inequality and the possible impact of new survey methods on its measurement by 1994 Klein award winner Paul Ryscavage, and Lauren A. Murray’s analysis of trends in textile and apparel jobs. M ichael H. Cimini and Charles J. Muhl present their regular analysis of current developments in industrial relations. Pat Nielsen reviews Why Our Kids D on’t Study: An Economist’s Perspective (by John D. Owen) and Steven 2 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Fields). The new retirem ent The incidence of retirement benefits was fairly stable in the 5-year period from 1989 to 1994, but the form o f benefit shifted sig nificantly, according to the Pension and Welfare Benefits Administration of the U.S. Department o f Labor. In their report, Re tirement Benefits of American Workers: New Findings from the September 1994 Current Population Survey, analysts Dan Beller and Richard Hinz find, “Virtually all retirees receive Social Security benefits after the age of 65 and somewhat less than one-half are able to supplement this income with a pri vate pension benefit.” The most significant change has been in the form in which retirement benefits are received. About 48 percent o f pension re cipients in 1994 received an annuity as part o f their income package, compared with fully 60 percent of recipients in 1989. In 1994, just over half of pension beneficia ries received only a lump-sum distribution. Overall, Social Security and private ben efits are replacing about 60 percent of nomi nal earnings. But, only a small proportion o f annuitants receive cost-of-living adjust ments. As a result, current retirees have a “real replacement rate” of less than one-half the purchasing power of their prior earn ings. “This,” the report concludes, “will re quire them to rely on individual savings or continue to keep working during retirement if they wish to maintain their standard of living.” Em ployee density Four of New York City’s five boroughs are among the 10 counties in the United States with the greatest “employment density” (that is, the number o f persons employed in the county per square mile of county area). Kent Halstead reports in Wages and Cost of Living: 508 County Indexes that Man hattan (New York) is the most dense, with 75,588 employees per square mile, followed by San Francisco (California) with a den sity of 9,760 employees. The other “dense” counties are Boston (Massachusetts), 7,457; Washington (District of Columbia), 5,893; Brooklyn (New York), 5,167; Bronx (New York), 4,053; Philadelphia (Pennsylvania), 3,999; Baltimore (Maryland), 3,998; Jersey City (New Jersey), 3,885; and Queens (New York), 3,667. C yc lic a l loss vs. regional growth Differences in net job growth across States are caused by variations in their rate of job creation, while fluctuations in employment over the business cycle are associated with variations in the rate of job destruction. This is the central finding o f Cyclical Versus Secular Movements in Employment Cre ation and Destruction ( n b e r Working Pa per No. 5162) by Randall W. Eberts and Ed ward Montgomery. Because the State-to-State pattern of net job dynamics is so different from the struc ture o f cy clica l em ploym ent variation, Eberts and Montgomery warn that policy makers should be cautious in applying cy clical models to regional issues. Specifi cally, they suggest that “promoting new firm creation and expansion might be more fruit ful in the long run” for local economies be cause their em ployment differences are driven by differences in rates of job cre ation. But, they note, “Clearly, definitive policy recommendations must await a more structural analysis o f the determinants of job creation and destruction.” Fewer J ap an ese businesses According to the June 1995 Japan Labor Bulletin, a recent survey o f Japanese busi nesses found that both the number of estab lishments and the count of employees work ing for them dropped below the levels reported in the previous survey (1991). “This clearly indicates that the adverse ef fects of the economic slowdown following the bursting of the financial bubble are enor mous. It was the first such drop since 1947 when the survey was originated.” In April 1994, there were about 6.55 million privatesector firms in operation, a drop o f 0.2 per cent from the 1991 survey. The total num ber of employees at these firms was 54,366 million in 1994, a decrease o f 1.2 percent from the earlier survey. Next month Next month’s Review will feature articles on earnings mobility, how the intermittent labor force affects women’s earnings, em ployment in the security brokers and deal ers industry, trends in unemployment insur ance benefits, and a discussion of the old and new measures o f educational attain ment in the Current Population Survey. □ Employment in Day Care Boom in d ay care industry the result of m any social changes The number of employees in the day care industry has increased at a much faster rate than working mothers; five major factors are responsible William Goodman he daily life of preschool children in the United States has changed dramatically in the last 20 years. Because mothers of young children are far more likely to work than at any other time in the past, mother and child now spend much less time at home.1 Further more, far more relatives—particularly women— also are employed, and have less time to spend with nephews, nieces, young cousins, and grand children. For these and other reasons, young chil dren are more likely to attend day care centers. During the 2 decades, employment in private-sector day care centers increased by more than 250 percent, gaining nearly 400,000jobs and continu ing to grow during two of the four recessions in the period. No single factor influencing the day care industry and examined here has increased as has employment in the industry. Instead, a combination of at least five major factors drives demand for the services of child-care centers. T Trends in day care jobs William G o o d m a n is an econom ist in th e O ffic e o f Em ploym ent a n d U nem ploym ent Statistics, Bureau of Labor Statistics. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Employment growth in the day care industry since 1972 has been much more rapid than the growth of most industries: overall, the number of day care jobs has grown by approximately 250 percent, or 375,000 jobs. Growth occurred almost through out the 22-year period, except for the early 1980’s, during which two back-to-back recessions oc curred. From early 1979 to summer of 1982, 30,000 jobs were lost in day care. Renewed growth from fall 1982 to mid-1985 expanded the number of jobs to above the preceding peak, and strong growth has since continued. Unlike most industries, child day care continued to expand vig orously during the recessions of 1973-75 and 1990-91. Explanations for these movements, in cluding the seemingly inconsistent behavior in the various recessions, are discussed below. Causes of growth One way to begin an analysis of employment growth in day care is to distinguish between growth attributable to greater enrollment and the effects of changes in the ratio of enrolled children to staff. Fewer children per staff member generally improve the quality of care. Consistent, regularly timed estimates of the ratio of children to staff are not available. But one publication calculates that the average ratio of children to caregivers and teachers in full-time centers (7 hours a day or more) increased considerably, from 6.8 to 8.5 children per worker, between 1976 and 1990.2 Because a staff member supervised more children in 1990, the change in the ratio pushed down employment. If the ratio had remained unchanged, employment in 1990 would have been greater by M o n th ly Labor R e v ie w A u g u s t 1995 3 Em ploym ent in D ay Care S cope of study This article primarily relies on estimates of employment in day care establishments from the Bureau of Labor Sta tistics monthly survey of employers. These statistics are from the Current Employment Statistics program of b l s . The c e s program produces estimates of employees on all nonfarm payrolls except in private households, based on a monthly survey of about 390,000 work sites. Data from the survey appear in the monthly b l s peri odical Employment and Earnings, c e s data in this article are seasonally adjusted unless otherwise indicated. For purposes of the survey, this article uses the Federal Office of Management and Budget’s Standard Industrial Classification Manual’s definition of the child day care industry, which includes private-sector “establishments primarily engaged in the care of infants or children, or in providing pre-kindergarten education, where medical care or delinquency correction is not a major element.” Including the education of the very young is appropriate, because a definite line between care and education cannot be drawn; many day care centers include education in their programs, and in earliest childhood, play and learning cannot be distinguished clearly. This definition of the day care industry includes large and small companies doing business for profit or for other purposes, such as social good. Secular and religious non profit organizations and for-profit companies are included. However, a few significant exclusions apply. Govern ment day care— for example, day care centers within pub lic school systems, or those provided by government agen cies for employees—is not included in the child day care 110,000 in full-time centers alone. Because fewer staff members now handle the same num ber of children, enrollment increases must account for the employment of larger numbers of teachers and child care workers in the industry. Consistent measures of total enroll ment of children in day care, at regularly timed intervals, also are not available.3 However, an abundance of indirect evidence indicates tremendous growth in enrollment. In ad dition, one source concludes that enrollment in full-time early education and care increased from 900,000 children in the mid-1970’s to 3.8 million in 1990.4 Why enrollment grew Several factors caused the growth in enrollment. Although an increase in the population of children is the most obvious cause, growth in the proportion of children who are in day 4 M onthly Labor Review August 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis industry data presented in this article, unless a separate, private organization performs the work of the center. In addition, if day care is provided onsite directly by an em ployer for its own employees’ children, without the use of a contractor but as a company-owned operation, the day care personnel are not included. When care of children is offered by an individual at their own residence, without the use of any employees, the provider is not counted, as the survey measures only employment on payrolls rather than self-employed workers. Nannies and, in fact, all do mestic workers also are excluded from the survey. Because of the various exclusions, the estimates being studied do not represent all child care workers in the coun try. Trends in Government day care, child care provided by employers for their employees’ children, care by do mestic workers in the child’s home, and care by entrepre neurs working in their own homes may not be exactly the same as the trends of private-sector day care centers. But an abundance of anecdotal evidence suggests that day care provided directly by employers for their own employees’ children is growing fast. Employment in the day care industry as estimated from the survey includes not only employees directly caring for children but all employees of day care companies. Ac cording to the b l s Occupational Employment Survey, 8 percent of the child care industry’s employees are manag ers or administrators, 15 percent are clerical workers, 33 percent are teachers, and 25 percent are child care work ers. The remaining 19 percent are widely scattered among a variety of other occupations. care programs has had much more influence. The increas ing percentage of children in day care reflects large gains in the number of their mothers who have jobs. U.S. population of youngsters. In 1990, children 3 to 5 years old accounted for 52 percent of day care enrollment; children under 6 accounted for 74 percent.5 (See table 1.) While the growth in the populations of these age groups has been gradual, at 1 to 3 percent annually, the aggregate growth of children younger than 6 from 1972 to 1994 has been 3 million. (See table 2 and chart 1.) The number of 3-to-5year-olds increased by 1.6 million.6 If the ratio of day care center employees to all children under 6 is held constant at the 1972 rate, the increase in the population of youngsters under 6 implies relatively slight growth in employment: 22,000 day care employees, or just 6 percent of actual growth. Clearly, changes in these popula tions are only a minor factor in the expansion of the industry. Evidently, additional factors strongly affect demand. Changes in the family. Children of working mothers are en rolled in centers as a primary arrangement for care nearly twice as frequently as children of mothers without jobs. As of 1990, if school is excluded as a child care arrangement, 17 percent of children younger than 13 with employed mothers were enrolled in a center as their primary arrangement; among children under 13 with mothers who did not hold jobs, 9 percent were enrolled in centers as a primary arrange ment.7 The number and proportion of women at work have increased greatly in the last 20 years, rising from 41 percent in 1972 to 54 percent in 1993.8 (See table 2 and chart 1.) The proportion of working mothers of children under 6 rose by an even greater percentage: from 33 percent in 1975 to 53 percent in 1993. Mothers of children under 3 also greatly increased their participation in employment, from 28 per cent in 1975 to 49 percent in 1993. (See table 1.) In 1975, 16 percent of mothers with children under 6 did not have a spouse in the household; in 1993, that proportion increased to 26 percent.9 One might expect that the absence of a working husband from the household would be a major explanation of why more mothers of young children are at work, but mothers with a husband in the household increased their jobholding far more. Between mothers of young chil dren who had husbands with them and those who did not, the percentages at work were fairly close in the mid-1970’s; but women with spouses present increased considerably in percentage employed, while those without spouses present increased only slightly in percent employed. Exact percent ages, derived from Current Population Survey data, are shown in the following tabulation: 1975 1993 children10 become unavailable as a greater percentage of the population becomes employed. From 1972 to 1993, the over all employment-to-population ratio increased from 57.0 per cent to 61.6 percent. Although the employment-to-popula tion ratio of men decreased by 5 percent, the ratio among women increased by 13 percentage points to 54.1 percent. At the start of the latest post-recession period, from early 1991 to the end of 1993, job growth among women was great est among 45-to-54-year-olds. Seventy-two percent of women in that age range were employed at the end of the period11— implying that a great many grandmothers and older aunts are not available as they once were to watch children during the day. While comprehensive, clear statistics are not available to show a shift from care by relatives to care in centers among all children, the Census Bureau has estimated use of various child-care arrangements by families with working mothers and children under 5 in various years. The results indicate that from 1977 to 1991, use of child care centers increased by 10 percentage points, from 13 percent of such families to 23 percent. Care by relatives other than parents dropped the most, from 31 percent to 24 percent. In addition, 1991 results appear to have been influenced by the recession and the continued post-recession decline in employment. An abnormally large number of laid-off rela tives may have been temporarily available to care for chil dren in 1991. Results from 1990, when employment was not so abnormally depressed, may better typify the 1990’s. In deed, 1990 shows more care in centers and less care by rela tives than in 1991. From 1977 to 1990, care in centers more than doubled, increasing from 13 percent to 28 percent, as opposed to 23 percent in 1991. The following tabulation shows the primary child care arrangement in families with children under age 5 and a working mother in selected years (in percent):12 1977 1985 1990 1991 Mothers of children under age 6: With spouse in household..................... Without spouse in household................. 32 42 56 44 Mothers of children aged 3 to 5: With spouse in household..................... Without spouse in household................ 37 49 60 55 Changes in needs and preferences that caused more of these mothers to go to work affected the group with a husband in the household far more than those without a husband. The group with a spouse present also is much larger. Women who live with their husbands, therefore, made the far heavier contribution to the increased employment of mothers of young children. The number of working women in general also is impor tant as a factor in the demand for child care: not only moth ers but also other relatives who might be available to watch https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Child cared for by— Father............................................. Relative other than parent....... Nonrelative in child’s h o m e .... Nonrelative in another home .... Organized fa c ility ...................... Mother at work............................ 14 31 7 22 13 11 16 24 6 22 23 8 17 23 5 20 28 6 20 24 5 18 23 9 The drop in care by nonrelatives in the child’s home is confirmed by the household survey’s estimate of child care workers in children’s homes. This estimate shows a 37-percent drop, representing a reduction of 200,000 workers from 1972 to 1993. The reduced use of child care workers in the parents’ home is related to increasing demand for the ser vices of centers, but the relationship between the two trends is not clear. The greater availability of child care centers may decrease the need for household workers. Alternately, M onthly Labor Review August 1995 5 Em ploym ent in Day C are household workers may be less desired by families than in the past. Or, with much larger proportions of women enter ing occupations in the executive, administrative, managerial, and professional specialty categories,13 a smaller proportion of women may be available for lower paying jobs, so house hold help may be harder to find. Factors relating to cost and convenience After 13 years of fairly steady and strong growth, the number of working mothers with children under age 6, and those of children from 3 to 5, seems to have about leveled off in the 1990’s.14 But the number of day care workers continued to increase about as steeply as ever. (See chart 1.) Contrasting trends also occurred in an earlier period: from 1979 to 1982, as the number of working mothers increased sharply, the number of day care workers declined. These contrasts indi cate that other factors have important effects on the number of day care workers. Certain developments have, in effect, lowered the price of day care, making it more practical for some mothers of young children to work outside the home. As a result, more young mothers may have started working.15 In addition, among working mothers and those who remain at home, these de velopments also may have increased the popularity of day care centers relative to other available child care arrange ments. Government funding. Several large Federal programs pay billions of dollars for the care and education of young chil dren outside the home, and in some large programs, the funds have increased greatly in recent years. The four largest Fed eral programs in this area totaled more than $5 billion in fiscal year 1994. Project Head Start is the most heavily funded of these pro Table 1. grams, with 1994 appropriations of $3.3 billion. Local em ployment in Head Start is largely in the private sector be cause the program funds local private organizations and lo cal government agencies that perform the work. Head Start is intended to provide comprehensive care for poor or dis abled children. Although the project began in 1965, the Con gress increased funding substantially in 1990 and continued to increase it greatly in each subsequent year through 1994. (See table 2.) Chart 2 compares the program’s appropria tions with growth in private-sector child care jobs. In addition to Head Start, Federal spending was increased significantly for young children in 1990 when, for the first time, comprehensive legislation regarding child care was passed. As in Project Head Start, Federal funds in other major programs are ultimately used to a great extent to pay for the services of private child-care organizations. The Child Care and Development Block Grant, which began in 1990, pro vides funds to the States for care of the children of poor fami lies and to improve the quality of care. Approximately $2.5 billion was appropriated for the first 3 years, and, in 1993, the fiscal-year funding rose from $825 million to $893 mil lion. Funding remained at that level in 1994. The “At-Risk” Child Care Program also was created in 1990. It is designed to provide care for children of families “at-risk” of becoming welfare recipients. States must pro vide matching funds to receive Federal money, which so far has been available at $300 million annually. The Family Support Act Child Care Programs started slightly earlier, in 1988. The Federal government distributes money to the States to provide child care for the children of parents receiving Aid to Families With Dependent Children benefits and working, looking for work, or in approved edu cation or training programs, as provided in the Job Opportu nities and Basic Skills ( j o b s ) program. The Family Support Act also provides funds for care of the children of parents Selected factors affecting demand for day care, by age group (In percent) Age group Under 3 ........................................... 3 to 5 ............................................. Under 6 ........................................... 6 to 9 ............................................... Under 1 0 ......................................... Resident U.S. population, 1994 (thousands)’ 11,705 11,906 23,611 14,975 38,586 Percent growth in population, 1972-94’ 17.2 15.8 16.5 -3.0 8.2 ’ Data are from the U.S. Bureau of the Census p p l -21 document. 2 Calculated from percentages In National Child Care Survey, 1990, p. 31, and up-to-date population weights. Calculated from percentages in preceding column and up-to-date popula tion weights. M onthly Labor Review A ugust 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Use of day care centers as primary arrangement, 19902 (percent) 12.0 29.1 20.6 9.1 15.9 Mothers who were em ployed4 Age group’s enrollment as a percentage of total d ay care enrollment, 19903 22 52 74 21 96 1975 28.3 539.6 33.2 49.0 558.3 52.3 — — — — * Data are from the Current Population Survey. These mothers had no children under the age of 3. N ote: Dash indicates data are not available. 1993 Employment in child day care services and related data Year Employment in child day care Industry (thousands) Population under 6 years old ¿¿thousands) Ratio of em ployed women to all women (percent) Working mothers of children under 6 (thousands) Working mothers of children under 6 (percent) Enrollment in Project Head Start (thousands) 1972.................................. 1973.................................. 1974.................................. 1975 .................................. 1976.................................. 145.5 151.0 172.0 198.9 214.6 20,570 20,248 19,937 19,667 19,251 41.0 42.0 42.6 42.0 43.2 4,851 4,957 33 35 379 379 353 349 349 1977.................................. 1978.................................. 1979.................................. 1980.................................. 1981 .................................. 245.2 284.8 303.1 298.9 289.8 18,898 18,891 19,155 19,631 20,022 44.5 46.4 47.5 47.7 48.0 4,887 5,297 5,594 5,886 6,227 36 39 41 42 44 333 391 388 376 387 1982.................................. 1983.................................. 1984.................................. 1985.................................. 1986.................................. 282.4 283.8 291.7 310.0 321.9 20,502 20,843 21,092 21,360 21,531 47.7 48.0 49.5 50.4 51.4 6,414 6,489 7,043 7,322 7,602 43 43 46 48 48 396 415 442 452 452 1987.................................. 1988 .................................. 1989.................................. 1990.................................. 1991 ................................. 333.4 356.3 378.4 391.4 417.2 21,662 21,822 22,067 22,528 22,897 52.5 53.4 54.3 54.3 53.7 8,137 8,104 8,478 8,732 8,758 51 51 53 54 53 447 448 451 541 583 1992.................................. 1993.................................. 1994.................................. 450.8 473.4 501.9 23,224 23,479 23,611 53.8 54.1 — 8,662 8,764 — 53 53 — 621 714 — N ote : — — — — Dash indicates data are not available or are not comparable. who have increased their earnings and have been able to leave the a f d c program in the past year. Funds for these Family Support Act programs nearly doubled from fiscal year 1992 to fiscal 1994, when $745 million was available. In addition to Federal initiatives, State and local govern ments provide many child care programs. The level of spend ing per child varies greatly by State.16 In addition to pro grams for poor children and others, State governments fre quently fund onsite day care for the children of public em ployees by setting up a private, not-for-profit corporation that operates the center rent-free.17 As State governments receive more Federal funds, their revenue may be made available for other purposes. Con versely, when Federal aid to States and localities is cut, the State or local government may find it necessary to reallocate funds from another area of spending. The curve on chart 2, which represents the number of employees in the day care industry, shows a decline in the early 1980’s, when two re cessions occurred, even though two other recessions, one in the mid-1970’s and another in the early 1990’s, had no ap parent effect on day care employment, which continued to grow vigorously. Federal outlays for education, training, employment, and social services, adjusted for inflation, represents the first re https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis lated statistic examined so far that may explain why em ployment in the industry dropped in the early 1980’s but not during the other recessions. As shown in chart 2, social spending was cut deeply in Federal budgets in the early 1980’s, while this broad category of Federal spending de clined less during the recession of the mid-1970’s and actu ally increased during the 1990-91 recession. As increases in such Federal spending occurred from 1975 to 1979 and again from 1987 to 1993, day care expanded at a pace greater than the growth rate in the number of children or of jobs held by their mothers. Tax breaks. In addition to explicit Federal spending, several U.S. tax provisions help bring day care in reach of many families. Perhaps the most important tax change was the initiation and expansion of the Earned Income Credit, which began in 1975 and was increased to a major extent in 1990 and again in 1993. Although a small amount of this credit can be claimed by low-income taxpayers with no children, it benefits primarily lower-income families with children. A credit of up to about $2,500 goes to taxpayers with earnings of $11,000 or less. The Earned Income Credit is different among such credits because when the amount claimed by a taxpayer exceeds the income tax liability, he or she is reimM onthly Labor Review August 1995 7 E m ploym ent in Day Care bursed for the balance. The total amount claimed each year under this credit has increased more than five-fold since 1975, even after inflation, partially because of numerous re visions in the applicable tax rules, particularly in 1987, 1990, and 1993. (See chart 2.) While the credit does not specifically provide for day care, the credit is often cited in literature concerning the financing of the care of young children. Low-income families use day care facilities; among children in families below the poverty line in which the mother works, 18 percent attended orga nized day care facilities in 1991.18 The Dependent Care Tax Credit benefits primarily a more middle-income group of families; in 1992, this credit was claimed to the greatest extent by families with incomes be tween $20,000 and $50,000. The credit can be claimed for expenses incurred for the care of dependents if the care is necessary for the taxpayer to be employed. After adjustment for inflation, the annual amount claimed by taxpayers about tripled from 1976 to 1988 In 1988, tax law changes re moved credit for the care of children over 13 and reduced the amount of expenses that could be claimed; the aggregate an nual amount claimed by taxpayers suddenly dropped and re mained at roughly the same level through 1994, according to projections. But the amount claimed in 1994 was still 85 percent above the 1976 level after adjustment for inflation.19 (See chart 2.) Since 1981, certain employer-provided dependent care has been excluded from an employee’s gross income for Federal income tax purposes. Such dependent care may be provided in the form of on-site or nearby child care facilities, reim bursement of employees for child care expenses, or reimburse ment accounts that are also usable for other nontaxable em ployee benefits. Many employers offer such benefits; in 1993, 40 percent of full-time employees of medium and large pri vate establishments were eligible for reimbursement accounts that could be used for dependent care.20 Private initiatives. Corporate and nonprofit organizations have made significant efforts to provide day care. The orga nizations represent a diverse group, including major corpo rations and religious and other nonprofit organizations. Employers sometimes operate their own day care centers for employees and in other cases contract with a for-profit or nonprofit child care organization. In at least a few cases, the service also is made available to nonemployee community members. Other companies reimburse parents’ expenditures on day care or arrange discounts. Consortiums of employ ers, in some cases also including labor unions, have started Employment in day care industry far outpaces factors influencing dem and for child care (Percent change in employment In day care industry and in selected factors affecting demand for child care, 1975-94.) Percent of Percent of 0 1975 1977 0 1979 1981 1983 1985 1987 1989 1991 1994 NOTE: Shaded areas denote recession from peak to trough, as defined by the National Bureau of Economic Research Inc. SOURCES: Current Employment Statistics program; Current Population Survey; and Bureau of the Census P-25 series of publications. 8 FRASER M onthly Labor Review A ugust 1995 Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis day care centers that are located near several places of work.21 day care industry in which employment has grown even faster than in the segments included in the establishment surveys. Cost effects From 1983 to 1993, the household survey measure of day The average hourly pay in 1994 for production or care employment more than doubled, gaining 465,000 jobs, nonsupervisory employees was $ 11.12 for the private sector and or 1 1 0 percent; the b l s establishment survey showed a gain $6.83 in the day care industry. From 1972 to 1994, average of 67 percent during the period. hourly pay of workers in the industry, excluding managers, The household survey estimates of employees in the day adjusted for inflation, declined by 10 percent.22 The cost of care industry include government employees, self-employed labor in day care centers is relatively inexpensive and has workers, and private-sector wage and salary workers. (The become less expensive over the years. two surveys of employers include only private-sector wage Despite the drop in real earnings of day care workers, the and salary workers.) Including these additional workers par price of day care to consumers, as estimated in the consumer tially explains the differences in numbers of employees, but price index, rose more rapidly than general inflation in the last the household survey’s estimates of private wage and salary few years. An index of day care prices was first produced for a workers in the day care industry are larger and faster grow complete year in 1990. From 1990 to 1994, day care prices ing than those of the b l s establishment survey. rose by 20 percent while overall consumer prices for all urban One reason for the differences in initial level and trend is consumers rose by only 13 percent. Tax breaks and govern related to the surveys’ different methods of determining the ment and private day care programs, which deliver care at a industry classification of workers. In the household survey, below-market price as in Project Head Start, reduce costs to the classification is based on individuals’ descriptions of their parents and partially account for the huge growth in day care workplaces. Many large employers in industries other than use despite the relatively rapid inflation in the industry. The day care provide onsite centers as a convenience to their em comparatively low cost of employing day care workers also ployees. The household survey assigns the day care workers helps explain the rapid growth of jobs in the industry. at such onsite centers to the day care industry if the workers themselves describe their workplace as a day care center. In Other surveys the establishment survey, if the day care workers are directly As previously mentioned, estimates of employment from the on the payroll of the main establishment, rather than that of monthly b l s survey of employers are used in this article as a separate organization, they are assigned to the main indus the primary measure of growth in employment. One advan try classification of the entire establishment. tage of this series of estimates is its relatively long history, The household survey also offers estimates of employment starting in 1972 and continuing into mid-1995. Estimates by occupation, including child care workers outside of pri from other relevant sources are available; in most cases, they vate households and, separately, child care workers in the differ in their scope and trend. child’s home. (These categories do not include all workers The Bureau of the Census estimates employment by in who supervise pre-school children; many employees of cen dustry, based on various Census Bureau sources.23 Day care ters are pre-kindergarten teachers, a category not distinguish services were first estimated in this program in 1988, and able in the survey from kindergarten teachers and therefore estimates for the industry have been produced up to reference not usable for our immediate purposes.) From 1972 to 1993, year 1992. Census Bureau estimates, like those from the b l s individuals employed in the occupation of child care worker survey of employers, are based on the definition of a day care not in the child’s residence increased from 358,000 to 1 mil establishment quoted earlier and exclude Government estab lion. (The trends of child care workers employed in the lishments from the sector. Over the 4-year span, this series, child’s home were discussed in an earlier section, in connec like the b l s survey of employers, shows growth, but not as tion with changes in the family.) much growth. Over the 1988-92 period, the Census Bureau All the surveys show substantial increases in the day care program indicates a gain of 55,000 employees, or 15 per center industry or portions of it. Rates of growth range from cent; the b l s series shows an increase of 27 percent. 4 percent a year, in the case of the Census Bureau data, to 8 The Current Population Survey ( c p s ) 24 of households also percent a year in the case of the broad industry series from estimates employment in the child day care industry, beginning the household survey. The b l s establishment survey’s indus in 1983. However, the c p s (household survey) definition of try estimates, which are the primary source of employment child day care is broader than that of the two employer data for purposes of this article, increased by 6 percent annu (establishment) surveys. The initial level of employment from ally, on average, from 1972 to 1994. the household survey was 418,000 in 1983, while the b l s Outlook establishment survey showed employment of 284,000. The household survey apparently includes segments of the Recently, the population of children has not only increased https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review A ugust 1995 9 Em ploym ent in Day Care Employment in day care industry far outpaces factors influencing dem and for child care. (Percent change in employment in day care industry and in selected factors affecting demand for child care. 1975-94) Percent of Percent of SOURCES: BLS Current Employment Statistics program and U.S. Department of Health and Human Services. NOTE: Shaded areas denote recessions from peak to trough, as defined by the National Bureau of Economic Research Inc. SOURCES: U.S. Office of Management and Budget and BLS Current Employment Statistics program. Dollars, in minions, Amounts claimed for Federal Earned Income tax credits Dollars, in millions, NOTES: Amounts for the Earned Income Credit are projected In 1992-96 and are preliminary in 1991. The Dependent Care Tax Credit amounts for 1991 and 1992 are preliminary, and amounts for 1993 and 1994 are projected. Dollars are deflated by the CPI-U, base period 1982-84. SOURCE: Joint Congressional Committee on Taxation. M onthly Labor Review August 1995 Digitized for10 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis but also accelerated in growth. Although future trends of most of the forces that have driven employment in the indus try cannot be predicted with confidence, extensive popula tion projections are available from the Bureau of the Census. These projections show a pattern of deceleration followed by decline in the population of young children: Time period Percent change in population 3 to 5 years old 1983-88 ............................ 1988-93............................ 1993-98............................ 1998-2003.......................... 6.2 7.7 4.8 -2 .9 Under 6 years old 4.7 7.6 .1 -2.1 As can be seen, the recent relatively strong gains in the most relevant age groups are forecast to decelerate by 1998; these populations will fall by 2003. While final Federal budget figures for fiscal year 1996 and later are not yet available, increases in Federal child care spending from 1994 to 1995 is expected to slow. Fed eral child-care spending on certain major programs jumped by 84 percent in 1991 after expansion of the jobs Child Care, Transitional Child Care, and Head Start programs, and cre ation of the “At-Risk” programs and the Child Care and De velopment Block Grants. Since then, the combined funding of these programs and Project Head Start has been increas ing by about 20 percent annually. But in 1995, their com bined funding is to grow by only 3 percent. Amounts claimed under the Federal Earned Income Credit are projected to grow vastly, by 89 percent, from 1993 to 1996. But even this growth represents a slight deceleration, as the amount claimed increased by 91 percent from 1990 to 1993.25 These developments suggest deceleration in day care em ployment. The eventual decrease in the population of young children suggests a greater deceleration or decline in em ployment in the industry. Although the percentage of work ing mothers of young children has leveled off in the last few years, projections do not exist. In s u m , the number of workers in the private day care indus try has more than doubled since its employment was first estimated in 1972, increasing by nearly 400,000 jobs. The industry has been influenced by the increasing population of children; the dramatically climbing percentage of job hold ers among mothers of young children, and among other women; Federal, State, and local government spending on child care; increased Federal tax breaks for families with children; and many private initiatives to provide needed day care. But at least two of these factors will not continue to increase so rapidly. Federal spending on certain major child care programs is to decelerate from fiscal 1994 to fiscal 1995, although it may possibly later accelerate. Growth in the U.S. population of young children will decelerate in the next 5 years, and this population will start to decline by 2003. As a result, the industry is unlikely to sustain the rapid growth it has experienced since 1972. □ Footnotes 1 See Howard V. Hayghe, “Are women leaving the labor force?” Monthly Labor Review, July 1994, pp. 37-39. 2 Ellen Eliason Kisker, Sandra L. Hofferth, Deborah A. Phillips, and Eliza beth Farquhar, A Profile of Child Care Settings: Early Education and Care in 1990 (Princeton, n j , Mathematica Policy Research, Inc., 1991), vol. I, p, 212. 3 Comparable estimates o f total enrollees in day care for considerably separated points in time will soon be available. The National Center for Education Statistics of the U.S. Department of Education is conducting the 1995 National Household Education Survey, which, like the 1991 and 1993 surveys o f that name, will generate an estimate of national enrollment in day care, and many other statistics relevant to early learning. 4 Kisker, Hofferth, Phillips, and Farquhar, A Profile of Child Care Set tings, vol. I, p. 208. 5 Sandra L. Hofferth, April Brayfield, Sharon Deich, and Pamela Holcomb, National Child Care Survey, 1990 (Washington, The Urban Insti tute Press, 1991), p. 31. 6 Population figures in this article are from the Bureau of the Census P-25 series o f publications and PPL-21. 7National Child Care Survey, 1990, p.29. 8 Statistics on working mothers in this article are from the Current Popu lation Survey. Results for time periods after 1993 are not comparable to earlier results because o f changes in methodology and population weights used. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 9 Data from the Current Population Survey. 10 Donald J. Hernandez and David E. Myers, “Family Composition, Par ents’ Work, and the Need for Child Care among Preschool Children: 19401987,” Paper presented at annual meeting of the Population Association o f America, New Orleans, 1987, p. 5. 11 Data from the Current Population Survey. Data after 1993 are not comparable to earlier data because o f changes in methodology and popula tion weights. 12 Lynne M. Casper, Mary Hawkins, and Martin O ’Connell, Who’s Mind ing the Kids? Child Care Arrangements, Fall 1991 (Washington, U.S. De partment of Commerce, Bureau of the Census, 1994), pp. 6, 7. 13 From Current Population Survey data. 14 For further information, see Hayghe, “Are women leaving the labor force?” pp. 37-39. 15 Jonathan R. Veum and Philip M. Gleason, “Child care: arrangements and costs,” Monthly Labor Review, October 1991, p. 14. 16Information on Federal and other government programs from The State of America’s Children Yearbook (Washington, Children’s Defense Fund, 1994), pp. 29-32, The State of America’s Children 1992 (Children’s Defense Fund, 1992), pp. 15-22, and Child Care and Development Key Facts (Children’s Defense Fund, 1994), pp. 13-17. 17 Barbara Adolph, “Work and family benefits come of age,” Government M on th ly Labor Review August 1995 11 Em ploym ent in Day Care Finance Review (October 1992), p. 46. 18 Casper, Hawkins, and O’Connell, Who ’s Minding the Kids? p. 14. 19 U.S. House Ways and Means Committee, Overview of Entitlement Pro grams (Washington, U.S. Government Printing Office, 1994), pp. 705-7. 20Employee Benefits in Medium and Large Private Establishments, 1993, Bulletin 2456 (Bureau o f Labor Statistics, November 1994), pp. 5-6. 21The State of America’s Children 1992, pp. 23, 24; Child Care and De velopment Key Facts, pp. 17-19; and Barri Bronston, “Child Care is Part of the Job,” The Times-Picayune (New Orleans, la , June 14, 1993), p. C l. 23County Business Patterns, U .S. G overnm ent Printing O ffice, Washington, annually. 24 The Current Population Survey produces estimates o f all civilian employment and unemployment, and other demographic estimates, based on a monthly survey o f 60,000 households. Results o f the survey appear in Employment and Earnings. R esults for periods after 1993 are not comparable to earlier results because o f changes in m ethodology and population weights used. 25 Figures from U.S. House Ways and Means Committee, Overview of Entitlement Programs (Washington, U.S. Government Printing O ffice, 1994), p. 704. 22From ces data. Where are you publishing your research? The Monthly Labor Review will consider for publication studies of the labor force, labor-management relations, business conditions, industry productivity, compensation, occupational safety and health, demographic trends, and other economic developments. Papers should be factual and analytical, not polemical in tone. Potential articles should be submitted to: Editor-in-Chief, Monthly Labor Review, Bureau of Labor Statistics, Washington, DC 20212-0001. 12 M onthly Labor Review A ugust 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Family Health C overage Health insurance co verag e for families with children Findings from Consumer Expenditure Survey show that families without health insurance are less likely to receive some kinds of care than families who are at least partially insured, even when income and other characteristics are held constant Geoffrey D. Paulin and Elizabeth M. Dietz G eo ffrey D. Paulin is an eco no m ist in th e Division o f Consumer Expenditure Surveys, a n d Elizabeth M. Dietz is an econom ist in th e Division o f O c c u p a tional Pay a n d Em ployee Benefit Levels, Bureau o f Labor Statistics. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis ealth insurance coverage is an impor tant ingredient in the maintenance of good health. This is particularly true for families with children. According to Peter J. Cunningham and Alan C. Monheit, children in families without health insurance coverage are “at a disadvantage regarding access to, quality of, and continuity of health care.”1Judith D. Kasper finds that uninsured children under 18 are less likely to see a physician at least once during the past year, and are less likely to visit a physician for an immunization or general check up.2 Such regular, preventive medical care is es pecially important for children who, in general, are more prone to illness than adults. Without preventive care, families may face large medical expenses as their children grow up. Additionally, health care costs have risen sub stantially in recent years. Data from the Con sumer Price Index show that the price of medi cal care has risen at a much higher rate than for all other goods and services. From 1989-94, the medical care index increased 41.3 percent, com pared with 18.2 percent for all items less medi cal care. In 1993, the Nation’s health care costs rose to $884.2 billion, up 7.8 percent from 1992.3 A recent article by Geoffrey D. Paulin and Wolf D. Weber suggests that as a result of these large increases, the direct costs of funding health care have been shifting from business and govern ment to families, thus affecting their expendi tures for nonhealth items.4 Meanwhile, in 1992, more than 8 million American children under age 18 had no health H insurance coverage of any kind.5 While many of the poorest families receive health insurance in the form of government-provided medicaid ben efits6 the percentage of children without public or private health insurance coverage grew by more than 40 percent between 1977 and 1987.7 This study identifies families with children that have full health insurance coverage, partial coverage, and no coverage. It examines the de mographic characteristics of each insurance group, types of policies held, health care expen diture patterns for each group, and the relation ship between the family’s demographics and the probability of being in a particular “coverage group.” Background. According to Gloria J. Bazzoli,8 studies examining the health insurance status of individuals in an attempt to measure medical indigence have generally defined medical indi gence as the “lack of public or private health insurance coverage. The rationale behind this definition is that the uninsured are entirely re sponsible for their own medical expenses. If they experience a costly illness, they are less likely to be able to afford necessary treatment than simi larly ill individuals with insurance coverage.”9 Bazzoli also describes a study in which the au thor examines “underinsurance,” a status that “depends upon the probability that an individual will experience large out-of-pocket expenses due to a costly illness.”10 In a subsequent study, Richard D. Miller11 uses data from the 1987 Consumer Expenditure M onthly Labor Review August 1995 13 Family Health C o ve ra g e Interview Survey to identify medically uninsured consumer units12 rather than uninsured individuals. Miller uses a bino mial logit model to estimate the relationships between vari ous independent variables and the probability that a family has inadequate coverage—that is, the probability of having at least one member of the consumer unit who lacks health insurance coverage. A later paper by Elizabeth M. Reise,13 which examines only families with children, divides the sample into three groups: those with full health insurance coverage (that is, all members are covered), partial health insurance coverage (that is, at least one, but not all, members are covered) and no health insurance coverage (that is, no member is cov ered). Reise uses an ordered multinomial logit to examine the probability of being in each group. Reise’s paper is im portant because it distinguishes between those families with no (or at most very limited) health insurance coverage and those families with at least some health insurance coverage. These families have different spending patterns, as described by Paulin and Weber. This study builds upon and extends the works of Miller and Reise in several ways. In addition to using more recent data, this study, as noted earlier, describes types of policies that families with insurance hold, as well as differences in levels of health care expenditures for families with different levels of coverage. It examines the probability of incurring health care expenditures as well as the probability of being insured. The data. The data for this study are selected from the 1991-93 Consumer Expenditure Interview Surveys for fami lies with all children under age 18.14 Families are defined as consumer units consisting of a husband, wife, and their own children with no other persons present, or single parents with their own children and no other persons present. Because the focus is on families who must rely on private coverage, families covered by the medicaid and medicare programs are excluded from the analysis. In addition to health benefits, medicaid recipients may receive other ben efits (such as food stamps) that would distort estimates of the relationship between characteristics (such as income) and the decision to purchase insurance. Similarly, virtually all U.S. citizens who are at least 65 years old are eligible for medicare, thus potentially distorting estimates of the rela tionship between age and the decision to purchase insurance. Additionally, the costs and benefits of enrolling in medicare (once eligible) are assumed to be different from those of en rolling solely in private insurance programs. Therefore, medicare recipients are also excluded.15 Consumer Expenditure Survey collects information on the number of family members covered by each policy. It does not record specifically which members are covered by the 14 M onthly Labor Review August 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis policy. The difference between the number of family mem bers and the number of members covered by a household policy is used as a proxy to measure complete or incomplete health insurance coverage. If the family holds more than one policy, the total number of members covered by all policies must be greater than or equal to the number of family mem bers for the family to be considered fully covered. It is as sumed that households do not overlap coverage for some members while having no coverage for others. Policies for persons outside the family, or that are limited in coverage (dental only or special policies for injuries related to school athletic programs) are counted as covering zero family mem bers for the purpose of defining coverage status. As in the studies by Miller and Reise, this analysis uses data only from the second interview of the Consumer Ex penditure Interview Survey. Consumer units are interviewed five times on a quarterly basis. The selection of only secondinterview families avoids biasing the results by ensuring that all families who are analyzed are unique. All data presented in this study are unweighted to be con sistent with those shown in the regression results. Logistic regression is sensitive to weighting, as described later. Demographic characteristics. Table 1 shows the differ ences in demographic characteristics of families with chil dren, by insurance coverage category. Although there is little difference in age or family size for the groups, income (as proxied here by total expenditure outlays16) appears to be correlated with insurance status. The fully covered have the highest incomes, while the uninsured have the lowest in comes. Similarly, uninsured families have lower levels of education, lower levels of work force participation and there fore fewer earners than the insured families. Uninsured fami lies are also more likely to be black or Hispanic17 than par tially or fully insured families. The uninsured are the only group whose families are about as likely to rent as to own their homes, although the rate of “outright” homeownership (that is, families that own with no mortgage) appears to be highest for the uninsured. Policies held. Table 2 shows that fully and partially in sured families have similar types of policies. About the same percentage in each group holds at least one Blue Cross/Blue Shield policy, other commercial health policy, or dental only policy. (However, the partially insured are less likely to be members of a health maintenance organization— h m o — and to have more limited coverage policies, as denoted by “other health insurance.”) The average number of policies held is also similar, though partially insured families have slightly fewer on average. But the quality of the policies held is dif ferent. Fully insured families on average cover 113 percent of their members. Partially insured families, however, cover Demographic characteristics of families with children by health insurance status, Consumer Expenditure Survey, 1991-93 Characteristic Fully insured Sample size ................................ 2,605 347 773 Characteristics of average family Age of reference person......... Family s iz e ............................ Number of earners.................. Persons under 18 years old........................... 37.3 3.8 1.8 37.1 3.6 1.7 35.7 3.7 1.5 Partially insured Uninsured 1.9 1.9 2.0 Total expenditure outlays (annual) M ean................................... Median................................. $40,785 $34,741 $32,491 $28,686 $28,613 $24,277 Other characteristics (in percent): Living in the— Northeast............................ Midwest............................... South................................... W est.................................... Urban area.......................... 22.8 28.6 27.2 21.5 87.8 16.7 24.2 36.3 22.8 87.3 14.8 19.3 35.5 30.5 89.0 Black......................................... Hispanic.................................... 7.0 4.7 7.8 8.7 10.9 15.3 Occupation of the reference person: Wage and salary................. Manager/professional....... Technical/sales................. Service.............................. Blue collar......................... Self-employed..................... Retired................................. Unemployed........................ Out of the labor force.......... 88.2 39.0 18.4 5.9 24.9 7.0 .3 .4 4.1 87.6 30.6 23.9 11.2 21.9 6.6 .3 .3 5.2 75.9 23.3 15.1 10.1 27.4 10.5 .3 1.3 12.0 Education of the reference person: Less than high school......... High school graduate/ some college..................... College graduate................. 7.0 10.7 22.7 58.7 34.3 65.4 23.9 57.2 20.2 Family composition: Single parent....................... Husband/wife family............ 12.6 87.4 30.0 70.0 22.5 77.5 Earner status: No earners.......................... One earner.......................... Two earners........................ At least three earners......... 0.8 30.9 60.8 7.5 1.4 39.2 51.6 7.8 6.9 44.1 43.3 5.7 Housing tenure: Homeowner with mortgage.. Homeowner, no mortgage ... Renter................................. 68.9 7.8 23.3 54.8 6.9 38.3 41.5 9.3 49.2 At least one child: Under age 6 ............................. 6 to 11 .................................. 12 to 1 7 ............................... 50.6 51.3 37.7 47.3 43.5 42.1 47.6 53.6 41.3 Student status of reference person: Full tim e............................... Part tim e.............................. 1.4 5.5 3.8 4.6 2.2 4.9 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 50 percent of their members. Although partially insured families are more likely to have at least one policy fully paid for by someone outside the family (such as an employer), fully insured families are more likely to have at least one partially paid policy, and partially insured families are more likely to have at least one policy for which they pay entirely. Children make up a large percentage of individuals not covered in partially insured families. Although the Consumer Expenditure Survey does not ask which members are cov ered by each policy, under the assumption made earlier that families do not overlap coverage as long as at least one member remains uncovered, a lower and upper bound on the number of children covered can be estimated. To get the lower bound, all families are assumed to follow an “adult first” strategy. That is, the first person covered will be an adult. If the family is a husband/wife family, then if only two mem bers are covered, they will be the husband and the wife. Only if three members are covered will a child be covered. To get the upper bound, families are assumed to follow a “child first” strategy. That is, only after all children are covered will an adult be covered. As shown in the following tabula tion, the average partially insured family, which has 1.9 chil dren, has between 0.5 children and 1.5 children covered: Number of children............................ 1.9 Number o f children covered: Adults first........................................... Children first....................................... 0.5 1.5 Percent of children covered: Adults first........................................... Children first....................................... 26.3 78.9 In other words, about one-fourth to three-fourths of chil dren are covered in partially insured families. This implies that at least one-fourth of all children in partially insured families have no health insurance coverage. If combined with children in uninsured families, this implies that between oneninth and one-sixth of the children in the sample lack health insurance coverage.18 Health care expenditures. Table 3 shows that the fully in sured pay the largest amount for health care in total. Al though partially insured families appear to pay slightly more for medical services than fully insured families, this differ ence is not statistically significant.19 When shares of the health care budget are considered, the fully insured spend the largest share (49 percent) on health insurance, but the smallest on medical services (39 percent). However, the fully and partially insured spend about the same share (12 percent) on prescription drugs. The uninsured spend the largest shares on medical services (57 percent) and prescription drugs and medical supplies (15 percent) and the smallest share for insurance (28 percent). M onthly Labor Review August 1995 15 Family Health C o ve ra g e However, insurance premium payments for the uninsured could be for someone outside the immediate family (perhaps an older relative, a child from a previous marriage, and so forth), and therefore perhaps should not be counted when comparing health care expenditures by insurance status. Furthermore, insurance policies may “favor” certain types of treatment—that is, they may pay for medical services, but not prescription drugs. Therefore, it is interesting to exam ine health care expenditures for items other than insurance premiums to see how levels and shares differ by insurance status. Of the health care dollars not spent on insurance pre miums, the fully insured allocate 76 percent to medical ser vices and 24 percent to prescription drugs and medical sup plies. This compares with an 81 -percent/ 19-percent split for the partially insured, and a 79-percent/21-percent split for the uninsured. Probability of purchase. The fact that the fully and partially insured families spend more on medical services, prescrip tion drugs, and medical supplies does not, by itself, indicate that insurance status is related to health care usage. The un insured have lower incomes than the insured, so it is to be expected that they spend less on these services. Therefore, to estimate the direct effect of health insurance status, all other factors, such as income, age, and family size must be held constant. Rose M. Rubin and Kenneth Koelln perform such a study.20 They find that indeed, ceteris paribus, the presence of insurance is positively correlated with expenditures for medical services, prescription drugs, and medical supplies. However, Rubin and Koelln do not measure frequency of usage of these goods and services. This may be because the Consumer Expenditure Survey does not measure usage di rectly; that is, the respondent is not asked how many times a member of the family went to the doctor during the past 3 months. However, if a respondent reports a medical expen diture, then someone in the family must have used such services. Results of a logistic regression modeling the probability of incurring expenditures for different types of health care are shown in table 4 (medical services) and table 5 (pre scription drugs and medical supplies). In this case, the lo gistic regression is binomial, meaning that the outcome pre dicted is either “yes” (family did incur an expenditure) or “no” (family did not incur an expenditure). The predicted probability of incurring an expenditure is: P= i/{ l +exp[-i *(a + p'x]} where P is predicted probability of incurring an expenditure a is a constant p is a vector of parameter estimates X is a vector of independent variables. 16 Monthly Labor Review August 1996 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis In tables 4 and 5, parameter estimates for the first column represent the coefficients for the fully insured. If statistically significant, these indicate that the variable is important in predicting the probability of incurring an expenditure for medical services (table 4) or prescription drugs (table 5). The second and third columns of parameter estimates show whether the relationship of the variable to the probability of incurring an expenditure is different for the partially in sured or uninsured than it is for the fully insured. If the pa rameter estimate is statistically significant, the relationship is different. As with any regression, it is important to define a refer ence group to make comparisons more accurate. In tables 4 and 5, each insurance group consists of families with median income (table 1), whose reference person is between 25 and 44 years old, married with two children, neither black nor Hispanic, and containing two earners.21 The probability of incurring an expenditure for each of these groups is shown in the tables. (For example, table 4 shows that members of the fully insured reference group are predicted to have a 73.2percent probability of incurring expenditures for prescription drugs and medical supplies, compared with a 66.1-percent probability for members of the uninsured reference group.) H<»nlth in s u rn n c e p o licies, by health insurance coverage status, 199 1-93 Characteristic Fully insured Partially insured Uninsured Family size..................................... Members covered.................... Percent of members covered.... 3.8 4.3 113.1 3.6 1.8 50.0 3.7 .0 .0 Percent with at least one— Blue Cross policy..................... Commercial health policy......... HMO policy............................... Dental only policy..................... Other health Insurance policies1 28.1 47.8 24.1 9.3 13.6 28.5 44.7 18.4 8.7 19.0 9.2 13.7 8.9 7.0 4.4 Average number of policies held .... Blue Cross................................ Commercial health.................... HMO.......................................... Dental on ly................................ Other health insurance1 .............. 1.39 .31 .56 .26 .10 16 1.32 .30 .50 .21 .09 .22 .45 .09 .15 .09 .07 .05 Percent with at least one policy paid for— Entirely by the family.................. Partially by someone else.......... Entirely by someone else........... 18.6 56.2 39.9 22.8 45.0 45.5 8.7 18.5 11.9 Number of policies paid for— Entirely by the family.................. Partially by someone else.......... Entirely by someone else........... .22 .68 .49 .29 .52 .50 .27 .60 .40 1 Includes policies providing special limited coverage, medicare supple ments, and other health Insurance policies. Health care expenditures by health insurance coverage status, 1991-93 Expenditure allocation Total health care (annual)................ Health insurance.......................... Medical services..................... Prescription drugs/ medical supplies...................... Fully insured Partially insured Uninsured $1,880 920 732 $1,668 663 811 $972 269 556 229 194 147 Percent of health care allocated to— ............................. Health insurance......................... Medical services........................ Prescription drugs/ medical supplies......................... 100.0 48.9 38.9 100.0 39.7 48.6 100.0 27.6 57.2 12.2 11.6 15.1 Percent of total expenditure outlays allocated to— Health insurance....................... Medical services.......................... Prescription drugs/ medical supplies....................... 2.3 1.8 2.0 2.5 .9 1.9 .6 .6 .5 67.3 70.1 58.8 62.0 23.0 51.2 57.7 54.2 40.5 Percent reporting expenditures (quarterly):1 Health insurance........................ Medical services........................ Prescription drugs/ medical supplies..................... 1 Does not include reimbursements for payments made in previous quarters but received in current quarter. In tables 4 and 5, probabilities for each group are pre dicted, given that each reference group family has $32,175 in total expenditure outlays, which is the median value for the sample as a whole. This value is substantially less than the median value for the fully insured (about $2,000 less), and substantially more than the median values for the par tially insured (about $6,500 more) and uninsured (about $7,800 more). Table 4 shows that insurance status is definitely impor tant for the reference group. The fully and partially insured have similar probabilities of incurring a medical service ex penditure. However, when the probability for the fully in sured (73.2 percent) is compared with the probability for the uninsured (66.1 percent), the difference is significant in a statistical and economic sense. Thus, the data may indicate that uninsured families are less likely to seek preventative care, as Kasper finds. By con trast, families with insurance may be more likely to visit the doctor for minor illnesses, as Rubin and Koelln imply. To further investigate the “usage” issue, expenditures for pre scription drugs and medical supplies are examined. A fam ily with insurance may automatically incur an expenditure for a doctor visit (either through a deductible or copayment). However, if the illness is not severe, the doctor need not pre scribe medicine. If insured families are more likely ceteris paribus to incur prescription drug expenditures, then it is https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis safe to assume that when they become ill, they become well faster than their uninsured counterparts. Furthermore, any reimbursements for these expenditures are treated as if no visit occurred, because the reimbursed visit may have taken place more than 3 months prior to the interview date. When all characteristics, including income, are held con stant, the predicted probabilities that the fully and partially insured will incur an expenditure are once again very simi lar: 58 percent for the fully insured and 61 percent for the partially insured (table 5). The predicted probability for the uninsured, 47 percent, suggests that this group is much less likely to incur an expenditure for prescription drugs or medi cal supplies than either of the insured groups, even when all else is held constant. However, because rieither the intercept nor income parameter estimate is statistically significant, caution must be used when interpreting this result. Given the findings of Kasper, those of Rubin and Koelln, and the results shown in tables 4 and 5, it appears that there is a relationship between level of insurance coverage and receipt of medical care. Therefore, it is important to under stand the relationship between demographic characteristics and level of insurance coverage. Probability of coverage. To estimate the relationship be tween level of health insurance coverage and demographic variables, a different kind of logistic regression is needed. In this case, there are three possible outcomes: full health in surance coverage, partial health insurance coverage, or no health insurance coverage. Therefore, the dependent value can take on values from 1 (fully insured) to 3 (uninsured). Because the dependent variable takes on three distinct, quali tative values of ascending order, the parameters of this model are estimated using an ordered multinomial logistic regres sion. From these estimated parameters the probabilities that a particular family will be fully, partially, or not insured can be predicted using the following formulas:22 p„ = F(P'x) = F(P'X+a,) - F(P’x) Pm-2 = F(P'x + a, + a 2) - F (px + a ,) where Pmis the probability of being fully insured (in this case) Pml is the probability of being partially insured Pm2 is the probability of being uninsured. The function F () has the same form as it does for a bino mial logit. For example, F(P'x) = 1/[1 + exp(-l * P'jc)] where fV is a vector of parameter estimates * is a vector of demographic characteristics. M onthly Labor Review August 1995 17 Family Health C o vera ge Several independent variables are chosen for this model. The first is annual total expenditure outlays for the family (that is, quarterly total expenditure outlays multiplied by four), which are used as a proxy for permanent income in accordance with Milton Friedman’s “permanent income hy pothesis.”23 Before using this variable, though, it is subjected to a Box-Cox transformation to normalize its distribution.24 The formula for a Box-Cox transformation is: Y* = (Y M )/^ where Y is the initial value of total expendi ture outlays X is a variable found through experi mentation Y* is the transformed value of total expenditures. Using a maximum-likelihood tech nique described by Stuart Scott and Daniel J. Rope,25 the best estimate of X is 1/8.26 (This transformation of total ex penditure outlays is also used in the bi nomial logit described earlier.) In addi tion to normalizing the distribution of total expenditure outlays, the fact that X is 1/8 is consistent with the assumption that the probability of a family having full health insurance coverage increases with income, but at a decreasing rate. This is a plausible assumption, as it in dicates that an increase in income (say, $1,000) is associated with an increase in probability of having full coverage, but that the increase in probability is greater for a low-income family than for a highincome family receiving the same in crease in income.27 Also included are several dummy variables describing characteristics of the reference person including age (under 25 or at least 45), ethnic origin (black or Hispanic), type of occupation or labor force status (if not working), level of edu cation, and student status (enrolled in college full time or part time). Dummy variables describing the family include number of children (one child or three or more), type of family (single parent or husband/wife), children’s age (at least one child is older than age 12 because older children may be less prone to ill M onthly Labor Review August 1995 Digitized for18 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis lU d iM ness than younger children), region of residence (Northeast, Midwest, or West),28 whether the family lives in an urban or rural area, number of earners (no earners, one earner, or at least three earners), and housing tenure (owner without mort gage or renter).29 The omitted category in each case is shown in table 6 with the regression results. The variables are meant to control for differences in “tastes” for insurance (family type, ethnic origin, education); opportunity of obtaining poli cies (occupation, number of earners, and student status, be cause some colleges and universities offer special policies to students); and other factors. Results of bine mial logit predicting probability of incurring expenditures for medical se rvices, with median income held constant for all insurance groups ($32,1 j'5) Characteristic Parameter estimate Estimate Estimate 1 2 Reference group:.................... (1) 0 (1) Intercept.................................. Standard error..................... 2-3.420 .587 -2.712 1.725 3-2.050 1.135 Annual expenditure outlays (Box-Cox) ............................. Standard error..................... 2.208 .027 3.134 .080 Reference person under age 2 5 ............................... Standard error..................... -.351 .285 Reference person over age 4 4 ............................... Standard error..................... Fully insured 0.732 Partially Uninsured insured 0.759 0.661 — — — — — — .081 .053 .737 .766 .669 — — — .648 .629 -.024 .449 .658 .809 — — .573 — .007 .129 -.076 .381 -.304 .273 .734 .747 .592 — — — Number of children (two) One child............................. Standard error..................... 2-.233 .101 .376 .297 2.457 .213 .684 .785 .710 — — — Three or more children....... Standard error..................... .058 .123 .104 .380 -.067 .245 .743 — .788 — .659 — Family type (husband/wlfe) Single parent....................... Standard error..................... -.058 .148 .402 .352 -.204 .276 .721 — .817 — .601 — Ethnic origin (whlte/other) B lack................................... Standard error..................... 2-.708 .163 .060 .473 -.033 .318 .574 — .623 — .505 — Standard error..................... 2 -.523 .194 -.421 .457 -.154 .301 .619 — .551 — .498 — Number of earners (one earner) No earners.......................... Standard error..................... -.487 .432 (4) (1) -.416 .313 -.731 .628 .627 — .660 — .366 — -.111 .213 .732 — .675 — .636 — .231 .184 .286 .396 .679 — .755 — .668 — Age of reference person (ages 25 to 44) Hispanic................................. One earner.......................... -1.39E-03 Standard error..................... 1.09E-01 At least three earners......... Standard error..................... -.257 .175 1 Not applicable. 2 Statistically significant at the 95-percent confidence level. 3 Statistically significant at the 90-percent confidence level. 4 Variable omitted from regression. None of the five families in this category incurred a medical service expenditure. Table 5. Results of binomial logit predicting probability of incurring expenditures for prescription drugs and medical supplies, with median income held constant for all insurance groups ($32,175) Characteristic Reference group:.................... Intercept.................................. Standard error..................... Parameter estimate (’> 2 -3 060 Estimate 1 Estimate 2 (') (’> 1 055 1.064 Fully Insured Partially Uninsured Insured 0.584 0.606 0.468 .528 1 fin^; 1.579 Annual expenditure outlays (Box-Cox)............................. Standard error..................... 2.160 024 .080 .073 .028 .049 .589 .612 .473 Age of reference person (ages 25 to 44) Reference person under 25. Standard error..................... -.135 .285 -.118 .609 .698 .437 .551 .544 .607 Reference person over age 4 4 ............................... Standard error..................... .098 119 -.018 .357 .181 .260 .608 .625 .538 Number of children (two) One child............................. Standard error................... -.070 093 .083 ?78 .256 206 .567 .609 .515 Three or more children....... Standard error..................... .158 .112 -.047 .344 .135 .235 .622 .632 .541 Family type (husband/wife) Single parent....................... Standard error..................... . .152 .141 -.178 .336 3 -.459 .621 .599 .393 Ethnic origin (white/other) Black.............................. Standard error...................... 3-.264 .161 -.424 .471 -.042 .314 .519 .436 .307 Hispanic.............................. Standard error..................... 2 -.976 .199 3.756 .446 .201 .315 .346 .552 .288 Number of earners (One earner) No earners........................... Standard error..................... 3-.922 .501 1.067 1.136 .096 .664 .359 .640 .278 One earner........................... Standard error...................... 2-.229 .099 .031 .301 .099 .204 .528 At least three earners.......... Standard error..................... 3.300 .170 -.580 .475 -.227 .381 .655 .273 — — — — — — — Not applicable. Statistically significant at the 95-percent confidence level. Statistically significant at the 90-percent confidence level. For the sample as a whole, the median value for annual total expenditure outlays is $32,175; the average age of the reference person is 36.9, with average family size of 3.8 per sons. Therefore, the reference group consists of husband/wife families with two children (both under age 12), median out lays,30 and two earners, whose reference person is between ages 25 and 44, neither black nor Hispanic, working for a wage or salary in a managerial or professional position, a high school (but not college) graduate, and not enrolled in college at present. These families live in homes they own (though they still pay a mortgage) in the urban South. The data used in this analysis are unweighted. As noted earlier, logistic regression can be sensitive to weighting. If https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis weighted, the parameter estimates tend to be statistically significant in every case. On the other hand, the relatively small sample size (especially for the partially insured and uninsured), may lead to large standard errors for some parameter esti mates, thus understating the number of significant relationships. Therefore, in the interest of obtaining conservative es timates of statistical significance, no weights are applied, but the 90-percent confidence level is used to define statis tical significance. Regression results are shown in table 6. Along with coefficients, the predicted difference in probability for each group, com pared to the reference group is shown. For example, families whose ref erence person is under age 25, but who are otherwise identical to the reference group, are about 7 percent less likely to have full coverage than families in the reference group. Thus, for the younger group, the value listed in the fully insured column is -0.074. The younger group has a 5-percent greater probability of being uninsured. Thus, for the uninsured col umn, the value is shown as 0.053. Income and insurance status. Perhaps the most important independent variable .557 .436 in any study of consumer expenditure patterns is income. Generally, the more .537 .486 income a family has, the more of any good or service it can afford to purchase, including health insurance. Therefore, it is not surprising that the parameter esti mate for income is statistically signifi cant at the 99.9 percent confidence level. However, despite the statistical strength of the relation ship, the probability that a family has full insurance cover age increases slowly with income. Table 7 shows how the predicted probability changes if a family with characteris tics of the reference group somehow obtains additional in come. Given a 1-percent increase in income, the probability of being fully insured barely increases—rising from 76.7 per cent to 76.9 percent. The table shows that even with fairly large increases of income (up to $3,000 per year, nearly a 10-percent increase), the probability of full coverage does not increase much, rising only to 78.1 percent. Nevertheless, because three-fourths of the reference group are predicted to have full coverage, and well over four-fifths M onthly Labor Review August 1995 19 Family Health C o ve ra g e are predicted to have at least partial cov erage, the reference group is predicted to be relatively well-off when it comes to insurance coverage. Therefore, it may be more interesting to study those who are least well-off: the uninsured. Table 8 shows the predicted probabili ties of coverage for a family with char acteristics typical of the uninsured. That is, the family is similar to the reference group, except that it has substantially lower income ($24,277, the median value for the uninsured), rents its home, has a reference person who is employed in a blue-collar job, and one earner (the ref erence person in this case). Uninsured families are similarly slow to purchase health insurance when they receive increases in income. For ex ample, an increase of $3,000 dollars (a 12-percent increase in income) is asso ciated with a higher probability of full coverage for families with characteris tics typical of the uninsured; however, the difference is small— 52.6 percent, compared with 50.2 percent. Other characteristics. Other demo graphic characteristics are also associ ated with differences in insurance cov erage. Families with young parents (that is those whose reference person is under age 25) are significantly less likely to have full coverage than older families. On the other hand, families with young children (all children are under age 12) are more likely to have health coverage than families who have at least one child over age 12. Families may choose health insurance coverage more readily when the perceived health risks to their chil dren are greater, during the years of early childhood development. Families with older children may also experience the financial pressure of putting extra sav ings into a college fund and may choose not to spend on health insurance as a result. Educational attainment also raises the probability of full coverage. Those who did not graduate from high school are less likely to be fully covered than 20 M onthly Labor Review August 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis P“ ™ * " P re d ic te d p ro b a b ilitie s fo r in s u ra n c e status, m u ltin o m ia l lo g it results Probability of being— Parameter Characteristic Fully Partially Uninsured estimate insured insured Sample (size: 3,725)............................ — 0.699 0.093 0.208 Reference group:................................... Intercept 1 .............................................. Standard e rro r.................................... — 1-3.743 .569 .757 — — .153 — — Intercept 2 .............................................. Standard e rro r.................................... ’-3.160 .568 — .090 — — — — Annual outlays (Box-Cox) ..................... Standard e rro r.................................... ’ .232 .025 2.005 — 2-.001 — 2-.003 — — _ — J Difference from reference group probability | Age of reference person (25 to 44) Reference person under age 2 5 ........ Standard e rro r.................................... 3-.381 .199 -.074 — .021 — .053 — Reference person at least age 4 5 ...... Standard e rro r.................................... .042 .120 .007 — -.002 — -.005 — Number of children (two children) One c h ild ............................................ Standard e rro r.................................... .129 .089 .022 — -.007 — -.015 — Three or more children...................... Standard e rro r.................................... .061 .103 .011 — -.003 — -.007 — Family type (husband/wife) Single parent....................................... Standard e rro r.................................... .083 .125 .014 — -.005 — -.010 — Ethnic origin (white/other) Black................................................... Standard e rro r.................................... .121 .140 .021 — -.007 — -.014 — -.081 — .023 — .058 — Hispanic.............................................. Standard e rro r.................................... ’-.412 .140- Occupation (manager/professional) Technlcal/sales................................... Standard e rro r.................................... -6.20E-04 .117 -.000 — .000 — .000 — Blue collar........................................... Standard e rro r.................................... -.052 .113 -.009 — .003 — .007 — Service............................................... Standard e rro r.................................... ’-.348 .152 -.068 — .019 — .048 — Self-employed..................................... Standard e rro r.................................... ’-.717 .147 -.150 — .038 — .112 — Retired................................................ Standard e rro r.................................... 1.185 .748 .147 — -.052 — -.095 — Unemployed....................................... Standard e rro r.................................... -.210 .483 -.039 — .012 — .028 — Out of labor force............................... Standard e rro r.................................... -.238 .196 -.045 — .013 — .032 — Education (high school/some college) Did not graduate high school............. Standard e rro r.................................... ’-.525 .120 -.106 — .029 — .077 — College graduate................................ Standard e rro r.................................... .012 .101 .002 — -.001 — -.001 — At least one child over age 12............ Standard e rro r.................................... ’-.258 .090 -.049 — .014 — .035 — Region (South) Northeast............................................ Standard e rro r.................................... '.648 .113 .095 — -.032 — -.063 — Midwest.............................................. Standard e rro r.................................... W est................................................... ’ .633 .104 -.044 .094 — -.008 -.032 — .002 -.062 — Age of children (all under age 12) .005 C ultural differences by race and ethnicity may make certain groups less averse to the risk of being uninsured. Al Parameter Fully Partially Characteristic Uninsured insured estimate insured though the coefficient for black families is not statistically significant, the coeffi Degree urbanization (urban) R ural.................................................. 0.188 0.032 -0.010 -0.022 cient for Hispanics is very significant. Its Standard error.................................... — — _ .123 negative sign indicates Hispanic families Number of earners (two earners) No earners......................................... 1-1 .266 -.285 are less likely to be insured. .055 .230 Standard error.................................. — — .339 Regional differences are significantly One earner........................................ ’-.368 -.072 .020 .052 related to differences in health insurance Standard error.................................... — — .097 At least three earners........................ coverage. Compared with the South, -.216 -.041 .012 .029 Standard error.................................... — _ .163 which is the most populous region, fami Housing tenure (owner with mortgage) lies in the Northeast and Midwest have a Owner, no mortgage.......................... -.199 -.037 .011 .026 Standard error.................................... — — .143 much higher probability of being fully Renter............................................ '-.531 -.107 .029 .078 insured. This may be attributed to any _ Standard error................................... — _ .091 number of factors, including differences Student status (nonstudent) Full-time.......................................... -.260 -.049 .014 .035 by region in State laws, costs of health Standard error.................................. — — .266 care, unionization of the work force Part-time............................................. .025 .004 -.001 -.003 Standard error................................... .172 (which may result in greater availability — of employer-provided health plans), rates 1 Statistically significant at the 95-percent confidence level. 2 Difference in predicted probability given $1,000 increase in annual outlays. at which employers offer benefits, or 3 Statistically significant at the 90-percent confidence level. other factors. The West, however, is not significantly different from the South. those who did graduate, although there is no statistically sig In most cases, the probability of be nificant difference in probability of full coverage for high ing partially insured does not change much with character school and college graduates. istics. This may imply that families “vault over” the par Occupational status appears to be associated with differ tially insured category—that is, if they get extra income, they ent levels of health insurance coverage. The reference group will move from no insurance to full coverage. But this is not consists of salaried professional or managerial workers; these necessarily true in all cases. For example, it is possible that are the workers who are expected to have high-coverage a two-eamer family with full insurance coverage moves to health benefit plans. However, of the wage or salary occupa the partial coverage class if an earner loses a job, rather than tions, only those families whose reference person is employed slipping all the way into no coverage. Some of those with in services have a lower probability of being fully insured partial coverage may move to the no coverage category than members of the reference group. Families whose refer under similar circumstances. Thus, the probability of par ence person is self-employed are even less likely to have full tial coverage is similar across demographic characteristics, coverage.31 even though some families may be moving in and out of the As expected, number of earners in the family is signifi category. cantly related to the level of health insurance coverage. Fami lies with two earners (the reference group) are expected to have more health coverage on average than families with Predicted probability of health insurance status for fewer earners but equal income, because the two-earner fam families with median income ($32,175) ily may have a choice between two employer-sponsored Probability of being— health insurance plans. (Or at least there is a greater chance Item Fully Partially that someone in the family is eligible for such a plan.) Fami Uninsured insured insured lies with more than two paychecks may need several incomes At present level to cover the family’s expenses. If all members earn relatively of incom e..................................... 0.767 0.088 0.145 low wages, they may be in jobs which have poor benefits. Given an increase in Therefore, families with more than two earners are expected income of— to have a lower probability of full coverage. The negative One pe rcent............................ 0.769 0.087 0.144 $1,000 .................................. 0.772 0.086 0.142 coefficient for multiple earner families seems to confirm this $2,000 .................................. 0.776 0.085 0.139 intuition, but it is not statistically significant. Therefore, no $3,000 .................................. 0.781 0.084 0.136 firm inference can be drawn. 1 0 2139 Continued— Predicted probabilities for insurance status, multinomial logit results https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Monthly Labor Review August 1995 21 Family Health C o vera ge e a l t h in s u r a n c e status plays an important role in provid ing health care to families. This study finds that families with children and at least partial coverage are more likely to receive at least some kinds of care (medical services) than uninsured families with children, even when income and other characteristics are equal. Certain characteristics are related to the ability to obtain health insurance coverage. In this study, income, age, edu cation and number of earners are found to be positively re lated to a family’s level of health insurance coverage. Char acteristics of the reference person such as being a service worker, self-employed, or Hispanic are negatively related to the probability of coverage. Although income is an important predictor of insurance status, families do not change their level of coverage much, even when income increases substantially. This would indi cate that if increased health insurance coverage is a desired outcome, direct grants of cash to families will not raise lev els of coverage in any substantial way. Although prices and qualities of insurance plans are not studied in this ar ticle it would be useful to find out what influence these fac- H Predicted probability of health insurance status for families with characteristics typical of the unin sured (median income: $24,277) Probability of being— Item Fully insured Partially insured Uninsured At present level of income................................... 0.502 0.142 0.357 Given an increase in income of— One percent........................... $1,000 ................................ $2,000 ................................ $3,000 ................................ 0.504 0.510 0.518 0.526 0.141 0.141 0.140 0.139 0.355 0.349 0.342 0.335 tors have on the probability of receiving coverage. Also, data on difficulty of obtaining access to health insurance cover age is useful to understanding why some families are unin sured. For example, if plans are readily available through an employer, are families likely to take advantage of them?32 Exploration of these issues should provide for interesting future research. □ Footnotes 1 Peter J. Cunningham and Alan C. Monheit, “Insuring the Children: A Decade o f Change,” Health Affairs, Winter 1990, p. 78. 2 Judith D. Kasper, “The Importance o f Type of Usual Source o f Care for Children’s Physician Access and Expenditures,” Medical Care, May 1987, 25(5), pp. 386-98, especially tables 4 and 7. 3HHS News, U.S. Department o f Health and Human Services, November 1994, p .l. 4 Geoffrey D. Paulin, and Wolf D. Weber, “The effects of health insurance on consumer spending.” Monthly Labor Review, March 1995, pp. 34-54. 5 Statistical Abstract of the United States: 1994 ( U.S. Bureau of the Census, 1994), table no. 165. “Health Insurance Coverage Status, by Selected Characteristics: 1987-92,” p. 118. 6 Cunningham and Monheit, pp. 77-78. 7 Cunningham and Monheit, p. 80. Based on data from the 1977 National Medical Care Expenditure Survey, 1977 and the National Medical Expendi ture Survey, 1987. (See exhibit 2, p. 81.) 8 Gloria J. Bazzoli, “Health Care for the Indigent: Overview of Critical Issues,” Health Services Research, August 1986, pp. 353-93. 9 Ibid., p. 356. 10 Ibid., p. 357. 11 Richard D. Miller, “Another Look at the Medically Uninsured Using the 1987 Consumer Expenditure Survey,” Bureau of Labor Statistics Working Paper 205, October 1990. 12 A consumer unit is a single person living alone or sharing a household with others who are all financially independent; members of a household re lated by blood, marriage, adoption, or other legal arrangement; or two or more persons living together who share responsibility for at least two out of three major types o f expenses: food, housing, and other expenses. 13 Elizabeth M. Reise, “A Look at Private Health Insurance Coverage of Families with Children under 18 Using Data from the Consumer Expenditure Interview Survey 1989-91,” Proceedings of the Social Statistics Section (Alexandria, v a , American Statistical Association, 1993), pp. 827-32. 14This includes all children living at home. Presumably, most children who 22 Monthly Labor Review August 1995 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis are over 18 and living away from home are independent, and responsible for their own health insurance. The Consumer Expenditure Survey considers col lege students who live at school to be separate consumer units. 15The numbers of famiL _:s excluded from the sample are as follows: medic aid only: 454; medicare only: 32; medicaid and medicare: 16. 16 The total expenditure definition used in the Consumer Expenditure Sur vey excludes mortgage principal payments (though it includes mortgage inter est payments), and includes the full purchase price of a vehicle, if one is pur chased. In the present study total expenditure outlays are defined to include mortgage principal payments, because they are an important component o f the homeowner’s budget, and are not easily changed once negotiated. Addition ally, the full purchase price o f a vehicle is replaced by actual outlays. That is, if the respondent reports vehicle payments, including finance charges, these are included rather than the full purchase price, unless the vehicle is purchased outright. 17Ethnic origin of the reference person is used to define these variables. Fami lies are defined as black if reference person’s ethnicity is described as “AfroAmerican.” Families are defined as Hispanic if the reference person’s ethnicity is described as “Mexican American,” “Chicano,” “Mexican,” “Puerto Rican,” “Cuban,” “Central or South American,” or “Other Spanish.” Families are de fined as white and other if the reference person’s ethnicity is described as “Ger man,” “Italian,” “French,” “Polish,” “Russian,” “English,” “Scottish,” “Dutch,” “Swedish,” “Hungarian,” “Other,” or “Do not know.” A separate variable identifying race of the reference person (white; black; American Indian, Aleut, Eskimo; Asian or Pacific Islander; other) is not used in these definitions. The distinction between race and ethnicity is especially important for the model results shown later. For example, someone who is Hispanic by ethnic origin but black by race is still classified as Hispanic in these models. 18 The number o f uninsured children is calculated by multiplying the aver age number of children per uninsured family (2.0) by the number of uninsured families (773). The number o f fully insured children found similarly for the fully insured families (1.9 multiplied by 2,605). Uninsured children from par tially insured families are found for “children first” families by multiplying the percentage of uninsured children (1-0.789) by the number of children in these families (1.9 multiplied by 347). Similarly, the number of uninsured children in partially insured, “adult first” families can be calculated. The total number o f uninsured children (that is, children from uninsured families added to unin sured children from partially insured families) provides the numerator for a percent calculation. The total number o f children, regardless of coverage, pro vides the denominator. If all partially insured families follow the “children first” strategy, then 11.2 percent of children in the sample are uninsured. If they all follow the “adult first” strategy, then 15.8 percent of children in the sample are uninsured. 19 The standard errors o f the means for medical services are 32.49 for the fully insured and 92.64 for the uninsured. 20 Rose M. Rubin and Kenneth Koelln, “Determinants of Household Out-ofPocket Health Expenditures,” Social Science Quarterly, December 1993 do 721-35. 21 These variables are a subset o f those chosen for the multinomial logit model described later in the multinomial logit section. 22 See G.S. Maddala, Limited Dependent and Qualitative Variables in Econometrics (Cambridge, England, Cambridge University Press, 1983), pp. 23 Milton Friedman, A Theory of the Consumption Function (Princeton, NJ, Princeton University Press for National Bureau of Economic Research 1957) p. 221. The use o f total expenditures as a proxy for permanent income is common in the literature (for example Miller, Reise, and Paulin and Weber). Rubin and Koelln use an instrumental variable form of total expenditures as a proxy for permanent income to avoid simultaneous equations bias in predicting health care expenditures (pp. 727-28). That is, health care expenditures are a sub component of total expenditures, so using total expenditures to predict health care expenditures may result in a bias. No such instrument is necessary in the present case, because only probabilities, not levels, o f expenditures are predicted. Other recent studies that use total expenditures as a proxy for permanent income to model expenditures other than health care include Julie Nelson, “In dividual Consumption Within the Household: A Study of Expenditure on Cloth ing,” Journal of Consumer Affairs, Summer 1989, pp. 21-43; and E. Raphael Branch, “Short Run Income Elasticity o f Demand for Residential Electricity Using Consumer Expenditure Survey Data,” The Energy Journal, 1993 on 27 Further evidence of the plausibility of this assumption comes from Reise, “A Look at Private Health Insurance” and Miller, “Another Look.” Both au thors test for a lack of health insurance coverage. Reise uses the natural log o f total expenditures in her model, and finds the coefficient negative and statisti cally significant, indicating that the probability o f a lack o f coverage decreases with income at a decreasing rate. Miller uses total expenditures and total ex penditures squared in his model. He finds a negative coefficient for total expen ditures and a positive coefficient for total expenditures squared. Both coeffi cients are statistically significant. As in Reise’s study, the signs o f Miller’s coefficients also indicate the lack of insurance coverage is decreasing at a de creasing rate with respect to income. If the problem is reversed, that is, the probability of full insurance coverage is estimated instead of a lack o f cover age, the signs of the coefficients reverse, indicating that the probability o f hav ing full insurance coverage increases with income, though still at a decreasing rate, as postulated in this article. Note also that both Reise’s and Miller’s specifications are forms o f the BoxCox transformation. Reise, in effect, assumes the optimal value o f 1is zero; that is, the natural log is the appropriate transformation. Miller assumes the opti mal value o f 1 is 2; that is, a squared term is appropriate. As noted earlier, in this study, the optimal value of 1 is found to be 1/8, which is between the Reise and Miller estimates. 28 Regions are designated by standard U.S. Bureau o f the Census defini tions. -9 In Miller, “Another Look,” the author includes a dummy variable for renters (as opposed to homeowners) “as a proxy for wealth” (p. 8), and finds that renters are significantly more likely to lack full insurance coverage than are homeowners (p. 24). In this study a dummy variable is also included to distinguish families that own their homes outright from families that still pay a mortgage. Paulin finds that families that own outright spend about 11 cents out of every additional dollar on health and personal care, compared to 5 cents for mortgage payers and renters. This may reflect a wealth effect, or simply the fact that families that own outright have more money available to spend than those who must pay a mortgage, ceteris paribus. See Geoffrey D. Paulin, “A Comparison o f Consumer Expenditures by Housing Tenure,” Journal of Con sumer Affairs, Summer 1995, pp. 164-98, especially p. 189. the Royal Statistical Society, Series B, 1964, pp. 211-43. 30 The median is chosen, as opposed to the mean, because outlays are not normally distributed. Table 3 shows that the mean is substantially higher than the median for all three insurance groups, which would raise predicted prob abilities. Because the median represents the “middle” family better than the mean in this case, median outlays are chosen for the reference group. 25 Stuart Scott and Daniel J. Rope, “Distributions and Transformations for Family Expenditures,” Proceedings of the Section on Social Statistics (Alex andria, va , American Statistical Association, 1993), pp. 741-46. 31 In fact, ceteris paribus, only families with no earners are predicted to have a lower probability of full coverage than those families whose reference person is self-employed. 26Using a computer program written by Daniel J. Rope, the variable 1 was tested over the a range o f values from zero to one with increments of 1/16. 32 See William J. Wiatrowski, “Who really has access to employer-provided health benefits?” Monthly Labor Review, June 1995, pp. 36—44. 111- 21 . FF' 24 G.E.P. Box and D.R. Cox, “An analysis of Transformations,”Journal of https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 23 Fatal Injuries Self-em ployed individuals fatally injured at work Individuals working for themselves, especially on farms and in retailing, typically face a higher risk of fatal injury than do their wage and salary counterparts “His brow is wet with honest sweat. He earns whate ’er he can, And looks the whole world in the face, For he owes not any man. ” Martin E. Personick and Janice A. Windau —Henry Wadsworth Longfellow The Village Blacksmith (1842) orking for oneself can be rewarding for individuals, like Longfellow ’s smithy, who place a high value on con trolling the nature and pace of their efforts and are not overly concerned about an unpredictable earn ings stream. Being self-employed, however, can carry considerable safety risks and responsibilities, such as tackling hazardous work activities without adequate resources for safety training and equip ment and without the oversight and guidance of government safety regulations. (See the appendix for a description of worker safety and health cover age by Federal and State agencies.) In 1993, the self-employed as a group made up about 1 in every 5 fatal injuries at work, higher than their one-tenth share of the American work force, according to the Census of Fatal Occupational Injuries and the Cur rent Population Survey (C PS).1 And certain groups of the self-employed faced an especially high risk of dying on the job, such as older farmers operat ing tractors and other vehicles and managers and proprietors tending stores, bars, restaurants, and repair shops where many robbery-related homi cides occur. This article analyzes new information on the self-employed who are fatally injured at work, such as their occupation, age, and other charac teristics; the industry they worked in; and the cir cumstances surrounding their death. The BLS W Martin E. Personick is an econom ist a n d Ja n ice A. W indau is an epidem iologist in th e O ffice o f Safety, Health a n d Working Conditions, Bureau o f Labor Statistics. 24 M on th ly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Census of Fatal Occupational Injuries is the source of these data. It cross-references death certificates, newspapers, and other reports to verify that fatal injuries were work related and to obtain key information on the “who and how” of each incident. Of the 6,271 fatal work injuries counted in the 1993 b l s census, 1,191 were iden tified as self-employed individuals, 4,981 were wage and salary workers, and 99 others were pri marily family workers. The self-employed at a glance Although some counts of the self-employed date back to the late 19th century, the 1940 Decennial Census marks the beginning of truly systematic efforts to count and profile that worker group. In 1940, there were nearly 10 million self-employed persons operating unincorporated business enter prises. Nine-tenths of those self-employed were men, most of them working in agriculture, for estry, and fishing.2 In 1993, the unincorporated self-employed still numbered about 10 million, but their char acteristics and share of the work force had changed dramatically since 1940. Back then, the self-employed were about 20 percent of the civil ian work force; now they are 9 percent of a much larger labor pool. Services industries, moreover, have replaced agriculture as. by far the leading industry of the self-employed, accounting for two-fifths of that group’s workers in 1993. And the share of self-employed women has grown from one-tenth of all self-employed in 1940 to one-third in 1993; still, that is somewhat lower than their 45-percent share of all workers.3 The employment characteristics of today’s self-employed differ in many respects from those of wage and salary work ers. The following comparisons of such staffing differences shed some light on why their fatality profiles also differ and why the self-employed as a group appear to be at a compara tively high risk of fatal injury. The self-employed tend to be older than wage and salary workers, a pattern evident over many decades.4 This differ ence is especially noteworthy for workers in the oldest age group because they face a relatively high risk of fatal injury.5 In 1993, about one-fifth of the self-employed were age 55 and older, double the proportion of wage and salary workers in this age category. The difference is even more pronounced within agriculture, where older workers are fully one-third of all the self-employed, but just one-tenth of all wage and salary workers. Most self-employed and wage and salary workers work in service-producing industries, where, with a few notable ex ceptions such as transportation industries, the risk of fatal injury is relatively low for both. Staffing divergences within three goods-producing industries, however, illustrate why the self-employed as a group face a relatively higher risk of fatal injury. For example, agriculture, the industry with the high est rate of fatal injury for all workers, accounted for 13 per cent of the self-employed, but just 2 percent of those working for wages and salaries. Construction, another high risk in dustry, engaged proportionately more of the self-employed (about one-sixth) than of all wage and salary workers (onetwentieth). And by contrast, manufacturing, an industry with a relatively low risk of fatal injury, accounted for a smaller share (one-twentieth) of the self-employed than its one-fifth share of all wage and salary workers. About half of all self-employed and wage and salary work ers held a white-collar job either within the broad occupa tional grouping of “managerial and professional specialty” or the classification, “technical, sales, and administrative support.” Both broad groupings carry a relatively low risk of fatal injury. However, within these groupings are two occu pations—managers of food serving and lodging services and sales supervisors and proprietors—for which there is an el evated risk of becoming a homicide victim during a robbery. Together, those two occupations made up a larger share (oneeighth) of self-employed workers than of wage and salary workers (one-twentieth). Self-employed workers also in cluded relatively large shares of farmers and construction tradesworkers, two other occupations with high rates of fatal injury. But proportionately more of the wage and salary workers (one-seventh) than the self-employed (one-twenti eth) were “operators, fabricators, and laborers,” a compara tively high risk group that includes, for example, motor ve hicle operators and construction laborers. Self-employed workers typically work longer hours than https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis do wage and salary workers and are paid less. The following tabulation shows the disparity between the two groups in av erage hours worked per week during 1993 for those on full time schedules:6 Average weekly hours Industry S elf em ployed Agricultural............. Nonagricultural....... 54 48 Wage and salary 47 43 The disparity is even more striking when one looks at the percentage of workers who logged more than 48 hours a week: P ercent working m ore than 4 8 hours Industry S e lf em ployed Agricultural............. Nonagricultural....... 60 46 Wage and salary 37 23 Thus, the average self-employed worker is exposed to work hazards for a longer period of time and also may be more sub ject to the effects of fatigue while operating a vehicle or hazard ous machinery.7 Finally, self-employed individuals typically earn less than their wage and salary counterparts and, thus, appear to have few extra resources to spend on safety education and equipment that often are provided by employers at little or no cost to their wage and salary workers.8 The fatalities The 1993 Census of Fatal Occupational Injuries counted 1,191 fatalities among self-employed persons who had been working either on a primary or a secondary job at the time of their death. Although it was designed to count only “the unincorporated” as self-employed, the b l s fatality census also includes in this count some owners of incorporated businesses and members of partnerships if their corporate status could not be ascertained through normal data collection efforts. Thus, the coverage of fatalities among the self-employed in the b l s census is somewhat broader than the Current Popu lation Survey’s definition of self-employed workers (unin corporated, primary job only). Because of these differences, fatality rates for the self-employed and for wage and salary workers by various worker characteristics and types of cases are not included in this article.9 Still, much can be learned about the relative fatality risks of the self-employed by identifying the leading ways in which they died, the primary industries and occupations where the fatal injury occurred, and the age group of the self-employed fatally injured. Tables 1 through 3 profile these characteris tics both for the self-employed and for the wage and salary worker, revealing several important differences in fatality M onthly Labor Review August 1995 25 Fatal Injuries patterns between the two. Fatal event and exposure. Work-related homicide led all other fatal event and exposure categories for the self-em ployed and ranked second to highway incidents for the wage and salary worker (table 1). Homicide accounted for a slightly larger share of fatal injuries among the self-employed fatally injured (22 percent) than among wage and salary workers (16 percent), suggesting that the risk of violent death at work is higher for the self-employed than for wage and salary work Fatal work injuries among self-employed and wage and salary workers, by event or exposure, 1993 [In percent] Selfemployed Event or exposure1 Wage and salary Number.................................... Percent.................................... 1,191 100 4,981 100 Transportation incident......................... Highway........................................ Collision between vehicles, mobile equipment........................ Noncollision.................................... Jack-knifed, overturned.............. Nonhighway (farm, industrial).......... Noncollision.................................... Overturned..................................... Fell from and struck by vehicle, mobile equipment........................ Aircraft....................................... Worker struck by vehicle.................... Water vehicle...................................... Railway.................................... 34 11 41 22 5 4 3 14 13 9 12 6 4 4 4 2 2 3 3 3 1 1 5 6 2 2 Assault and violent a c t........................ Homicide........................................... Shooting................................ Stabbing....................................... Self-inflicted injury............................ 29 22 19 1 6 19 16 13 2 3 Contact with object, equipment............ Struck by object................................ Falling object.............................. Caught in or compressed by equipment or object......................... Running equipment, machinery..... Caught in or crushed in collapsing materials......................... 20 12 7 16 8 5 6 3 4 2 2 2 Fall................................................ From roof....................................... From ladder, scaffold, staging........... 8 2 2 10 2 2 7 3 10 2 2 2 2 2 4 Exposure to harmful substance or environment................................. Contact with electric current............. Exposure to caustic or noxious substance......................... Oxygen deficiency, including drowning, submersion.................... Fire and explosion................................ 1 Based on the 1992 Structures. bls 6 Occupational Injury and Illness Classification NOTE: Total for a major event category may include data for subcategories not shown separately. Percentages may not add to totals because of rounding. M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 ers.10 The self-employed also were more likely to die at work of a self-inflicted injury than were wage and salary workers. Nonhighway fatalities, except rail, air, and water inci dents, were the second leading way in which the self-em ployed died at work. Many happened on farms and com monly involved tractors and other farm vehicles overturning on their drivers or occupants falling from and being struck by such vehicles. Some nonhighway incidents occurred off of farms (for example, on industrial premises) and in other ways, such as self-employed workers killed solely by falling from a moving vehicle or piece of mobile equipment or by colliding with other vehicles or striking stationary objects, such as trees. The whole category “nonhighway incidents, except rail, air, and water” accounted for 14 percent of the self-employed fatalities and 4 percent of all wage and salary worker deaths reported in the 1993 b l s census. Highway incidents and persons struck by objects other than vehicles or mobile equipment were the two other event and exposure categories to account for at least one-tenth each of the self-employed fatality total. About half of the highway fatalities resulted from collisions between vehicles or mobile equipment; most of the rest were noncollision incidents re sulting from vehicles jackknifing, overturning, or running off the highway. Falling objects, such as trees and construc tion materials, also pose a notable hazard for the self-em ployed. Unlike the other major categories of fatal events, highway incidents appear to pose a lower fatality risk for the self-employed than for wage and salary workers. Occupation of the fatally injured. Farm operator and man ager was, by far, the occupation with the largest number of self-employed fatal injuries reported by the 1993 b l s census. (See table 2.) That farming category accounted for threetenths of the 1,191 self-employed fatalities, triple its onetenth share of the 10 million unincorporated self-employed reported in the 1993 CPS. The following tabulation shows the various types of fatal events and exposures that occurred to the self-employed in farming and other agricultural occupa tions such as groundskeepers and gardeners: Farming fatalities: N um ber..................................................................... P ercent...................................................................... Transportation incident............................................... Nonhighway (for example, tractor rollover)....... Other............................................................................. Contact with object or equipment............................ 413 100 49 34 15 34 Struck by object................................................. 17 Caught in or compressed by equipment orobject O ther............................................................................. Exposure to harmful substance or environment.... All other events............................................................. 13 4 7 10 Sales occupations accounted for about one-sixth of all selfemployed fatalities. Most of the fatalities to self-employed salesworkers were robbery-related homicides involving shop- keepers and other proprietors of small businesses. Sales su pervisors and proprietors, in fact, were especially risky occu pations for the self-employed, accounting for 13 percent of all fatal work injuries among those who work for themselves, yet making up about 8 percent of the employment total for the unincorporated self-employed. By contrast, sales super visor and proprietor occupations had roughly the same share (about 2 percent) of both the fatality and employment totals for wage and salary workers.11 The classification “executive, administrative, and mana gerial” is the remaining occupational group having at least one-tenth of the fatality total for the self-employed. Like sales occupations, many workers in this group were homi cide victims; but most were not, as the following tabulation of fatal events for self-employed executives, administrators, and managers points out: Fatalities to executives, administrators, and managers: Num ber..................................................... Percent...................................................... Assault and violent a c t ................................ H om icid e..................................................... Self-inflicted injury................................... Transportation incident................................ Highway....................................................... A ircraft........................................................ Other............................................................. Contact with object or equipment............ F a ll................................................................... Exposure to harmful substance or environment................................................ Other............................................................. Fatal work injuries among self-employed and wage and salary workers, by occupation, 1993 [In percent] 168 100 Occupation1 SelfWage and employed salary 45 35 10 19 9 5 5 14 11 9 2 Other characteristics of the fatally injured. More than ninetenths of both classes of workers who were fatally injured were men, well above their shares of the Nation’s employ ment. (See table 3.) Men are fatally injured more often than women primarily because of differences in the jobs men and women hold. By race, whites dominate employment and fa tality counts, but Asians, Pacific Islanders, and races other than white or black appear to have a higher risk of a fatal injury on the job than the average self-employed or wage and salary worker.12 A partial explanation for their higher risk may be that, compared with blacks and whites, they are em ployed disproportionately in jobs in which the risk of violent death is relatively high. Homicide accounted for four-fifths of fatal on-the-job injuries to the self-employed who were not black or white and for about half of the wage and salary work ers of these minority races. By contrast, homicide accounted for 22 percent of all self-employed workers and 16 percent of wage and salary workers dying on the job. (See table 1.) As mentioned earlier, older workers face a higher risk of fatal injury than do younger workers. This is especially true for the self-employed, 55 years and older. They made up https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis more than two-fifths of all self-employed fatally injured in 1993, well above their one-fourth share of all employment for the unincorporated self-employed. Those self-employed, aged 65 years and older faced an even higher fatality risk, accounting for nearly one-tenth of the employment, but nearly one-fourth of the fatal injuries of the self-employed. Wage and salary workers also face higher risks with increasing age. Agricultural industries accounted for more fatalities among the self-employed than any of the other major indus try divisions. (See table 3.) Agriculture includes crop and livestock production as well as services performed on a con tract or fee basis, such as crop harvesting, veterinary medi cine, and landscaping. These agricultural activities are Number............................................ Percent............................................. 1,191 100 4,981 100 Managerial and professional....................... Executive, administrative, and managerial........................................ Manager, food serving and lodging establishment....................... Professional specialty.............................. Writer, artist, entertainer, athlete......... 17 10 14 5 3 3 1 1 4 1 17 16 13 2 12 7 Service.......................................................... 2 10 Farming, forestry, fishing.............................. Farm operator and manager..................... Farmworker and supervisor...................... Timber cutting and logging........................ Fisher........................................................ 42 29 4 3 3 8 1 3 2 1 Precision production, craft, and repair......... Mechanic and repairer.............................. Vehicle repairer...................................... Construction trade..................................... Nonsupervisory worker.......................... Carpenter............................................ Electrician............................................ 12 4 2 6 4 1 1 19 Operator, fabricator, laborer......................... Transportation and material moving operation.................................... Motor vehicle operator........................... Truck driver......................................... Cab driver and chauffeur.................... Material moving equipment operator..... Handler, helper, laborer............................. 10 37 8 7 4 2 22 17 14 2 1 1 3 11 Military occupation........................................ - Technical, sales, and administrative support....................................................... Sales occupation....................................... Supervisor, proprietor............................ Technical and administrative support........ 2 5 5 3 10 8 2 1 2 1Based on the 1990 Occupational Classification System developed by the Bureau of the Census. NOTE: Totals for major occupational categories may include data for subcategories not shown separately. Percentages may not add to totals because of rounding. Dash indicates that the category is not applicable. M onthly Labor Review A ugust 1995 27 Fatal Injuries highly risky and account for about one-third of the fatal work injury total of the self-employed, but only about one-eighth of their employment total. Wage and salary workers in agri culture also face fatality risks much higher than their 2-percent share of wage and salary employment would suggest. Interestingly, workers, 55 years and older are a clear major ity of the self-employed fatally injured in agricultural indus tries, but are a small fraction of wage and salary workers dying in that industry. Retail trade establishments, such as grocery stores and restaurants, had contrasting risk patterns by class of worker. Their share of the self-employed who were fatally injured (18 percent) was slightly larger than their 15-percent share of the unincorporated self-employed in 1993. But wage and salary workers in retail trade faced below-average risks of fatal injury (11 percent share of the wage and salary fatality total and 17 percent of wage and salary employees). Part of the difference may reflect the elevated risk of robbery-related homicide faced by the self-employed when working alone in retail businesses during evening hours. Services industries are relatively safe workplaces both for the self-employed and for wage and salary workers. Both groups had about a one-eighth share of total fatalities, which is well below the shares (ranging from 25 percent for wage and salary workers to nearly 40 percent for the self-employed) of their employment totals. For the self-employed, “automo tive repair, services, and parking” was the services industry reporting the most fatal injuries in 1993; 44 out of 147 deaths in all services. For wage and salary workers, business ser vices, such as armored car and personnel supply firms, led all other services industries; they reported 172 out of 604 service industry deaths. Like retail trade, construction industries manifest contrast ing risk patterns by type of worker. But in the construction industry, it is the wage and salary worker, rather than the self-employed individual, who faces relatively high fatality risks on the job.13 Construction makes up 16 percent of all wage and salary workers fatally injured, triple its 5-percent share of the employment total for that worker group. By contrast, the industry’s share of the self-employed fatally in jured (11 percent) was slightly lower than its 15-percent em ployment share, suggesting that the fatality rate is lower for self-employed construction workers than for the average selfemployed worker. Relatively low fatality risks for the self-employed in con struction partly reflect their favorable mix of relatively safe construction work, such as carpentry and painting.14 Differ ences in work experience and the amount of actual construc tion work performed are other factors that might help ex plain why the self-employed in the construction industry typi cally face a lower risk of fatal injury than do the wage and salary worker, even within the same trade. M onthly Labor Review Digitized for28 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis A ugust 1995 Summary findings Data from the 1993 Census of Fatal Occupational Injuries and 1993 Current Population Survey show that the self-em ployed as a group sustain a larger share of all fatal work inju ries than their share of total employment would suggest. Compared with wage and salary workers, the self-employed as a group show relatively high risks of fatal injuries, partly reflecting their disproportionate employment in hazardous industries like agriculture and construction and their tendency to be older workers, who are more prone to a fatal injury. In construction, the fact that the self-employed appear to be at less risk than wage and salary workers offsets, in part, the industry’s contribution to the risk differences between the two working groups. Many occupational groups of the self-em ployed also tend to be at relatively high risk, especially farm ers and shopkeepers. Fatal work injuries among self-employed and wage and salary workers, by sex, age, race, and major industry, 1993 [In percent] Characteristic Number................................................. Percent................................................. Selfemployed Wage and salary 1,191 100 4,981 100 Men....................................................... Women................................................. 95 5 92 8 Both sexes: Under 35 years................................. 35 to 44 years................................... 45 to 54 years................................... 55 years and older............................ 55-64 years.................................. 65 years and older........................ 16 22 20 42 19 23 39 26 19 17 12 5 85 6 5 4 80 12 3 5 Agriculture............................................ Under age 5 5 .................................... 55 years and older............................ 36 15 21 6 4 1 Nonagricultural (private)....................... Forestry and fishing.......................... Mining................................................ Construction...................................... Manufacturing................................... Transportation and public utilities....... Wholesale trade................................ Retail trade........................................ Finance, insurance, and real estate .. Services............................................ 64 4 1 11 5 7 2 18 2 12 81 1 3 16 14 16 5 11 2 12 Government......................................... — 13 Sex and age Race W hite.................................................... Black..................................................... Asian or Pacific Islander....................... Other or unspecified............................. Major industry NOTE: Percentages may not add to totals because of rounding. Dash indicates that the category is not applicable. The Census of Fatal Occupational Injuries contains rich sets of information about how deadly incidents occur. Such deadly patterns differed by type of worker. The self-employed were more likely to become a homicide victim than were wage and salary workers. The next most common ways in which the self-employed died at work were tractor rollovers and other nonhighway events, being struck by trees and other nonvehicular objects, and highway incidents. The latter deadly events led all others for wage and salary workers, fol lowed by homicides, being struck by objects, and falls from elevations. Clearly, safety and health practitioners who study these fatalities in greater depth could gain valuable insights into the safety and health problems of the self-employed and their wage and salary counterparts. □ Footnotes 1 For a comprehensive account o f the 1993 b l s Census o f Fatal Occupa tional Injuries, see Guy Toscano and Janice Windau, “The changing character o f fatal work injuries,” Monthly Labor Review, October 1994, pp. 17-28. The 1993 employment data are based on the Current Population Survey ( c p s ), conducted for the Bureau o f Labor Statistics by the Bureau o f the Cen sus. The c p s estimates about 10 million self-employed operating unincorpo rated businesses in 1993. In addition, there were about 3 to 4 million incor porated self-employed that year counted in the c p s as “other wage and salary workers.” The self-employed as a percent o f the total work force (about 120 million in 1993) increases slightly to almost an eighth if both groups o f selfemployed are combined, still less than their share of all fatal injuries at work. il , 2See Joseph D. Phillips, The Self-Employed in the United States (Urbana, University o f llinois, 1962), p. 28. 3 See Phillips, The Self-Employed, for 1940 data and the Current Popula tion Survey, 1993 annual averages. “For an analysis o f age differences between the self-employed and work ers paid wages and salaries, see Eugene H. Becker, “Self-employed workers: an update to 1983,” Monthly Labor Review, July 1984, pp. 14-18. Current data are from the c p s , 1993 annual averages. 5 The fatality rate was 7 per 100,000 workers, aged 55 to 64 and 15 per 100.000 workers, 65 years and older. These compare with a rate of 5 per 100.000 workers, ages 25 to 34. For more information on serious injuries affecting older workers, see Martin Personick and Janice Windau, “Charac teristics o f older workers’ injuries,” Fatal Workplace Injuries in 1993: A Col lection of Data and Analysis, Report 891 (Bureau of Labor Statistics, June 1995), pp. 23-27. 6 The hours at work data are from unpublished tabulations o f Current Population Survey, 1993 annual averages. 7 See Factors that Affect Fatigue in Heavy Truck Accidents, Safety Study (Washington, National Transportation Safety Board, January 1995). n t s b / ss -95/01 8 For a discussion of earnings levels by class of worker, see Theresa J. Devine, “Characteristics o f self-em ployed women in the United States,” Monthly Labor Review, March 1994, especially pp. 29-32. 9 Even when the incorporated self-employed and individuals who work as wage and salary workers in their primary job, but who are self-employed in their second job, are included in the self-employed’s employment figures, the fatality share for the self-employed is greater than their employment share. And the fatality-rate gap would narrow somewhat between the self-employed and wage and salary workers when the longer hours o f the self-employed are considered. 10Because the overall fatality rate is higher for the self-employed than for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis wage and salary workers, the risk premium for the self-employed is some what larger than the overall premium for fatal event and exposure categories that make up an equal or larger share o f all self-employed fatalities than o f wage and salary workers. For example, let us assume an overall fatality rate of 10 per 100,000 self-employed and 5 per 100,000 wage and salary work ers. Applying the homicide shares to each overall rate, the 22-percent share for the self-employed results in a homicide rate of 2.2 per 100,000 self-em ployed; the 16-percent share for wage and salary workers results in a 0.8-rate per 100,000 workers. Moreover, the self-employed may also face a relatively higher risk for certain other events and exposures, like fatal falls, when such events are a slightly larger share o f the wage and salary fatality total than o f the selfemployed fatality total. Using the same overall fatality rates, the self-em ployed fatality rate for falls would be about 0.8 per 100,000 workers (8 per cent of an overall rate of 10 per 100,000 workers), compared with 0.5 for wage and salary workers (10 percent o f a rate of 5 per 100,000 workers). 11Employment by occupation and class of worker appears in unpublished tabulations from the Current Population Survey, 1993 annual averages. 12Employment by race and class o f worker appears in unpublished tabu lations from the Current Population Survey, 1993 annual averages. The tabu lations show that races other than white or black were 4 percent o f the selfemployed and 2 percent o f the wage and salary employment totals that year. Shares o f fatal work injuries held by “races other than white or black” were well above the employment shares for this group in 1993. 13 This pattern also holds for an important subset o f occupations in the construction industry— construction trades. This subset excludes two risky jobs in the construction industry— construction helpers and laborers— which employ far more wage and salary workers than self-employed individuals. Table 2 shows that construction trades composed 6 percent o f all self-em ployed fatalities, which compares with 11 percent o f total employment for the unincorporated self-employed in 1993. By contrast, those trades were 10 percent of the fatality total for wage and salary workers, well above their 3percent share of total employment for those workers. 14Risk differences in construction between the two classes o f workers in part are explained by differences in staffing patterns among individual con struction trades. Within the construction trades category, the self-employed are mostly employed as carpenters or painters, two trades having a relatively low risk o f fatal injury; those two trades are only a third of all wage and salary workers in construction trades. Electricians, electrical power install ers and repairers, and structural metal workers, by contrast three occupations with relatively high fatality risks, together are about 20 percent o f total wage and salary worker employment in all construction trades, but only 5 percent of the self-employed total for all construction trades. M onthly Labor Review A ugust 1995 29 Fatal Injuries APPENDIX: The Census of Fatal O ccu p tio n al Injuries Definitions. For a fatality to be considered within the scope of the program, the decedent must have been employed (that is, working for pay, compensation, or profit) at the time of the event, engaged in a legal work activity, or present at the site o f the incident as a re quirement of his or her job. These criteria are generally broader than those used by Federal and State agencies administering spe cific laws and regulations. Fatalities that occur during a person’s commute to or from work are excluded from the census counts. Data presented in this article include deaths occurring in 1993 that resulted from traumatic occupational injuries. An injury is defined as any intentional or unintentional wound or damage to the body resulting from acute exposure to energy, such as heat or electricity or kinetic energy from a crash, or from the absence of such essentials as heat or oxygen caused by a specific event or incident or series o f events within a single workday or shift. In cluded are open wounds, intracranial and internal injuries, heat stroke, hypothermia, asphyxiations, acute poisonings resulting from a short-term exposure (limited to the worker’s shift), sui cides and homicides, and work injuries listed as underlying or con tributory causes of death. Information on work-related illnesses are excluded from the b l s census because of the latency period of many occupational illnesses and the resulting difficulties associated with linking illnesses to work. Partial information on fatal occupational illnesses, compiled separately, is available for 1991 through 1993 in b l s Report 891. M easurem ent techniques and lim itations. Data for the Census of Fatal Occupational Injuries are compiled from various State and Federal administrative sources— including death certificates, work ers’ compensation reports and claims, reports to various regulatory agencies, and medical examiner reports— as well as news reports. Multiple sources are used because studies have shown that no single source captures all job-related fatalities. Source documents are matched so that each fatality is counted only once. To ensure that a fatality occurred while the decedent was at work, information is verified from two or more independent source documents, or from a source document and a followup questionnaire. Approximately 30 data elements are collected, coded, and tabulated, including infor mation about the worker, the fatal incident, and the machinery and equipment involved. Because some State laws and regulations prohibit enumerators from contacting the next-of-kin, it was not possible to independently verify work relationship (whether a fatality is job related) for 277 fatal work injuries in 1993; however, the information on the initiating source document for these cases was sufficient to determine that 30 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 the circumstances of the incident was likely to be job related. Data for these fatalities, which primarily affected the self-employed, are included in the Census of Fatal Occupational Injuries counts. An additional 49 fatalities submitted by the States were not included because the initiating source document had insufficient information to determine work relationship, which could not be verified by either an independent source document or a followup questionnaire. States may identify additional fatal work injuries after data col lection closeout for a reference year. In addition, other fatalities excluded from the published count because of insufficient informa tion to determine work relationship may be subsequently verified as work related. States, therefore, have up to 1 year to update their initial published State counts. This procedure ensures that fatality data are disseminated as quickly as possible and that no legitimate case is excluded from the counts. As data collection methods im prove, future fatal work injury counts may become more complete. F ederal/State agency coverage. The Census of Fatal Occupational Injuries include data for all fatal work injuries, whether they are covered by the Occupational Safety and Health Administration (OSHA) or other Federal or State agencies or are outside the scope of regulatory coverage. Thus, any comparison between the b l s census counts and those released by other agencies should take into ac count the different coverage and definitions being used. Several Federal and State agencies have jurisdiction over work place safety and health, o s h a and affiliated agencies in States with approved safety programs cover the largest portion of America’s workers. However, injuries and illnesses occurring in several other industries, such as coal, metal, and nonmetal mining, and transpor tation on water, rails, or in the air, are excluded from o s h a coverage because they are covered by other Federal agencies, such as the Mine Safety and Health Administration, the U.S. Coast Guard, the Federal Railroad Administration, and the Federal Aviation Admin istration. Fatalities occurring in industries regulated by Federal agencies other than o s h a accounted for about 11 percent o f the fatal work injuries in 1993. Fatalities occurring among several other groups o f workers gen erally are not covered by any Federal or State agencies. These groups include self-employed and unpaid family workers, which together accounted for about 21 percent of the fatality total; labor ers on small farms, making up about 5 percent o f that total; and State and local government employees in States without 0SHA-approved safety programs, about 4 percent. (About half of the States have approved o s h a safety programs which include State and local government employees in their coverage.) Unemployment Indicators International unem ploym ent indicators, 1983-93 Sweden has the largest increase in labor underutilization for 1983-93 when part-time work for economic reasons is taken into account; Japan’s rate increases most when discouraged workers are added Constance Sorrentino C o nstan ce Sorrentino is a n e c o n o m is t in th e Division o f Foreign La bo r Statistics, Bureau of Labor Statistics. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis even unemployment indicators, known as U -l to U -7, for nine major industrial countries were presented in the March 1993 issue of the Monthly Labor Review.' The data in the initial analysis covered just the year 1989. The indicators have a large cyclical com ponent, and international relationships might change, depending on the phase of the business cycle in each country. To investigate these rela tionships further, this article presents data for a series of years, spanning relatively high and low unemployment periods from 1983 to 1993. The sequence of indicators U -l to U-7 illus trates a range of unemployment measures going from a very narrow to a very broad view. Under this framework, U-5 is the official, usually cited U.S. unemployment rate, referred to as the con ventional measure here. U -l through U-4 nar row in on certain types of unemployment that reflect parts of U-5, while U-6 and U-7 portray broader concepts of underutilization than U-5, respectively bringing into consideration persons working part time for economic reasons and dis couraged workers. In general, this article reinforces the findings of the 1993 one. The principal finding of that study was that Japan and Sweden, the countries with the lowest unemployment rates as conven tionally measured, had by far the largest in creases when the definition was expanded to in clude persons working part time for economic reasons and discouraged workers. This contin ued to be the case. The current study shows that, S in times of recession and recovery alike, the Japanese unemployment rate consistently tripled when these additional measures of underutili zation of labor were incorporated. For Sweden, the most inclusive indicator more than doubled until 1992-93, when labor market conditions de teriorated drastically and the conventional rate jumped sharply, resulting in some closing of the differential between the conventional and ex panded rates. Sweden’s unemployment rate, which was the lowest of all countries in the earlier study, has subsequently risen to unprecedented postwar lev els due to a severe recession. In 1993, Sweden’s unemployment rate of 9.3 percent, as conven tionally defined, surpassed the U.S. rate for the first time. Understanding the effect of Sweden’s pioneering programs for retraining and employ ing the unemployed is important to gaining an appreciation of that country’s labor market situ ation. The addition of persons in labor market programs further increased Sweden’s already high 1993 conventional unemployment rate to 14 percent. Of course, other countries have per sons in labor market programs, but their pro portion of the labor force is small compared with Sweden’s. In the earlier study, Sweden maintained the low est rates for most of the indicators, even when la bor market program participants were added. In this new study, Japan replaces Sweden as the coun try with the best labor market performance across the entire spectrum of indicators in 1992-93. M onthly Labor Review August 1995 31 U nem ploym ent Indicators Upcoming changes in alternative indicators From 1976 to 1993, the Bureau of Labor Statistics pub lished a range of indicators known as U -l to U-7. The framework embodying these indicators was introduced in Julius Shiskin, “Employment and unemployment: the doughnut or the hole?” Monthly Labor Review, February 1976, pp. 3-10. From January 1977 until December 1993, the seven indicators for the United States were published each month in the news release, Employment Situation. The Current Population Survey, which is the source of the U.S. data used in the current article, was revised as of January 1994. The survey was redesigned to include new and revised questions regarding individuals’ employment and unem ploym ent activities, and the collection methodology was changed to a totally computerized environment. (For further information, see “Revisions in the Current Population Survey Effective January 1994,” Employment and Earnings (Bureau of Labor Statistics, February 1994), pp. 17-22.) As a result, publication of the alternative unemployment indicators for the United States was suspended. A forthcoming article in the Review will introduce a new framework of alternative indicators for the United States. The series of international indicators, U -l to U-7, ends with the 1993 Figures shown in the current article. Upon its introduction, the new U.S. framework will be assessed to see whether international comparisons are feasible. Another way of looking at the data is to present them in the form of three elements of labor underutilization: unemploy ment, part-time work for economic reasons, and discourage ment with the labor market. Such a classification shows that unemployment is the largest of the three in all of the countries studied except Japan and Sweden. Thus, for these two coun tries, standard unemployment comparisons miss a great deal of labor force underutilization. Also, ranking the countries ac cording to total labor underutilization rates differs from rank ing them according to unemployment rates. For example, Italy was in the middle of the range of unemployment rates, but had the highest rate of total labor underutilization. Data for Australia, which was not covered in the earlier study, are included in this article. For Germany, the earlier study re ferred to the former West Germany. In the present study, data for West Germany continue to be presented until 1992, when the coverage changes to unified Germany. The addition of what was formerly East Germany raised the indicators for Germany throughout the spectrum. Some small revisions are made to the previously published data for Sweden and the United King dom, and significant revisions are made to three of the indica tors for France and to the U-7 indicator for Japan. (See the appendix for information about these revisions.) 32 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Seven indicators In recognition of the fact that the official rate of unemploy ment is not ideally suited to all types of analyses or uses, the Bureau of Labor Statistics for many years published a series of alternative measures of unemployment based on definitions that were either narrower or broader than the conventional measure. The box on page 33 defines the seven indicators.2 Some of the indicators yield lower unemployment figures than the conventional standard does, while others result in higher figures. Under the U -l through U-7 framework, U-5 is the official, usually cited unemployment rate—the rate from which all the others are derived by either adding or subtracting different population groups. The first four, narrow, indicators (U -l to U-4) focus on certain “more serious” types of unem ployment—respectively, long-term unemployment, job loss, adult unemployment, and unemployment of seekers of full time jobs. U-6 and U-7 portray broader concepts of unemployment than does U-5, bringing into consideration two additional elements of underutilization of labor: persons working part time for eco nomic reasons and discouraged workers.3 U-6 includes the number of unemployed persons seeking full-time work, plus one-half of the number of unemployed persons seeking parttime work and one-half of the number of those involuntarily on part-time schedules for economic reasons. The reasoning behind this formulation is that involuntary part-time workers should be counted as at least partially unemployed; similarly, unemployed persons seeking only part-time work should be given just half the weight of unemployed persons seeking full time jobs, because their employed counterparts work, on aver age, only about half of a full workweek. This indicator moves from the activity-based concept of the labor force used in all the earlier indicators to a “time lost” type of concept. Discouraged workers, added at U-7, are defined as persons without work who want a job, but who are not looking for work because they believe that their search will be unsuccessful.4 Discouraged workers are somewhat more broadly defined in the data presented for Japan and Italy. In both countries, be cause of the special nature of their labor markets, there is a sizable group of persons who want work, are available for work, and are classified as unemployed,5 even though they did not seek employment in the 4 weeks preceding the survey. These persons are awaiting the results of previous applications. The Bureau adjusts the data for Japan and Italy by removing such individuals from U-5, but adding them to U-7. This group does not fit precisely into the framework of rates, falling some where between U-5 and U-7. No similar adjustment is needed for the other countries studied, because the numbers involved are small.6 The conventionally defined unemployment rate, U-5, re mains the most widely accepted measure of unemployment in all countries. Although the other indicators—particularly the expanded ones—are viewed with interest, none of them has been widely adopted by data users for either domestic or international analysis.7 There are three basic reasons for this. First, the U-5 definition is simple and objective, in volving no value judgments about a person’s relative need for work or personal characteristics. Second, as will be shown later, while the alternative measures differ signifi cantly in level, they reflect very similar trends over time; that is, they all send out essentially the same “signal” re garding whether labor market conditions are improving or deteriorating. Third, for purposes of comparison with other countries—especially the major U.S. trading partners—us ers recognize the need for a “common currency”: the rate based on the International Labor Office standards. U-5 is the most readily available, well-understood, and comparable measure. Nevertheless, it is instructive to assess international differ ences in terms of the alternative measures, because they point out differences that are not expressed by the conventional measure. Period studied The year 1983 was chosen as the initial year for the analysis because it was the first year a new series of European Union labor force surveys8 was compiled in accordance with International Labor Office (ILO ) concepts that allowed for international comparisons. A historically compatible series of indicators could be calculated for the full period 1983-93 for five countries: the United States, Canada, Australia, France, and the United Kingdom. However, even for three of these countries, a few indicators were missing for some years: U -7 was unavailable for France before 1989, and U -2 began in 1987 for Australia and in 1984 for the United Kingdom. Japan’s series was fully available from 1984 onward. Thus, only the United States and Canada had the full complement of indicators available for all of the years studied. For the other countries examined, time series analysis for the period was further constrained by changes in surveys. Because of the unavailability of comparable data for earlier years, the German series begins (partially) in 1984, Italy’s in 1986, and Sweden’s in 1987. Only three of the indicators could be calcu lated for Germany in 1984; a more complete series (missing only U-7) begins in 1985. In 1992, revisions were made in European Union survey definitions, causing a historical break more significant for Italy and the Netherlands than for France, Germany, and the United Kingdom. Because of this break, as well as a signifi cant modification in the Dutch national definitions, the data series for the Netherlands terminates in 1991 in this article. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Italian data for 1992 and 1993 are shown, but the rates for earlier years are somewhat understated. The data are annual averages for the United States, Canada, Australia, and Sweden. Japan’s data refer to Feb ruary of each year, and the data for the European Union countries generally refer to the spring, except that Italian data for 1992 are for October. Patterns over time Table 1 shows the seven indicators for the United States and the nine foreign countries studied for the years from 1983 to 1993 for which data were available. The figures relate to both sexes combined; figures were also calculated for men and women separately, but are not shown in the table.9 Some averages for men and for women are presented later in the article. Chart 1 depicts the trend over time of six indicators (U-4 is excluded because it is virtually the same as U-5) for the United States, Australia, Japan, France, Italy, and Sweden. Alternative unemployment indicators U -l Long-duration unemployment rate: Persons un employed 13 weeks (see footnote 2 in text) or longer, as a percent of the civilian labor force. U-2 Job loser rate: Job losers, as a percent of the civilian labor force. U-3 Adult unemployment rate: Unemployed persons aged 25 and older, as a percent of the civilian labor force aged 25 and older. U -4 Full-time unemployment rate: Unemployed seek ers of full-time jobs, as a percent of the full-time labor force. U-5 Conventional unemployment rate: Number of persons not working, but available for and seeking work, as a percent of the civilian labor force. Only persons on layoff and persons waiting to start a new job are not re quired to seek work in the past 4 weeks, a necessary con dition for all others classified as unemployed. U-6 Rate encompassing half of the persons working part time for economic reasons: Number of seekers of full-time jobs, plus one-half of all seekers of part-time jobs, plus one-half of all persons working part time for economic reasons, as a percent of the civilian labor force, less one-half of the part-time labor force. U-7 Rate adding discouraged workers: U -6 plus discouraged workers in the numerator and denominator. M onthly Labor Review August 1995 33 U nem ploym ent Indicators Table 1. Alternative unemployment indicators, U-1 to U-7, 10 countries, available years, 1983-93 [In percent] Country and year U-1 U-2 U-3 U-4 U-5 U-6 U-7 4.0 2.6 2.2 2.1 1.8 1.5 1.2 1.3 2.0 2.8 2.5 5.6 3.9 3.6 3.4 3.0 2.5 2.4 2.7 3.7 4.2 3.7 7.5 5.8 5.6 5.4 4.8 4.3 4.0 4.4 5.4 6.1 5.6 9.5 7.2 6.8 6.6 5.8 5.2 4.9 5.2 6.5 7.1 6.5 9.6 7.5 7.2 7.0 6.2 5.5 5.3 5.5 6.7 7.4 6.8 12.6 10.1 9.6 9.4 8.5 7.6 7.2 7.6 9.2 10.0 9.3 13.9 11.2 10.6 10.3 9.3 8.4 7.9 8.2 10.0 10.8 10.2 6.1 5.4 5.0 4.3 4.0 3.3 3.1 3.3 4.8 5.7 5.9 7.0 6.4 5.8 5.3 4.8 4.0 3.9 4.4 6.1 6.7 6.5 10.3 9.3 8.8 8.0 7.5 6.7 6.6 7.0 9.0 9.9 9.9 11.9 11.2 10.3 9.4 8.7 7.6 7.4 8.0 10.3 11.1 11.0 11.8 11.2 10.5 9.5 8.8 7.8 7.5 8.1 10.3 11.3 11.2 14.3 13.8 12.9 12.0 11.1 9.8 9.5 10.1 12.9 14.2 14.4 15.7 14.8 13.8 12.7 11.7 10.3 9.9 10.6 13.6 14.9 15.2 6.2 5.7 5.1 4.7 4.8 4.1 3.2 3.5 5.9 7.4 7.4 (’) (’) (<) (’) 2.7 2.3 1.8 2.4 4.1 4.4 3.9 7.0 6.3 5.9 5.7 5.9 5.3 4.6 5.1 7.3 8.4 8.7 10.1 9.0 8.1 7.9 8.0 6.9 5.8 6.7 9.6 10.9 11.0 10.0 9.0 8.3 8.1 8.1 7.2 6.2 6.9 9.6 10.8 10.9 12.2 11.0 10.1 10.1 10.3 9.3 8.3 9.4 12.9 14.7 14.8 13.6 12.3 11.2 11.1 11.4 10.3 9.2 10.4 14.3 16.2 16.3 1.4 1.3 1.4 1.6 1.4 1.1 1.0 .9 .9 1.1 .8 .8 .8 .7 .7 .5 .4 .4 .4 .6 2.3 2.2 2.2 2.3 2.1 1.8 1.7 1.4 1.5 1.8 2.2 2.2 2.2 2.3 2.0 1.8 1.6 • 1.5 1.6 1.8 2.6 2.6 2.6 2.8 2.6 2.2 2.1 1.9 1.9 2.2 3.8 3.7 3.7 3.9 3.3 3.1 2.7 2.5 2.7 3.2 7.6 8.0 8.1 8.6 7.7 7.1 6.4 6.0 6.1 7.0 .9 .7 .6 .6 1.2 2.7 5.1 1.2 .9 .7 .8 1.7 3.5 6.4 1.6 1.4 1.1 1.3 2.3 4.2 6.7 2.2 2.0 1.6 1.9 3.3 6.2 9.9 2.2 1.9 1.6 1.8 3.1 5.6 9.3 4.9 4.1 3.7 4.1 6.0 9.5 14.3 5.5 4.5 4.1 4.6 6.9 10.8 15.8 6.7 8.0 8.9 8.8 9.2 8.6 8.1 3.4 .9 4.1 4.2 4.7 4.4 4.1 5.6 6.5 7.2 7.7 8.4 8.2 8.1 8.3 10.2 10.9 10.8 11.3 10.7 10.0 8.0 9.6 10.3 10.3 10.8 10.3 9.7 9.5 11.5 12.5 13.3 13.5 12.8 12.3 0 (’) (') (') (’) (’) 12.4 United States 1983 ...................................... 1984...................................... 1985 ...................................... 1986 ...................................... 1987...................................... 1988 ...................................... 1989 ...................................... 1990 ...................................... 1991 ...................................... 1992...................................... 1993 ...................................... Canada 1983...................................... 1984 ...................................... 1985 ...................................... 1986 ...................................... 1987...................................... 1988 ...................................... 1989 ...................................... 1990 ...................................... 1991 ...................................... 1992...................................... 1993 ...................................... Australia 1983 ...................................... 1984...................................... 1985 ...................................... 1986 ...................................... 1987...................................... 1988 ...................................... 1989 ...................................... 1990...................................... 1991 ...................................... 1992...................................... 1993...................................... Japan 1984 ...................................... 1985 ...................................... 1986 ...................................... 1987 ...................................... 1988 ...................................... 1989....................................... 1990 ...................................... 1991 ...................................... 1992 ...................................... 1993 ...................................... Sweden 1987...................................... 1988 ...................................... 1989 ...................................... 1990...................................... 1991 ...................................... 1992 ...................................... 1993...................................... European Union France 1983...................................... 1984...................................... 1985 ...................................... 1986 ...................................... 1987...................................... 1988 ...................................... 1989 ...................................... 34 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Continued—Alternative unemployment indicators, U -l to U -7 . 10 countries, available v e a r s . 1983-93 [In percent] C ountry a n d y e a r U -1 U -2 U -3 U -4 U -5 U -6 U -7 7.6 7.5 7.5 8.5 4.5 4.5 5.9 6.9 7.7 7.7 8.7 9.6 9.7 9.7 10.8 12.1 9.5 9.3 10.4 11.5 11.7 11.3 12.7 14.5 11.8 11.5 12.9 14.7 C ontinued— France 1990 1991 1992 1993 ............................ ............................ ............................ ............................ G e rm a n y West G e rm a n y 1983 ............................ 1984 ............................ 1985 ............................ 1986 ............................ 1987............................ 1988 ............................ 1989 ............................ 1990 ............................ 1991 ............................ (’) (’) (’) (') (') 5.8 6.2 6.3 6.7 6.2 5.8 5.0 4.2 O 2.4 2.3 2.5 2.1 1.7 1.3 1.1 6.5 6.2 6.5 5.9 5.3 4.6 4.0 6.7 6.9 6.7 6.9 6.4 5.8 4.9 4.1 (’) 7.2 7.0 7.3 6.7 6.0 5.2 4.5 (’) (’) (') (’) O (1) (’) (’) (’) 5.0 6.1 3.6 4.4 6.4 7.8 6.4 7.9 6.4 7.7 7.1 8.8 (’) (’) 6.8 7.2 7.3 7.3 6.3 6.4 8.0 9.3 .6 .7 .6 .6 .5 .6 1.4 1.9 3.3 3.7 3.9 4.3 3.8 3.9 6.0 6.8 7.4 7.9 8.0 8.0 6.9 7.0 9.5 10.4 7.2 7.6 7.7 7.8 6.6 6.8 9.5 10.4 9.7 10.3 10.1 10.0 8.5 9.0 11.5 12.7 15.9 16.1 16.0 15.8 13.8 15.0 6.2 18.0 ( 1) 9.5 11.6 11.9 (’) (’) (1) 0 8.8 5.4 5.6 5.5 5.6 5.2 4.6 4.0 3.2 O O Unified G e rm a n y 1992............................ 1993 ............................ Italy 1986............................. 1987............................ 1988 ............................ 1989 ............................ 1990 ............................ 1991 ............................ 19922 .......................... 1993 ............................ Netherlands 1983 ............................ 1984 ............................ 1985 ............................ 1986 ............................ 1987 ............................ 1988 ............................ 1989 ............................ 1990 ............................ 1991 ............................ 10.4 O 9.2 ( ') ( ’) 7.8 7.5 6.9 5.9 5.3 1.2 1.1 .6 .6 9.0 8.7 9.1 8.9 8.5 6.8 5.2 4.7 5.8 7.4 8.2 3.2 2.8 2.7 2.6 2.1 1.5 1.4 2.6 4.0 4.2 0) 10.2 O O 10.6 (') 12.1 12.4 n ( 1) 8.0 8.1 7.6 6.9 6.4 7.8 7.5 6.9 5.8 5.5 10.0 9.5 8.8 7.8 7.4 12.5 12.4 11.8 10.5 10.2 13.4 13.3 12.6 11.4 10.9 8.5 8.6 9.5 9.5 9.6 7.8 6.6 6.1 7.3 8.4 8.8 13.0 12.5 12.5 12.6 12.2 9.7 8.0 7.5 9.6 11.5 12.1 11.1 11.0 11.5 11.6 11.1 9.1 7.4 7.0 8.6 9.8 10.3 13.1 13.0 13.3 13.4 13.0 10.6 8.7 8.1 10.3 12.2 13.1 13.9 13.8 14.1 14.3 13.6 11.1 9.1 8.4 10.6 12.8 13.8 ( ') ( ’) O United Kingdom 1983 ............................ 1984 ............................ 1985 ............................ 1986 ............................ 1987 ............................ 1988 ............................ 1989 ............................ 1990 ............................ 1991 ............................ 1992 ............................ 1993 ............................ ( ’) 1 Not available. Break in series for Italy. New survey methods were introduced in 1992 that raised the adjusted U-5 rate by approximately 1 percentage point. U-6 , rate encompassing persons working part time for ec:onomic reasons; UI—7, U-6 plus discouraged workers. SouRCE: Compi|ed by Bureau of Labor Statistics frQm |abor force su(veys for NOTE: U-1, long-term unemployment rate; U-2, job loser rate; U-3, adult | unemployment rate; U-4 , full-time unemployment rate; U-5, conventional rate; each country. Some adjustments are made for comparability with U.S. concepts. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 35 U nem ploym ent Indicators C h art 1. Alternative unemployment indicators, U-l to U-3 and U-5 to U-7, six countries, 1983-93 Australia United States Percent Percent France Japan Percent Percent Italy 36 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Sweden Percent Percent August 1995 Table 2. Alternative unemployment indicators, U-l to U-7, 10 countries, average rates for available years, 1983-93 [In percent] Country Years U -l U-2 U-3 U-4 U-5 U-Ó U-7 Both sexes United States Canada ........ Australia....... Japan ........... Sweden ......... European Union: France.................. Germany3 ............ West Germany.... Unified Germany. Ita ly ...................... Netherlands......... United Kingdom 1983-93 1983-93 1983-93 1984-93 1987-93 2.2 4.6 5.3 1.2 1.7 3.5 5.5 1 3.1 .6 2.2 5.4 8.5 6.4 1.9 2.7 6.5 9.7 8.5 1.9 3.9 6.8 9.8 8.6 2.4 3.6 9.2 12.3 11.2 3.3 6.7 10.1 13.0 12.4 7.3 7.5 1983-93 1985-93 1985-91 1992-93 1986-93 1983, 1985, 1987-91 1983-93 8.1 5.0 4.8 5.6 7.3 4.6 2.4 1.9 4.0 .9 7.8 6.1 5.8 7.1 4.5 10.4 5.9 5.6 7.2 8.1 10.0 6.2 6.0 7.1 8.0 12.3 6.6 6.3 8.0 10.2 ! 12.7 7.6 7.5 «.9 «2.7 7.9 8.2 7.9 11.0 9.4 9.9 11.7 11.7 12.4 12.3 1983-93 1983-93 1983-93 1984-93 1987-93 2.6 4.8 5.6 1.2 2.0 4.3 6.5 ’ 3.9 .7 2.6 5.4 8.1 6.4 1.7 3.0 6.5 9.6 8.3 1.9 4.1 6.9 9.9 8.5 2.1 4.1 8.8 11.3 10.1 2.7 5.5 9.5 11.9 10.6 4.3 6.2 1983-93 1985-93 1985-91 1992-93 1986-93 1983, 1985 1987-91 1983-93 6.4 4.2 4.1 4.4 5.2 4.3 2.2 1.9 3.2 .8 6.2 5.0 4.8 5.7 3.0 8.4 5.2 5.0 5.7 5.8 8.0 5.2 5.1 5.8 5.7 9.2 5.5 5.2 6.3 7.5 2 9.2 (4) (4) (4) 10.3 6.3 8.5 5.9 «3.7 6.2 8.9 7.3 11.1 7.7 10.7 8.7 11.7 9.0 12.3 1983-93 1983-93 1983-93 1984-93 1987-93 1.8 4.3 4.8 1.3 1.4 2.6 4.3 1 2.0 .5 1.7 5.3 8.7 6.3 2.4 2.3 6.5 9.8 9.2 2.0 3.5 6.7 9.9 8.8 2.8 3.6 9.7 13.7 13.0 4.3 8.2 10.9 14.7 15.5 10.3 6.1 5.8 7.0 11.2 5.1 2.6 1.9 5.1 .9 9.8 7.7 7.3 9.1 7.2 13.6 7.4 6.8 9.7 13.1 12.4 7.6 7.3 8.8 12.0 16.7 8.6 8.1 10.6 15.7 ! 17.4 9.6 6.0 5.9 «1.4 11.0 7.3 9.4 10.7 12.2 8.8 17.9 11.7 19.2 12.4 (4) (4) (4) 15.9 M en United States........ Canada ................. Australia................ Japan .................... Sweden................. European Union: France................... . Germany 3.............. West Germany.... Unified Germany. Italy........................ Netherlands........... United Kingdom Women United States........... Canada .................... Australia................... Japan ....................... Sweden .................... European Union:...... France....................... Germany3 ................ . West Germany...... Unified Germany ... Ita ly ........................... Netherlands.............. United Kingdom 1983-93 1985-93 1985-91 1992-93 1986-93 1983, 1985, 1987-91 1983-93 11987-93. 21989-93. 3 Former West Germany, 1985-91; unified Germany, 1992-93. 4 Data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 11.8 9.1 ( 4) (4) (4) 25.7 51988-91. «1984-93. SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for each country. Some adjustments are made for comparability with U.S. concepts. M onthly Labor Review A ugust 1995 37 U nem ploym ent Indicators The general pattern of all seven indicators in all of the coun tries studied, including those not shown, is movement in tan dem. Another observation is that only in the two North American countries (Canada’s pattern is similar to the United States’) and Sweden did U -l through U-7 represent a pro gression from low to successively higher unemployment rates. Although U-4 is not shown in the chart, some mention of it should be made. In most countries, the unemployment rate relating to full-time workers (U-4) was noticeably higher than the adult unemployment rate (U-3). The gap between these two rates was widest in Italy, where adult unemploy ment is very low and most unemployment is associated with young persons. By contrast, in Japan, the youth-adult differ ential was much narrower than in Italy, and the two rates tended to be the same. Germany and the Netherlands had the same pattern as Japan for U-3 and U-4. In all but the Netherlands and the United Kingdom, U-4 (the rate for full-time workers) virtually coincided with U-5, the conventional measure. In these two countries, the unemployment rates associated with seekers of full-time and of part-tim e jobs were widely different. In the Netherlands, the rate for seekers of part-time jobs was almost twice as high as the rate for seekers of full-time jobs. Consequently, U -4 was substantially below U-5 in that country. In the United Kingdom, the opposite was true, and the high rate for seekers of full-time jobs was reflected in U -4 ’s surpassing U-5. The upward climb of unemployment in Sweden since 1990 is dramatically portrayed in the chart. Sweden’s series begins with the year 1987, but earlier years would have shown rates in the range of the low 1987 levels. Sweden’s U-5 rate averaged 3 percent from 1983 to 1986, equivalent to about 2.6 percent according to the survey methods and definitions used in 1993. Averages over time Table 2 presents the indicators in terms of their averages over the available years of the 1983-93 period. Table 3 expresses these figures in terms of each indicator’s ratio to the conventional measure, U-5. This is a convenient means of comparing the various rates within and among countries. The averages for the period would generally show the same comparative results as the figures for any given year; exceptions are the higher levels of unem ploym ent experienced in Sweden and unified Germany in 1992-93, which changed some relationships that existed in prior years. Tables 2 and 3 show the data for the former West Germany and unified Germany separately. In each table, figures are shown for both sexes, for men, and for women. Data for U-7 are not available for Germany. For France, data on discouraged workers were available only 38 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 for 1989-93, and the average for these years is included in the table. Tables 2 and 3 recapture some of the findings already por trayed in chart 1. The ratios form a progression from low to successively higher rates only in the United States and Canada. Sweden’s pattern is similar, except that U -4 is above U-5. All the European Union countries had much higher ratios at U -l than at U-2, and Australia was more like the European countries than the North American coun tries. Italy was at the extreme: on average, long-duration unemployment made up more than 90 percent of conven tionally measured unemployment in Italy, while job losers accounted for only about 10 percent. West Germany had a very low job loser rate, but unified Germany’s rate was above the U.S. average. Table 3 shows that Sweden had by far the largest propor tionate increases in unemployment as measured by U-6, which takes into account the hours lost by persons working part time for economic reasons. The Swedish U-6 rate was more than 80 percent higher than the U-5 rate, on average, whereas the increases for the other countries were much smaller. Sweden’s ratio of U-6 to U-5 declined as unem ployment rose in 1992-93. However, even the lower values of this ratio were higher than the U -6/U-5 ratio in other countries. Germany had the smallest increase in U-6 over U-5, and even the higher 1992-93 figures for unified Ger many were lower than for the other countries. In the United States, U -6 ranged from 31 percent to 38 percent higher than U-5 throughout the 1983-93 period. Except for Swe den, other countries also had ratios that fluctuated over time within a narrow range. Japan had by far the largest proportionate increase in unemployment as measured by U-7. The rate accounting for both persons holding part-time jobs for economic reasons and discouraged workers was about triple the conventional measure in every year of the period. In those years in which unemployment was lowest in Japan (1991-92), U-7 was about 320 percent higher than U -5; in the year when Japanese unemployment was highest (1987), U-7 was 307 percent higher than the conventional rate. Thus, a large contingent of potential workers who are not in the labor force overhangs the Japanese labor market at all times. Japan’s increase in U-6 over U-5 was about the same as that for the United States, but the addition of discouraged workers made U-7 increase much more in Japan than in the United States and other countries. Italy also experienced a large increase in its U-7 rate. With some differences in degree, the foregoing relation ships held for both men and women. (See table 3.) For the narrower indicators, U -l through U-4, the differences be tween the rates for men and women in relation to U-5 were not large for most countries. Women tended to have lower Table 3. Alternative unemployment indicators, U-l to U -7 ,10 countries, average ratios of each indicator to U-5 for available years, 1983-93 [In percent] Country Years U-l U-2 U-3 U-4 1983-93 1983-93 1983-93 1984-93 1987-93 32 47 62 50 47 51 56 1 36 25 61 79 87 74 79 75 96 99 99 79 108 100 100 100 100 100 135 126 130 138 186 149 133 144 304 208 1983-93 1985-93 1985-91 1992-93 1986-93 1983,1985, 1987-91 1983-93 81 81 80 79 91 46 39 32 56 11 78 98 97 100 56 104 95 93 101 101 100 100 100 100 100 123 106 105 113 128 * 127 (4) (4) (4) 199 81 76 5 10 e27 84 83 84 111 100 100 124 118 132 124 1983-93 1983-93 1983-93 1984-93 1987-93 38 48 66 57 49 62 66 1 46 33 63 78 82 75 81 73 94 97 98 90 100 100 100 100 100 100 128 114 119 129 134 138 120 125 205 151 1983-93 1985-93 1985-91 1992-93 1986-93 1983,1985, 1987-91 1983-93 80 81 80 76 91 54 42 37 55 14 78 96 94 98 53 105 100 98 98 102 100 100 100 100 100 115 106 102 109 132 2 115 (4) O (4) 181 82 79 M2 6 35 81 83 95 104 100 100 113 109 117 115 1983-93 1983-93 1983-93 1984-93 1987-93 27 43 55 46 39 39 43 1 23 18 47 79 88 72 86 64 97 99 105 71 97 100 100 100 100 100 145 138 148 154 228 163 148 176 421 253 1983-93 1985-93 1985-91 1992-93 1986-93 1983,1985, 1987-91 1983-93 83 80 79 80 93 41 34 26 58 8 79 101 100 103 60 110 97 93 110 109 100 100 100 100 100 135 113 111 120 131 2 140 79 68 57 6 16 90 83 77 122 100 100 147 133 157 141 U-5 U-6 U-7 Both sexes United States....................... C anada.................................. Australia.............................. Japan .................................. Sweden ............................... European Union: France................................. Germany3 ........................... West Germany................ Unified Germany............. Italy...................................... Netherlands......................... United Kingdom.................. Men United States....................... Canada................................ Australia.............................. Japan .................................. Sweden ............................... European Union: France................................. Germany3 ........................... West Germany................ Unified Germany............. Italy...................................... Netherlands......................... United Kingdom.................. Women United States...................... Canada................................ Australia.............................. Japan .................................. Sweden............................... European Union: France................................. Germany3 ........................... West Germany................ Unified Germany............. Italy..................................... Netherlands....................... United Kingdom................. M 987-93 21989-93. 3 Former West Germany, 1985-91; unified Germany, 1992-93. 4Data not available. *1988-91. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 8 (4) 214 *1984-93. SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for each country. Some adjustments are made for comparability with U.S. concepts. M onthly Labor Review August 1995 39 U nem ploym ent Indicators U -l (long-duration unemployment) rates, compared with U-5, than did men in those countries that were not mem bers of the European Union. Within the Union, except for the United Kingdom, the differences between U -l and U-5 were about the same for men as for women. In all the coun tries, the job loser rate (U-2) was more favorable for women than for men, compared with U-5. With few exceptions, adult unemployment rates (U-3) and full-time unemploy ment rates (U-4) had similar relationships to U-5 for both men and women. Greater sex-related differences showed up in the expanded rates. In every country studied except Italy, underutilization, as measured by U-6 and U-7, increased to a considerably greater extent for women than it did for men, and in Sweden and Japan in particular, the difference was very large. (See Table 4. Rank table 3.) In Sweden, the U-7 rate increased just 50 percent for men, but about 2-1/2 times for women, over the U-5 rate. In Japan, U-7 for men was more than double the U-5 rate, but for women it was more than 4 times as great as U-5. In Italy, the ratios of U -6 to U -5 were virtually the same for both sexes, but the spread at U-7 was less favor able for women. These tendencies generally held during re cession and recovery alike. Rankings Table 4 ranks the 10 countries examined in terms of each of the seven indicators, from lowest (best) to highest (worst), on average, over the available years of the 1983-93 period. Japan’s labor market outperformed the others with regard to every Rankings of 10 countries from lowest to highest average rate, available years, 1983-93 U-2 U -l U-3 U-4 U-5 U-6 U-7 Both sexes 1.2 1.7 2.0 4.6 5.0 5.3 7.3 7.5 7.6 8.1 Japan Italy Netherlands Sweden Germany United Kingdom Australia United States France Canada 0.6 .9 .9 2.2 2.4 2.7 3.1 3.5 4.6 5.5 Japan Sweden Italy United States Germany Australia France Netherlands United Kingdom Canada 1.9 2.7 4.5 5.4 6.1 6.4 7.8 7.9 8.2 8.5 Japan 1.9 Sweden 3.9 Germany 5.9 6.5 United States 7.9 Netherlands 8.1 Italy Australia 8.5 Canada 9.7 10.4 France United Kingdom 11.0 2.4 Japan Sweden 3.6 6.2 Germany United States 6.8 8.0 Italy 8.6 Australia Netherlands 9.4 9.8 Canada United Kingdom 9.9 10.0 France Japan 3.3 Germany 6.6 6.7 Sweden 9.2 United States 10.2 Italy 11.2 Australia 11.7 Netherlands United Kingdom 11.7 Canada 12.3 12.3 France Japan 7.3 Sweden 7.5 United States 10.1 United Kingdom 12.3 12.4 Australia 12.4 Netherlands 12.7 France 13.0 Canada 15.9 Italy Germany (1) 1.2 2.0 2.6 4.2 4.8 5.2 5.6 6.3 6.4 8.5 Japan Italy Netherlands Germany Sweden United Kingdom Australia United States France Canada .7 .8 .9 2.2 2.6 3.7 3.9 4.3 4.3 6.5 Japan Italy Netherlands Germany Sweden United Kingdom Australia United States France Canada .7 .8 .9 2.2 3.0 3.7 3.9 4.3 4.3 6.5 Japan Sweden Germany Italy United States Netherlands Australia France Canada United Kingdom 1.9 4.1 5.2 5.8 6.5 7.3 8.3 8.4 9.6 11.1 Japan 2.1 4.1 Sweden Germany 5.2 5.7 Italy United States 6.9 7.7 Netherlands France 8.0 Australia 8.5 9.9 Canada United Kingdom 10.7 2.7 Japan Germany 5.5 Sweden 5.5 7.5 Italy Netherlands 8.7 United States 8.8 France 9.2 Australia 10.1 Canada 11.3 United Kingdom 11.7 Japan 4.3 Sweden 6.2 Netherlands 9.0 9.2 France United States 9.5 10.3 Italy 10.6 Australia Canada 11.9 United Kingdom 12.3 Germany (’) Japan 1.3 1.4 Sweden United States 1.8 Canada 4.3 4.8 Australia United Kingdom 6.0 Germany 6.1 Netherlands 9.6 France 10.3 11.2 Italy Japan Italy Netherlands United Kingdom Sweden Australia Germany United States Canada France .5 .9 .9 1.4 1.7 2.0 2.6 2.6 4.3 5.1 Sweden 2.3 2.4 Japan 5.3 United States 6.3 Australia 7.2 Italy United Kingdom 7.3 Germany 7.7 8.7 Canada 9.8 France Netherlands 11.0 Japan 2.0 Sweden 3.5 United States 6.5 Germany 7.4 9.2 Australia 9.4 Netherlands Canada 9.8 United Kingdom 10.7 Italy 13.1 France 13.6 Japan 2.8 Sweden 3.6 6.7 United States Germany 7.6 8.8 Australia United Kingdom 8.8 9.9 Canada 12.0 Italy 12.2 Netherlands 12.4 France Japan 4.3 Sweden 8.2 Germany 8.6 9.7 United States United Kingdom 11.7 Australia 13.0 13.7 Canada 15.7 Italy 16.7 France 17.9 Netherlands Sweden 9.1 United States 10.9 Japan 11.8 United Kingdom 12.4 14.7 Canada Australia 15.5 17.4 France 19.2 Netherlands 25.7 Italy Germany (’) 1 ..... Japan 2 ..... Sweden 3 ..... United States 4 ..... Canada 5 ..... Germany 6 ..... Australia 7 ..... Italy 8 ..... United Kingdom 9 ..... Netherlands 10...... France Men 1 ..... 2...... 3 ..... 4 ..... 5 ..... 6 ..... 7 ..... 8 ..... 9 ..... 10...... Japan Sweden United States Germany Canada Italy Australia Netherlands France United Kingdom Women 1 ..... 2 ..... 3 ..... 4 ..... 5 ..... 6 ..... 7 ..... 8 ..... 9 ..... 1 0 ..... 1 No data available to rank Germany. NOTE: See table 2 for available years for each indicator. SOURCE: Table 2. 40 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 indicator. Sweden was second to Japan except for U-2 (job losers), where it was displaced by Italy and the Netherlands, and U-6, where it was virtually tied with Germany for second place. Sweden’s rankings are undoubtedly affected by the lack of data for the years 1983-86, which were years of relatively low unemployment. If they had been included, Sweden would most likely have outranked Japan, as it did in each year of the 1987-90 period.10 Also, the table ranks Germany’s averages for the 1985-93 period, with the 1985-91 data referring to the former West Germany and 1992 and 1993 referring to unified Germany. Because of the higher unemployment in the former East Germany, a ranking for unified Germany based only on the 1992-93 period would have been less favorable for all of the indicators except U-6. The United States ranked from third to fourth best for every indicator except job losers (U-2). At 3.5 percent, the U.S. average for this rate was relatively high. Indeed, only France’s and Canada’s U -2 rates were higher. Job loser unemployment averaged under 1 percent in Japan, Italy, and the Netherlands. All indicators for France, Canada (except U -l), and the United Kingdom, the countries with the highest conventional (U-5) rates, were at the high (worst) end of the spectrum. Canada had the highest job loser and adult unemployment rates and was virtually tied with France for the highest U-6 rate. France’s long-duration unemployment rate (U -l) ranked highest, while the United Kingdom had the highest full-time unemployment rate (U-4). Italy, which had a midrange U-5 rate, had the highest U-7 rate. The rankings changed somewhat when the sex of the person was taken into account. The most striking change was for Japa nese women, who experienced a relatively high U-7 rate. Rank ing best in their U-6 rate among women in all the countries Table 5. studied, Japanese women fell behind women in both the United States and Sweden when discouraged workers were added. Dutch women had the highest (again, worst) U-3 and U-6 rankings and the next-to-highest U-5 and U-7 rankings. Dutch men fared much better in these categories. The 1993 study presented an indepth analysis of each of the seven indicators and the reasons behind the international differences noted. The next two sections highlight results relating to two of the narrow indicators—U-2 and U -3— and the section that follows uses the data developed for U-6 and U-7 to present measures of total labor underutilization. The final section, on Sweden, takes into account that country’s participants in labor market programs, through a broader measure of labor underutilization. Unemployment by former status Unemployed persons can be classified into four categories based on their former employment status: job losers, job leavers, new entrants into the labor force, and reentrants into the labor force. Table 5 shows each of these four groups as a percent of the civilian labor force, averaged for the available years from 1983 to 1993. U -2 focuses on job losers. The foregoing analysis showed that U -2 rates were relatively low in Japan and Europe (except for France), compared with North America, throughout the period studied. This reflects the greater level of job security and protection for regular workers in Japan and Europe. Italy was an extreme case, with virtually no job loser un employment, but a very high proportion of unemploy ment associated with new entrants into the labor market. Throughout the 1986-93 period, new entrants in Italy Unemployment rates by former status, average of available years, 1983-93 [In percent] Country Job losers United States.......................................................................'............ Canada ............................................................................................ Australia............................................................................................ Japan ................................................................................................ Sweden ............................................................................................. Job leavers New entrants 3.5 5.5 3.1 .6 2.2 0.8 1.7 1.4 .9 .3 0.8 .4 1.5 (1) .5 1.7 2.3 2.2 (') .6 4.6 2.4 1.9 4.0 .9 .9 2.7 2.0 1.9 2.0 1.4 .2 1.9 2.6 1.3 .4 .5 .3 5.2 1.7 1.0 2.1 1.5 1.6 1.4 1.7 3.7 3.2 Reentrants European Union France............................................................................................... Germany.......................................................................................... West Germany (1985-91)............................................................ Unified Germany (1992-93)......................................................... Netherlands...................................................................................... United Kingdom................................................................................ ’ Not available separately; combined rate for new entrants and reentrants was 0.9 percent. NOTE: Available years as noted on table 1 for U-2. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for each country. Some adjustments are made for comparability with U.S. concepts. M onthly Labor Review August 1995 41 Unem ploym ent Indicators had unemployment rates in the 5-percent range. This figure stands out because none of the other countries studied had an unem ploym ent rate for new entrants exceeding 2 percent during the period. Among the European Union countries, only France had a pattern similar to North America’s, with job losers bear ing the brunt of unemployment among the four catego ries listed. The 1993 study postulated that this was be cause 1989 was a year of high unemployment for France, and job losses tend to be cyclical. However, even in France’s years of lower unemployment during the 1980’s, the higher job loser rates persisted. West Germany had the more typical European Union pattern in most years, with job losers having rates similar to or lower than those of job leavers. Nonetheless, unified Germany experienced much higher job loser rates compared with the other cat egories. This resulted in the job loser average for Ger many moving above the averages of the other groups for the period. The phenomenon was related to the difficul ties of transition to a market economy in the former East Germany. Youth and adult unem ploym ent Unemployment among adults (aged 25 and older), as re flected in U-3, was significantly lower than unemployment among youth (under age 25) in every country studied except Germany, where a strong apprenticeship system shields many youth from unemployment. In all the other countries, there was a significant youth-adult differential, as shown in the following tabulation of averages for the available years: Adult rate Youth rate Ratio, youth to adult United States......................... ............ Canada.................................... ............ 5.4 13.1 2.4 8.5 Australia................................ ............ Japan ....................................... ............ 6.4 15.9 15.8 1.9 2.5 2.7 5.6 9.7 2.8 S w ed en ................................... ............ European Union: France ..................................... ............ Germ any................................ ............ 7.8 6.0 22.5 7.1 7.2 2.9 2.0 3.6 Unified Germany................ ............ Italy......................................... ............ Netherlands........................... ............ 7.0 1.2 1.2 1.0 4.5 25.9 5.8 7.9 15.3 1.9 United Kingdom................... ............ 8.2 15.8 1.9 West Germany.................... ............ 5.8 7.1 Because of the low youth-adult unemployment differential in Germany, that country’s U-3 and U-5 unemployment rates were virtually identical. The incorporation of the former East M onthly Labor Review Digitized for42 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Germany into unified Germany in 1992 did not alter this fact. In contrast, U-3 was significantly lower than the conventional U-5 rate in all the other countries studied. (See table 3.) Italy’s U-3 measure was particularly low in relation to U-5 because youth unemployment there was about 6 times higher than adult unemployment. Indeed, most Italian unemployment occurs among persons under age 25, a phenomenon related to the job loser-new entrant difference for Italy. New entrants into the Italian labor market tend to be young persons, and adults with established jobs tend to be shielded from unemployment in Italy, although they may be subject to underemployment in the form of reduced hours. Nevertheless, the gap between youth and adult unemployment closed somewhat in 1992 and 1993 as the youth-to-adult ratio fell to under 5 percent. Some of this decline could have been caused by the changes instituted in the Italian survey in 1992. (See appendix.) Elements of labor underutilization Going beyond the U -l to U-7 framework, we can use the data developed in this study to analyze labor underutilization across countries in its three readily measurable forms: un employment as conventionally defined (the U-5 indicator); persons working part time for economic reasons (part of the U-6 indicator); and discouraged workers (added at the U-7 level). In the reformulation of the data that is set forth in this section, there is no half-weighting of involuntary part-time workers and persons seeking part-time jobs, as was done with U -6 and U-7 earlier. Therefore, the new indicator to be pre sented represents the number of people underutilized to some degree, either partially or totally. Two types of measurement are shown in table 6: (1) a proportionate distribution of the three types of labor underutilization and (2) each form of underutilization as a percent of the civilian labor force. (Note that discouraged workers are not part of the labor force, but if they were added to the labor force in these calculations, the results would be virtually the same.) The data are averages for the available years from 1983 to 1993. Table 6 and chart 2 show that unemployment is the largest of the three elements in all of the countries studied except Japan and Sweden. By this measure, unemployed persons in the United States comprised, on average, a little more than half of all underutilized persons. The unemployed were around three-fifths of the total in Canada, Australia, and the Netherlands, and accounted for even higher proportions in France, Germany, and the United Kingdom. (However, Ger many does not measure discouraged workers, so that the German proportions relate to only two of the three elements.) In Japan, unemployed persons made up only somewhat more than one-quarter of all persons who were underutilized. Table 6. Elements of labor underutilization, 10 countries, averages of available years, 1983-93 Percent distribution Country United States.......................... Canada ................................... Australia.................................. Japan ...................................... Sweden ................................... Percent of civilian labor force Unemployed Part time for econom ic reasons Discouraged workers Unemployed Part time for econom ic reasons Discouraged workers 54.6 64.0 58.6 27.3 40.8 38.0 30.7 32.6 23.7 50.5 7.4 5.2 8.7 48.9 8.7 6.8 9.8 8.6 2.3 3.6 4.7 4.7 4.8 2.0 4.5 0.9 .8 1.3 4.2 .8 12.4 15.3 14.8 8.6 8.9 70.2 85.7 86.9 83.1 45.3 62.9 77.4 28.7 14.3 13.1 16.9 18.9 32.8 17.9 1.1 (1) 10.1 6.2 5.9 7.1 8.0 9.5 9.8 4.1 1.0 .9 1.4 3.3 5.0 2.3 .2 14.3 (’) (’) (’) 17.5 15.2 12.7 Total labor underutilization European Union France..................................... Germany................................. West Germany...................... Unified Germany................... Italy.......................................... Netherlands............................ United Kingdom...................... V) ’ Not available. NOTE: See table 7 for available years. Persons seeking part-time jobs and persons working part time for economic reasons are fully counted in this tabu lation, in contrast to U-6 and U-7, for which they are only half-weighted. Discouraged workers were the predominant manifestation of labor underutilization in Japan, at almost half of the total. Thus, discouraged workers in Japan comprised about the same proportion of underutilization as unemployed persons did in the United States. In Sweden, persons involuntarily working part time were the main element of underutilization. Persons working part time for economic reasons and dis couraged workers together added 5 to 7 percentage points to the unemployment rate in most countries, on average, for the 1983-93 period. The United Kingdom had the smallest addition—about 3 percentage points, while Italy had the larg est—9.5 percentage points. Unemployment rates, on average for the period, varied from 2.3 percent in Japan to 10 percent in France. On the other hand, the rate of total labor underutilization varied from 8 percent in Japan and 10 percent in Sweden to 17.5 percent in Italy. France, the country with the highest unem ployment rate, ranked in the middle of the range on the total underutilization basis because its discouraged worker rates were very low. (The discouraged worker rates for France were averages for 1989-93, the only years for which such rates were available.) Italy, on the other hand, ranked in the middle of the range of unemployment rates, but had the highest rate of total labor underutilization. The economic part-time rate was highest in the Nether lands, at 5 percent. With the exception of the Netherlands, involuntary part-time rates in the European Union countries were significantly lower than in North America, Australia, and Sweden. The discouraged worker rates were 4 percent in Japan and 6 percent in Italy, far higher than in any of the other countries. As noted earlier, the definition of discour https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis n 35.8 4.4 4.7 o (1) (’) 6.3 .7 .6 SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for each country. Some adjustments are made for comparability with U.S. concepts. aged workers is somewhat broader in these countries, in cluding within its scope persons who are awaiting the re sults of jobseeking efforts. Discouraged worker rates were 1 percent or less in all the other countries studied. In Japan, large numbers of women who are temporary or casual workers withdraw from the labor force when they lose their jobs, rather than seek work. Such workers generally bear the brunt of labor market adjustments in Japan. In this way, Japanese employers have flexibility in their work forces during economic downturns, enabling regular workers—pre dominantly men in larger Japanese enterprises—to be virtu ally assured of employment until they retire, under Japan’s so called lifetime employment system.11 Italy’s labor market matches people with jobs very slowly. Hence, there is a large number of persons who want work and are awaiting the results of previous job applications or are awaiting the results of competitions for jobs in the public sector (which can take a year or longer), rather than active ly seeking work. As noted earlier, they have been added to the discouraged worker figures for Italy, even though they may not be in a state of mind we would characterize as discouragement. Over time, the three component rates of labor under utilization tended to move cyclically in the same direc tion, as would be expected, but cyclical movements in the rates of unemployment were generally greater than movements in the rates of those working part time for economic reasons and in the rates of discouraged work ers. These trends are illustrated in table 7. There were some exceptions, however. In the United States, unemployment declined from 7.4 per- M onthly Labor Review August 1995 43 U nem ploym ent Indicators Chart 2. Elements of labor underutilization, averages of available years, 10 countries, 1983-93 Percent Percent United States Australia Canada Sweden Japan cent in 1992 to 6.8 percent in 1993, but the involuntary parttime and discouraged worker rates remained the same. Thus, improvement in the labor market was first seen in the unem ployment rate, but other forms of labor underutilization re mained high. In previous years, when the declines in unem ployment rates were greater, these other forms also moved downward. Sweden's sharp upward trend in unemployment in the early 1990’s was accompanied by significant increases in both involuntary part-time and discouraged workers. The unemployment rate in 1993 was more than 4 times as high as the rate in 1987, while the discouraged worker rate in 1993 was 2-1/2 times the rate in 1987. The invol untary part-time rate was about 40 percent higher in 1993 than in 1987. Unified Germany’s upward movement in unemployment was accompanied by increases in involuntary part-time work ers. Prior to 1992, the rate of those working part time for economic reasons moved narrowly and was generally 1 per cent or less of the labor force. In 1992-93, for unified Ger many, the rate rose to more than 1 percent of the labor force. (No data on discouraged workers were available for Ger many for the entire period studied.) 44 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Germany France Italy Netherlands United Kingdom Sw eden’s labor m arket programs Sweden has been a pioneer in the provision of labor mar ket programs for retraining and employing the unemployed.12 These programs have been used as an economic instrument for countercyclical purposes. For many years, the programs helped keep Swedish unemployment low, even during eco nomic downturns. However, as Swedish unemployment rose to unprecedented postwar levels in the early 1990’s, the num ber of persons participating in the programs increased, but they could no longer hold down unemployment, as they had in previous, milder recessions. Even after completing the programs, participants could not find work, due to a lack of job creation in Sweden. A special unemployment rate can be constructed to take into account Sweden’s labor market programs, which absorb a substantial number of potentially unemployed persons. In 1993, when the conventionally unemployed in Sweden to taled 415,000, there were, on average, about 220,000 per sons in these programs. Without such programs, most of these individuals would probably have been either unem ployed or discouraged workers. Sweden’s U-5 rate of 9.3 percent in 1993 would have risen Table 7. Elements of labor underutilization in 10 countries, available years, 1983-93 Country and year Unempployed Part time for economic Discouraged workers reasons Total labor under utilization 9.6 7.5 7.2 7.0 6.2 5.5 5.3 5.5 6.7 7.4 6.8 6.8 5.6 5.1 4.8 4.7 4.5 4.3 4.0 4.1 4.8 5.0 5.0 4.7 1.4 1.1 1.0 1.0 .9 .8 .7 .7 .8 .9 .9 .9 16.7 13.7 13.1 12.7 11.6 10.6 9.9 10.3 12.4 13.3 12.7 12.4 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992....................... 1993 ....................... Average, 1989-932... 11.8 11.2 10.5 9.5 8.8 7.8 7.5 8.1 10.3 11.3 11.2 9.8 4.6 4.9 4.8 4.7 4.4 4.0 3.7 3.9 4.9 5.6 6.2 4.7 1.5 1.2 .9 .8 .7 .5 .5 .5 .8 .8 .9 .8 18.0 17.3 16.1 15.0 13.9 12.2 11.8 12.5 16.017.7 18.3 15.3 1985 ....................... 1986 ....................... 1987....................... 1988 ....................... 1989 ....................... 1990....................... 1991 ....................... Average, 1985-91 .. 10.0 9.0 8.3 8.1 8.1 7.2 6.2 6.9 9.6 10.8 10.9 8.6 4.0 3.7 3.5 3.8 4.2 4.0 4.1 4.7 6.1 7.0 7.0 4.8 1.6 1.4 1.2 1.1 1.1 1.1 .9 1.0 1.5 1.7 1.7 1.3 15.6 14.1 12.9 13.0 13.4 12.3 11.2 12.6 17.1 19.5 19.6 14.8 2.6 2.6 2.6 2.8 2.6 2.2 2.1 1.9 1.9 2.2 2.3 2.4 2.4 2.4 2.5 1.9 2.1 1.6 1.4 1.6 2.1 2.0 4.0 4.6 4.7 5.0 4.6 4.1 3.9 3.7 3.6 3.9 4.2 9.1 9.5 9.7 10.3 9.1 8.4 7.5 6.9 7.1 8.2 8.6 2.2 1.9 1.6 1.8 3.1 5.6 9.3 3.6 4.4 3.6 3.4 3.6 4.6 5.6 6.3 4.5 .6 .4 .4 .5 .8 1.3 1.5 .8 7.1 5.9 5.3 5.9 8.5 12.5 17.2 8.9 8.0 9.6 2.4 2.9 0 (’) (’) (1) C an ada 1983 ....................... 1984 ....................... 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1983-93 .. Australia 1983 ....................... 1984 ....................... 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1983-93 .. Sweden 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1987-93 .. European Union: France 1983 ....................... 1984 ....................... 1 Not available. 2 Averages calculated only for 1989-93 because of lack of data on discour aged workers in 1983-88. 3 Break In series for Italy. New survey methods were Introduced that raised the adjusted U-5 rate by approximately 1 percentage point. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Part time for economic Discouraged workers reasons Total labor under utilization 10.3 10.3 10.8 10.3 9.7 9.5 9.3 10.4 11.5 10.1 3.3 4.9 4.4 4.2 4.4 3.8 3.4 3.9 5.0 4.1 6.9 6.7 6.9 6.4 5.8 4.9 4.1 5.9 .9 1.0 1.1 1.0 .9 .7 .7 .9 (1) n n (1) (') o (’) 0 (’) (1) (’) (’) n (1) n n 1992....................... 1993 ....................... Average, 1992-93 .. 6.4 7.7 7.1 1.2 1.6 1.4 n n 0 n n 0 Average, 1985-93 .. 6.2 1.0 n n 7.2 7.6 7.7 7.8 6.6 6.8 9.5 10.4 8.0 3.5 3.8 3.4 3.3 2.9 3.2 3.1 3.3 3.3 6.9 6.5 6.6 6.4 5.8 6.6 5.1 6.1 6.3 17.6 17.9 17.7 17.5 15.3 16.6 17.8 19.8 17.5 11.9 (’) 10.6 (’) 10.0 9.5 .2 (’) .4 (1) .9 .9 .7 7.8 7.4 1.0 (1) 2.8 (1) 5.8 6.2 6.4 5.9 5.9 .6 13.1 (1) 13.7 n 16.7 16.6 15.9 14.5 13.9 9.5 5.0 .7 15.2 11.1 11.0 11.5 11.6 11.1 9.1 7.4 7.0 8.6 9.8 10.3 9.8 1.9 2.2 2.2 2.3 2.4 2.2 1.8 1.6 2.2 2.9 3.3 2.3 .8 .9 .9 .9 .6 .4 .4 .3 .3 .6 .7 .6 13.8 14.1 14.6 14.8 14.1 11.7 9.6 8.9 11.0 13.2 14.3 12.7 n n n n .2 .2 .1 .1 .2 .2 0 (') (') n 14.3 13.5 12.8 14.4 16.7 14.3 Germ any West Germ any Unified Germ any Italy 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 19923 ..................... 1993....................... Average, 1986-93 .. Netherlands Japan 1984 ....................... 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1984-93 .. Unem ployed Continued— France United States 1983 ....................... 1984 ....................... 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1983-93 .. Country and year 1983....................... 1984....................... 1985 ....................... 1986 ....................... 1987 ....................... 1988 ....................... 1989 ....................... 1990 ....................... 1991 ....................... Average, 1983,1985, 1987-91 ............... 8.8 .8 United Kingdom 1983....................... 1984 ....................... 1985 ....................... 1986 ....................... 1987....................... 1988 ....................... 1989 ....................... 1990....................... 1991 ....................... 1992 ....................... 1993 ....................... Average, 1983-93 .. Note : Persons seeking part-time jobs and persons working part time for economic reasons are fully counted In this tabulation, in contrast to U-6 and U-7, for which they are only half-weighted. SOURCE: Compiled by Bureau of Labor Statistics from labor force surveys for each country. Some adjustments are made for comparability with U.S. concepts. M onthly Labor Review August 1995 45 U nem ploym ent Indicators to 14 percent if all of the individuals in the labor market pro grams had been unemployed. Adding these persons to the U-7 rate would have increased it from 15.8 percent to 20.8 percent. A figure of this magnitude would have ranked Sweden, instead of Italy, as the country with the highest U-7 rate. This is a major change from the situation in 1989, when a comparably derived rate left Sweden virtually tied with Japan for the low- est U-7 rate among the countries studied. In terms of total labor underutilization, Sweden’s 1993 rate would have in creased from 17 percent to 22 percent of the labor force. With U-7 measured this way, Sweden would have had the highest labor underutilization of all the countries studied. Of course, other countries have persons in labor market programs, but in each, the size of the group is small compared with Sweden’s. Footnotes A c k n o w l e d g m e n t : The author thanks Neil Bain of the Statistical Office of the European Union for providing expert advice and many unpublished tabula tions from the Union’s labor force surveys. Thanks also go to the following persons in national statistical offices, for providing special tabulations and ex pert interpretation o f their data: John E. Bregger, Harvey Hamel, and John F. Stinson, Jr., o f the U.S. Bureau of Labor Statistics; Richard Phillips of the Aus tralian Bureau o f Statistics; Doreen Duchesne and Earnest Akyeampong of Statistics Canada; Takahara Yanai o f the Japanese Statistics Bureau; J. L. Faure o f the French National Institute of Statistics and Economic Studies; Paolo Garonna, Director General of the Italian National Institute o f Statistics; Alois Van Bastelaer o f Statistics Netherlands; Anita Olofsson of Statistics Sweden; and J.B. Werner and Chris Woolford of the U.K. Department of Employment. Joyanna Moy and William McMichael of the Division of Foreign Labor Statis tics assisted in tabulating the data. Sara Elder o f the same Division provided research assistance while working on a cooperative educational assignment. 1 Constance Sorrentino, “International comparisons o f unemployment indi cators,” Monthly Labor Review, March 1993, pp. 3-24. 2 U—1 has been redefined slightly for comparative purposes. In the pub lished figures pertaining to the United States, it represented persons unem ployed 15 weeks or longer, as a percent of the civilian labor force. However, most other countries break their categories denoting duration of employment at 3 months (13 weeks), rather than 15 weeks. Because U.S. data are available (in unpublished form) for durations of a single week, these data were used to modify the U - l measure for the United States to conform with the definition citing 13 weeks or longer as the breakpoint. This modification makes only a slight differ ence in the U - l rate for the United States, increasing it by about one-tenth of 1 percentage point. 3 U -7 is not available for Germany throughout the years covered and is not available for France prior to 1989. 4 This was the U.S. definition prevailing prior to the 1994 revisions to the Current Population Survey. Beginning in 1994, persons classified as discour aged must also have looked for a job within the past year and must have been available for work during the reference week. (A direct question on availabil ity was added in 1994; previously, the availability of these persons had been inferred from other responses.) APPENDIX: 5 Italy has excluded these persons from the unemployed since October 1992. (See appendix.) 6 For example, Canada’s 1993 survey enumerated only 21,000 persons “waiting for replies” among those who want work and are available for work, but who are not classified as unemployed. Their inclusion would add 0.1 per centage point to the Canadian discouraged worker rate. Data from the Statisti cal Office of the European Communities ( e u r o s t a t ) also indicate very small numbers of such persons in the major European Union countries, except for Italy. 7 The Organization for Economic Cooperation and Development ( o e c d ) fre quently cites data on persons working part time for economic reasons and on discouraged workers in analyses published in its Employment Outlook series. The July 1995 edition of Employment Outlook contains a chapter entitled “Supplementary Measures o f Labour Market Slack,” which examines in detail the data on involuntary part-time workers and discouraged workers in o e c d member countries. 8E u r o s t a t processes and disseminates data forwarded by member countries from labor force surveys conducted each spring. These surveys have been car ried out annually in most countries since 1983. 9 Tabulations of the indicators by sex are available upon request from the author. 10 Sweden’s unemployment rates in 1983-86 averaged about 3 percent, slightly above the average for Japan (2.7 percent). However, Sweden’s rates for 1983-86 are probably overstated by about 0.4 percentage point for com parisons, because they include persons seeking jobs within the past 60 days. In 1987, Sweden’s definition of unemployment was changed to come into accord with the 4-week job search period used in the United States. 11 A deep recession in Japan beginning in the early 1990’s has resulted in pressures on the lifetime employment system. Indeed, some employers in hardhit industries have begun to solicit the early retirement of middle-aged whitecollar workers who expected lifetime employment. For a further analysis, see Haruo Shimada, “Recession and changes in labour practices in Japan,” Inter national Labour Review, vol. 132, no. 2, 1993, pp. 159-60. 12 For further information see Sorrentino, “International comparisons, ” p. 17, and the accompanying citations. Revisions a n d addition of statistics on Australia This appendix presents information on (1) revisions to the Euro pean Union surveys; (2) revisions to a component of the statistics on persons working part time for economic reasons in France and on discouraged workers in the United Kingdom; (3) revisions made in the methods applied to the data on Japanese unemploy ment; (4) revisions to account for a break in the series on Swedish unemployment; and (5) unemployment statistics for Australia, a country not included in the 1993 study. That study 1 contained an appendix 2 explaining the sources, methods, and definitions used. The information is, in general, applicable to the current study and will not be repeated in this appendix. European Union surveys. The European Union surveys compiled and published by the Statistical Office o f the European Union M onthly Labor Review Digitized for46 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 ( euro stat ) are the source of data on the alternative indicators for France, Germany, Italy, the Netherlands, and the United Kingdom. The concepts and definitions used in the e uro stat surveys have been derived from the International Labor Office ( il o ) guidelines since 1983. With minor exceptions, the United States and other countries also apply these guidelines. The integration into the 1992 surveys of a more exact implemen tation of the il o guidelines implies that the comparability between the 1983-91 series and the new series from 1992 is slightly im paired. euro stat states that “the fact that both sets o f definitions continue to rest upon the ILO guidelines ensures that the differ ences are minimal.”3 The first of the changes instituted in 1992 has to do with the definition of the population of working age, which has been modi- Tied to apply to persons aged 15 years or older (instead of 14 years, as in the previous survey). The effect of this change is minimal, as very few 14-year-olds were included in the labor force of the Euro pean Union countries in 1991. The definition of employed persons is unchanged. The definition of unemployed persons contains the following differences: • Persons seeking to become self-employed are now considered unemployed only if they satisfy the same criteria of seeking work and availability for work as persons seeking work as employ ees. That is, they must be taking specific actions to become self-employed in the past 4 weeks (such as applying for a busi ness license or looking for a business location) and be available to start work in the next 2 weeks. Before 1992, these criteria were not applied to this small group. • Persons not at work and hoping to be reengaged by a former employer (“temporary layoffs”) are, similarly, now considered unemployed only if they satisfy the usual criteria of seeking work and availability for work, which were not previously ap plied. These individuals also are a very small group. • Persons without employment are considered unemployed only if they are available for work and have used an active method of job search within the past 4 weeks. The survey questionnaires were modified to permit active methods to be distinguished from passive methods. Persons using only passive forms of job search—awaiting the results of having applied for a job, wait ing for a call from a public employment office, awaiting the results of a competitive recruitment exam for the public sec tor—are no longer enumerated as unemployed.4 In the absence of comparative data from both the old and new sets of questions, it is difficult to estimate the effect of this change, but most member countries had already complied with the new definition. All three of the foregoing modifications serve to lower unem ployment, compared with the prior surveys. Together, then, they could result in some degree of overstatement in those surveys, com pared with the 1992-93 surveys, e u r o s t a t believes that the effect of the changes in 1992 were negligible for France, Germany, and the United Kingdom, but considerable for the Netherlands and Italy. e u r o s t a t provided the following tabulation estimating unemploy ment under the old definition and comparing it with unemploy ment under the new definition in 1992 for four of the countries (figures are in thousands): France Germany Italy United Kingdom ............. ............. ............. ............. ............. ............. ............. ............. Old New 2,524 2,494 3,141 2,795 2,514 2,467 2,191 2,755 The Bureau of Labor Statistics has made adjustments to the pre1992 data for Italy that mitigate the difference indicated by this tabu lation. These adjustments were also made to the 1989 data for Italy in the 1993 article and throughout the time series for Italy for 1986-91 in the current article. (See the discussion of Italy in the next column.) No adjustments were made for the other countries because, except for the Netherlands, the differences were small, ( e u r o s t a t could not provide data on the old basis for the Netherlands.) The changes that were implemented may have resulted in https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis certain inconsistencies in the data, which should be remedied as the new version of the survey becomes more familiar. In some countries, it was not possible for all of the modifications to be implemented fully. In France, the new questionnaire was implemented only for that section of the sample which was interviewed using computers, with the result that nonresponse rates were very high for some variables. This effect will gradu ally disappear with the general phasing-in of computer inter viewing. Nonresponses were distributed by b l s according to the proportions derived from the respondents. In the Netherlands, beginning in 1992, the i l o guidelines were not observed with respect to the 1-hour criterion for clas sification as employed, so certain figures had to be imputed by EUROSTAT. The Dutch national definition was changed in 1992 to include an employment threshold of 12 hours: persons were counted as employed only if they worked 12 or more hours dur ing the reference week and as unemployed only if they sought at least 12 hours of work for that week. The i l o definition rec ommends the use of a 1-hour threshold for employment and imposes no hours threshold for the seeking of employment. Be cause there are no Dutch data relating to these two conditions, the i l o (and e u r o s t a t ) definition could not be well reproduced in the data for the Netherlands. Indeed, after careful study, b l s found the 1992 and 1993 Dutch data out of line with past trends and decided to exclude those years from the study, ending the Dutch series of indicators in 1991. Italy’s statistical office made a major revision to the labor force survey in October 1992 that brought it more in line with the EUROSTAT guidelines. A new method of automatic editing and imputation of missing data was introduced. The definition of unemployment was changed to include only those who were actively looking for a job within the 30 days preceding the survey and who were available for work. Under the definitions prevailing prior to 1992, the Italian national data, as well as the data reported by e u r o s t a t , counted many persons as unemployed who engaged in passive job searches only, such as awaiting the results of recruitment exams in the public sector. In the 1993 study, b l s made an adjustment to exclude these persons, but data on both the old and the new basis for 1992 indicate that the adjustment was probably too high. The adjustment of the old 1992 data resulted in an unemployment rate that was 1 percentage point below the rate for the data on the new basis. This overadjustment was partially due to inaccurate adjustments for nonrespondents. The change in the Italian survey methods and questionnaire also had an impact on the results. The new survey questionnaire, for example, has produced an increase in reported job search activity by unemployed persons. b l s has adjusted Italy’s unemployment rates for 1987-91 down ward by excluding from the unemployed persons who had not ac tively sought work in the past 30 days (plus an estimated number of nonrespondents), according to data reported by the Italian statistical office. Although this adjustment is probably too high (based on the aforementioned 1992 relationships), it continues to be used in the present study because the Italian statistical office has not published detailed data on the new basis for any period prior to October 1992. Thus, Italy’s unemployment rates for 1991 and earlier years shown in this study are likely to be somewhat understated in comparison with the 1992-93 data. e u r o s t a t used the October 1992 survey results for Italy, rather than the spring survey results, because of the aforementioned change. For all other European Union countries, the 1992 survey data refer to the spring. Data for 1993 refer to the spring for all European Union countries, including Italy. M onthly Labor Review A ugust 1995 47 U nem ploym ent Indicators For France, in the 1993 study, a proxy had to be used for “persons working part time because they could not find full-time work,” a component of persons working part time for economic reasons (involving calculations of U-4, U-6, and U-7). The proxy was the number of persons working part time who worked their usual (or more) hours and who were seeking another or a second job. The 1993 article had noted that “this proxy under states the true number to the extent that persons working part time involuntarily did not seek more work.”5 In 1992, an actual figure for the group working part time because they could not find a full time position became available from the French labor force survey, as reported to Eu r o s t a t . The new data revealed that the proxy se verely understated the size of this group: instead of the 276,000 persons indicated by the proxy, 852,000 persons were enumerated as working part time because they could not find a full-time posi tion. Using the actual figure, BLS raised U-6 from 11.6 percent to 12.7 percent in 1992 and moved U-7 up from 11.7 percent to 12.9 percent. U-4, the unemployment rate applicable to persons seek ing full-time jobs, was revised downward from 11.2 percent to 10.8 percent because the level of the full-time labor force was increased by the revision. (The full-time labor force includes all persons work ing part time for economic reasons.) A similar downward revision was indicated by the 1993 figures. An adjustment was made for all years from 1983 to 1991, based on the 1992 proportions. Revision for France. The British Department of Em ployment alerted BLS to an error in the calculation of data on dis couraged workers reported to EUROSTAT. This error has now been corrected by the Department, and the revised figures were sup plied to b l s for all years relevant to the study. The effect of the revision was small, lowering the 1989 U-7 rate from 9.3 percent to 9.1 percent. Revision for the United Kingdom. Consultation with the Japanese Statistics Bureau and statistics available for the first time in the 1994 survey resulted in some revisions to the Japanese data. The following three revisions were made: Revisions for Japan. • Previously, the entire National Defense Force was subtracted from the labor force in the surveys, to arrive at the civilian labor force. However, members of the National Defense Force who reside in private households are included in the surveys, and they amount to about half of the total National Defense Force. Therefore, only half of the National Defense Force should be subtracted from the reported labor force. • A previous adjustment to the Japanese data added all per sons, except students, waiting to start a new job within 30 days to the unemployed, for comparability with U.S. con cepts.6 This adjustment was too high, because some of these persons were not available to begin work, a requirement under U.S. concepts, and no information was available on their number. The February 1994 Report on the Special Sur vey of the Labour Force Survey provided such information for the first time, indicating that about half of the persons enumerated as waiting to start a new job in March (exclud ing students) were not available for work in February.7 Therefore, b l s has excluded half of these persons from the adjustment in all years of the study period. • The method of allocating “jobseekers not in the labor force” according to whether they were seeking full-time or parttime work was modified, on the advice of the Japanese Sta- 48 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 tistics Bureau. The result was an increase in the number of persons seeking a full-time job and a decrease in the num ber of persons seeking a part-time job. The overall effect of these changes was small, lowering both the Japanese conventional unemployment rate and the alternative in dicators by no more than one-tenth of 1 percentage point in some years and leaving them unchanged in most years. A more significant change is the b l s revision of the data on dis couraged workers used in the U-7 rate for Japan. Discouraged workers are not enumerated as such in the Japanese survey. In the 1993 study, BLS constructed an estimate of discouraged workers under U.S. concepts by summing the following groups: (1) all per sons who were not in the labor force, who wanted work but were not seeking it because there was “no prospect of finding a job,” and who said that they were available to take a job if they found one; (2) half of the persons who were not in the labor force, who wanted work but who were not seeking work because there was “no pros pect of finding a job,” and who were either not available or unde cided about their availability for work if offered a job; and (3) half of the persons enumerated as unemployed, but who were not seek ing work in the past 4 weeks because they were awaiting the re sults of previous job applications. The rationale for half-weighting groups (2) and (3) was that they seemed to only partially fit the U.S. concept of discouraged workers. In the current study, b l s has reconsidered the treatment of groups (2) and (3). This réévaluation led to the elimination of group (2) and the inclusion of all persons in group (3), rather than only half of them, in the estimate of discouraged workers for Japan. Overall, the revised method resulted in a decrease of about 0.7 percentage point in Japan’s U-7 rate: the rate published for 1990 in the 1993 article was 7.2 percent, and it decreased slightly to 7.1 percent due to the preceding three revisions. The rate decreased further to 6.4 percent with the changes in the method of determining the number of discouraged workers. Some discussion of the U.S. method of enumerating discouraged workers prior to 1994 is necessary to explain the reasons behind the elimination of group (2). All persons not in the labor force are first asked, “Do you want a regular job now, either full or part time?” All who respond “Yes” or “Maybe, it depends” are then asked why they did not look for work in the previous 4 weeks. If multiple responses are given, reasons indicating that respondents are not discouraged take precedence over reasons indicating that they are. For example, if the multiple responses are “believes no work is available” and “in school,” the respondent is not classified as discouraged. Thus, an implied availability test is built into the classification method. In the Japanese survey, persons not in the labor force are first asked whether they want work. The question is phrased as follows: “Do you wish to do any work for pay or profit?” Those responding “Yes” or “Yes, if conditions are favorable” are then asked why they are not looking for work. Unlike the U.S. survey, which allowed multiple responses, the Japanese survey permits only one response. Presumably, the response given is the main reason why the person is not seeking work. Thus, all respondents who indicate that they are discouraged (“no prospect of finding a job”) are potentially discouraged under U.S. concepts. The Japanese survey then asks an explicit question about the respondent’s availability: “If you find a job now, can you take it up?” Possible responses to this question are “Yes, immediately,” “Yes, but later,” and “No or undecided.” The main point to note is that the U.S. survey had an implied availability requirement, while the Japanese survey actually asks explicitly whether a person could take up a job now if he or she found one. The U.S. and Japanese questions are clearly different, and a decision must be made on the best match with the U.S. concept, b l s decided that the responses “Yes” and “Yes, if conditions are favorable” to the first question in the Japanese survey approximate the responses “Yes” and “Maybe, it depends” to the first question in the U.S. survey. Of those who answer in either of the two ways mentioned in the Japanese survey, all who further respond “no prospect of finding a job” and also respond “Yes, immediately” or “Yes, but later” are taken to be discouraged workers under U.S. concepts. The group responding “Yes, but later” is included because these are persons who would accept a job now to start later. It is likely that a person in this situation would have been enumerated as discouraged in the U.S. survey. However, those responding “no or not decided” to the last question in the Japanese survey w’ould probably not have been counted as discouraged in the United States, as those who meant “no” would not be counted because they were not available. Those who were not sure of their availability (“not decided”) would most likely not be classified as discouraged under the U.S. concept either, because they were undecided about their availability rather than about their desire for a job. They are apparently interested in having a job at some time, but are not sure they would accept a job now even if one were offered. This implies a stage of labor force inactivity that lies beyond the scope of being a discouraged worker under U.S. concepts. Consider now the group of persons who are classified as unem ployed in the Japanese survey, but were not considered unemployed under U.S. concepts because they were not actively seeking work in the past 4 weeks. Instead, they were awaiting the results of pre vious job applications, b l s subtracts this group from U-5. Mem bers of the group are in a situation somewhere between unemploy ment and discouragement. Some may be discouraged, while others are waiting for developments in the process of job selection, but are ready and willing to go to work now. These latter individuals, as well as those who were truly discouraged, should be fully, rather than partially, counted in a measure of underutilization, and it was decided to count them fully in the U-7 measure. In 1993, the measurement period for the Swedish labor force survey was changed to represent all 52 weeks of the year, rather than 1 week each month, and a new adjustment for population totals was introduced. The impact was to raise the unemployment rate by approximately 0.5 percentage point. One reason for the increase is that the prior surveys for the month of June were taken in a week before students were out of school; now all weeks in June are surveyed, and school leavers seeking vacation work are included in the unemployed. Other school vacation or holiday periods are also more completely covered by the new survey. As a result, youth unemployment moved upward more sharply in 1993 than would have been the case under the previous surveys. Statistics Sweden has published adjustment factors for 1987-92 in considerable detail, and b l s has applied these factors to arrive at adjusted figures for these years. Data needed to adjust the Swedish data on discouraged workers to U.S. concepts are not published. Statistics Sweden has provided unpublished data to BLS for the years 1989 and 1991-93. Figures for the other years were estimated on the basis of proportions emerg ing from these data. In Sweden, the concept that corresponds to “discouraged worker” is latent arbetssokande, or “potentially looking for a job.” Falling into this category are persons who wanted work and were available for work in the reference week, but who were not seeking work for Break in series and adjustments fo r Sweden. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis reasons related to the labor market (for example, because no suitable work was available locally or because they thought they had little chance of finding work). One of the reasons listed in the Swedish survey is “never got around to looking for work.” In addition, under Swedish definitions, full-time students who were currently available and actively seeking work during the school term are included in the concept of latent arbetssokande. Both of these groups have been excluded from the discouraged worker count for comparability with U.S. concepts. The students (published data on their numbers are available each year) have been reclassified as unemployed under the definition of U-5, while people who “never got around to looking for work” (number provided by Statistics Sweden for 1989 and 1991-93 and estimated by b l s for other years) remain outside the labor force. The adjustment for students is normally small, but in 1993 it be came more significant because of both the general rise in Swedish unemployment and the changes in the Swedish survey’s timing. In 1993, the adjustment resulted in an increase in the Swedish U-5 rate from 8.1 percent to 9.3 percent. Before 1992, the number of students looking and available for work during the school term was very small each year. In addition to the preceding adjustments for historical compara bility, several small adjustments were made to the Swedish data on persons working “part time for economic reasons,” for comparabil ity with U.S. concepts. For the 1993 study, Statistics Sweden pro vided b l s with unpublished tabulations of adjusted data for 1989. Because the adjustments were very small, b l s has applied the 1989 proportions to adjust data for the other years. Australia. The Australian Bureau of Statistics compiled the data for the U—1 to U-7 indicators for this article based on specifications supplied by the Bureau of Labor Statistics. The data are annual aver ages for the period 1983-93 derived from the monthly labor force survey. The Australian survey is very close in concepts and defini tions to the U.S. labor force survey, and no adjustments were made to any of the indicators for comparability with U.S. concepts. There is a slight understatement of persons working part time for economic reasons in the Australian statistics because the category “bad weather and plant breakdown” could not be divided into two separate subcategories. Working part time because of “bad weather” is not considered an economic reason in the U.S. survey, while doing so because of a “plant breakdown” is an economic reason. On the advice of the Australian Bureau of Statistics, BLS decided to exclude the entire category. Data on discouraged workers in Australia were available not for every month, but generally only for March and September of each year. The Australian Bureau of Statistics annualized the semian nual figures for this study. Data for job losers (U-2) were available only from 1987 onward, because no such data were collected in the earlier years. The appendix to the 1993 study included a tabulation showing, for each country, the significant aspects of coverage and reliability of the labor force surveys used to calculate the alternative indica tors. The following tabulation gives similar data for Australia, re lating to the year 1989: • • • • • • • Number of households in sample: 30,903 Number of persons in sample: 66,769 Sampling ratio: 0.5 percent Origin of sampling frame: population census Unemployment rate, 1989: 6.2 percent One standard error: 6.1 percent to 6.3 percent Two standard errors: 6.0 percent to 6.4 percent. M onthly Labor Review August 1995 49 Unem ploym ent Indicators Footnotes to the appendix 1Constance Sorrentino, “International comparisons o f unemployment indi cators,” Monthly Labor Review, March 1993, pp. 3-24. 2Ibid., pp. 19-24. 3Labour Force Survey: Results, 1992 (Luxembourg: Office for Official Publications o f the European Union, 1994), p. 10. “However, persons only looking at advertisements in newspapers or journals are counted as unemployed in the 1992 and earlier European Union sur veys. Such a form o f job search is not enough for classification as unem ployed in the United States, but it is in Canada, where those who em ploy only this method account for about 5 percent o f the unemployed. In the European Union countries, indications are that this group is also in the 5percent range o f the unemployed. No adjustment has been made on this point for Canada or the European Union countries. (Although for Italy, because the group is relatively large, an adjustment is made to exclude passive jobseekers from U -5 and add them to U -7 prior to 1992; for 1992 50 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 and 1993, data on such persons continue to be collected even though they are no longer counted as unemployed in the U -5 measure. For those 2 years, b l s has added them to U -7 without needing to subtract them from U -5 .) In Japan, the number o f passive jobseekers— mainly persons await ing the results o f having applied for a job — is also large, and an adjust ment is made to exclude them from U-5 and add them to U -7 . 5 Sorrentino, “International comparisons,” p. 21. 6 In January 1994, the U.S Current Population Survey definitions were changed to require a job search on the part of persons waiting to start a new job within 30 days. However, the data used in this article are not adjusted to the new U.S. concept, but remain in accord with the concepts in place prior to 1994. 1Report on the Special Survey of the Labour Force Survey (Japanese Statis tics Bureau, Management and Coordination Agency, 1994). Incom e Inequality A surge in growing incom e inequality? Examination of a reported surge in income inequality in 1993 indicates that, despite changes in survey methodology, patterns of employment growth were consistent with greater income dispersion Paul Ryscavage Paul R yscavage is a senior labor econom ist, Housing a n d House hold Econom ic Statistics Division, Bureau o f th e Census, The views expressed in this article are th e author's a n d are not a ttrib u ta b le to the Bureau o f th e Census. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis ast fall, the Census Bureau announced that in 1993 incomes had dropped and poverty had increased. The Agency also reported that income inequality had risen.1 The latter piece of news received much attention, similarly to other reports in recent years that have focused on the growing dispersion in the distribution of household incomes. Inequalities of various kinds in the United States have become a popular topic in the me dia. But growing income inequality is particu larly worrisome because of its immediate impli cations for social conflict and tension. The economist Paul Krugman recently wrote: ‘The ultimate effect[s] of growing economic dispari ties on our social and political health may be hard to predict, but they are unlikely to be pleas ant.”2 Krugman’s statement is significant be cause the size of the 1992-93 increase in income inequality reported by the Census Bureau could be easily characterized as a surge. The Gini in dex, one of the tools the Agency uses to measure income inequality, rose from .434 in 1992 to .447 in 1993, the largest 1-year increase since the sta tistical series on household income inequality began in 1967.3 (See chart 1.) But this apparent surge was qualified by the Census Bureau in its analysis of the data. The Census Bureau cautioned that the size of the increase may have been an artifact of techni cal changes made in how the data on income were collected in the Current Population Survey (CPS).4 In addition, other changes to the CPS could have affected the income data for 1993. The increase in inequality nevertheless oc curred at a time when an increase might have L been anticipated. The recession of 1990-91 had an unusually strong impact on well-paid whitecollar workers caught in the downsizing of much of corporate America. In the ensuing recovery between 1991 and 1993, many of these workers resumed their full-time careers. Not only was employment rising and unemployment falling, but according to the Bureau of Labor Statistics, when the data are stratified by occupation, most of the net increase in employment in the 1992— 93 period occurred in jobs paying above-aver age wages.5 The question therefore becomes, How much of the increase in income inequality between 1992 and 1993 was due to changes in the economy, and how much was due to techni cal changes in the c p s ? This article explores both aspects of this ques tion in a descriptive way, to provide users wi‘h further evidence concerning the issue of rising income inequality between 1992 and 1993. First, CPS income data are discussed—in particular, changes that were made in the collection of the 1993 data. Then, long-run and short-run trends in household income inequality are reviewed. Next, the 1992-93 changes are examined, first from the standpoint of the technical changes in the CPS and then from the standpoint of the changes that took place in the economy. Finally, the conclusions of the analysis are presented. cps d ata and technical changes The CPS, of course, is one of the primary sources of income data used by researchers for measur ing and studying how the Nation’s income (as well as earnings) distribution has changed. A M onthly Labor Review August 1995 51 Income Inequality survey of some 60,000 households, the CPS is designed to measure employment and unemployment each month for the Bureau of Labor Statistics by means of a series of questions relating to current labor force activity. In March, an addi tional series of questions, called the Annual Demographic Supplement, is asked. These questions concern the work ex perience and the sources and amounts of income of survey members in the previous calendar year. Concept and limitations. The CPS questions on income re late to money income only (that is, they exclude all noncash income items, such as food stamps and employer-provided health insurance, as well as any capital gains), before de ductions for Federal, State, and local taxes are applied. Money income is broken down into labor market money income (wage and salary earnings, as well as farm and non farm self-employment income) and non-labor-market money income (for example, interest, dividends, and pensions). The money income data collected in the CPS also contain certain limitations. Underreporting of income and trunca tion bias are two limitations that have particular significance for studying income inequality. Because the CPS is based on a probability sample of households, all the estimates de rived from it are subject to sampling and nonsampling er Chart 1. rors. The income estimates are known to be biased down ward due to nonsampling error (relating, for example, to noninterviews, undercoverage, inaccurate responses, and missing data). For 1990, the CPS collected data on 8 8 per cent of aggregate income derived from independent esti mates. While it did quite well for wages and salaries (ac counting for 97 percent of such income), it did poorly for dividend income (gamering information on only 33 percent of this source of income).6 Obviously, underreporting of in come can affect income inequality measurements, because both the receipt and the amounts of certain income items vary across the distribution. Truncation bias occurs as a result of the suppression of income amounts above a certain upper limit. These amounts are suppressed in order to reduce the effects of interviewer error and to provide confidentiality to survey respondents. However, the limits, or top codes, can be problematic in the measurement of income inequality:7 if the distribution is be coming more unequal as a result of rising incomes at the upper end, top codes will bias measurements of income in equality downward, because the high incomes will be sup pressed. Constant nominal-dollar top codes have been used in the CPS questionnaire and are increased from time to time to accommodate rising incomes. While one-time adjustments Gini index, household income distribution, 1967-93 Index Index 52 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 0.45 0.44 0.43 0.42 0.41 0.4 0.39 0.38 August 1995 reduce truncation bias, the top codes will eventually become problematic again. Technical changes. During the 1980’s and early 1990’s, the Bureau of Labor Statistics, with the assistance of the Census Bureau, was engaged in an effort to modernize the monthly CPS. In general, the focus of the modernization was on rede signing the monthly labor force questionnaire and introduc ing a system known as computer-assisted survey information collection (CASIC). Beginning in January of 1994, the new CPS was put into operation. The redesign had implications for the Annual Demographic Supplement conducted in March of that year. While the questions on work experience and income concerning calendar year 1993 were not changed from those of previous years, the new CASIC system was used. The CASIC technology replaced the traditional paper-andpencil interviewing procedure. In that procedure, two sepa rate questionnaires—the Monthly Labor Force questionnaire and the Annual Demographic Supplement questionnaire— were filled out by the CPS enumerator in the course of the March interview. In the CASIC system, all the CPS questions are administered from a computer (either a laptop or a com https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis puter located in a centralized telephoning facility), as if only one questionnaire is in use. Unlike previous March CPS in terviews, in which the interviewer had to physically shift from the labor force questionnaire to that on work experi ence and income, the mechanics of CASIC avoid any signifi cant interruption of the interview process. In addition to this change in mode of interview, two other technical changes occurred in the March 1994 c p s that could affect income data and the measurement of income inequal ity for 1993.8First, as occurs after every decennial census of the population, data from Census Bureau surveys are reweighted in accordance with estimates of the civilian noninstitutional population derived from the most recent de cennial census. The CPS income data for 1993 reflect new weights derived from the 1990 census, and they have also been adjusted for the estimated census undercount. The second change concerns top codes. As mentioned earlier, top codes used in the CPS are occasionally increased to reflect rising nominal incomes; such an increase occurred in the March 1994 CPS. The most important top code that was increased related to earnings from the longest job or business. It was increased from $299,999 to $999,999 be- Monthly Labor Review August 1995 63 Income Inequality $50,000 (31.0 percent, compared with 39.3 percent), and slightly fewer below [In percent] $15,000 (23.4 percent, compared with 25.1 percent). Median household income Lowest Second Third Fourth Highest Top Gini IfeCf grew from $28,434 in 1967 to $33,685 fifth fifth fifth fifth fifth 5 percent index by 1989, but then declined to $31,241 in 1993, largely reflecting the recession of 1967........... 4.0 10.8 17.3 24.2 43.8 17.5 0.399 1968........... 4.2 11.1 17.5 24.4 42.8 16.6 .388 the early 1990’s. Had the rate of growth 4.1 1969........... 10.9 17.5 24.5 43.0 16.6 .391 in median household income occurred uniformly across the entire distribution 1970........... 4.1 10.8 17.4 24.5 43.3 16.6 .394 19711.......... 4.1 10.6 17.3 24.5 43.5 16.7 .396 from 1967 to 1993, there would have 1972........... 4.1 10.5 17.1 24.5 43.9 17.0 .401 been no change in inequality. 1973........... 4.2 10.5 17.1 24.6 43.6 16.6 .397 In measuring inequality, the Census 1974........... 4.3 10.6 17.0 24.6 43.5 16.5 .395 1975........... 4.3 10.4 17.0 24.7 43.6 16.6 .397 Bureau ranks household incomes from 1976........... 4.3 10.3 17.0 24.7 43.7 16.6 .398 poorest to richest and then divides them 1977........... 4.2 10.2 16.9 24.7 44.0 16.8 .402 into equal quantiles. From such a rear 1978........... 4.2 10.2 16.9 24.7 44.1 16.8 .402 19792.......... 4.1 10.2 16.8 24.7 44.2 16.9 .404 rangement, it becomes possible to ob serve how much of aggregate income is 1980........... 4.2 10.2 16.8 24.8 44.1 16.5 .403 received by similar proportions of house 1981 ........... 4.1 10.1 16.7 44.4 24.8 16.5 .406 1982........... 4.0 10.0 16.5 24.5 45.0 17.0 .412 holds and how these proportions have 1983........... 4.0 9.9 16.4 24.6 45.1 17.1 .414 changed over time. Table 1 presents the 1984........... 4.0 9.9 16.3 24.6 45.2 17.1 .415 shares of aggregate income received by 19853.......... 3.9 9.8 16.2 24.4 45.6 .419 17.6 1986 ........... 3.8 9.7 16.2 24.3 46.1 18.0 .425 each fifth, or quintile, of the household 1987........... 3.8 9.6 16.1 24.3 46.2 18.2 .426 income distribution for the entire 19671988........... 3.8 9.6 16.0 24.3 46.3 18.3 .427 93 period. The Gini index of income con 1989........... 3.8 9.5 15.8 24.0 46.8 18.9 .431 centration, a summary measure of in 1990........... 3.9 9.6 15.9 24.0 46.6 18.6 .428 come inequality, is also presented.11 1991 ........... 3.8 9.6 15.9 24.2 46.5 18.1 .428 Generally speaking, the table shows 1992........... 3.8 9.4 15.8 24.2 46.9 18.6 .433 19924.......... 3.8 9.4 15.8 24.2 46.9 18.6 .434 that from the end of the 1960’s to the end 19935.......... 3.6 9.1 15.3 23.8 48.2 .447 20.0 of the 1980’s, the share of income going 19936.......... 3.6 9.0 15.1 23.5 48.9 21.0 .454 to the households in the highest quin tile increased, while the shares going to 11mplementation of weights derived from 1970 population census. 2Implementation of weights derived from 1980 population census. the lower quintiles declined or changed 3 Upper limit for earnings from longest job or business raised to $299,999; upper limits for other very little. The dividing line between the income items also raised. top of the fourth quintile and the bottom 4Implementation of weights derived from 1990 population census. of the fifth increased from $47,136 (in 5Upper limits in effect in 1992 applied to 1993 income data. 1993 dollars) in 1967 to $60,280 in 6Introduction of casic; upper limit for earnings from longest job or business raised to $999,999; upper limits for other income items also raised. (See footnote 9 in text.) 1993. The Gini indexes indicate that the long-run trend toward greater income in tween 1992 and 1993. The last time a change was made on equality did not occur smoothly over the 1967-93 period. this top code was in March 1986, for the survey year 1985, Indeed, as shown in chart 1, the trend was very gradual from when it was raised from $99,999 to $299,999. 1967 to 1979. Between 1979 and 1989, however, the index grew rapidly—from .404 to .431—after which it slowed, end ing at .433 in 1992.12 Trends in inequality The slowing growth of household income inequality was Chart 2 depicts how the Nation’s household income distri no doubt related to the winding down of the economic ex bution changed between 1967 (in 1993 dollars) and 1993.10 pansion of the 1980’s and the ensuing recession in the early Clearly, there was a shift to the right, with greater propor 1990’s. This slowdown received little attention in the media tions of households in 1993 having incomes above $50,000 and in the research community, but developments during the than in 1967 (28.8 percent, compared with 16.8 percent), a period can help one gain an understanding of the apparent much smaller proportion with incomes between $15,000 and surge in inequality between 1992 and 1993. Table 1.1 Shares of aggregate household income received by each fifth and top 5 percent of households, 1967-93 64 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Table 2 presents real mean household incomes for each quintile (as well as households in the top ventile) of the in come distribution for the years 1979, 1989, 1991, 1992, and 1993, as well as the annual rates of change between each succeeding pair of years. Chart 3 displays the annual rates of change. The statistical cause of the rise in inequality in the 1980’s can be seen quite easily: mean household incomes for the richest 20 percent of households were increasing by 1.7 percent a year, compared with a 0.4-percent increase for the poorest 20 percent. The situation in the 1989-91 period stands out in stark contrast to that in 1979-89. During 1989-91, mean house hold incomes plummeted, not only for the lowest quintile, but also for those quintiles in the middle and at the top of the distribution. The mean household income in the highest ventile slid by almost 5 percent a year. The impact of corpo rate downsizing and restructuring was particularly severe among white-collar workers.13 Ironically, the collapse of in comes across the distribution in this period halted the rise in income inequality.14 (See chart 1.) By 1992, the economy was slowly beginning to recover from the recession. Mean household income remained virtu ally unchanged between 1991 and 1992, but not for all house holds in the distribution. In particular, mean incomes of households in the bottom three quintiles continued to de cline, while those of the top 5 percent continued to grow (although the increase was not statistically significant). This difference in income growth, however, helped push the Gini index up from .428 to .433, and although it was not a statis tically significant change, it perhaps was a signal of things to come. The change in inequality in the 1992-93 period is con siderably more difficult to interpret, because of the afore mentioned technical changes in the CPS. Some of the effects of the changes, however, are quantifiable and are presented in table 1. With respect to the reweighting of estimates as a result of the 1990 decennial census, the impact on measur ing inequality was minimal. As shown in the table, the 1992 income shares and Gini indexes have been calculated using both 1980 and 1990 population weights. Shares were unaf fected in 1992, and the Gini index was only slightly differ ent (rising from .433 to .434, but not a statistically signifi cant change). Increasing the upper limits, or top codes, in 1993, how ever, had a significant impact both on the Gini index and on the shares of aggregate income received by various quintiles of the distribution, as can be seen in the table. If the new top codes had been used, the Gini index for 1993 would have been .454 instead of .447— .020 point higher than the 1992 Gini, instead of .013 point higher. Using comparable top codes between 1992 and 1993, however, preserved some ana lytical comparability between years. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Table 2. Mean income of each fifth and top 5 percent of the household income distribution, 1979, 1989, 1991,1992, and 1993 [In 1993 dollars] Lowest fifth Second fifth Third fifth Fourth fifth $7,823 8,182 7,706 7,547 $19,457 20,278 19,255 18,828 $32,079 33,707 $84,484 $128,847 99,669 93,501 7,506 7,411 18,725 18,647 31,716 31,548 31,260 $47,076 50,986 48,758 48,649 48,429 48,572 94,233 93,837 98,589 161,030 145,913 149,592 148,937 163,228 0.4 -3.0 0.4 -2.6 0.5 -2.6 0.8 -2.2 1.7 -3.2 -4.9 1991-92s -2.1 -2.2 -.8 -.2 .8 1992-93 -1.3 -.4 -.9 .3 5.1 Year 1979..... 1989..... 1991 ..... 19921.... 19922.... 19933.... 31,984 Highest Top fifth 5 percent Annual rate of change (percent):4 1979-89 1989-91 2.2 2.5 9.6 1Survey weights derived from 1980 population census. 2Survey weights derived from 1990 population census. 3Introduction of casic; upper limits in 1993 are the same as in 1992. 4Compounded. 5Change based on income data using 1980 weights. Chart 3 and table 2 show the percent changes in mean household incomes across quintiles (and in the top ventile) for the 1992 and 1993 distributions, both of which are weighted according to 1990 population controls, and both of which use the upper income limits of 1992. Incomes in the top ventile rose from $149,000 to $163,000, or almost 10 percent. The highest quintile’s mean income increased by 5.1 percent, from $94,000 to almost $99,000. In contrast to the further declines in mean incomes in the bottom and third quintiles, these very sizable increases pushed inequality up, as measured by Gini index, by the largest amount for 1 year since the statistical series on household income inequality began. The question, of course, remains: even after controlling for changes in the weighting of the income data and for top coding between 1992 and 1993, how much of the increase was due to the new mode of data collection (CASIC), and how much was due to changes taking place in the economy? Survey changes or economic changes? Attempts to quantify or decompose the effects of various fac tors on changes in survey data are a common exercise among economists and other researchers. Several statistical proce dures are available for estimating such effects. In the case of Monthly Labor R eview A ugust 1995 55 Income Inequality the apparent surge in income inequality between 1992 and 1993, however, the potential source of the change arises not only from factors outside the survey (that is, the economy), but also from factors inside the survey (for ex ample, the data collection methodology). Untangling these potential effects, therefore, is even more challenging and, for the purposes of this article, will consist simply of draw ing inferences from evidence relating to changes in the quality of the data and evidence relating to changes in the nature of job growth. Changes in the quality of the data. Because the rede sign of the monthly CPS was so extensive, the Census Bu reau and the Bureau of Labor Statistics went to great lengths to assess the impact of the changes on the monthly estimates of employment and unemployment.15The results of their evaluation suggested that the national unemploy ment rate would be 0.5 percentage point higher in 1993 based on a parallel survey using the new questionnaire and technology than it actually was using the old ques tionnaire and collection methods.16 Since that time, how ever, b l s has reexamined the effects of the changes and Chart 3. found them to be less (0.2 percentage point), but the Agency continues to warn data users about the possible effects of the changes on the estimates.17The assessment of c a s i c ’s impact on the income data collected in the March 1994 CPS Annual Demographic Supplement, on the other hand, was much more lim ited, because only the mode of collection had been changed.18Basically, aspects of data quality were examined. One of the most important reasons for computer-assisted interviewing is to simplify the job of the interviewer. The com puter automatically brings the appropriate questions to the screen, it can be programmed to perform editing functions and identify inconsistent answers, and it has the ability to store and display data from earlier interviews. With these advantages, however, come certain disadvantages, such as a breakdown or malfunction of the computer, interviewer errors in recording responses, and, in those households in which a laptop com puter was used in the home, the possible inhibiting influence on respondents of the computer’s presence. In reviewing the income data that were collected in March 1994, it was observed that certain income estimates were sig nificantly lower than the previous year’s estimates. Further re view found that an unusually large number of subannual (that Annual rates of change in real mean household income, by quintiles and top 5 percent, 1979-89,1989-91, 1991-92, and 1992-93 Percent change Percent change 10 5 0 -5 -10 Note: Annual rates of change for 1 9 7 9 -8 9 and 1989-91 are average annual rates; 1 9 9 2 -9 3 changes are based on 1990 weights. 56 Monthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 is, weekly or monthly) income amounts were being recorded. improvements were statistically significant in the earnings Lack of familiarity with the new technology on the part of classes below $50,000 and between $75,000 and $99,999. the interviewers was the suspected cause of the problem. To The lowering of this rate is probably the result of the smooth correct for those income recipients with unusually low er transition between the monthly portion of the CPS and the amounts, reinterviews were conducted in August 1994, and supplemental questions as a result of CASIC. the incorrect amounts were adjusted.19 Other than this find Reaching any firm conclusion about the impact of CASIC ing, the evidence with respect to the quality of the data was on the quality of the income data after examining these esti inconclusive. The Census Bureau, however, warned users that mates is difficult because the evidence is mixed: imputations the data from the March 1994 CPS would “not [be] strictly by item increased, but overall imputations declined. In addi comparable to [data from] earlier years.”20 tion, the fact that there was no discernible pattern across earn Another aspect of the quality of the data that has been ings classes lends further support to the notion that CASIC’s examined involves the imputation of information on income impact on the income data was inconclusive. that occurs because a response to a question about income was not forthcoming. Table 3 presents information on this Changes in the nature of job growth. Research into the issue. For persons with earnings (wages and salaries, or in causes of rising inequality of incomes among households in come from self-employment, or both) from their longest job recent years has generally focused on changes taking place or business in 1992 and 1993, the table shows the propor in the Nation’s economy— specifically, changes in the wage tions that (1) actually reported their earnings from their long distribution. This is because labor market earnings repre est job or business, or (2) had only their earnings from their sent such a large part of aggregate household income. longest job or business imputed, using the Census Bureau’s As has been well documented, the wage distribution has “hot deck” procedure, or (3) had all information on them grown more unequal over time, just as the income distribu imputed in the Annual Demographic Supplement, including tion has. Shifts in labor demand toward more highly skilled earnings from their longest job or business.21 These propor and well-educated workers within industries and away from tions are displayed by broad earnings classes to see whether workers with relatively poorer skill endowments are thought differential effects were evident. to be responsible for this development.22 Technological For many households, of course, the earnings of persons changes in the production of goods and services that are “skill from their longest jobs or businesses represents the largest biased” are thought to underlie these shifts. part of household income and should be a fairly good indica The impact of this economic development on growing in tor of the quality of the household income data. Table 3 shows come inequality has been compounded by societal changes that there was a slight overall decline from 1992 to 1993 in in living arrangements. The well-known rise in single-par the proportion of individuals who actually reported their ent households over the last couple of decades has increased earnings to Census Bureau interviewers—from 79.6 percent income dispersion because single-parent households tend to to 77.7 percent. By earnings classes, changes in the propor have much lower incomes than married-couple households tions of persons who actually reported their earnings were do.23 In addition, to the extent that growing proportions of statistically significant, with the lone exception of those with men and women with similar skill profiles, and therefore earnings of $75,000 or more. A significant increase took place from 1992 to 1993 in the proportion of per Table 3. Percent of persons with earnings from longest job or business whose earnings were actually reported, item imputed, or totally imputed, by sons who had only their earnings from earnings, 1992 and 1993 the longest job or business imputed— Item imputed Reported Totally imputed from 9.3 percent to 12.8 percent. How Earnings 1992 1993 1992 1993 1992 1993 ever, all earnings classes experienced significant increases in imputations by Total............................. 79.6 77.7 9.3 12.8 11.1 9.5 item. High earners—those with earnings Less than $25,000........... 79.5 9.2 9.7 77.0 13.3 11.3 of $100,000 a year or m ore— had a $25,000 to $49,999.......... 80.3 79.7 8.9 10.7 11.3 9.0 higher rate of imputation by item than $50,000 to $74,999.......... 10.4 79.6 78.1 10.0 12.3 9.6 $75,000 to $99,999.......... 75.5 11.2 76.0 14.9 9.2 13.3 did any of the other earnings groups— $100,000 or m ore............ 73.2 17.4 70.8 14.3 12.4 11.8 17.4 percent. The proportion of earners who had all their work experience and income infor N ote : Estimates are based on weighted counts of earners in 1992 and 1993; weights are derived from 1990 population census. mation imputed declined from 11.1 per cent in 1992 to 9.5 percent in 1993. The https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 57 Inco m e Inequality P ercen t distribution o f Dersons with w o rk e x o e r ie n c e . b v ho urlvr e a rn in a s .......^ and household income, 1979 and 1993 Hourly earnings Total Less than $14,000 $14,000 to $27,999 $28,000 to $41,999 $42,000 to $55,999 $56,000 or more Total ......................... 100.0 7.2 17.7 22.0 19.8 33.2 1979 (in 1993 dollars) Less than $ 7 .0 0 ....... 31.0 5.6 7.6 6.3 4.5 7.0 $7.00 to $13.99........ 38.5 1.3 9.0 9.9 7.9 10.3 $14.00 to $20.99...... 18.7 .2 .7 5.2 5.2 7.4 $21.00 to $27.99...... 6.7 .1 .2 .3 1.9 4.2 $28.00 or m o re ........ 5.1 .2 .2 .2 .3 4.4 Total ....................... 100.0 8.1 18.3 20.4 17.3 35.8 Less than $ 7 .0 0 ....... 32.9 6.7 QO 6.8 4.0 6.3 $7.00 to $13.99........ 36.7 1.1 qq 9.3 7.6 10.0 1993 $14.00 to $20.99...... 17.5 .2 .6 3.6 4.0 9.1 $21.00 to $27.99...... 6.8 .1 .1 .3 1.2 5.1 $28.00 or m o re ........ 6.1 .1 .2 .3 .3 5.3 Note: Due to rounding, totals may not equal sums of individual items. earnings, tend to marry and work, they also produce disper sion in the income distribution.24 By themselves, however, changes in living arrangements occur only over long periods of time and were not likely to have any appreciable effect on the apparent surge in income inequality between 1992 and 1993.25 Rather, most of the surge is likely to be related to changes in the nature of the employment growth that oc curred during the period. Some perspective on the nature of employment growth between 1992 and 1993 can be obtained by comparing that growth with what happened in the 1979-89 and 1989-92 periods. Table 4 shows the distribution of persons with some work experience in 1979 and 1993, cross-classified by their average hourly earnings and the annual income of the house hold in which they lived.26The table relates to all workers— from those who worked only a few weeks at part-time jobs to those who worked year round at full-time jobs. The data can be summarized by focusing on three broad groups account ing for approximately 75 percent of all persons with work experience in both years: • Persons with hourly earnings of less than $7 and house hold incomes of less than $42,000 a year • Persons with hourly earnings between $7 and $27.99 and annual household incomes between $14,000 and $56,000 • Persons with hourly earnings of more than $14 and yearly household incomes of $56,000 or more. 58 M o n th ly L a b o r R e vie w https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis A ug ust 1995 As is known, both earnings and in come inequality rose between 1979 and 1993, and the changes in the proportions of persons in these groups help to ex plain why. Low-earning workers from households with incomes of less than $42,000 a year increased from 19.5 per cent to 22.7 percent of all workers, those with midlevel earnings and income de clined from 39.1 percent to 34.3 percent of the total, and those with hourly earn ings from the middle to high range who lived in high-income households in creased from 16.0 percent to 19.5 per cent of all workers. In other words, the table shows the much-talked-about shift of middle-earnings employment away from middle-income households to lowincome households and especially highincome households. (It is interesting to note that about 10 percent of all workers earned less than $7 an hour, but were from households with incom es of $42,000 a year or more.) Table 5 presents the average annual changes that occurred in these broad earnings-income groups from 1979 to 1989, 1989 to 1992, and 1992 to 1993. The table shows that between 1979 and 1989 employment was growing rapidly—by 1.8 million per sons a year. Much of the increase in average annual employ ment was taking place among persons with middle to high earnings who lived in high-income households. Employment in this earnings-income category was rising, on average, by about 921,000 persons a year during the 1980’s. Employ ment was also growing, however, at the other end of the earn ings-income distribution. The employment of workers with low hourly earnings who were from households with incomes of less than $42,000 a year increased by about 494,000 per sons per year. But among workers with middle-level earn ings who were from middle-income households, employment growth was meager at best—35,000 persons a year. The fol lowing tabulation presents Gini indexes for earnings alone for selected years from 1979 to 1993 (the figures in paren theses are the years of population censuses from which the survey weights for the given years are derived): Year Gini index 1979 (1 9 8 0 )........... ...................385 1989 1992 1992 1993 (1980)........... ...................428 (1 9 8 0 )........... ...................414 (1 9 9 0 )........... ...................414 (1990)........... ...................449 (817,000 per year) and workers in the middle of the earnings and income dis tribution (342,000). These net changes [In thousands] actually produced a decline in earnings Hourly Less than $14,000 to $28,000 to $42,000 to $56,000 inequality: the Gini index was .428 in Total earnings $14,000 $27,999 $41,999 $55,999 or more 1989 and .414 in 1992. The 1992-93 period represented a re 1979-89 turn to the pattern of employment growth Total ........................ 1,756 116 187 132 74 1,248 of the 1980’s, but in a more extreme way. Table 5 shows that the employment Less than $7.00......... 602 152 217 125 39 68 growth of persons with middle to high *~9 $7.00 to $13.99.......... 361 -28 82 58 258 earnings who were from high-income $14.00 to $20.99........ 340 -6 -16 -48 -22 433 households rose by 949,000 during that $21.00 to $27.99........ 201 0 -3 -2 -26 232 $28.00 or m ore.......... 252 period. At the same time, however, there -3 -2 -1 1 256 was only modest employment growth 1989-92 among persons with low earnings who Total........................... 310 465 663 120 168 -1,106 were from low- to middle-income house holds—about 317,000 persons. And, as Less than $7.00......... 603 381 71 296 140 -284 in the 1980’s, persons in the middle earn $7.00 to $13.99.......... 366 56 291 77 182 -241 ings and income group experienced no $14.00 to $20.99........ -212 15 56 -113 4 -174 employment growth. (The group actually $21.00 to $27.99........ -203 -2 2 9 -99 -112 lost 53,000 workers.) The Gini index for $28.00 or m ore.......... -244 15 18 8 10 -295 these workers’ earnings distributions 1992-93 shot up from .414 to .449 between 1992 and 1993, and although 1-year changes Total........................... 1,459 -21 290 545 -721 1,366 should obviously be viewed with caution, Less than $7.00......... 421 it is clear that this development was re -183 380 -425 120 530 $7.00 to $13.99.......... 510 86 flected in the apparent surge in income -77 699 -85 -113 $14.00 to $20.99........ -424 38 -45 -316 inequality. -299 199 $21.00 to $27.99........ 246 23 0 -25 25 222 According to these data, then, the pat $28.00 or m ore.......... 706 16 33 66 63 528 tern of employment growth in the 199293 period represented not only a return to the pattern seen in the 1980’s, but an N ote : Data for 1992 and 1993 use survey weights from the 1990 population census. Due to rounding, totals may not equal sums of individual items. exaggeration of that pattern. While the ratio of employment growth at the top During the 1979-89 period, the Gini index based on these end of the distribution to that at the bottom end averaged workers’ earnings distributions increased from .385 to .428, about 1.86 to 1 in the 1980’s, in the 1992-93 period it was reflecting the foregoing annual average net changes in 2.99 to 1. This development may have been the result of the employment. combined effect of the return to the work force of many highly Table 5 also presents data for the recession that took place paid workers who were laid off in the early 1990’s along between 1989 and 1992. The annual average net change in with the resumption of the secular trend toward job creation employment during that period was much less than that of at both ends of the wage distribution with little growth in the the previous period—only 310,000 persons a year—and there middle. were noticeable differences in where employment was grow ing. Employment declined, on average, by 581,000 persons Conclusions for those with middle to high earnings who were from highincome households. This decline reflected not only the loss The result of efforts to improve the quality of economic data of many high-paying blue-collar jobs as a result of the reces oftentimes is like a two-edged sword: on the one hand, the sion, but also a reduction in employment of high-paying data are improved, but on the other, the comparability of the white-collar jobs. improved data with previously collected data comes into In contrast, employment gains were recorded among lowquestion. Such is the situation confronting those examining earning workers in low- to middle-income households the change in income inequality between 1992 and 1993. Table 5. Annual average net change in persons with work experience, by hourly earnings and household income, 1979-89, 1989-92, and 1992-93 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M o n th ly L a b o r R e v ie w A ugust 1995 59 Incom e Inequality This article has discussed, in an inferential way, one pos sible interpretation of the change. It does appear that the re ported surge in income inequality was driven by an unusu ally large increase in incomes in the highest quintile of the distribution—especially the top 5 percent of households.27 An examination of the effects of the introduction of c a s i c on the data showed that incomes of a certain number of house holds had been misrecorded, but that this misrecording affected only households in much lower income ranges. Imputation rates also were examined, especially at the high end of the distribution, but the changes there did not indicate any greater inclination on the part of high earners to report their earnings. For those who did report, however, it was ap parent that considerably greater earnings were being reported, given the overall increase in incomes at the top end of the distribution. Whether or not the use of the computer in the survey process caused those who reported their earnings and incomes to be more forthcoming than usual is, unfortunately, a difficult hypothesis to test. Evidence was shown that the increase in inequality could have been induced by changes taking place in the nature of employment growth as the economy moved out of the reces sion. Very strong employment gains were registered among persons with middle to high earnings who lived in high-in come households. With the return to work at full capacity of many highly paid white-collar workers caught in the reces sion of the early 1990’s, and with the resumption of the “twotiered” employment growth characteristic of the 1980’s, the forces for greater income inequality may have been particu larly strong between 1992 and 1993. It remains for us to await the data from the March 1995 CPS to obtain more evidence on how to apportion the 1992-93 changes in household in come inequality between changes in survey techniques and changes in the nature of employment growth. □ Footnotes 1See “Census Bureau Announces Number o f Americans in Poverty Up for a Fourth Year although Poverty Rate Unchanged; Household Income and Health Care Coverage Drop,” United States Department of Commerce News, C B 94159 (Bureau o f the Census, Oct. 6, 1994). See also Daniel H. Weinberg, press briefing statement on the 1993 income and poverty estimates (Bureau of the Census, Oct. 6, 1994). 2 See Paul Krugman, “Long-Term Riches, Short-Term Pain,” The New York Times, Sept. 25, 1994, p. F9. 3The Gini index is a bounded measure of income inequality that ranges from 0 (all households receive the same share o f aggregate income) to 1 (one house hold receives all income). There are many other measures o f inequality, such as the ratio o f incomes o f households at the 90th percentile of the distribution to those o f households at the 10th percentile, the variance of the logarithms of incomes, the coefficient o f variation, the Theil index, and so on. While all of these measures are constructed differently and have different properties, each has indicated a growing dispersion in household income distribution in recent years. 4See Weinberg’s press briefing statement, p. 5. 5 See “Nature o f Employment Growth Examined by 410 (Bureau o f Labor Statistics, Aug. 24, 1994), p. 2. b l s ,” n e w s , u sd l 94- 6 See “Money Income o f Households, Families, and Persons in the United States: 1992,” Current Population Reports, Consumer Income, Series P 60184 (Bureau o f the Census, September 1993), p. C-12. 7 See Rudy Fichtenbaum and Hushang Shahidi, “Truncation Bias and the Measurement o f Income Inequality,” Journal of Business and Economic Sta tistics, vol. 6, no. 3, July 1988, pp. 335-37. 8 For a further discussion of these changes, see “Money Income o f House holds, Families, and Persons: 1993,” Current Population Reports, Consumer Income, Series P60-188 (Bureau of the Census, forthcoming). 9 Other top codes that were increased were earnings from all other jobs or businesses (from $99,999 to $999,999), income from Social Security (from $29,999 to $49,999), Supplemental Security Income (from $9,999 to $24,999), public assistance (from $19,999 to $24,999), and veteran’s benefits (from $29,999 to $99,999). Top codes appearing in c p s public-use data files, how ever, were not changed and are lower than pre-1993 top codes. For example, the top code on the public-use file for earnings from the longest job or business is $99,999. 10 All income data in this article have been adjusted for inflation using the experimental consumer price index for all urban consumers, abbreviated bls C P 1 -U -X 1 . 11 Two facts about the measurement of income inequality should be men tioned in this context. First, all measures of inequality have certain limitations M onthly Labor ReviOw Digitized for60 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 embodied in them. The Gini index, which is a summary measure, can obscure the location in the income distribution where changes are occurring. A concep tually more difficult problem occurs when Lorenz curves, from which the Gini index is derived, cross. Lorenz curves show the relationship between the cumu lative percentage of aggregate income and the cumulative percentage of recipi ents, and when the curves intersect for different years (or countries, groups, and so forth), a condition of Lorenz dominance prevails that makes it impossible to determine which distribution o f income is more unequal. Second, researchers who study income inequality and who focus more di rectly on the welfare implications of their findings customarily adjust the house hold or family income data for differences in the number of household or family members because o f presumed economies o f scale. No such adjustments were made to the data reported by the Census Bureau, nor were they made to the data used in this article; and even if they were made, they would not substantively change the findings presented. 12 Actually, the slowdown began in 1987. The change in the Gini index between 1987 and 1989 was not statistically significant, nor was the change between 1989 and 1992. Changes in estimates are statistically significant un less otherwise stated. 13 See Joseph Meisenheimer II, Earl Mellor, and Leo Rydzewski, “Job mar ket slid in early 1991, then struggled to find footing,” Monthly Labor Review, February 1992, pp. 3-17, especially p. 14; and Jennifer M. Gardner, “The 199091 recession: how bad was the labor market?” Monthly Labor Review, June 1994, pp. 3-11. 14Income growth patterns in the five quintiles during the 1987-88 and 1988— 89 periods were also more uniform than in the 1979-87 period, and income inequality was virtually unchanged in the first two periods. 15For a discussion of the two Agencies’ evaluation plan, see Chester E. Bowie, Lawrence S. Cahoon, and Elizabeth A. Martin, “Overhauling the Current Popu lation Survey: Evaluating changes in the estimates,” Monthly Labor Review, September 1993, pp. 29-33. 16See Sharon R. Cohany, Anne E. Polivka, and Jennifer M. Rothgeb, “Revi sions in the Current Population Survey Effective January 1994,” Employment and Earnings (Bureau of Labor Statistics, February 1994), pp. 13-37. 17See “Statement of Katharine G. Abraham, Commissioner, Bureau o f La bor Statistics, before the Joint Economic Committee, United States Congress,” Dec. 2, 1994, p. 4. 18 “Money Income: 1993.” 19A total 5,422 cases were targeted for reinterview, and 3,634 of those were completed. A proportion o f the cases that were targeted but not reinterviewed had their income amounts adjusted on the basis of likelihood functions derived from completed reinterviews. See “Money Income: 1993.” 20 “Money Income: 1993.” 21 For a discussion of the “hot deck” method of imputation and recent changes to it, see Edward J. Welniak, Jr., “Effects of the March Current Population Survey’s New Processing System on Estimates o f Income and Poverty,” paper presented before the 1990 meeting of the American Statistical Association, Ana heim, California, Aug. 2,1990. 22 See Lawrence F. Katz and Kevin M. Murphy, “Changes in Relative Wages, 1963-1987: Supply and Demand Factors,” Quarterly Journal of Economics, February 1992, pp. 35-78; and John Bound and George Johnson, “Changes in the Structure o f Wages in the 1980’s: An Evaluation of Alternative Explana tions,” American Economic Review, June 1992, pp. 371-92. 23 See, for example, Lynn Karoly, “The Trend in Inequality among Families, Individuals, and Workers in the United States: A Twenty-Five Year Perspec tive,” in Sheldon Danziger and Peter Gottschalk, eds., Uneven Tides: Rising Inequality in the 1980s (New York, Russel Sage Foundation, 1993); and Paul Ryscavage, Gordon Green, and Edward Welniak, “The Impact of Demographic, Social, and Economic Changes on the Distribution of Income,” in Studies in the Distribution of Income, Current Population Reports, Consumer Income, P60-183 (Bureau o f the Census, October 1992). 24 See Lynn A. Karoly and Gary Burtless, “The Effects of Rising Earnings https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Inequality on the Distribution of U.S. Income,” Dec. 20,1993 (mimeograph). 25 It is interesting to note that, while the proportion of all households that were maintained by single parents was 15.7 percent in 1992 and 15.8 percent in 1993, the proportion o f all families in which a wife was in the paid labor force increased from 46.0 percent to 47.0 percent. 26 Average hourly earnings were obtained by dividing the annual earnings (wages and salaries, as well as self-employment income) of those workers by the product of the number o f weeks and the usual number o f hours per week they worked. Although this technique for estimating annual hours is crude because it involves usual, and not actual, hours worked (as well as having other problems), the resulting estimates are sufficiently reliable for the purpose of the intended comparison. The 1979 data are weighted according to 1980 weights, and the 1993 data are weighted according to 1990 weights. 27 According to early estimates from the Internal Revenue Service for 1993, the number of tax returns with adjusted gross incomes of $ 100,000 or more was 3,557,000. This was 7.4 percent more than the figure for 1992 (3,312,000). The number of returns increased by 0.4 percent. (See SO/ Bulletin, vol. 14, no. 2 (Internal Revenue Service, Fall 1994), p. 20; and SOI Bulletin, vol. 13, no. 2 (Internal Revenue Service, Fall 1993), p. 24. LABSTAT Available via World Wide Web the Bureau of Labor Statistics public data base, provides current and his torical data for many b l s surveys, as well as numerous news releases. l a b s t a t Public Access has introduced a new production Internet service over the World Wide Web. b l s and regional offices programs are described using hypertext pages. Access to l a b s t a t data and news releases is provided by a link to the b l s gopher server. The URL is: labstat, http://stats.bls.gov/blshome.html If you have questions or comments regarding the l a b s t a t system on the Internet, address e-mail to: labstat.helpdesk @bls.gov M onthly Labor Review August 1995 61 Textile, Apparel E m p lo y m e n t* Unraveling em ploym ent trends in textiles and apparel Both of these industries continue to shed large numbers of workers; although textiles and apparel are closely related, the reasons for their job losses, and the prognosis for their future, differ Lauren A. Murray Lauren A. Murray is an econom ist form erly with th e Division o f M onthly Industry Em ploym ent Statistics, Bureau of Labor Statistics. he U.S. textiles and apparel industries employ about 1.6 million U.S. workers— 1 in 10 manufacturing workers and more than the auto and aircraft industries combined.1 Textiles and apparel reached employment peaks long ago and both have been influenced by simi lar forces, including productivity, foreign trade, competition and business cycles. While employ ment losses have affected the two industries, the duration and depth of those losses differ. The textiles industry produces base products such as threads, yarn, and cordage and woven fabrics, carpets, and rugs; in contrast, the ap parel industry produces finished clothing prod ucts made from base fabrics. Employment in the textiles industry peaked in 1948, 25 years be fore the apparel industry. The textiles industry has lost one-half of its employment base since its peak level; the apparel industry has trimmed one-third of its jobs since its peak in 1973. And since 1970, the industries have lost 30 percent of their combined work force; in the current expansion, the industries have failed to par ticipate in the strong cyclical growth that has been prevalent in much of manufacturing. (See table 1.) Although the textiles and apparel industries are closely related, different reasons account for their respective job losses. Both industries will continue to face intense global competition in the current decade, and, while some manufac turers may become more profitable, employment will most likely continue to fall. T Monthly Labor Review Digitized for62 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 This article focuses on the employment trends in textiles and apparel over the past half cen tury, with an emphasis on developments since the 1970’s. The underlying causes of the pro tracted employment declines in each industry are examined and some of the issues that will affect future employment needs are discussed. Long-term trends Em ploym ent in the U.S. textiles industry reached an all-time high of 1.3 million jobs in June 1948, reflecting the overwhelming domi nance of the United States in the world economy following World War II. Employment subse quently declined through several business cycles, with new levels rarely returning to 1 million. However, this long-term decline in employment is not reflected in a corresponding drop in pro duction. On the contrary, production increased by nearly 190 percent between 1948 and 1994 while employment dropped by nearly 50 per cent.2 (See chart 1.) Labor productivity grew by 180 percent in the textiles industry between 1950 and 1973.3 In contrast, the apparel industry ex perienced productivity growth of only 73 per cent during that same period, which was more in line with total manufacturing labor produc tivity growth of 84 percent. Thus, labor produc tivity growth in the textiles industry was twice the rate of all of manufacturing, while labor pro ductivity growth in the apparel industry lagged behind other manufacturing. The apparel industry’s all-time peak employment level of 1.4 million occurred in April 1973. (See chart 2.) The level of apparel employment appears to have been greatly influ enced by the amount of apparel imports entering the United States. Beginning in the 1960’s, imports of apparel products increased rapidly and gained a larger share of the domestic market, contributing to the subsequent employment declines in the industry. In the early 1960’s, imports comprised about 2 percent of domestic consumption; by 1980 the proportion had risen to nearly 15 percent,4 and in 1988 it was 26 per cent. (See chart 3.) Since its peak in 1973, the long-term employment trend of the apparel industry has closely followed that of the tex tiles industry. Through successive business cycles, apparel manufacturers failed to fully recover jobs lost during down turns. Moreover, underscoring the industry’s long-term, noncyclical decline, periods of employment growth have been shorter, while the periods of job loss have become more per sistent. The most recent employment contraction lasted 7 years and followed a growth cycle of only 16 months. The industry lost 220,000 jobs between its April 1984 peak and April 1991 recession trough, while productivity increased by 13 percent and imports continued to expand. The textiles industry Increased spending by textile manufacturers in the 1970’s set the stage for productivity advances that occurred in the 1980’s. The increased spending boosted productivity levels substantially, which helped manufacturers compete with ris ing imports. Several recessions, combined with continued technological advances and rising imports, produced a pe riod of rapid employment losses. Productivity and structural changes. In the late 1960’s and early 1970’s, textiles manufacturers made major strides in automation. Although the industry has historically spent con siderable amounts of money on capital investments, spend ing in the 1970’s was significant because most of it was in vested in radical new technologies. Before 1968, the primary source of productivity gains was decreased manual handling of materials.5 For more than 100 years the industry had up dated and modified existing machinery. But in the 1970’s, completely new technology, such as open-end spinning and shuttleless looms, became available. These technologies dras tically reduced the time and number of workers needed to produce fabrics. For example, a water- or air-driven shuttle less loom not only produced fabric three times faster than its wooden fly shuttle predecessor, but it also could produce seven or eight times more fabric because it was able to weave wider widths. Open-end spinning boosted the rate of pro duction of yarn four times over the older ring-spinning tech https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Table 1. Employment in apparel and textiles, selected years, 1939-94 Apparel Textiles Employment in thounsands Percent change 1939.......... 1949 .......... 1959 .......... 1969.......... 1979.......... 1,193.0 1,187.0 945.7 1,002.5 885.1 (’) -0.5 -20.3 1989.......... 1990.......... 1991 .......... 1992.......... 1993.......... 1994.......... 719.8 691.4 670.0 674.1 674.8 672.0 -18.7 -3.9 -3.1 Year Employment in thousands Percent change 924.0 1,173.0 1,225.9 1,409.1 1,304.3 (’) 26.9 4.5 14.9 -7.4 1,075.7 1,036.2 1,006.0 1,007.2 984.6 954.3 -17.5 -3.7 -2.9 6.0 -11.7 .6 .1 -.4 .1 -2.2 -3.1 1 Data are not available. ñique and reduced the number of steps involved in manu facturing some kinds of yarn from 15 to 3.6 While the technology available was revolutionary, it also was expensive. U.S textile manufacturers spent an average of $3.1 billion (in constant 1987 dollars) annually between 1969 and 1974 on capital purchases, 90 percent of which was for new equipment purchases. During the first half of the decade, manufacturers spent between 6 percent and 7 percent of their value of shipments on capital investment. In the latter half of the decade the spending dropped to about 5 percent of the value of shipments, or $2.4 billion annually. During much of the 1970’s, capital expenditures for the in dustry were greater than profits.7 As a result of the automation during the 1970’s, labor productivity, expressed in terms of output per employee hour, increased 56 percent between 1969 and 1979. Constant dol lar shipments8 rose by $11.5 billion annually during the de cade, while employment declined by more than 125,000jobs. In the early and mid-1980’s, profits in the textile industry began to decline dramatically due to the rising value of the dollar, a substantial drop in exports of textile products, and two recessions in the early 1980’s. Capital spending declined to an average of $2.2 billion, and in 1986, fell to $1.8 bil lion, its lowest level since 1963. In the mid-1980’s, textile manufacturers took part in several mergers and acquisitions. This restructuring led to the establishment of several domi nant firms in the industry.9 Many textiles companies were the targets of leveraged buyouts. Because the industry had a history of erratic earn ings, many manufacturers’ stock was traded below book value. Its low was attractive to buyers who were able to raise capital by using the company’s assets as collateral. This was the case for at least four major manufacturers: Cannon Mills, Cone Mills, Dan River Inc., and Burlington, which were purchased during the 1980’s. The size of the new firms lent M onthly Labor Review August 1995 63 Textile, Apparel Employment itself to achieving greater economies of scale, and gave the newly formed com panies a larger capital base with which to invest in emerging technologies. Capi tal investments rebounded to an average of $2.4 billion between 1987 and 1990.10 Between Decem ber 1978 and the April 1991 employment trough, employ ment declined 26 percent, or 230,000 jobs. Labor productivity gains averaged 2.7 percent a year between 1979 and 1991, more in line with total manufac turing productivity growth of 2.6 percent. Production grew even as employment losses persisted, and reached a new alltime high in April 1989, before the most recent recession began and demand weakened. Following the 1990-91 reces sion, the textile industry enjoyed 2 years of employment growth before it again began trimming payrolls in June 1993. However, production continued to in crease: December 1994 levels were 8 per cent above the April 1989 peak level. Chart 1. Employment and production in textiles, 1950-94 Employment, 1987=100 Production, 1987=100 180 160 140 120 100 80 60 40 20 So u r c es : Employment data from the Bureau of Labor Statistics; production data Imports and exports. A second reason from the Federal Reserve Board for the decline in textile employment was increased imports. The textile industry fared far better than the apparel industry against rising im From 1980 to 1988, the import share of total U.S. textile ports in the 1970’s. The textile industry not only kept its consumption increased by less than 3 percentage points, ris share of the domestic market throughout the decade, but it ing to 7 percent of domestic consumption. In contrast, the also maintained a trade surplus for the latter half of the de apparel industry’s import penetration had reached 26 per cade and into the early 1980’s. The ability of the industry to cent by 1988, an increase of 13 percentage points from 1980. maintain its market share was, very likely, due to the tech In 1992, imports still accounted for a relatively small 11 per nological advances that reduced needed labor and acceler cent of all domestic textile consumption. ated the production process. Capital expenditures required Exports offset some of the increase in textile imports dur to obtain this type of technology were prohibitive to many ing the late 1980’s. Although exports fell during the first half developing countries, particularly those with a large number of the decade because of an overvalued dollar, they began to of small, fragmented producers. Low wages in developing rebound in 1986, providing some stimulus for the industry. countries may also have limited pressures on those textile In 1989, exports comprised 4 percent of industry shipments. manufacturers to introduce new labor-saving technologies.11 The impact of exports on employment is even greater when Thus, U.S. manufacturers were more competitive with the indirect exports, such as the use of fabric in clothing that is low-wage countries. exported, is considered; neaily 10 percent of textile employ The U.S. textiles industry also performed much better than ment was related to direct and indirect exports in 1989.13 its European counterparts. The United States was the only As was indicated above, the U.S. textiles industry does major industrialized country to maintain its domestic mar not appear to have greatly suffered from direct imports. How ket share in the 1970’s; imports comprised only 4.5 percent ever, the industry was significantly affected by the surge of of domestic market share in 1970 and 1980. Germany’s and apparti imports. The U.S. textile industry supplies most of the United Kingdom’s textile import penetration increased the textile products required by domestic apparel producers. substantially. Import penetration by Japan, the largest postAs apparel imports rose and continued to gain domestic World War II exporter, and Italy, while still posting a trade market share, U.S. apparel producers required less domestic surplus in the textiles industry, also increased.12 textile products. M onthly Labor Review Digitized for 64 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 The apparel industry Chart 2. Employment and production In apparel, 1950-94 Employment in the apparel industry de clined significantly in the 1970’s and 1980’s. Technology introduced in this period was less revolutionary than that in the textiles industry. Most likely, ap parel imports had the principal influence on employment. Apparel employment peaked in 1973 with production peaking in July 1987; both production and em ployment have continued to decline in the 1990’s. Productivity and structural changes. Technological innovations in the apparel industry during the 1970’s and 1980’s were less sweeping and more incremen tal than changes in the textiles industry. Examples of technologies that were de veloped in the 1970’s and 1980’s are pro grammable sewing machines that allow operators to work more than one machine at a time, Computer Aided Design (CAD) that reduces lead time, and computer con trolled cutting of material. Labor produc Sources : Employment data from the Bureau of Labor Statistics; production data from the Federal Reserve Board. tivity increased by 26 percent between 1969 and 1979; this was slightly less than the 33-percent rate for all manufacturing. low profit margin, and the cost of new, technologically ad In the 1970’s, the apparel industry spent more on capital vanced equipment would be prohibitive to many of them. But investments than it had during the 1950’s and 1960’s com labor productivity continued to rise in the 1980’s as produc bined. However, the industry still spent at only two-fifths of tion of apparel products grew by 7 percent while employ the textiles industry’s rate, primarily due to a lack of new ment fell. Labor productivity grew at an annual average rate technology. (See chart 4.) The new technology that was avail of 2.4 percent between 1979 and 1991.15 Yet it is impossible able to apparel manufacturers was not as powerful or expen to know if employment would have declined less without the sive as that available to textile manufacturers. However, an productivity gains, because the higher labor costs would have other reason for the low level of spending, and perhaps the made the industry even less competitive with imports. limited new technology available, can be explained by the In 1990, 30 percent more labor was required for every structure of the apparel industry: firms in the apparel indus dollar of output in the apparel industry than in the textiles try are typically smaller and more disconnected than firms industry.1 6 The textiles industry continued to invest far more in the textiles industry. For example, 23,600 domestic ap in capital in the 1980’s than the apparel industry, spending parel establishments employed about 1.3 million people in $23 billion, or 4 percent of the industry’s value of shipments, January 1976. By contrast, about 7,300 textile establishments while the apparel industry spent only $8 billion, or 1.5 per employed slightly more than 900,000 workers. Twenty-four cent of that industry’s value of shipments. In addition, the percent of textile workers were employed in establishments apparel industry directed only half of those expenditures to of more than 1,000 employees in 1976 compared with only 8 new equipment, while the textiles industry spent threepercent in the apparel industry; at the other extreme, nearly fourths of its outlays on new equipment. 20 percent of apparel workers were employed in establish ments of fewer than 50 workers, versus less than 7 percent Imports and exports. Imports in the apparel industry in of textile workers.14 creased from 5 percent of total consumption in 1970 to 26 The size of many apparel firms was often an obstacle to percent in 1988, or from $1.3 billion to $22 billion annually. large capital investments. Small firms typically operate on a This contrasts with the textiles industry, which lost less mar https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M ontN y Labor Review A ugust 1995 65 Textile, A p p are l Em ploym ent ket share to overseas productions. Ap Chart 3. Textile and apparel imports as a proportion of parel imports not only grew rapidly, but domestic consumption, 1970 and 1 comprised a large share of total sales. This import growth led to large-scale em 1970 Textiles 1988 ployment declines. The apparel industry was particularly hard hit by imports from developing countries. Less developed countries tra ditionally have begun industrialization with the apparel and textiles industries because raw materials are relatively com 6.8 mon, and because the two industries re quire less capital than most other manu facturing activities.17 Thus, developing countries with an abundance of cheap la bor but very little capital can produce tex tiles and apparel products. An example of this type of industrial ization policy can be seen in Japan fol lowing World War II. Faced with the de Apparel struction of much of their manufacturing (in percent) base, the Japanese focused on the textiles and apparel industries to rebuild. In 1950, textiles accounted for 24 percent of total shipments and 48 percent of ex ports. By 1980, the figures had dropped to 5.2 and 4.8 percent. Textiles and ap 5.2 parel declined in importance as Japan became more industrialized and wage 26.1 pressures grew. Japanese industrial policy focused more on high technology industries with larger profit margins. Japanese textile producers today are simi n Domestic lar to U.S. producers: they are more capi | Imports tal intensive, and they also manufacture SOURCE: U.S. Department of Commerce more expensive fabrics. D eveloping countries rapidly in creased their share of the world export market in apparel. In for only 1.8 percent of world apparel exports), and grew modestly in the latter half. But in contrast to the textiles 1965, world apparel exports totaled $3 billion and develop industry, the apparel industry never experienced a trade sur ing countries supplied only 14 percent; by 1991, world ap parel exports totaled $119 billion and developing countries plus. In 1989, exports accounted for only 4 percent of total supplied 59 percent. The developing economies in Asia shipments (the same ratio as for textiles), and were over (China, Korea, Mongolia, and Vietnam) supplied half of whelmed by imports. The industry’s trade imbalance has steadily worsened since 1980. In 1992, the apparel industry’s the world’s apparel exports in 1991, while the United States supplied less than 3 percent. At the same time, the Unites trade deficit was nearly $26 billion, eight times greater than States received 19.4 percent of world exports, including a the textile industry’s imbalance, and the worst imbalance of third of the exports from developing countries.18 (See table all the manufacturing industries. (See chart 6.) The apparel industry’s practice of using manufacturing 2 and chart 5.) workers in Caribbean countries contributed to a portion of Despite the loss of international market share in the 1970’s, U.S. apparel exports increased in value. During the increased imports. “Sourcing,” or “807 Sourcing,” as it is called in the apparel industry, refers to cutting material in first half of the 1980’s, apparel exports declined as the value the United States and assembling it in other nations.19 The of the dollar rose (in 1984, U.S. apparel exports accounted 66 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Chart 4. Capital investment by the apparel and textiles Industries in constant dollars, 1965-92 Thousands Thousands $4 0 0 0 1------ $4,000 H Apparel □ Textiles 3,000 3,000 2,000 2,000 1,000 1 1965 1967 1969 1971 1973 I 1975 1977 1979 1981 1983 1985 1987 lili 1989 1,000 1991 Source: U.S. Department of Commerce product is then imported back to the United States, with du ties paid only on the value added, and shipped by the U.S. manufacturer for sale.20 Thus, the count of imports includes the value added by assembly in these sourcing arrangements. Although this practice began in the late 1960’s, the amount of shipments allowed to reenter the United States was limited by quotas. In 1985, under new bilateral agree ments with the Caribbean Basin countries,21 unlimited ac cess was negotiated for firms that, in addition to cutting the material in the United States, also used U.S.-made material. This new sourcing agreement is termed 807a, a traditional type of outsourcing. Firms in the United States operate un der 807 and 807a sourcing methods. As a result of this lift ing of import quotas, imports from the Caribbean Basin have grown rapidly. Between 1987 and 1992, imports under the 807 sourcing programs increased by 180 percent, to $3.8 billion in 1992. Nevertheless, this was still just 14 percent of total U.S. apparel imports.22 Despite the use of labor that is outside the United States, determining the precise impact on jobs is impossible. Many industry leaders— in the American Apparel Manufacturers Association, the U.S. Department of Commerce, and other organizations and agencies—believe that, without the prac tice of 807 sourcing, many U.S. apparel manufacturers https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis would go out of business, causing a significant loss of jobs in the industry. Because of this arrangement, domestic manu facturers have been able to take advantage of the relatively cheap labor in Mexico and the Caribbean to manufacture apparel products that are more competitively priced com pared with East-Asian products. For this reason, 807 sourc ing may have reduced the demand for imports from Asia, protecting the employment of domestic workers who con tribute to some parts of the manufacturing process. As a re sult, although some apparel assembly jobs in the United States have moved to the Caribbean Basin or Mexico, even more might have been lost to East-Asian imports without this legislation. Meanwhile, the apparel industry is still confronted by growing imports. While imports under section 807 are com prising a larger share of total imports, most imports con tinue to come from developing Asia (nearly 80 percent in 1990).23 In 1992, apparel imports accounted for 31 percent of domestic consumption. Employment outlook and trade agreements and the Multi-Fiber Arrangement. Among the factors that are expected to have a substantial impact on employ- g att M onthly Labor Review August 1995 67 Textile, A p p a re l Em ploym ent Developing and developed countries’ share of the world export market, in percent, 1965-90 Textiles D eve lo p in g D e v e lo p e d D eve lo p in g m a rk e t m a rk e t m a rk e t e c o n o m ie s e c o n o m ie s e c o n o m ie s Year 1965 1970 1975 1980 1985 1990 ......................... ......................... ......................... ......................... ......................... ......................... N ote: A p p a re l 16.0 15.4 17.6 22.1 28.0 39.0 76.4 77.6 74.6 69.8 62.2 59.1 14.8 21.1 32.0 36.5 47.9 56.4 D e v e lo p e d m a rk e t e c o n o m ie s 69.7 63.5 54.5 51.2 41.5 41.3 Based on sue 65 for textiles and sue 84 for apparel. S ource: United Nations ment in the textiles and apparel industries, perhaps the most influential will be the trade policy agreed to in the General Agreement on Tariffs and Trade (GATT). With the support of the United States, the Multi-Fiber Arrangement will be phased out over 10 years. This arrangement has been the textiles and apparel trade agreement in effect among most nations since 1974, and has been renegotiated and ratified four times, most recently in 1986.24 The Multi-Fiber Arrangement, a network of bilateral trade agreements, operates outside the regulations of g a t t , and al lows countries to place import quotas on textiles and apparel products that, under g a t t , would not be permitted. The MultiFiber Arrangement permits importing countries to place quotas on apparel and textile products from selected coun tries to avoid domestic market disruption. While the arrange ment has undoubtedly protected some domestic jobs, it was criticized by consumer groups, several academics, and pro ponents of free trade because of its cost to consumers and its protectionist type quotas. A study by William Cline found that 214,000 jobs were saved in the apparel industry due to the Multi-Fiber Arrangement, at a cost to consumers of $46,000 annually per job.25 A separate study by Gary Clyde Hufbauer, Diane Berliner, and Kimberly Ann Elliott found that the Multi-Fiber Arrangement had saved 460,000 jobs in the apparel industry at a consumer cost of $39,000 per job.26 With the phase-out of the Multi-Fiber Arrangement, tex tile and apparel trade will be conducted under rules and regu lations of GATT. The phase-out of the Multi-Fiber Arrange ment will allow increased imports by releasing some prod ucts from quota limits at set intervals, while the quota limits on the remaining protected products are raised each year. These regulations will be set for participating countries and should allow for freer trade of textile and apparel products among these countries. As a result of the phase-out, import restrictions will be eliminated 10 years after it is enacted.27 Several groups have estimated the impact on employment from the phase-out of the Multi-Fiber Arrangement, but es 68 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 timates vary dramatically. Estimating effects on employment is difficult because several important facets of the agreement have not yet been decided.28 For example, the status of quota limits for products from China is unknown because that country is not a member of g a t t .29 Estimating demand for U.S. products from foreign countries that will have freer markets also is difficult. In a study published in January 1992, Wharton Economic Forecasting Associates states that the “direct and indirect impact on the textile and apparel industries is estimated to be a job loss of 647,000 . . .”.30 A study by the American Textile Manufacturers Institute estimates that number of jobs will fall by 1.4 million dur ing the same period, leaving only 300,000 jobs in the indus tries.31 However, the U.S. International Trade Commis sion estimated that eliminating all import quotas and tariffs would reduce employment in the two industries by between 230,000 and 290,000. The Congressional Budget Office notes that the losses may be even lighter than the trade commission estimates because the commission’s study did not take into account the proposal that all industrialized countries remove their restrictions at the same time; the continued application of import quotas to countries that are not members of g a t t , such as Taiwan and China; and that tariffs on the products may still remain even after quotas are removed.32 The apparel industry, which is far more labor intensive and less competitive internationally than the textile indus try, will probably sustain most of the losses from the new trade environment. As noted, the textiles industry does not suffer from severe import competition as does the apparel industry, but is affected more indirectly: less domestic ap parel production means fewer domestic textiles are needed. A possible advantage of the new agreements would be the opening of markets in developing countries that restrict im ports of U.S. textile and apparel products. Because the U.S. textiles industry uses fairly efficient production processes, demand from foreign apparel producers could increase. NAFTA. Future employment levels also will be affected by the North American Free Trade Agreement ( n a f t a ). The agreement, which took effect January 1,1994, created a freetrade zone among the United States, Canada, and Mexico. n a f t a is expected to contribute to employment declines in the apparel industry but may generate job growth in the tex tiles industry. With the relatively cheap labor that is available in Mexico, some apparel manufacturers are likely to move their opera tions south to be more competitive, n a f t a also may cause apparel manufacturers to slowly discontinue 807 sourcing operations in the Caribbean as they reinvest in Mexico, where finished products would not be subject to duties. A study by the International Trade Commission concluded that a free trade agreement would introduce incentives that favor ap supply that is inadequate for dyeing and finishing yams will parel investment shifts from Caribbean Basin countries to impede investments in the near future.34 This will provide Mexico; but the study could not quantify any effects of this further stimulus to the U.S. textiles industry. In addition, shift.33 According to this study, companies that already have n a f t a will boost production and imports of U.S.-made invested heavily in the Caribbean may invest in Mexico to * fabrics, according to the Wharton Economic Forecasting remain competitive, although this would require large capi Associates.35 tal expenditures. The impact of n a f t a on imports, exports, and employ The textiles industry would probably not undergo the same ment would be expected to occur incrementally over many shift in its manufacturing base. Because the textiles industry years. During 1994, the first year after n a f t a took effect, an is much less labor intensive than the apparel industry, U.S. nual average employment in textiles was relatively flat for companies would not have the same incentive to relocate pro the third consecutive year, and declines in apparel contin duction. Further, the United States is the largest supplier of ued. Both developments were in line with expectations for textile goods to Mexico’s clothing manufacturers and, for employment trends under n a f t a . apparel products to remain duty-free throughout the freetrade zone, the apparel products must be made from North Eastern Europe. The changing political and economic sta American fiber, spun in North American mills. With an effi tus of Eastern Europe also may negatively affect employment cient production process in place, U.S. textiles manufactur prospects for apparel. With the opening of Eastern European ers would benefit from increased production in the free-trade markets, these countries have the ability to become bigger zone. The U.S. textiles manufacturers are more efficient than players internationally. Unlike many apparel workers in East Mexican textile manufacturers, and the elimination of tariffs Asia, those in Eastern European countries are very skilled. would make U.S. textile products more attractive to Mexican This level of skill, coupled with the very low wages, may apparel producers. Mexican textile manufacturers could, in allow these countries to produce more expensive apparel prod the long run, invest in better facilities, but the large capital ucts, such as tailored suits and coats, at a fraction of the price outlays required for efficient plants, coupled with a water paid by U.S. manufacturers. For example, in 1991 the averChart 5. Imports and exports of apparel products, 1965-91 Percent Percent 1965 1970 1975 1980 1985 1991 SOURCE: United Nations https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 69 Textile, A p p a re l Em ploym ent Chart 6. Developing countries' share of world exports in apparel products, 1965-92 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 S o u r c e : Department of Com merce age U.S. apparel worker earned $6.77 an hour; a similarly skilled worker in the former Soviet Union earned $0.36.36 As incomes rise, however, the appeal of U.S. clothing could attract buyers in these same countries. Productivity Even if the current trade regime were to remain unchanged, the industries’ employment levels would still be expected to decline. The Bureau of Labor Statistics estimates that, de pending on the economy’s growth, the textiles industry will lose between 85,000 and 160,000 jobs between 1992 and 2005, while losses in the apparel industry will range from 240,000 to 350,OOO.37 Under the current trade regulations, the Wharton estimate is that the textile and apparel indus tries, combined, will lose 400,000 jobs during the 19932002 period. This estimate also is based on expected pro ductivity increases and the domestic industries’ competi tive disadvantages. Productivity will continue to have a major impact on em ployment in the 1990’s. Productivity advances will continue to build on the uses of computer integrated manufacturing and quick response. Use of computer integrated manufac M onthly Labor Review Digitized for 70 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 turing already has begun in the textiles industry. A fully com puter-integrated spinning mill that virtually eliminates the need for laborers already has been established in Japan. The entire process, from placing bales in the opening line to load ing trucks for shipment, is achieved without human hands touching the material; maintaining and controlling the entire plant requires only nine employees. In the United States, many plants use some form of com puter integration in manufacturing. For example, a Moun tain City, t n , automated yarn spinning plant produces 600,000 pounds per week of cotton yarn with fewer than 200 employ ees. The only handling of material occurs when cotton is un loaded from trucks and when packed yarn is reloaded for de livery.38 Computer integrated manufacturing reduces labor costs and enhances quality and reduces error. Optical scan ning can detect errors and alert operators immediately. Fully automated apparel plants are only in the early stages of development. A fully operational computer integrated man ufacturing system has the potential to reduce the time needed to complete a season’s line from 30 weeks to between 5 and 6 weeks.39 Many apparel manufacturers already have started using computer-aided design systems and modular manufac turing. These systems have allowed garment manufacturers to substantially reduce the time needed for design. Modular manufacturing consists of units or small teams of employees who produce an entire garment. This team system has in creased quality and minimized downtime in many plants.40 Dean Vought, president of Textile and Clothing Technol ogy Corp., an independent research firm, believes that “advances in manufacturing technology, while needed and welcome, have a limited impact. . .the wide variety of style changes and limp fabrics that must be accommodated in manufacturing make it unlikely that we could reduce direct labor content by more than 25 percent through all currently conceivable mechanization and automation.” That still may not be enough to compete with low wage countries. Vought emphasized that resources may be better spent “on developing technology to reduce calendar time rather than cost Time, service and more accurate response to consumer demand are where we have an advantage that can be strengthened through technology.” Thus, computer inte grated man-ufacturing in the apparel industry may be fo cused on time-saving techniques. This type of technology takes the form of improved communications, data manipu lation, graphics, video imaging, and satellite transmissions and can be used in product development, marketing and cus tomer service.41 Quick response manufacturing follows the time-oriented concept that quicker is better, and is becoming the norm in the apparel and textiles industry. Quick response programs use computers to speed the goods, services, and information in domestic apparel production, tying apparel producers with textile suppliers and retailers.42 Quick response has become important in the apparel industry because more retailers are demanding it as they seek to minimize inventories and markdowns while restocking popular items. For apparel manu facturers to provide retailers with goods on a quick-turn around basis, they must be able to receive their manufactur ing inputs quickly. Therefore, this chain of demand is re quiring closer partnerships among retailers, apparel manu facturers, and textile manufacturers. Quick response helps the U.S. apparel industry to com pete against foreign manufacturers. Many retailers have little control over the quality of the products they purchase from abroad, and many times the quality of the products is not consistent among shipments. Quick response gives domes tic manufacturers an advantage because they can deliver bet ter quality items more quickly. The link between manufac turers and retailers also provides incentives for producers to deliver better quality items. One survey of apparel manufac turers found that 61 percent of respondents had quick re sponse programs with their retail partners in 1991, up from https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 51 percent in 1990, while 32 percent had such programs with their textile partners, up from 23 percent in 1990.43 All of the above technologies and trends are combining to enable producers to create better quality products, more quickly and for less money in both industries. In a time of rapidly changing economies, and with prospects of freer trade on the horizon, these practices can enable the textiles and apparel industry to maintain, or perhaps increase, their share of the world market. s u m , employment has declined in the textile and apparel industries over the past two decades—together they have lost more than 750,000 jobs. Although the industries are closely linked, their operations are very different. The textiles in dustry is concentrated, automated, and efficient. Because the apparel industry is still very labor intensive, despite new technologies, it has difficulty competing with foreign pro ducers in low-wage countries. The apparel industry also is not as concentrated as the textiles industry. In the United States in 1987, 21,000 apparel companies shipped goods valued at $64 billion. The textiles industry had only 5,000 companies producing $63 billion in shipments.44 Between 1949 and 1991, labor productivity in the textiles industry grew at an average annual rate of 3.9 percent, much faster than the annual average rate of 2.5 percent for all manufacturing. Labor productivity in the apparel industry grew at an annual average rate of only 2.2 percent during the same time period, slightly slower than the rate for all manufacturing. Imports in the textile industry gained about 5 percentage points of domestic market share from 1970 to 1993, rising from 4.5 percent to 9 percent. The apparel industry, by con trast, saw imports rise from about 5 percent to 31 percent during the same period. Textile production continues to reach new heights, but apparel production has not returned to its peak level that occurred in 1987. Industrial production in the apparel industry is off 6 percent from its July 1987 peak, according to December 1994 data. Although the apparel industry continued to lay off work ers in 1994, employment in textiles was relatively flat. Over the long term, declines are expected to continue, particu larly in apparel. Competition will be even fiercer with stepped up global trade and the lifting of import restrictions. Labor-saving and time-saving technologies will help domes tic manufacturers compete against low-wage countries to maintain (and perhaps expand) domestic and world market share. Therefore, emerging technologies and opening mar kets should be the main forces behind the employment trends in the next 10 years. □ In M onthly Labor Review August 1995 71 Textile, Apparel E m ploym ent Footnotes 1Employment data are from the Current Employment Statistics Survey and appear in Employment, Hours, and Earnings, United States, 1909-1990, Vol ume II, Bulletin 2370, and Employment, Hours, and Earnings, United States, 1981-93, Bulletin 2429 (Bureau of Labor Statistics, 1991 and August). 2 Production data from Federal Reserve Statistical Release, Industrial Pro duction and Capacity Utilization, (Federal Reserve System), various issues. 3Productivity data based on unpublished data from the Office o f Productiv ity and Technology, Bureau o f Labor Statistics, September 1992. Productivity data for apparel and textiles are available only through 1991. 4 William R. Cline, The Future of World Trade in Textiles and Apparel (Washington, Institute for International Economics, 1987), table 2.5. 5Centre on Transnational Corporations, Transnational Corporations in the Man-made Fibre, Textile and Clothing Industries (United Nations, 1987), p. 75. 6 Fariborz Ghadar, William H. Davidson, and Charles S. Feigenoff, U.S. Industrial Competitiveness, The Case of the Textile and Apparel Industries (Lexington, m a , Lexington Books, D.C. Heath and Co., 1987), pp. 19-20. 7 Data are “corporate profits before taxes” obtained from U.S. Department o f Commerce, Bureau o f Economic Analysis, National Income and Products Accounts, 1959-1988, vol. 2, ( July 1992), table 6.17. 8 Constant-dollar shipments were deflated using the Producer Price Index for textile and apparel products. The base year is 1982. 9 Some of the larger consolidations were West Point-Pepperell’s acquisition o f J.P. Stevens and Cluett, Peabody & Co.; the subsequent acquisition o f West Point-Pepperell by a majority stockholder o f Fruit o f the Loom; the merger of Spring Industries and M. Lowenstein; and the sale of Cannon Mills to Fieldcrest, becoming Fieldcrest Cannon. Standard and Poor’s Industry Surveys, Nov. 28, 1991, pp. T76-T77. 10The information on leveraged buy-outs was primarily obtained from Stan dard and P oor’s Industry Surveys, Nov. 28, 1991, pp. T76-T77. 11 United Nations Centre on Transnational Corporations, Transnational Corporations in the Man-made Fibre, Textile and Clothing Industries, p. 80. 12 Cline, The Future of World Trade, table 5.5. The high level of import penetration in the European countries also reflects a higher degree of intraindustry trade in the European Economic Community. All international trade statistics are based on Standard Industrial Trade Class ification codes 65 for textile products and 84 for apparel products, s i t c 65 in cludes fabricated textile products; SIC 22 does not. s i t c 84 includes only cloth ing while sic 23 includes clothing and fabricated textile products. Therefore, sic’s 22 and 23 are not strictly comparable to s i t c ’ s 65 and 84. 13 Exports From Manufacturing Establishments, 1988 and 1989, AR89-1 (Bureau o f the Census, November 1992), p. 30. 14 Bureau o f Labor Statistics, Office o f Employment and Unemployment Statistics, unpublished data. Data available beginning in 1976. lsThe labor productivity rates may be overstated because some U.S. apparel products are shipped to the Caribbean or Mexico for assembly or other work, and then shipped to the United States where they are included in the U.S. industry’s total shipments. Therefore, some labor used in manufacturing the product may not be included in the productivity measures. 16This figure was derived using the annual average aggregate hours from the Current Employment Statistics Survey and total shipments from the Bu reau o f the Census. 17 Ghadar and others, U.S. Industrial Competitiveness, pp. 16-17. 18Monthly Bulletin of Statistics, vol. XXXV, no. 5, special table D, and vol. XI, no. 2, special table C and various other issues including special tables C and D. (New York, United Nations, Department of Economic and Social De velopment, Statistical Division, May 1981). The makeup of countries included in the developing economies has changed as centrally planned economies, such as Eastern European countries, shift to open markets. 19 “The term 807 refers to a tariff paragraph in Schedule 8 o f the U.S. Tariff Code that defines the covered articles as follows: ‘Articles assembled abroad in whole or in part o f fabricated components, the product o f the United States, which a) were exported in condition ready for assembly without further fabri cation, b) have not lost their physical identity in such articles by change in form, shape or otherwise, and c) have not been advanced in value or improved in condition abroad except by being assembled and except by operations inci dental to the assembly process such as cleaning, lubricating, and painting.’” See U.S. Apparel Imports Under807 (Arlington, v a , American Apparel Manu- 72 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 facturers Association, undated), p. 1. 20Although most o f tariff code 807 imports are from the Caribbean Basin, the same agreement is in effect with Mexico and is called Special Regime. These imports from Mexico still enter the United States under tariff code 807 and any reference here to 807 imports includes imports from the Caribbean and Mexico. 21 Belize, Costa Rica, the Dominican Republic, El Salvador, Guatemala, Haiti, Honduras, and Jamaica are the primary countries in the Caribbean Basin initiative. 22 “U.S. 807 Apparel Imports,” Table 1. 23 Monthly Bulletin of Statistics, vol. XLV1I, no. 5 (New York, United Na tions, Department of Economic and Social Development, Statisticals Division), special table D . 24 Four multi-fiber arrangements were negotiated between 1973 and 1986 (MFAI - MFAIV). The Multi-Fiber Arrangement was not negotiated and rati fied again upon its expiration in 1991 because most countries had agreed that it would be eliminated. But until negotiations for elimination of the arrangement were completed, MFA IV was extended. 25 Cline, The Future of World Trade, p. 193. 26Gary Clyde Hufbauer, Diane Berliner, and Kimberly Ann Elliott, Trade Protection in the United States: 31 Case Studies (Washington, Institute for International Economics, 1986), p. 148. 27The information on the schedule o f the Multi-Fiber Arrangement phase out was obtained from “Multilateral Trade Negotiations, The Uruguay Round,” UR-91-0185 (New York, Trade Negotiations Committee, General Agreement on Tariffs and Trade Secretariat, December 20,1991). 28Three studies from the Wharton Economic Forecasting Association, Ameri can Textile Manufacturers Institute, and U.S. International Trade Commission assume that import quotas will be lifted from all countries. 29According to the Executive Summary, Results of the gait Uruguay Round of Multilateral Trade Negotiations “China will not be permitted to sign the agreement on textiles and clothing until it becomes a member of g a t t , and, until then, will not be the beneficiary of any quota liberalization by the United States.” 30 “The Impact o f Eliminating the Multi-Fiber Arrangement on the U.S. Economy, Isolating the Textile and Apparel Components of g a t t ” (Philadel phia, the w e f a Group, 1992). 31 Carlos Moore, “Phasing Out the Multi-Fiber Arrangement in the Uruguay Round: The Impact on U.S. and Foreign Producers” (Washington, D C , Ameri can Textile Manufacturers Institute, March 1991). 32“Trade Restraints and the Competitive Status o f the Textile, Apparel, and Nonrubber Footwear Industries” (Congressional Budget Office, 1991). 33“Potential Effects of a North American Free Trade Agreement on Apparel Investment incBERA Countries” Report to the U.S. Trade Representative (Wash ington, United States International Trade Commission, July 1992) p. 72. 34 “Potential Impact on the U.S. Economy and Selected Industries o f the North American Free-Trade Agreement,” Publication 2596 (Washington, U.S. International Trade Commission, January, 1993) p. 8-3. 35 “A brighter day is dawning for U.S. textiles in 1993,” Textile World, Janu ary 1993, p. 40. 36The hourly wage figure for workers in the former Soviet Union was ob tained from “Labor costs - From Pakistan to Portugal,” Bobbin Magazine, September 1992, pp. 116-119. 37 James C. Franklin, “Industry output and employment,” Monthly Labor Review, November 1993, p. 54, table 50. 38 “Mountain City: Oh, What a M ill!” Textile World, June 1991, p. 50. 39 “The Impact of Technology on Apparel, Part 1,” 1991 Report of the Tech nical Advisory Committee, American Apparel Manufacturers Association, p. 12. 40 Industry Trade and Technology Review (Washington, U.S. International Trade Commission, October, 1992), p. 9. 41 “Time is of the Essence at [TC]2,” Bobbin Magazine, May 1992, p. 24. 42 Industry Trade and Technology Review (Washington, U.S. International Trade Commission, October, 1992), p. 9. 43 Ibid., p. 9. 441987 Census of Manufacturers: Concentration Ratios in Manufactur ing. MC87-S-6 (Bureau of the Census, February 1992), table 5. Rubber Workers ends strike The United Rubber Workers ended its 10-month strike against Bridgestone/ F irestone, Inc.— the longest work stoppage ever in the rubber industry— following the return to work of 700 members of Local 713 in Decatur, i l . The union accepted the terms of the tiremaker’s “final offer,” which had triggered the international’s walkout at five of the company’s plants last July, idling some 4,200 workers. After the walkout, Bridgestone/Firestone uni laterally imposed terms of its final offer, which included cuts in wages, health insurance, and pension benefits, and changes in work rules. In addition, the company hired some 2,300 workers to permanently replace strikers. According to one union insider, the agreement to return to work was not a capitulation on the part of the union, but a strategic attempt to forestall a union decertification election, keep the company from hiring more replacement workers, and stop union members from crossing picket lines at the plants. Ac cording to the press, the union also was worried about its members, who had been without paychecks for 10 months. A Bridgestone/Firestone spokesper son said the company was glad to re ceive the union’s offer to uncondition ally return to work. He said the com pany would evaluate workload and staffing requirements before informing the union of the number of employees who would be needed. Press reports subsequently indicated that the com pany would recall 153 strikers. Under terms of the imposed agree ment, hourly wages for most job classi fications are slashed $5.34, to around $12. Pay for new hires is cut 30 per cent, and incentive rates are reduced. “ Industrial Relations” is prepared by Michael H. Cimini and Charles J. Muhl of the Division of D evelop ments In Labor-Management Rela tions, Bureau of Labor Statistics, and is largely based on information from secondary sources. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Pension benefits are frozen at their ex isting levels. The work schedule is amended to allow for continuous opera tions with 12-hour shifts—that is, 12 hours on, followed by 12 hours off. Following its failed strike against B ridgestone/Firestone, the Rubber Workers ( u r w ) approved a merger with the United Steelworkers of America ( u s a ). In a joint statement, union lead ers said the merger will “combine our strength and resources in the political and legislative arenas, at the bargain ing table, and.. .will open the door wide for aggressive organizing among work ers wanting to join a growing force in democratic unionism.” Both unions have suffered declining membership in recent years. The cur rent URW membership of 98,000 is down from a peak of 180,000 in 1980, while USA membership has steadily fallen from more than 1 million in 1980 to its current level of 565,000. The merger will result in a combined union of approximately 665,000 members. The merger gives u r w members ac cess to the USA strike fund, currently at $162 million. The financial support is im portant because the walkout at Bridgestone/Firestone depleted the URW’s strike fund in December 1994. The union was forced to borrow $3 mil lion and raise membership dues to con tinue paying strike benefits. The timing of the merger is also fortuitous for the u r w because the union faces a heavy bar gaining schedule in 1995-96, when it renegotiates 232 contracts. Cost saving plans re ac h e d at usAir On the heels of a similar settlement with the Air Line Pilots Association, usAir Group signed a 5-year tentative agreement with the International Asso ciation of Machinists (IAM ) — moving the financially strapped carrier closer to its goal of reducing total labor costs by $2.5 billion over the next 5 years. The airline reportedly has pledged to slash an additional $2.5 billion in oper ating costs over the same period by elimi nating routes, selling old aircraft, and instituting other cost savings as part of a broader financial rescue package de signed to ensure the carrier’s survival. Like the Pilots’ agreement, the i a m pact is contingent on approval of usA ir’s board of directors and stockholders, as well as the signing of agreements with all the carrier’s unions. Negotiators for usAir and the i a m agreed to cut wages and introduce rule changes that are intended to provide “substantial” cost savings to the carrier in exchange for improved job security, a greater say in how the company is run, and certain financial returns. The ac cord covered some 14,500 i a m mem bers, including 8,000 mechanics and related employees and 6,500 fleet ser vice employees, for whom this will be their first agreement. The major terms of the cost saving plan call for i a m members to take a 12.9-percent pay cut in exchange for 20 percent of usA ir’s common stock and $400 million in preferred stock to be distributed among all employees, 4 em ployee-selected members on the company’s new 12-member board of directors, and a profit-sharing plan. The accord also enhances job security by including a no-layoff clause for the duration of the agreement, banning the transfer of work to foreign-based main tenance facilities, granting preferential hiring at commuter carriers that are part of the usAir system, and provid ing job protection in event of an asset sale or merger. Other terms allow for 4-day, 10-hour-a-day workweeks; and increase pension benefits by $15,000 for employees aged 58 or older. The Association of Flight Atten d ee s tentatively signed a pact similar to the one reached by the i a m , but it was rejected by the rank and file. The carrier has yet to negotiate an agree ment with its remaining union, the Transport Workers, which represents about 270 employees. M onthly Labor Review August 1995 73 Industrial Relations Early settlem ent a t Bell Atlantic More than 3 months before their con tract was set to expire, Bell Atlantic Corp. and Locals 827 and 1944 of the International Brotherhood of Electrical Workers reached agreement on a 5-year contract covering some 9,500 employ ees, most of whom work in New Jersey and Pennsylvania. Bell Atlantic hopes that the settlement will serve as a pat tern for its other major bargaining unit, 37,000 employees represented by the Communications Workers of America. According to Bell Atlantic’s chief ne gotiator, A1 Koeppe, “This is a progres sive contract that fairly balances the needs of Bell Atlantic in a competitive marketplace with the needs of employ ees and the i b e w for job security. It em bodies the spirit of respect, trust, and teamwork between the company and the i b e w —and our resolve to work coopera tively to meet competitive threats.” The accord calls for a $1,000 rati fication bonus, plus wage increases of 3 percent in the first year of the con tract, 2.75 percent in both the second and third years, and 3 percent in each of the final 2 years. The first $300 of the first-year wage increase will be paid as a lump sum. The settlem ent includes several changes in benefits and work rules. It improves the profit-sharing plan and increases pension benefits. The contract requires employees who retired after 1989 to contribute 2 percent of their an nual pension benefits to a trust fund to help pay for health insurance premiums beginning in 1997, with the rate in creasing to a maximum of 10 percent after the year 2000. The pact establishes two pilot programs, a 9-month test pro gram of 4-day workweeks for construc tion workers and a 1-month test of telecommuting (working at home using computers and other electronic equip ment) by clerical workers. Under the telecommuting program, the company will provide all necessary equipment. Digitized for74 FRASER M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 Other terms add coverage of preventive care services to health benefits; provide $750 awards to employees who com plete training programs “which en hance competitive technology and cus tomer service skills in telecommunica tions”; and strengthen job security pro visions by providing protection against layoffs for many bargaining unit em ployees and guaranteeing “virtually all” feeder and distribution facilities work on Bell Atlantic’s new broadband net work to bargaining unit employees. Twin Cities nurses reach a c c o rd Using interest-based bargaining that emphasized the exchange of issues important to each side, the Minnesota Nurses Association and the M etro politan Healthcare Council settled on a 3-year pact that clarifies the role of registered nurses in the health care delivery process. The agreem ent, which also provides wage increases, im proves advanced education ben efits, and addresses workplace vio lence, covers some 7,000 nurses at 12 M inneapolis-St. Paul area hospitals represented by the council. Using the “win-win” bargaining approach, the parties were able to reach agreement 2 weeks prior to the expiration of the previous contract, in stark contrast to past contentious negotiations that in cluded a 39-day strike in 1984. The parties recognized “a mutual interest in developing health care delivery systems which will provide quality care on a cost efficient basis [and] recognize the accountability of the registered nurse.” Like other health care providers nationwide, the Twin Cities hospitals faced declining revenues and increas ing expenses in recent years. Fearing that local hospitals might follow the industry pattern of replacing higherpaid re g istered nurses w ith u n li censed technical or assistant person nel to reduce labor costs, the union sought to include protective measures to ease the transition following a change in work force composition. The accord addresses a number of w o rk p lace issu es, in clu d in g the nurses’ role in providing health care to patients. Contract language guar antees that only nurses will “assess, plan, and evaluate patient or client nursing care needs.” The pact estab lishes a labor-management committee to address any proposed changes in health care delivery systems and to determine the exact role of nurses and unlicensed assistants in delivering care. Nurses are perm itted “to del egate those aspects of nursing care the nurse determines appropriate based on her or his assessment.” Each hos pital must provide a system of patient classification based on demonstrated patient needs and appropriate nursing interventions that will be used to de termine nursing staff levels. Any po tential changes to patient care deliv ery systems must be discussed jointly by the committee and the hospitals. The hospitals agreed to provide cross-training to prepare nurses for in dustry changes that may result in the use o f more unlicensed assistants. Nurses are eligible for up to $300 per year for training to prepare them for a second clinical service, for national cer tification in their area of practice, or for complementary therapies that may en hance their skills. Nurses pursuing an advanced degree also are eligible for annual tuition reimbursement of $2,000 (was $1,500) and may work flexible schedules to attend classes. The pact requires the hospitals to notify nurses of an impending layoff, and to offer voluntary leaves of ab sence to all nurses before reducing nursing care hours. Nurses adversely affected by a reduction in nursing care hours have the option to transfer to other vacant positions for which they are qualified, to replace less senior nurses within their clinical group or in other clinical groups, or to accept layoff and retain full recall rights. In the event of a layoff or major restructuring, full-time senior nurses aged 58 or older with 20 years of service have the option to choose early retirement with complete health insurance until age 65. To protect bargaining unit positions, hospitals are required to give advance notice of any promotion or transfer of an employee out of the bargaining unit. Furthermore, hospitals must provide written notice of the establishment of any new nonexecutive position and their initial determination as to whether the position will be included in the bargain ing unit— which the union may contest. The union also must be notified of any new programs or business ventures, in cluding any possible effect on the num ber of positions in the bargaining unit. Nurses will receive wage increases of 3 percent in the first and second contract years, and 2.6 percent in the third year. The starting salary for nurses ranges from $2,774 to $2,872 per month, depending on educational level. Nurses with 20 or more years of experience earn between $4,161 and $4,263 per month. Effective June 1, 1997, each nurse certified in a specialty area will receive an annual bo nus of $360. Citing a commitment to provide a workplace free of hostile, abusive, and disrespectful behavior, the parties agreed to form “response teams” to address all emergency situations in which physical violence, the threat of physical violence, or verbal abuse occurs. Participating hospitals will educate employees on methods of preventing workplace violence. In addition, nonemergency incidents will be recorded, reported, and evaluated by the nursing Health and Safety Committee when a registered nurse is involved. Other terms of the contract grant 3 additional days of leave for nurses with 15 to 19 years of service and 5 addi tional days for those with 20 or more years of service for professional deve lopment, continuing education, or per sonal renewal; provide a $100 monthly https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis supplement to nurses with master’s de grees beginning in 1996; and increase the maximum monthly long-term dis ability payment to 65 (was 60) percent of monthly compensation, to a maxi mum of $5,000, while lowering the work requirement for long-term disabil ity insurance eligibility from 64 to 48 hours every 2 weeks. LA cleanin g service p a c t As part of its “Justice for Janitors” drive to organize and bargain for commercial cleaning service workers, Local 339 of the Service Employees International Union ( s e i u ) negotiated separate but parallel 5-year contracts covering some 8,500 janitors working for 21 cleaning companies in the Los Angeles, CA, area. The pacts bring workers under one uni fied wage and benefit system, while maintaining health and pension benefits and strengthening job protection. The two largest employers participating in the coordinated bargaining were Inter national Service Systems, Inc. and American Building Maintenance, each with about 3,000 employees. The settlement will replace the 4tiered wage and benefit structure with one that provides the same wage and benefit levels to all employees. Under the prior contract, tier 1 employees received a starting rate of $6.80 per hour and full family health care cov erage paid for by the employers; tier 2 employees received $5.40 per hour and full individual health care cover age; and tier 3 workers received $4.70 per hour and no benefits except for paid vacations. The union was recog nized as the bargaining agent for tier 4 workers, but did not negotiate economic benefits for them. Tier 1 employees will receive a wage increase of $1 per hour over the contract term, while employ ees in tiers 2-4 will be brought up to the existing wage and benefit levels speci fied for tier 1 workers over the next 5 years. Language changes in the contract im prove job security and selection provi sions. Employers must now cite specific reasons, such as a building vacancy or a change in cleaning specifications, before implementing a work force reduction. Previously, the employers could lay off employees based solely on their own or their clients’ needs. Terms also stipulate that the selection of employees for vacan cies will be determined by seniority as long as selected applicants can perform the job in question. Seniority had previ ously been the determining factor only when merit and ability were judged equal. Other terms of the pact include a maintenance of benefits provision for health care, under which employers pay all premium costs and cover prescrip tion drugs and vision care; and a con tinued employer contribution of 10 cents per hour to the pension fund for tier 1 employees. The new agreement is the culmina tion of an 8-year organizing campaign by the union to represent workers of commercial cleaning firms in the Los Angeles area. The union has increased its representation in the industry from about 1,500 workers in 1987 to 8,500 in 1995, about 70 percent of the area’s cleaning service employees. A laska Airlines p a c t ends long stalem ate After more than 3-1/2 years of contract talks, negotiators for Alaska Airlines and the International Association of Machinists ( i a m ) reached agreement on a 4-year contract covering 2,200 cleri cal, office, and passenger service work ers employed in a variety of locations served by the airline, including Anchor age and Juneau, a k ; Portland, o r ; L os Angeles and San Francisco, CA; Phoe nix, a z ; and Seattle, WA. The settlement came just 4 days after the National Me diation Board—the Federal Agency that administers labor law in the industry— declared a “30-day cooling-off’ period following the parties’ refusal to resolve their dispute through arbitration. Wage M onthly Labor Review August 1995 75 Industrial Relations increases and benefits were the major sticking points in negotiations. Alaska Airlines sought a 5-year wage freeze, elimination of the cost-of-living adjustment (CO LA) provision, and in creased employee copayments towards health insurance premiums, while the union opposed these proposals. The eventual settlement between the carrier and i a m allows Alaska airlines to hold operating costs in check and preserves employees’ health care coverage. The contract calls for seniority-based bonuses ranging between $750 and $1,500 in each of the first 3 contract years. In the fourth year, employees will receive a general wage increase of 3 percent. The settlement eliminates the parties’ c o l a clause. Other changes increase the maxi mum annual accrual of compensatory time from 40 to 120 hours; permit train ing to be counted as time worked for overtime calculation; and continue the employee option to use a health mainte nance organization or preferred-pro vider organization, while adding dental and vision coverage. The parties also agreed to an “early reopener” in May 1999, which requires them to seek me diatory assistance from the National Mediation Board if a settlement is not reached within 6 months. Like many carriers in the industry, Alaska Airlines was in a financially pre carious position in the late 1980’s be cause of revenue decreases that had re sulted from fare wars and cut-throat competition in its short-haul Northwest markets, and because of high operating costs, in part from labor contracts. When current chairman and CEO Ray Vecci took control in 1991, the airline undertook severe cost-cutting measures that included canceling construction of two new maintenance bases, deferring planned aircraft purchases worth $2 bil lion, renegotiating aircraft leases, dis Digitized for 76 FRASER M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 continuing flights in unprofitable mar kets, and even cutting back on the in flight meals that had contributed to the carrier’s high customer service ratings. Furthermore, Alaska Airlines attempt ed to negotiate cost cuts and constraints in its labor contracts, producing strained relations and protracted negotiations with pilots, flight attendants, and other service workers. The carrier reached cost-cutting agreements that included flexibility in pay and scheduling with iAM-represented ground service workers in November 1992, after 4 years of negotiations (see Monthly Labor Review, Feb. 1993, p. 65); the pilots in January 1993; and flight attendants in February 1994, after 3-1/2 years of negotiations and a number of short, sporadic work stoppages (see Monthly Labor Review, June 1994). In spite of the sometimes tense negotiations between the parties, airline and union leaders have indicated that their relationship has improved because they have recognized the need for collective effort in meeting the challenges presented in their markets. As a result of Alaska Airlines’ cost cutting initiatives, its financial viability has recently improved, despite the en try of Southwest Airlines and the United Shuttle into its market. During the first 9 months of 1994, the carrier reported a profit of $27.6 million on $997.7 mil lion in gross revenue, compared with a $10.6 million loss on $851.1 million in revenue during the same period in 1993. The carrier’s cost per seat mile declined from 10.2 cents in 1992 to 9.9 cents in 1993, and to 8.6 cents in 1994. Settlem ent a t Rockwell International Members of Local 1362 of the Interna tional Brotherhood of Electrical Work ers approved a tentative 3-year contract covering some 2,000 production and maintenance workers at Rockwell Inter national Corp.’s Collins Division facil ity in Cedar Rapids, i a . The settlement calls for an immedi ate $600 lump-sum payment, a 50-cent hourly wage increase in the first year of the contract, an $1,800 lump-sum pay ment in the second year, and a 3-per cent wage increase in the third year. It continues the existing cost-of-living ad justm ent provision, which provides quarterly payments equal to 1 cent an hour for each 0.3-point increase in the Consumer Price Index for Urban Wage Earners and Clerical W orkers— but adds a trigger in each year. The index must rise 4 percent in the first year and 3 percent in the last 2 years before c o l a ’s are paid. The pact introduces several changes in benefits. It sets employee contribu tions towards medical insurance premi ums at $4 per month (was $14) for single coverage, $7 per month (new) for 2-party coverage, and $11.50 per month (new) for family coverage. The contract levies a $35-per-m onth penalty for spouses of employees enrolled in a Rockwell health care plan who refuse coverage under their own employers’ health care plans. The accord cuts the amount of time laid-off employees can continue medical coverage at their own expense, from 24 to 18 months immedi ately and to 12 months effective May 1, 1996. The settlement obligates Rockwell to match the first 1 percent of salary that an employee invests in the 401(k) thrift savings plan, up to $250 per year. Other terms create an employee skill development program designed to pro vide employees with skills they will need in the future; enhance recall rights; and require the company to discuss sub contracting of work that can not be done by bargaining unit employees for “com petitive reasons.” □ M aking school p a y Why Our Kids D on ’t Study: An Economist’s Perspective. John D. Owen. Baltimore, m d , The Johns Hopkins University Press, 1995, 136 pp„ $29.95. High school graduates in the United States are academically among the most poorly prepared in the world. John D. Owen, in Why Our Kids Don’t Study: An Economist’s Perspective, suggests that this situation can be explained as an economic phenomenon. Students are economic beings and, in their scho lastic behavior, respond to incentives, or the lack of them. Owen, an economist at Wayne State University in Detroit, uses the tools of labor economics to analyze shortfalls in student achievement. He has tried to reach beyond economists and other so cial scientists by avoiding mathematical analysis, graphs and charts, and fully explaining technical terms. The result is a highly readable book that will appeal to anyone concerned with problems in education in the United States. Owen briefly reviews the prevailing theories about why students do not study. Among the culprits are excessive exposure to television and popular mu sic; the notion that study is a challenge to youth self-esteem; and that adults place little value on studying and achievement. Although these factors may play a part in low academic achieve ment, the real explanation is that study ing does not pay, Owen writes. In other words, students do not see economic returns from their academic effort. Stu dents generally may stay in high school with little effort, and upon graduation, find their academic record counts for very little in obtaining a job. In addi tion, colleges, particularly those that are not among the elite, may accept stu dents more on their ability to pay than on their academic record. As a result, the labor market does not adequately reward study and does not provide https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis needed incentives to achieve in school. Moreover, bias against academic achievement is a problem in the public school system, Owen writes. Institutions receive financial incentives for large en rollments, regardless of the quality of stu dents, and may even receive additional funds when achievement drops. He also cites studies that imply a societal bias against education for its own sake when education promotes appreciation of sub jects such as art and literature, or what is termed “culture.” Owen proposes to change the incen tives for students, teachers, and schools. Students would work harder if schools and employers improved the exchange of student academic information and employers used this information in hir ing decisions. He includes a role for Federal Government policies that could foster integration of school and work in work-study programs. National or regional examinations might encourage students, teachers, and schools to work harder if employ ers used the results of these exams in hiring decisions. Policies to encourage school choice would force schools to com pete for students and students would compete for school admissions. Not everyone will agree with Owen’s analysis of the problem or with his pro posals, but few would dispute the need for a better educated work force to raise U.S. productivity and allow corporations to better compete in world markets. The findings and proposals in John Owen’s book are valuable additions to the debate about educational reform. —Pat Nielsen Bureau of Labor Statistics A tlan ta region Labor rights overseas Trade and Labor Standards: A Review of the Issues. Gary Fields, ed. Paris, o e c d , 1995, $14, 35 pp. The decision last year by officials of the Organization for Economic Coop- eration and Development to study trade and labor standards represented a break from the past. In April, the o e c d , through the efforts of its two director ates covering trade and employment and labor issues, released the first prod uct, Trade and Labor Standards: A Re view of the Issues, edited by economist Gary Fields. The book aims to review the main issues of the debate on whether and how to promote labor rights internationally. The book’s strongest feature is its analytical framework. It contends that certain labor regulations may reflect “basic human rights in the workplace” to be honored in poor and rich coun tries alike. These include: • a prohibition on slavery; • a responsibility to provide informa tion about unhealthy working con ditions; • the right of children to not work; long hours whenever family circum stances allow; and • freedom of association. Fields suggests that governments seek international agreements on these rights. But he does not explain why the current International Labor Organiza tion Conventions on these issues are in adequate. Beyond these four rights, the book suggests that setting labor standards be left to individual countries. He criti cizes more ambitious efforts to coordi nate labor standards for being intrusive, patronizing, or protectionist. The book also faults national laws banning the import of prison-made goods despite in ternational trade rules that permit such bans. Fields says that if prison inmates are forced to work, their output should be marketed in domestic and foreign markets. Another issue the book covers is whether legislation can “push up,” or improve labor conditions. The author suggests that labor markets do not suf fer “market failure,” and that, as a re sult, government’s role should be mini- M onthly Labor Review A ugust 1995 77 Book Reviews mal. Yet little is said about the inability of employers to tailor labor standards to each employee. Moreover, the book does not discuss noneconomic ration ales for government intervention. This is an odd omission in a book about la bor standards, considering the longtime international cooperation in advancing worker rights. Fields suggests that the “pull” of eco nomic development on labor conditions can be powerful. Relying on several studies, he concludes that higher na tional income translates into greater re turns to labor. He also cites evidence from Asian economies demonstrating that “labour earnings do not have to be suppressed in order for outward-ori ented economic growth to be rapid.” Fields also points to some negative im plications. G iving “prim acy to labour standards, if premature, can pre clude com petitiveness in trade,” he says. Unfortunately, he does not cite specific examples to back this claim. The reader is left to wonder if these cases involve adherence to interna tional labor conventions, or episodes in which governments have taken actions not required by ilo conventions, such as raising wages. The greatest disappointment in the book is its failure to review many key issues. For example, do high labor stan dards contribute to human development M onthly Labor Review Digitized for 78 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis and economic growth? What have been the economic effects in episodes where governments retreated on legislated worker rights? Does a higher g d p per capita increase the chances that a gov ernment will ratify il o conventions? How much international trade is pro duced in conditions that seriously vio late core il o Conventions? In 1964, when the Johnson Adminis tration first considered seeking oecd in volvement in matters related to trade and labor standards, an internal Federal Government memorandum cautioned that “ oecd consideration of a matter of this kind is likely to be very slow mov ing.” More than 30 years later, this pre diction remains on the mark. For a first effort, this new o e c d publication is a useful addition to the literature. But as the o ecd continues its work program on this topic, I hope that future studies will offer more in-depth analysis. Steve Chamovitz Com petitiveness Policy Council W ashington, DC State of the union The State of Working America, 19941995. By Lawrence Mishel and Jared Bernstein. Armonk, n y , M. E. Sharpe, 1994, 410 pp., $55, cloth, $24.95, paper. August 1995 Every 2 years the Economic Policy In stitute releases its latest findings on the country’s economic health, with empha sis on changes affecting working men and women. In this volume, fourth in the series, the authors present a broad variety of published and unpublished data about employment, unemployment, wages, hours, family incomes, taxes, wealth, and poverty in well-crafted prose, and illustrated in 225 tables and 77 charts. All told, their diagnosis is “one of great disparities” in income and wealth, caused partly by market disadvantages that hinder three-fourths of the work force who do not have a college degree. Their docum entation of disturbing trends in wages and benefits is particu larly comprehensive; much of it is based on their own original analysis of de tailed data. In their view, the forces behind those trends— shrinking manufacturing jobs, dwindling unionization, a falling mini mum wage, defense downsizing, and expansion of international trade—hold out no prospect for an early decline in inequality. The fifth volume in this se ries, due in December 1996, will reex amine that prognosis. —Robert A. Senser Reston, va Current Labor Statistics Notes on Labor Statistics.................... so Comparative indicators 1. Labor market indicators........................................................ 2. Annual and quarterly percent changes in compensation, prices, and productivity.......................... 3. Alternative measures of wages and compensation changes....................................................... 90 91 91 Labor force data 4. Employment status o f the population, seasonally adjusted............................................................. 5. Selected employment indicators, seasonally adjusted............................................................. 6. Selected unemployment indicators, seasonally adjusted............................................................. 7. Duration o f unemployment, seasonally adjusted............................................................. 8. Unemployed persons by reason for unemployment, seasonally adjusted............................................................. 9. Unemployment rates by sex and age, seasonally adjusted............................................................. 10. Unemployment rates by States, seasonally adjusted............................................................. 11. Employment o f workers by States, seasonally adjusted............................................................. 12. Employment of workers by industry, seasonally adjusted............................................................. 13. Average weekly hours by industry, seasonally adjusted............................................................. 14. Average hourly earnings by industry, seasonally adjusted............................................................. 93 94 94 95 95 96 96 97 99 99 16. Average weekly earnings by industry................................ 101 17. Diffusion indexes of employment change, seasonally adjusted............................................................. 102 18. Annual data: Employment status of the population........ 102 19. Annual data: Employment levels by industry..................... 103 20. Annual data: Average hours and earnings levels by industry....................................... 103 Labor compensation and collective bargaining data https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 27. Average specified compensation and wage rate changes, bargaining agreements covering 1,000 workers or more....................................................... 28. Specified changes in cost o f compensation in private industry settlements covering 5,000 workers or more.................................................................. 29. Specified compensation and wage adjustments, State and local government bargaining situations covering 1,000 workers or more...................................... 30. Work stoppages involving 1,000 workers or more........... 111 112 113 113 92 15. A verage hourly earnings b y in d u s tr y ...................................... 100 21. Employment Cost Index, compensation, by occupation and industry grou p ................................... 22. Employment Cost Index, wages and salaries, by occupation and industry grou p ................................... 23. Employment Cost Index, benefits, private industry workers, by occupation and industry group.................. 24. Employment Cost Index, private nonfarm workers, by bargaining status, region, and area s iz e ................... 25. Participants in employer-provided benefit p la n s............ 26. Specified compensation and wage rate changes from contract settlements, and effective wage rate changes, agreements covering 1,000 workers or m ore................................................. ................ Labor compensation and collective bargaining data—Continued 104 106 107 108 109 Price data 31. Consumer Price Index: U.S. city average, by expenditure category and commodity and service groups................. 114 32. Consumer Price Index: U.S. city average and local data, all ite m s............................................................ 117 33. Annual data: Consumer Price Index, all items and major groups................................................................ 118 34. Producer Price Indexes by stage of processing................. 119 35. Producer Price Indexes for the net output o f major industry groups.................................................. 120 36. Annual data: Producer Price Indexes by stage of processing........................................................ 120 37. U.S. export price indexes by Standard International Trade Classification........................................................... 121 38. U.S. import price indexes by Standard International Trade Classification............................................................ 122 39. U.S. export price indexes by end-use category................. 123 40. U.S. import price indexes by end-use category................ 123 41. U.S.international price indexes for selected categories o f services......................................................... 124 Productivity data 42. Indexes o f 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......................................................... 45. Annual indexes o f output per hour for selected industries............................................................................. 124 125 125 126 International comparisons data 46. Unemployment rates in nine countries, data seasonally adjusted.................................................... 128 47. Annual data: Employment status o f the civilian working-age population, 10 countries........................... 129 48. Annual indexes of productivity and related measures, 12 countries......................................................................... 130 Injury and Illness data HO 49. Annual data: Occupational injury and illness incidence rates.................................................................... 131 M onthly Labor Review August 1995 79 Notes on Current Labor Statistics This section of the Review presents the prin cipal statistical series collected and calcu lated by the Bureau o f Labor Statistics: series on labor force; employment; unem ployment; labor compensation; collective bargaining settlements; consumer, producer, and international prices; productivity; inter national 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 in formation are cited. General notes The following notes apply to several tables in this section: Seasonal adjustment. Certain monthly and quarterly data are adjusted to eliminate the effect on the data of such factors as cli matic conditions, industry production sched ules, opening and closing of schools, holi day buying periods, and vacation practices, which might prevent short-term evaluation of the statistical series. Tables containing data that have been adjusted are identified as “seasonally adjusted.” (All other data are not seasonally adjusted.) Seasonal effects are estimated on the basis o f past experi ence. When new seasonal factors are com puted each year, revisions may affect sea sonally adjusted data for several preceding years. Seasonally adjusted data appear in tables 1-14, 16-17, 42, and 46. Seasonally ad justed labor force data for 1994 in tables 1 and 4 -9 were revised in the February 1995 issue of the Review. Seasonally adjusted es tablishment survey data shown in tables 1214 and 16-17 were revised in the July 1995 Review and reflect the experience through March 1995. A brief explanation o f the sea sonal adjustment methodology appears in “Notes on the data.” Revisions in the productivity data in table 42 are usually introduced in the Sep tember issue. Seasonally adjusted indexes and percent changes from month-to-month and quarter-to-quarter are published for nu merous Consumer and Producer Price Index series. However, seasonally adjusted in dexes are not published for the U.S. aver age 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 14— are adjusted to eliminate the ef fect o f changes in price. These adjustments are made by dividing current-dollar values by the Consumer Price Index or the appro 80 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis priate component of the index, then multi plying by 100. For example, given a current hourly wage rate o f $3 and a current price index number o f 150, where 1982 = 100, the hourly rate expressed in 1982 dollars is $2 ($3/150 x 100 = $2). The $2 (or any other resulting values) are described as “real,” “constant,” or “ 1982” dollars. Sources of information Data that supplement the tables in this sec tion are published by the Bureau in a vari ety of sources. Definitions o f each series and notes on the data are contained in later sec tions of these Notes describing each set of data. For detailed descriptions of each data series, see b l s Handbook of Methods, Bul letin 2414. Users also may wish to consult Major Programs of the Bureau of Labor Sta tistics, Report 871. News releases provide the latest statistical information published by the Bureau; the major recurring releases are published according to the schedule ap pearing on the back cover of this issue. More information about labor force, em ployment, and unemployment data and the household and establishment surveys under lying the data are available in the Bureau’s monthly publication, Employment and Earnings. Historical unadjusted data from the household survey are published in La bor Force Statistics Derived From the Cur rent Population Survey, BLS Bulletin 2307. H istorical seasonally adjusted data are available from the Bureau upon request. Historically comparable unadjusted and sea sonally adjusted data from the establishment survey are published in Employment, Hours, and Earnings, United States, a BLS annual bulletin. Additional information on labor force data for sub-States are provided in the BLS annual report, Geographic Profile of More detailed data on consumer and pro ducer prices are published in the monthly periodicals, The CPI Detailed Report and Producer Price Indexes. For an overview of the CPI reflecting 1982-84 expenditure pat terns, see The Consumer Price Index: 1987 Revision, b l s Report 736. Additional data on international prices appear in monthly news releases. For a listing of available industry pro ductivity indexes and their components, see Productivity Measures fo r Selected Indus tries and Government Services, BLS Bulle tin 2440. For additional information on interna tional comparisons data, see International Comparisons of Unemployment, BLS Bulle tin 1979. Detailed data on the occupational injury and illness series are published in Occupa tional Injuries and Illnesses in the United States, by Industry’, a BLS annual bulletin. Finally, the Monthly Labor Review car ries analytical articles on annual and longer term developments in labor force, employ ment, and unemployment; employee com pensation and collective bargaining; prices; productivity; international comparisons; and injury and illness data. Symbols n.e.c. = not elsewhere classified, n.e.s. = not elsewhere specified. p = preliminary. To increase the time liness of some series, preliminary figures are issued based on repre sentative but incomplete returns, r = revised. Generally, this revision reflects the availability o f later data, but may also reflect other ad justments. Employment and Unemployment. More detailed information on employee compensation and co llective bargaining settlements is published in the monthly pe riodical, Compensation and Working Con ditions. For a comprehensive discussion of the Employment Cost Index, see Employ ment Cost Indexes and Levels, 1975-93, BLS Bulletin 2447. The most recent data from the Employee Benefits Survey appear in the following Bureau o f Labor Statistics bulle tins: Employee Benefits in Medium and Large Firms; Employee Benefits in Small Private Establishments; and Employee Benefits in State and Local Governments. Historical data on the collective bargaining settlements series appear in the March issue o f Com pensation and Working Conditions. August 1995 Comparative Indicators (Tables 1-3) Comparative indicators tables provide an overview and comparison of major b l s sta tistical series. Consequently, although many of the included series are available monthly, all measures in these comparative tables are presented quarterly and annually. Labor market indicators include em ployment measures from two major surveys and information on rates of change in com pensation provided by the Employment Cost Index (ECi) program. The labor force partici pation rate, the employment-to-population ratio, and unemployment rates for major demographic groups based on the Current Population (“household”) Survey are pre sented, while measures of employment and average weekly hours by major industry sec tor are given using nonfarm payroll data. The Employment Cost Index (compensation), by major sector and by bargaining status, is chosen from a variety of b l s compensation and wage measures because it provides a comprehensive measure o f employer costs for hiring labor, not just outlays for wages, and it is not affected by employment shifts among occupations and industries. Data on changes in compensation, prices, and productivity are presented in table 2. Measures of rates of change o f com pensation 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 o f changes in consumer prices for all urban consumers; producer prices by stage of processing; over all prices by stage of processing; and overall export and import price indexes are given. Measures o f productivity (output per hour of all persons) are provided for major sectors. Alternative measures of wage and compensation rates of change, which re flect the overall trend in labor costs, are summarized in table 3. Differences in con cepts and scope, related to the specific purposes o f 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. Em ploym ent an d U nem ploym ent D ata (Tables 1; 4-20) Household survey d ata Description of the series in this section are ob tained from the Current Population Survey, a program of personal interviews conducted monthly by the Bureau o f the Census for the Bureau of Labor Statistics. The sample con sists of about 60,000 households selected to represent the U.S. population 16 years of age and older. Households are interviewed on a rotating basis, so that three-fourths o f the sample is the same for any 2 consecutive months. E m p l o y m e n t data https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Definitions tio is employment as a percent of the civil Employed persons include (1) all those who worked for pay any time during the week which includes the 12th day o f 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, vaca tion, industrial dispute, or similar reasons. A person working at more than one job is counted only in the job at which he or she worked the greatest number of hours. Unemployed persons are those who did not work during the survey week, but were available for work except for temporary ill ness and had looked for jobs within the pre ceding 4 weeks. Persons who did not look for work because they were on layoff are also counted among the unemployed. The unem ployment rate represents the number unem ployed as a percent of the civilian labor force. The civilian labor force consists of all employed or unemployed persons in the ci vilian noninstitutional population. Persons not in the labor force are those not classi fied as employed or unemployed. This group includes discouraged workers, defined as persons who want and are available for a job and who have looked for work sometime in the the past 12 months (or since the end of their last job if they held one within the past 12 months), but are not currently look ing, because they believe there are no jobs available or there are none for which they w ould qualify. The civilian nonin stitutional population comprises all per sons 16 years of age and older who are not inmates of penal or mental institutions, sani tariums, or homes for the aged, infirm, or needy. The civilian labor force participa tion rate is the proportion o f the civilian nonin-stitutional population that is in the la bor force. The employment-population ra- Revisions to household data Data relating to 1994 and subsequent years are not directly comparable with data for 1993 and earlier years because of the introduction o f a major redesign of the survey questionnaire and collection methodology, and the introduction o f 1990 census-based population controls, adjusted for the estimated undercount. An explanation of the changes and their ef fect on labor force data appears in the February 1994 issue of Employment and Earnings, a monthly publication of the Bureau of Labor Statistics. Seasonally adjusted data for 1994 were revised at the end of 1994. Addi tional information on the revisions ap pears in the January 1995 issue of Em ployment and Earnings. ian noninstitutional population. Notes on the data From time to time, and especially after a de cennial census, adjustments are made in the Current Population Survey figures to correct for estimating errors during the intercensal years. These adjustments affect the compa rability of historical data. A description of these adjustments and their effect on the various data series appears in the Explana tory Notes of Employment and Earnings. Labor force data in tables 1 and 4 -9 are seasonally adjusted. Since January 1980, national labor force data have been season ally adjusted with a procedure called X -ll a r i m a which was developed at Statistics Canada as an extension of the standard X11 method previously used by b l s . A de tailed 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, January 1983). At the end o f each calendar year, season ally adjusted data for the previous 5 years usually are revised, and projected seasonal adjustment factors are calculated for use during the January-June period. Because of the changes introduced into the CPS in Janu ary 1994, only seasonally adjusted data for 1994 were revised at the end of 1994. In July, new seasonal adjustment factors, which incorporate the experience through June, are produced for the July-December period, but no revisions are made in the his torical data. F o r a d d i t i o n a l i n f o r m a t io n on national household survey data, contact the Division of Labor Force Statistics: (202) 606-6378. Establishment survey d ata Description of the series E m p l o y m e n t , h o u r s , a n d e a r n i n g s d a t a in this section are com piled from payroll records reported monthly on a voluntary ba sis to the Bureau o f Labor Statistics and its cooperating State agencies by about 390,000 establishments representing all industries except agriculture. Industries are classified in accordance with the 1987 Standard In dustrial Classification (SIC) Manual. In most industries, the sampling probabilities are based on the size of the establishment; most large establishments are therefore in the sample. (An establishment is not necessar ily a firm; it may be a branch plant, for ex ample, or warehouse.) Self-employed per sons and others not on a regular civilian pay roll are outside the scope o f the survey M onthly Labor Review August 1995 81 Current Labor Statistics because they are excluded from establish ment records. This largely accounts for the difference in employment figures between the household and establishment surveys. Definitions An establishment is an econom ic 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 in cluding the 12th day of the month. Persons holding more than one job (about 5 percent of all persons in the labor force) are counted in each establishment which reports them. Production workers in manufacturing include working supervisors and nonsupervisory workers closely associated with pro duction operations. Those workers men tioned in tables 11-16 include production workers in manufacturing and mining; con struction workers in construction; and nonsupervisory workers in the following indus tries: transportation and public utilities; wholesale and retail trade; finance, insur ance, and real estate; and services. These groups account for about four-fifths of the total employment on private nonagricultural payrolls. Earnings are the payments production or nonsupervisory workers receive during the survey period, including premium pay for overtime or late-shift work but exclud ing irregular bonuses and other special payments. Real earnings are earnings ad justed to reflect the effects o f changes in consumer prices. The deflator for this series is derived from the Consumer Price Index for Urban Wage Earners and Clerical Work ers (CPI-W). Hours represent the average w eekly hours of production or nonsupervisory work ers for which pay was received, and are dif ferent from standard or scheduled hours. Overtime hours represent the portion of average weekly hours which was in excess of regular hours and for which overtime pre miums were paid. The Diffusion Index represents the per cent of industries in which employment was rising over the indicated period, plus onehalf of the industries with unchanged em ployment; 50 percent indicates an equal bal ance 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. Table 17 pro vides an index on private nonfarm employ ment based on 356 industries, and a manu facturing index based on 139 industries. These indexes are useful for measuring the 82 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis dispersion of economic gains or losses and are also economic indicators. Notes on the data Establishment survey data are annually ad justed to comprehensive counts of employ ment (called “benchmarks”). The latest ad justment, which incorporated March 1994 benchmarks, was made with the release of May 1995 data, published in the July 1995 issue o f the Review. Coincident with the benchmark adjustment, seasonally adjusted data were revised to reflect the experience through March 1995. Comparable revisions in State data (table 11) occurred with the publication o f January 1995 data. Unad justed data from April 1994 forward and seasonally adjusted data from January 1991 forward are subject to revision in future benchmarks. The b l s also uses the X - ll a r i m a meth odology to seasonally adjust establishment survey data. Beginning in June 1989, pro jected seasonal adjustment factors are cal culated and published twice a year. The change makes the procedure used for the establishment survey data more parallel to that used in adjusting the household survey data. Revisions of data, usually for the most recent 5-year period, are made once a year coin cid en t with the benchmark revisions. In the establishment survey, estimates for the most recent 2 months are based on in complete returns and are published as pre liminary in the tables (12-17 in the Review). When all returns have been received, the es timates are revised and published as “final” (prior to any benchmark revisions) in the third month of their appearance. Thus, D e cember data are published as preliminary in January and February and as final in March. For the same reasons, quarterly establish ment data (table 1) are preliminary for the first 2 months o f publication and final in the third month. Thus, fourth-quarter data are published as preliminary in January and February and as final in March. A comprehensive discussion of the dif ferences between household and establish ment data on employment appears in Gloria P. Green, “Comparing employment esti mates from household and payroll surveys,” Monthly Labor Review, December 1969, pp. 9-20. F o r a d d i t i o n a l in f o r m a t i o n on estab lishment survey data, contact the Division of Monthly Industry Employment Statistics: (202) 606-6555. lation Survey (CPS) and the Local Area Un em ploym ent Statistics (LAUS) program, which is conducted in cooperation with State employment security agencies. Monthly estimates o f the labor force, employment, and unemployment for States and sub-State areas are a key indicator of local economic conditions, and form the ba sis for determining the eligibility of an area for benefits under Federal economic assis tance programs such as the Job Training Partnership Act. Seasonally adjusted unem ployment rates are presented in table 10. Insofar as possible, the concepts and defini tions underlying these data are those used in the national estimates obtained from the CPS. Notes on the data Data refer to State o f residence. Monthly data for 11 States— California, Florida, Illi nois, Massachusetts, Michigan, New York, New Jersey, North Carolina, Ohio, Pennsyl vania, and Texas— are obtained directly from the CPS because the size o f the sample is large enough to meet b l s standards of reliability. Data for the remaining 39 States and the District o f Columbia are derived using standardized procedures established by b l s . Once a year, estimates for the 11 States are revised to new population con trols, usually with publication o f January estimates. For the remaining States and the District of Columbia, data are benchmarked to annual average CPS levels. Data for 1994 are not directly comparable with those for 1993 as a result of the redesign of the c p s and other methodological changes. See “Re visions in State and Area Estimates Effec tive January 1994,” Employment and Earn ings, March 1994. For additional information on data in this series, call (202) 606-6392 (table 10) or (202) 606-6589 (table 11). Compensation and Wage Data (Tables 1-3; 21-30) C o m p e n s a t io n a n d w a g e d a t a 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 Unemployment data by State Description of the series Description of the series The Employment Cost Index (ECI) is a quarterly measure of the rate o f change in compensation per hour worked and includes wages, salaries, and employer costs of em- Data presented in this section are obtained from two major sources— the Current Popu- August 1995 ployee benefits. It uses a fixed market basket of labor—similar in concept to the Consumer Price Index’s fixed market bas ket of goods and services—to measure change over time in employer costs of em ploying labor. Statistical series on total compensation costs, on wages and salaries, and on benefit costs are available for private nonfarm work ers excluding proprietors, the self-employed, and household workers. The total compen sation costs and wages and salaries series are also available for State and local gov ernment workers and for the civilian non farm 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 4,400 private non farm establishments providing about 23,000 occupational observations and 1,000 State and local government establishments pro viding 6,000 occupational observations se lected to represent total employment in each sector. On average, each reporting unit pro vides wage and compensation information on five well-specified occupations. Data are collected each quarter for the pay period in cluding the 12th day of March, June, Sep tember, and December. Beginning with June 1986 data, fixed employment weights from the 1980 Census of Population are used each quarter to calculate the civilian and private indexes and the index for State and local govern ments. (Prior to June 1986, the employment weights are from the 1970 Census of Pop ulation.) These fixed weights, also used to derive all of the industry and occupation series indexes, ensure that changes in these indexes reflect only changes in compensa tion, not employment shifts among indus tries or occupations with different levels of wages and compensation. For the bargain ing status, region, and metropolitan/nonmetropolitan area series, however, employ ment 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 em ployee benefits. Wages and salaries consist of earnings before payroll deductions, including produc tion bonuses, incentive earnings, commis sions, and cost-of-living adjustments. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Benefits include the cost to employers for paid leave, supplemental pay (includ ing nonproduction bonuses), insurance, re tirement and savings plans, and legally re quired 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. Notes on the data The Employment Cost Index for changes in wages and salaries in the private nonfarm economy was published beginning in 1975. Changes in total compensation cost—wages and salaries and benefits combined—were published beginning in 1980. The series of changes in wages and salaries and for total compensation in the State and local govern ment sector and in the civilian nonfarm economy (excluding Federal employees) were published beginning in 1981. Histori cal indexes (June 1981 = 100) of the quar terly rates of change are presented in the March issue of the BLS periodical, Compen sation and Working Conditions. F or a d d it io n a l inform ation on the Employment Cost Index, contact the Divi sion of Employment Cost Trends: (202) 606-6199. Employee Benefits Survey Description of the series Employee benefits data are obtained from the Employee Benefits Survey, an annual survey of the incidence and provisions of selected benefits provided by employers. The survey collects data from a sample of approximately 6,000 private sector and State and local government establishments. The data are presented as a percentage of em ployees who participate in a certain benefit, or as an average benefit provision (for example, the average number of paid holi days provided to employees per year). Se lected data from the survey are presented in table 25. The survey covers paid leave benefits such as lunch and rest periods, holidays and vacations, and personal, funeral, jury duty, military, parental, and sick leave; sickness and accident, long-term disability, and life insurance; medical, dental, and vision care plans; defined benefit and defined contribu tion plans; flexible benefits plans; reimburse ment accounts; and unpaid parental leave. Also, data are tabulated on the inci dence of several other benefits, such as severance pay, child-care assistance, well ness programs, and employee assistance programs. Definitions Employer-provided benefits are benefits that are financed either wholly or partly by the employer. They may be sponsored by a union or other third party, as long as there is some employer financing. However, some benefits that are fully paid for by the em ployee also are included. For example, long term care insurance and postretirement life insurance paid entirely by the employee are included because the guarantee of insurabil ity and availability at group premium rates are considered a benefit. Participants are workers who are cov ered by a benefit, whether or not they use that benefit. If the benefit plan is financed wholly by employers and requires employ ees to complete a minimum length of ser vice for eligibility, the workers are consid ered participants whether or not they have met the requirement. If workers are required to contribute towards the cost of a plan, they are considered participants only if they elect the plan and agree to make the required contributions. Defined benefit pension plans use pre determined formulas to calculate a retire ment benefit, and obligate the employer to provide those benefits. Benefits are gener ally based on salary, years of service, or both. Defined contribution plans generally specify the level of employer and employee contributions to a plan, but not the formula for determining eventual benefits. Instead, individual accounts are set up for partici pants, and benefits are based on amounts credited to these accounts. Tax-deferred savings plans are a type of defined contribution plan that allow par ticipants to contribute a portion of their sal ary to an employer-sponsored plan and de fer income taxes until withdrawal. Flexible benefit plans allow employees to choose among several benefits, such as life insurance, medical care, and vacation days, and among several levels of care within a given benefit. Notes on the data Surveys of employees in medium and large establishments conducted over the 1979-86 period included establishments that em ployed at least 50, 100, or 250 workers, de pending on the industry (most service industries were excluded). The survey con ducted in 1987 covered only State and local governments with 50 or more employees. The surveys conducted in 1988 and 1989 included medium and large establishments with 100 workers or more in private industries. All surveys conducted over the 1979-89 period M onthly Labor Review August 1995 83 Current Labor Statistics excluded establishments in Alaska and Ha waii, as well as part-time employees. Beginning in 1990, surveys of State and local governments and small establishments are conducted in even-numbered years and surveys of medium and large establishments are conducted in odd-numbered years. The small establishment survey includes all pri vate nonfarm establishments with fewer than 100 workers, while the State and local gov ernment survey includes all governments, regardless of the number of workers. All three surveys include full- and part-time workers, and workers in all 50 States and the District of Columbia. F or additional information on the Em ployee Benefits Survey, contact the Division of Occupational Pay and Employee Benefit Levels: (202) 606-6222. Collective bargaining settlements Description of the series Collective bargaining settlements data pro vide statistical measures of negotiated changes (increases, decreases, and zero change) in wage rates alone and in compen sation (wages and benefits), quarterly for private nonagricultural industries and semi annually for State and local governments. Wage rate changes cover collective bargain ing settlements negotiated in the reference period involving 1,000 or more workers, and compensation changes cover settlements reached in the reference period involving 5,000 or more workers. These data are not seasonally adjusted and are calculated using information obtained from bargaining agree ments on file with the Bureau, parties to the agreements, and secondary sources, such as newspaper accounts. The wage and compensation rate changes are the percent difference between the aver age rate per work hour just prior to the start of a new agreement and the average rate per work hour that would exist at the end of the first 365 days of the new agreement (firstyear measure) or at its expiration date (overthe-life measure). These data exclude lump sum payments. The compensation cost change is the per cent difference between the average cost of compensation per work hour, including the hourly cost of lump-sum payments made dur ing the term of the expiring agreement, just prior to the start of a new agreement and the average cost of compensation per work hour under the settlement. The timing of the changes in compensation rates is reflected in the compensation cost series, but not in compensation rate series. 84 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Data on changes in settlements exclude potential changes under cost-of-living adjust ment clauses. Averages reflect the change under each settlement weighted by the num ber of workers covered. Estimates of changes are based on the assumption that conditions existing at the time of the settlement (for example, composition of the labor force or methods of funding pensions) will remain constant over the term of the agreement. Wage rate changes under all major agreements (those covering 1,000 or more workers) measure all wage increases, de creases, and zero changes occurring in the reference period, regardless of the settle ment date. Included are changes from settle ments reached in the calendar year, changes deferred from settlements negotiated in ear lier years, and changes under cost-of-living adjustment (COLA) clauses. The change in the wage rate for each agreement is the per cent difference between the average wage rate just prior to the start of the reference period and the average wage rate at the end of the reference period. The change for each agreement is weighted .by the number of workers covered to determine the average change under all agreements. Definitions Wage rate is the average straight-time hourly wage rate plus shift premiums. Compensation rates include the wage rate, premium pay (for example, for over time and holidays); paid leave; life, health, and sickness and accident insurance; pen sion and other retirement plans; severance pay; and legally required benefits. Compensation costs include the items covered by compensation rates plus speci fied lump-sum payments, the cost of contractually required training programs that are not a cost of doing business, and the ad ditional costs of changes in legally required insurance known at the time of settlement to be mandated during the contract term. Cash payments include wages and lump-sum payments. Contingent pay provisions are clauses which could provide compensation changes beyond those sp ecified in the settlement. cola c la u se s and lum p-sum p ro v isio n s that call for a paym ent on ly if a c o m pany’s profits exceed a specific amount are exam ples. August 1995 Professional and white-collar employees, for example, make up a much larger propor tion of the workers covered by government than by private industry settlements. Lump sum payments and cola clauses, on the other hand, are rare in government but com mon in private industry settlements. Also, State and local government bargaining fre quently excludes items such as pension ben efits and holidays, that are prescribed by law, while these items are typical bargain ing issues in private industry. F or additional information on collec tive bargaining settlements, contact the Di vision of Developments in Labor-Manage ment Relations: (202) 606-6276 (private industry data) or (202) 606-6280 (State and local government data). Work stoppages Description of the series Data on work stoppages measure the num ber and duration of major strikes or lock outs (involving 1,000 workers or more) oc curring during the month (or year), the num ber of workers involved, and the amount of time lost because of stoppage. Data are largely from newspaper ac counts and cover only establishments di rectly 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 short ages or lack of service. Definitions 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 in volved in the stoppages. Number of stoppages: Days of idleness as a percent of esti mated working time: Aggregate work days lost as a percent of the aggregate num ber of standard workdays in the period mul tiplied by total employment in the period. Notes on the data 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 characteristics. This series is not comparable with the one terminated in 1981 that covered strikes in volving six workers or more. F or additional information on work stoppages data, contact the Division of De- velopments in Labor-Management Rela tions: (202) 606-6288. Price D ata (Tables 2; 31-41) are gathered by the Bureau of Labor Statistics from retail and pri mary markets in the United States. Price in dexes are given in relation to a base pe riod—1982 = 100 for many Producer Price Indexes, 1982-84= 100 for many Consumer Price Indexes (unless otherwise noted), and 1990 = 100 for International Price Indexes. P rice data Consumer Price Indexes Description of the series The Consumer Price Index (CPI) is a mea sure of the average change in the prices paid by urban consumers for a fixed market bas ket of goods and services. The CPI is calcu lated monthly for two population groups, one consisting only of urban households whose primary source of income is derived from the employment of wage earners and clerical workers, and the other consisting of all ur ban households. The wage earner index (CPIW) is a continuation of the historic index that was introduced well over a half-century ago for use in wage negotiations. As new uses were developed for the cpi in recent years, the need for a broader and more representa tive index became apparent. The all-urban consumer index (CPI-U), introduced in 1978, is representative of the 1982-84 buying hab its 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 cleri cal workers, the CPI-U covers professional, managerial, and technical workers, the selfemployed, short-term workers, the unem ployed, retirees, and others not in the labor force. The cpi is based on prices of food, cloth ing, shelter, fuel, drugs, transportation fares, doctors’ and dentists’ fees, and other goods and services that people buy for day-to-day living. The quantity and quality of these items are kept essentially unchanged be tween 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 19,000 retail establishments and 57,000 housing units in 85 urban areas across the country are used to develop the “U.S. city average.” Separate estimates for 15 major urban cen https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis ters are presented in table 32. 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 differ ences 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 cpi-u . A rental equivalence method replaced the asset-price approach to homeownership costs for that series. In January 1985, the same change was made in the CPi-w. The central purpose of the change was to separate shelter costs from the investment component of home-owner ship so that the index would reflect only the cost of shelter services provided by owneroccupied homes. An updated cpi-u and cpiw were introduced with release of the Janu ary 1987 data. F or additional information on con sumer prices, contact the Division of Con sumer Prices and Price Indexes: (202) 606-7000. Producer Price Indexes Description of the series Producer Price Indexes (PPi) measure av erage changes in prices received by domes tic producers of commodities in all stages of processing. The sample used for calculating these indexes currently contains about 3,200 commodities and about 80,000 quotations per month, selected to represent the move ment of prices of all commodities produced in the manufacturing; agriculture, forestry, and fishing; mining; and gas and electricity and public utilities sectors. The stage-ofprocessing structure of ppi organizes prod ucts by class of buyer and degree of fabrica tion (that is, finished goods, intermediate goods, and crude materials). The traditional commodity structure of ppi organizes prod ucts by similarity of end use or material composition. The industry and product structure of ppi organizes data in accordance with the Standard Industrial Classification (SIC) and the product code extension of the SIC developed by the U.S. Bureau of the Census. To the extent possible, prices used in cal culating Producer Price Indexes apply to the first significant commercial transaction in the United States from the production or central marketing point. Price data are gen erally collected monthly, primarily by mail questionnaire. Most prices are obtained di rectly from producing companies on a vol untary and confidential basis. Prices gener ally are reported for the Tuesday of the week containing the 13th day of the month. Since January 1992, price changes for the various commodities have been averaged together with implicit quantity weights rep resenting their importance in the total net selling value of all commodities as of 1987. The detailed data are aggregated to obtain indexes for stage-of-processing groupings, commodity groupings, durability-of-product groupings, and a number of special compos ite groups. All Producer Price Index data are subject to revision 4 months after original publication. F or a dd itio nal information on pro ducer prices, contact the Division of Indus trial Prices and Price Indexes: (202) 606-7705. International Price Indexes Description of the series The International Price Program produces monthly and quarterly export and import price indexes for nonmilitary goods traded between the United States and the rest of the world. The export price index provides a measure of price change for all products sold by U.S. residents to foreign buyers. (“Residents” is defined as in the national income accounts; it includes corporations, businesses, and individuals, but does not re quire the organizations to be U.S. owned nor the individuals to have U.S. citizenship.) The import price index provides a measure of price change for goods purchased from other countries by U.S. residents. The product universe for both the import and export indexes includes raw materials, agricultural products, semifinished manu factures, and finished manufactures, includ ing both capital and consumer goods. Price data for these items are collected primarily by mail questionnaire. In nearly all cases, the data are collected directly from the ex porter or importer, although in a few cases, prices are obtained from other sources. To the extent possible, the data gathered refer to prices at the U.S. border for exports and at either the foreign border or the U.S. border for imports. For nearly all products, the prices refer to transactions completed during the first week of the month. Survey respondents are asked to indicate all dis counts, allowances, and rebates applicable to the reported prices, so that the price used in the calculation of the indexes is the ac tual 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 catego ries of exports and imports. These catego- M onthly Labor Review August 1995 85 Current Labor Statistics ries are defined according to the five digit level of detail for the Bureau of Eco nomic Analysis End-use Classification (Sue), and the four-digit level of detail for the Harmonized System. Aggregate import indexes by country or region of origin are also available. bls publishes indexes for selected cat egories o f internationally traded services, calculated on an international basis and on a balance-of-payments basis. Notes on the data The export and import price indexes are weighted indexes of the Laspeyres type. Price relatives are assigned equal impor tance within each harmonized group and are then aggregated to the higher level. The val ues 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 re late to 1990. Because a price index depends on the same items being priced from period to pe riod, it is necessary to recognize when a product’s specifications or terms of transac tion have been modified. For this reason, the Bureau’s questionnaire requests detailed de scriptions 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 ob tain 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 pre ferred 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 ship ment cost to the port of exportation. An at tempt is made to collect two prices for im ports. The first is the import price f.o.b. at the foreign port of exportation, which is con sistent with the basis for valuation of imports in the national accounts. The second is the import price c.i.f.(costs, insurance, and freight) at the U.S. port of importation, which also includes the other costs associ ated 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. F or additional information on inter national prices, contact the Division of In ternational Prices: (202) 606-7155. 86 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Productivity D ata (Tables 2; 42^15) Business sector and major sectors Description of the series The productivity measures relate real physi cal output to real input. As such, they en compass a family of measures which include single-factor input 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 in puts). The Bureau indexes show the change in output relative to changes in the various inputs. The measures cover the business, nonfarm business, manufacturing, and nonfinancial corporate sectors. Corresponding indexes of hourly com pensation, unit labor costs, unit nonlabor payments, and prices are also provided. Definitions Output per hour of all persons (labor pro ductivity) is the value of goods and services in constant prices produced per hour of la bor input. Output per unit of capital ser vices (capital productivity) is the value of goods and services in constant dollars pro duced per unit of capital services input. Multifactor productivity is the value of goods and services in constant prices pro duced per combined unit of labor and capi tal 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 capacity utilization, research and development, skill and effort of the work force, management, and so forth. Changes in the output per hour measures re flect 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 pri vate benefit plans, and the wages, salaries, and supplementary payments for the selfemployed (except for nonfinancial corpora tions in which there are no self-employed)— the sum divided by hours at work. Real compensation per hour is compensation per hour deflated by the change in Consumer Price Index for All Urban Consumers. Unit labor costs are the labor compen sation costs expended in the production of a unit of output and are derived by dividing compensation by output. Unit nonlabor payments include profits, depreciation, August 1995 interest, and indirect taxes per unit of out put. They are computed by subtracting com pensation of all persons from current-dollar value of output and dividing by output. Unit nonlabor costs contain all the compo nents of unit nonlabor payments except unit profits. Unit profits include corporate profits with inventory valuation and capital con sumption adjustments per unit of output. Hours of all persons are the total hours at work of payroll workers, self-employed persons, and unpaid family workers. Capital services are the flow of services from the capital stock used in production. It is developed from measures of the net stock of physical assets—equipment, structures, land, and inventories—weighted by rental prices for each type of asset. Combined units of labor and capital inputs are derived by combining changes in labor and capital input with weights which represent each component’s share of total output. The indexes for capital services and combined units of labor and capital are based on changing weights which are aver ages of the shares in the current and preced ing year (the Tornquist index-number formula). Notes on the data The output measure for the business sector is equal to constant-dollar gross national product, but excludes the rental value of owner-occupied dwellings, the rest-ofworld sector, the output of nonprofit insti tutions, the output of paid employees of pri vate households, general government, and the statistical discrepancy. Output of the nonfarm business sector is equal to busi ness sector output less farming. The mea sures are derived from data supplied by the U.S. Department of Commerce’s Bureau of Economic Analysis and the Federal Re serve Board. Quarterly manufacturing out put indexes are adjusted by the Bureau of Labor Statistics to annual estimates of man ufacturing output (gross product originat ing) from the Bureau of Economic Analy sis. Compensation and hours data are de veloped from data of the Bureau of Labor Statistics and the Bureau of Economic Analysis. The productivity and associated cost measures in tables 42^15 describe the rela tionship 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 mea sure the contributions of labor, capital, or any other specific factor of production. Rather, they reflect the joint effect of many influences, including changes in technology; capital investment; level of output; utiliza tion of capacity, energy, and materials; the organization of production; managerial skill; and the characteristics and efforts of the work force. FORADDITIONAL INFORMATION On this pro ductivity series, contact the Division of Pro ductivity Research: (202) 606-5606. all persons (including self-employed) are constructed. FOR ADDITIONAL INFORMATION on this se ries, contact the Division of Industry Pro ductivity Studies: (202) 606-5618. Industry productivity measures Labor force and unemployment Description of the series Description of the series The bls industry productivity data supple ment the measures for the business economy and major sectors with annual measures of labor productivity for selected industries at the three- and four-digit levels of the Stan dard Industrial Classification system. The industry measures differ in methodology and data sources from the productivity mea sures for the major sectors because the in dustry measures are developed indepen dently of the National Income and Product Accounts framework used for the major sec tor measures. Tables 46 and 47 present comparative mea sures of the labor force, employment, and unemployment—approximating U.S. con cepts—for the United States, Canada, Aus tralia, Japan, and several European coun tries. The unemployment statistics (and, to a lesser extent, employment statistics) pub lished by other industrial countries are not, in most cases, comparable to U.S. unem ployment statistics. Therefore, the Bureau adjusts the figures for selected countries, where necessary, for all known major defi nitional differences. Although precise com parability may not be achieved, these ad justed figures provide a better basis for in ternational comparisons than the figures regularly published by each country. Definitions Output per employee hour is derived by dividing an index of industry output by an index of aggregate hours of all employees. Output indexes are based on quantifiable units of products or services, or both, com bined with value-shared weights. Whenever possible, physical quantities are used as the unit of measurement for output. If quantity data are not available for a given industry, data on the constant-dollar value of produc tion are used. The labor input series consist of the hours of all employees (production and nonproduction workers), the hours of all persons (paid employees, partners, propri etors, and unpaid family workers), or the number of employees, depending upon the industry. Notes on the data The industry measures are compiled from data produced by the Bureau of Labor Sta tistics, the Departments of Commerce, Inte rior, and Agriculture, the Federal Reserve Board, regulatory agencies, trade associa tions, and other sources. For most industries, the productivity indexes refer to the output per hour of all employees. For some transportation indus tries, only indexes of output per employee are prepared. For some trade and service industries, indexes of output per hour of https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis International Com parisons (Tables 46^-8) Definitions For the principal U.S. definitions of the la bor force, employment, and unemploy ment, see the Notes section on Employment and Unemployment Data: Household survey data. Notes on the data The adjusted statistics have been adapted to the age at which compulsory schooling ends in each country, rather than to the U.S. stan dard of 16 years of age and older. There fore, the adjusted statistics relate to the population age 16 and older in France, Swe den, and from 1973 onward in the United Kingdom; 15 and older in Canada, Austra lia, Japan, Germany, Italy, the Netherlands, and prior to 1973, the United Kingdom; and 14 and older in Italy prior to 1993. The in stitutional population is included in the de nominator of the labor force participation rates and employment-population ratios for Japan and Germany; it is excluded for the United States and the other countries. In the U.S. labor force survey, persons on layoff who are awaiting recall to their jobs are classified as unemployed. European and Japanese layoff practices are quite dif ferent 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 us ing adjustment factors based on labor force surveys for earlier years and are considered preliminary. The recent-year measures for these countries, therefore, are subject to revision whenever data from more current labor force surveys become available. There are breaks in the data series for the United States (1994), Italy (1986, 1991, 1993), and Sweden (1987, 1993). For the United States, the break in series reflects a number of changes in the labor force survey beginning with data for January 1994. Data for 1994 are not directly comparable with those for earlier years. See the Notes sec tion on Employment and Unemployment Data of this Review. For Italy, the 1986 break in series reflects more accurate enumeration of the number of people reported as seeking work in the last 30 days. The impact was to increase the Italian unemployment rates approximating U.S. concepts by about 1 percentage point. In 1991, the survey sample was modified to obtain more reliable estimates by sex and age. The impact was to raise the adjusted Italian unemployment rate by approximately 0.3 percentage point. In 1993, the survey methodology was revised and the definition of unemployment was changed to include only those who were actively looking for a job within the 30 days preceding the survey and who were available for work. In addi tion, the lower age limit for the labor force was raised from 14 to 15 years. (Prior to these changes, bls adjusted Italy’s pub lished unemployment rate downward by ex cluding from the unemployed persons who had not actively sought work in the past 30 days.) The break in the series also reflects the incorporation of the 1991 population census results. The impact of these changes was to raise Italy’s adjusted unemployment rate by approximately 1.1 percentage points. These changes did not affect employment significantly, except in 1993. Estimates by the Italian Statistical Office indicate that employment declined by about 3 percent in 1993, rather than the 4.5 percent indicated by the data shown in table 47. This differ ence is attributable mainly to the incorpora tion of the 1991 population census bench marks in the 1993 data. Data for earlier years have not yet been adjusted to incorpo rate the 1991 census results. Sweden introduced a new questionnaire in 1987. Questions regarding current avail ability were added and the period of active M onthly Labor Review A ugust 1995 87 Current Labor Statistics workseeking was reduced from 60 days to 4 weeks. These changes result in lowering Sweden’s unemployment rate by 0.5 percent age point. In 1993, the measurement period for the labor force survey was changed to represent all 52 weeks of the year, rather than one week each month, and a new ad justment for population totals was intro duced. The impact was to raise the unem ployment rate by approximately 0.5 percent age point. The data for 1993 onward are not seasonally adjusted because the previous seasonal adjustment pattern is not applicable following the 1993 break in series. Preliminary estimates by the Swedish Statistics Bureau indicate that employment linked for the 1993 break in series declined by about 5-1/2 percent in 1993, rather than the nearly 7 percent indicated by the data shown in table 47. F or additional information on this se ries, contact the Division of Foreign Labor Statistics: (202) 606-5654. Manufacturing productivity and labor costs Description of the series Table 48 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, in tercountry series of changes over time— rather than level comparisons because reli able international comparisons of the levels of manufacturing output are unavailable. The hours and compensation measures re fer to all employed persons, including selfempoyed persons and unpaid family work ers, in the United States and Canada and to all employees (wage and salary earners) in the other countries. Definitions Output, in general, refers to value added in manufacturing (gross product originating) in constant prices from the national accounts of each country. However, output for Japan prior to 1970 and the Netherlands from 1969 to 1977 are indexes of industrial production. The national accounts measures for the United Kingdom are essentially identical to its indexes of industrial production. While methods of deriving national accounts mea sures differ substantially from country to country, the use of different procedures does not, in itself, connote lack of comparabil ity—rather, it reflects differences among countries in the availability and reliability of underlying data series. 88 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis Hours refer to hours worked in all coun tries. The measures are developed from sta tistics of manufacturing employment and average hours. The series used for France (from 1970 forward), Norway, and Swe den are official series published with the national accounts. Where official total hours series are not available. The measures are developed by the Bureau using employ ment figures published with the national ac counts, or other comprehensive employment series, and estimates of annual 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 ad dition, for some countries, compensation is increased to account 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 costs. The costs of recruitment, em ployee training, and plant facilities and ser vices—such as cafeterias and medical clin ics—are not covered because data are not available for most countries. The compen sation measures are from the national ac counts, except those for Belgium, which are developed by the Bureau using statistics on employment, average hours, and hourly compensation. Self-employed workers are included in the U.S. and Canadian compen sation figures by assuming that their hourly compensation is equal to the average for wage and salary employees. Notes on the data In general, the measures relate to total manufacturing as defined by the Interna tional Standard Industrial Classification. However, the measures for France. Italy (be ginning 1970), and the United Kingdom (be ginning 1971) refer to mining and manufac turing less energy-related products; the mea sures for Denmark include mining and exclude manufacturing handicrafts from 1960 to 1966; and the measures for the Netherlands exclude petroleum refining and include coal mining from 1969 to 1976. The figures for one or more recent years are generally based on current indicators of manufacturing output (such as industrial production indexes), employment, average hours, and hourly compensation and are con sidered preliminary until the national ac counts and other statistics used for the long term measures becomes available. F or additional information on this se ries, contact the Division of Foreign Labor Statistics: (202) 606-5654. A ugust 1995 O c c u p a tio n a l Injury a n d Illness D ata (Table 49) 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. Ex cluded from the survey are self-employed in dividuals, farmers with fewer than 11 em ployees, employers regulated by other Fed eral safety and health laws, and Federal, State, and local government agencies. Because the survey is a Federal-State co operative program and the data must meet the needs of participating State agencies, an independent sample is selected for each State. The sample is selected to represent all private industries in the States and terri tories. The sample size for the survey is de pendent upon (1) the characteristics for which estimates are needed; (2) the indus tries for which estimates are desired; (3) the characteristics of the population being sampled; (4) the target reliability of the es timates; 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 char acteristics 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. Definitions Recordable occupational injuries and ill nesses are: (1) occupational deaths, regard less of the time between injury and death, or the length of the illness; or (2) nonfatal occupational illnesses; or (3) nonfatal occu pational injuries which involve one or more of the following: loss of consciousness, re striction of work or motion, transfer to an other 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 result ing from an occupational injury, caused by exposure to environmental factors associ ated 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 in volve days away from work, or days of re stricted work activity, or both. Lost workday cases involving re stricted 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 activ ity 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; (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 du ties normally connected with it. The number of days away from work or days of restricted work activity does not in clude the day of injury or onset of illness or https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 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 em ployment-size classes and for severity clas sification: fatalities, lost workday cases, and nonfatal cases without lost workdays. Lost workday cases are separated into those in which 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 em ployee years (2,000 hours per employee). Full detail of the available measures is pre sented 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 Ad ministration and the Federal Railroad Ad ministration. Data from these organizations are included in bls and State publications. Federal employees 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. The Supplementary Data System pro vides detailed information describing vari ous factors associated with work-related in juries and illnesses. These data are obtained from information reported by employers to State workers’ compensation agencies. The Work Injury Report program examines se lected types of accidents through an em ployee survey which focuses on the circum stances surrounding the injury. These data 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 Oc cupational Safety and Health Act of 1970. F or additional information on occupa tional injuries and illnesses, contact the Di vision of Safety and Health Statistics: (202) 606-6166. M onthly Labor Review A ugust 1995 89 Current Labor Statistics: 1. C o m p a ra tiv e Indicators Labor market indicators 1993 Selected indicators 1993 1994 1995 1994 II III IV I II III IV I Employment data1 Employment status of the civilian noninstitutionalized population (household survey):2 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............................................................ 66.2 61.6 6.8 7.1 14.3 5.8 6.5 12.2 5.4 66.6 62.5 6.1 6.2 13.2 4.8 6.0 11.6 4.9 66.2 61.6 7.0 7.3 14.9 5.8 6.6 12.6 5.4 66.1 61.7 6.7 7.1 14.2 5.8 6.4 11.7 5.3 66.2 61.9 6.5 6.7 13.5 5.5 6.3 11.6 5.3 66.7 62.3 6.6 6.7 14.1 5.2 6.4 12.1 5.3 66.5 62.4 6.2 6.2 13.3 4.8 6.2 11.9 5.0 66.5 62.5 6.0 6.0 13.1 4.7 5.9 11.6 4.8 66.6 62.9 5.6 5.6 12.2 4.4 5.6 11.0 4.5 66.9 63.2 5.5 5.5 11.9 4.2 5.6 11.2 4.4 Total ..................................................................................... Private sector...................................................................... Goods-producing.................................................................. Manufacturing.................................................................... Service-producing ................................................................ 110,730 91,889 23,352 18,075 87,378 114,034 94,917 23,913 18,303 90,121 110,354 91,550 23,301 18,064 87,052 111,021 92,143 23,345 18,049 87,676 111,816 92,877 23,481 18,096 88,335 112,655 93,656 23,646 18,181 89,008 112,995 93,990 23,534 18,020 89,461 114,481 95,314 23,978 18,333 90,503 115,329 96,099 24,162 18,436 91,167 116,078 96,841 24,329 18,517 91,749 Average hours: Private sector ...................................................................... Manufacturing ................................................................. Overtime........................................................................ 34.5 41.4 4.1 34.7 42.0 4.7 34.5 41.3 4.1 34.5 41.5 4.1 34.5 41.7 4.4 34.6 41.7 4.5 34.7 42.1 4.7 34.7 42.0 4.7 34.7 42.1 4.8 34.7 42.1 4.8 Percent change in the ECI, compensation: All workers (excluding farm, household, and Federal workers) ..... Private industry workers ....................................................... Goods-producing3............................................................ Service-producing3 ........................................................... State and local government workers..................................... 3.5 3.6 3.9 3.6 2.8 3.0 3.1 3.1 2.9 3.0 .7 .8 .9 .8 .3 1.0 .9 .7 1.0 1.5 .6 .6 .6 .7 .4 .9 1.0 1.0 .9 .6 .7 .8 1.0 .7 .4 1.0 .8 .7 .9 1.5 .4 .4 .3 .4 .5 .8 .8 .8 .9 .6 Workers by bargaining status (private industry): Union................................................................................. Nonunion ........................................................................... 4.3 3.5 2.7 3.1 1.1 .8 .8 .9 .8 .6 .8 1.0 .9 .8 .7 .8 .3 .4 .7 .9 Employment, nonfarm (payroll data), in thousands:2 Employment Cost Index 1 Data for 1994 are not directly comparable with data for 1993 and prior years. For additional information, see the box note under “Employment and Unemployment Data” in the notes to this section. 90 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 2 Quarterly data seasonally adjusted. 3 Goods-producing industries include mining, construction, and manufacturing. Serviceproducing industries include all other private sector industries. 2. Annual and quarterly percent changes in compensation, prices, and productivity 1994 1993 Selected measures Compensation data: 1993 1995 1994 II III IV I II III IV I 2 Employment Cost Index-compensation (wages, salaries, benefits): Civilian nonfarm ........................................................... Private nonfarm .......................................................... Employment Cost Index-wages and salaries Civilian nonfarm ........................................................... Private nonfarm .......................................................... 3.5 3.6 3.0 3.1 0.7 .8 1.0 .9 0.6 .6 0.9 1.0 0.7 .8 1.0 .8 0.4 .4 0.8 .8 3.1 3.1 2.8 2.8 .6 .6 1.0 1.0 .6 .6 .6 .7 .7 .8 1.0 .8 .5 .5 .7 .8 Consumer Price Index (All urban consumers): All items..... 2.7 2.7 .5 .5 1.0 .5 .9 .2 1.1 .7 Producer Price Index: Finished goods............................................................ Finished consumer goods............................................ Capital equipment ...................................................... Intermediate materials, supplies, components ................. Crude materials........................................................... .2 -.2 1.8 1.0 .1 1.7 1.6 2.0 4.4 -.5 -1.4 -1.5 -.5 .1 -3.1 .2 -.2 1.7 -.7 .0 .6 .6 .8 .7 3.1 .6 .6 .4 1.2 -.9 .0 .2 -.5 1.6 -3.4 .5 .3 1.2 .8 .8 .6 .5 .7 2.1 1.8 1.0 1.2 .4 1.8 1.1 1.3 1.3 2.8 2.4 2.2 2.5 .6 .4 4.6 2.2 2.9 3.2 5.0 4.2 3.9 1.8 1.7 2.0 -1.4 -1.4 -.8 3.2 2.7 1.6 4.3 4.3 3.4 2.2 2.7 1.8 Price data:1 Productivity data:3 Output per hour of all persons: Business sector.......................................................... Nonfarm business sector............................................. Nonfinancial corporations 4.......................................... 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. 3 Annual rates of change are computed by comparing annual averages. Quarterly percent changes reflect annual rates of change in quarterly in dexes. The data are seasonally adjusted. 4 Output per hour of all employees. Alternative measures of wage and compensation changes Quarterly average Components 1994 1993 IV Four quarters ended- I II III IV 1995 1993 I IV 1994 I II 1995 IV . Ill I Average hourly compensation:1 All persons, business sector......................................................... All persons, nonfarm business sector............................................ 1.7 1.6 5.1 4.9 0.9 1.4 3.1 2.7 3.6 3.8 4.0 4.3 2.3 1.9 2.9 2.6 2.3 2.3 2.7 2.6 3.2 3.2 2.9 3.0 Employment Cost Index-compensation: Civilian nonfarm 2 ....................................................................... Private nonfarm ........................................................................ Union .................................................................................... Nonunion............................................................................... State and local governments...................................................... .6 .6 .8 .6 .4 .9 1.0 .8 1.0 .6 .7 .8 .9 .8 .4 1.0 .8 .7 .8 1.5 .4 .4 .3 .4 .5 .8 .8 .7 .9 .6 3.5 3.6 4.3 3.5 2.8 3.2 3.3 3.5 3.3 2.8 3.2 3.4 3.3 3.4 2.9 3.2 3.3 3.2 3.3 3.0 3.0 3.1 2.7 3.1 3.0 2.9 2.9 2.6 3.0 3.1 Employment Cost Index-wages and salaries: Civilian nonfarm2 ........................................................................ Private nonfarm ....................................................................... Union.................................................................................... Nonunion............................................................................... State and local governments....................................................... .6 .6 .8 .6 .3 .6 .7 .7 .7 .6 .7 .8 .9 .8 .2 1.0 .8 .9 .8 1.7 .5 .5 .4 .5 .5 .7 .8 .6 .8 .7 3.1 3.1 3.0 3.1 2.7 2.9 2.9 3.0 2.9 2.7 3.0 3.1 3.2 3.0 2.8 2.9 2.9 3.3 2.8 2.9 2.8 2.8 2.9 2.7 3.1 3.0 2.9 2.8 2.9 3.2 .7 .5 .2 .4 .1 .3 .8 .2 .6 .1 .9 .1 .7 .1 .6 .2 .3 .1 .3 .2 3.0 .9 1.9 .2 2.9 .9 1.8 .2 2.7 .9 1.7 .2 2.9 .8 1.9 .2 2.7 .6 1.9 .2 2.6 .5 1.9 ,3 Total effective wage adjustments3...................................................... From current settlements............................................................. From prior settlements................................................................ From cost-of-living provision......................................................... (4) (4) (4) (4) Negotiated wage adjustments from settlements:3 First-year adjustments ................................................................. Annual rate over life of contract................................................... 2.8 2.0 3.0 2.4 2.0 2.4 1.0 1.9 2.2 2.5 1.9 1.9 2.3 2.1 2.4 2.1 2.2 2.1 2.3 2.2 2.0 2.3 1.8 2.3 Negotiated wage and benefit adjustments from settlements:5 First-year adjustment ................................................................... Annual rate over life of contract................................................... 3.8 2.5 3.0 2.6 3.4 2.9 (4) 1.4 1.5 2.1 1.4 1.6 3.0 2.4 3.0 2.3 3.1 2.4 3.1 2.5 2.3 2.4 2.1 2.3 1 Seasonally adjusted. 2 Excludes Federal and household workers. 3 Limited to major collective bargaining units of 1,000 workers or more. The most recent data are preliminary. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 4 Data round to zero. 5 Limited to major collective bargaining units of 5,000 workers or more. The most recent data are preliminary. M onthly Labor Review August 1995 91 Current Labor Statistics: 4. Labor Force D ata Employment status of the population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted (Numbers in thousands) Annual average 1994 1995 Employment status 1994 1993 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May TOTAL Civilian noninstitutional population'................................ Civilian labor force.................... Participation rate ............... Employed.............................. Employment-population ratio2 ............................... Unemployed........................... Unemployment rate............ Not in labor force ..................... 193,550 196,814 196,510 196,693 196,859 197,043 197,248 197,430 197,607 197,765 197,753 197,886 198,007 198,148 198,286 128,040 131,056 130,699 130,538 130,774 131,086 131,291 131,646 131,718 131,725 132,136 132,308 132,511 132,737 131,811 66.6 66.4 66.4 66.2 66.5 66.5 66.6 66.7 66.7 66.8 66.6 66.9 66.9 67.0 66.5 119,306 123,060 122,703 122,635 122,781 123,197 123,644 124,141 124,403 124,570 124,639 125,125 125,274 125,072 124,319 61.6 8,734 6.8 65,509 62.5 7,996 6.1 65,758 62.4 7,996 6.1 65,811 62.3 7,903 6.1 66,155 62.4 7,993 6.1 66,085 62.5 7,889 6.0 65,957 62.7 7,647 5.8 65,957 62.9 7,505 5.7 65,784 63.0 7,315 5.6 65,889 63.0 7,155 5.4 66,040 63.0 7,498 5.7 65,617 63.2 7,183 5.4 65,578 63.3 7,237 5.5 65,496 63.1 7,665 5.8 65,412 62.7 7,492 5.7 66,476 85,907 66,069 76.9 61,865 87,151 66,921 76.8 63,294 87,000 66,652 76.6 63,080 87,095 66,602 76.5 63,043 87,123 66,747 76.6 63,076 87,248 66,817 76.6 63,271 87,321 66,909 76.6 63,517 87,439 67,177 76.8 63,820 87,529 67,345 76.9 64,051 87,617 67,450 77.0 64,281 87,528 67,539 77.2 64,133 87,572 67,552 77.1 64,478 87,622 67,643 77.2 64,465 87,664 67,563 77.1 64,224 87,691 67,250 76.7 63,841 72.0 2,263 59,602 4,204 6.4 72.6 2,351 60,943 3,627 5.4 72.5 2,384 60,696 3,572 5.4 72.4 2,334 60,709 3,559 5.3 72.4 2,314 60,762 3,671 5.5 72.5 2,377 60,894 3,546 5.3 72.7 2,293 61,224 3,392 5.1 73.0 2,329 61,491 3,357 5.0 73.2 2,377 61,674 3,294 4.9 73.4 2,410 61,871 3,169 4.7 73.3 2,390 61,743 3,406 5.0 73.6 2,512 61,965 3,074 4.6 73.6 2,519 61,946 3,178 4.7 73.3 2,384 61,840 3,339 4.9 72.8 2,242 61,599 3,410 5.1 94,388 55,146 58.4 51,912 95,467 56,655 59.3 53,606 95,329 56,545 59.3 53,481 95,407 56,384 59.1 53,328 95,469 56,536 59.2 53,541 95,544 56,747 59.4 53,722 95,658 57,031 59.6 54,044 95,729 56,951 59.5 54,090 95,821 56,984 59.5 54,129 95,873 56,725 59.2 54,037 95,961 56,951 59.3 54,134 96,020 57,096 59.5 54,334 96,037 57,042 59.4 54,242 96,099 57,360 59.7 54,403 96,141 56,819 59.1 54,097 55.0 599 51,313 3,234 5.9 56.2 809 52,796 3,049 5.4 56.1 789 52,692 3,064 5.4 55.9 739 52,589 3,056 5.4 56.1 790 52,751 2,995 5.3 56.2 815 52,907 3,025 5.3 56.5 847 53,197 2,987 5.2 56.5 863 53,227 2,861 5.0 56.5 850 53,279 2,855 5.0 56.4 882 53,155 2,688 4.7 56.4 877 53,257 2,817 4.9 56.6 898 53,436 2,763 4.8 56.5 913 53,329 2,800 4.9 56.6 925 53,477 2,957 5.2 56.3 828 53,268 2,722 4.8 13,255 6,826 51.5 5,530 14,196 7,481 52.7 6,161 14,181 7,502 52.9 6,142 14,191 7,552 53.2 6,264 14,267 7,491 52.5 6,164 14,251 7,522 52.8 6,204 14,269 7,351 51.5 6,083 14,261 7,518 52.7 6,231 14,257 7,389 51.8 6,223 14,274 7,550 52.9 6,252 14,263 7,646 53.6 6,372 14,294 7,660 53.6 6,313 14,348 7,826 54.5 6,567 14,385 7,814 54.3 6,446 14,454 7,742 53.6 6,381 41.7 212 5,317 1,296 19.0 43.4 249 5,912 1,320 17.6 43.3 240 5,902 1,360 18.1 44.1 221 6,043 1,288 17.1 43.2 229 5,935 1,327 17.7 43.5 244 5,960 1,318 17.5 42.6 271 5,812 1,268 17.2 43.7 302 5,929 1,287 17.1 43.6 273 5,950 1,166 15.8 43.8 240 6,012 1,298 17.2 44.7 308 6,064 1,274 16.7 44.2 245 6,068 1,347 17.6 45.8 266 6,300 1,260 16.1 44.8 285 6,160 1,369 17.5 44.1 287 6,094 1,360 17.6 Men, 20 years and over Civilian noninstitutional population'............................... Civilian labor force.................... Participation rate ............... Employed .............................. Employment-population ratio2 ............................... Agriculture ........................... Nonagricultural industries...... Unemployed........................... Unemployment rate............ Women, 20 years ond over Civilian noninstitutional population'............................... Civilian labor force.................... Participation rate ............... Employed .............................. Employment-population ratio2 ............................... Agriculture ........................... Nonagricultural industries...... Unemployed........................... Unemployment rate............ Both sexes, 16 to 19 years Civilian noninstitutional population'............................... Civilian labor force.................... Participation rate ............... Employed .............................. Employment-population ratio2 ............................... Agriculture ........................... Nonagricultural industries...... Unemployed........................... Unemployment rate............ White Civilian noninstitutional population’ ............................... Civilian labor force.................... Participation rate ............... Employed .............................. Employment-population ratio2 ............................... Unemployed........................... Unemployment rate............ 163,921 165,555 165,351 165,472 165,576 165,696 165,832 165,954 166,072 166,175 166,361 166,444 166,521 166,613 166,708 109,359 111,082 110,829 110,523 110,911 111,186 111,381 111,555 111,637 111,715 111,876 111,830 111,999 112,153 111,568 66.7 67.1 67.0 66.8 67.0 67.1 67.2 67.2 67.2 67.2 67.2 67.2 67.3 67.3 66.9 102,812 105,190 104,978 104,687 105,006 105,401 105,740 106,010 106,242 106,352 106,366 106,604 106,698 106,500 105,935 62.7 6,547 6.0 63.5 5,892 5.3 63.5 5,851 5.3 63.3 5,836 5.3 63.4 5,905 5.3 63.6 5,785 5.2 63.8 5,641 5.1 63.9 5,545 5.0 64.0 5,395 4.8 64.0 5,363 4.8 63.9 5,510 4.9 64.0 5,226 4.7 64.1 5,301 4.7 63.9 5,653 5.0 63.5 5,633 5.0 22,329 13,943 62.4 12,146 22,879 14,502 63.4 12,835 22,824 14,510 63.6 12,810 22,855 14,481 63.4 12,838 22,883 14,380 62.8 12,767 22,917 14,429 63.0 12,795 22,955 14,477 63.1 12,927 22,990 14,649 63.7 13,022 23,023 14,578 63.3 13,054 23,052 14,541 63.1 13,119 23,089 14,697 63.7 13,192 23,117 14,868 64.3 13,362 23,142 14,818 64.0 13,370 23,169 14,938 64.5 13,337 23,192 14,803 63.8 13,336 54.4 1,796 12.9 56.1 1,666 11.5 56.1 1,700 11.7 56.2 1,643 11.3 55.8 1,613 11.2 55.8 1,634 11.3 56.3 1,550 10.7 56.6 1,627 11.1 56.7 1,524 10.5 56.9 1,422 9.8 57.1 1,505 10.2 57.8 1,505 10.1 57.8 1,448 9.8 57.6 1,601 10.7 57.5 1,467 9.9 Black Civilian noninstitutional population'............................... Civilian labor force.................... Participation rate ............... Employed.............................. Employment-population ratio2 ............................... Unemployed........................... Unemployment rate............ See footnotes at end of table. M onthly Labor Review Digitized for 92 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 4. Continued— Employment status of the population, by sex, age, race and Hispanic origin, monthly data seasonally adjusted (Numbers in thousands) Annual average 1994 Employment status 1995 1993 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 15,753 10,377 65.9 9,272 18,117 11,975 66.1 10,788 18,041 11,916 66.0 10,735 18,092 11,896 65.8 10,682 18,143 11,956 65.9 10,760 18,193 12,002 66.0 10,786 18,244 11,997 65.8 10,806 18,291 12,222 66.8 11,074 18,339 12,324 67.2 11,236 18,385 12,224 66.5 11,105 18,368 12,036 65.5 10,811 18,413 12,017 65.3 10,943 18,458 12,001 65.0 10,903 18,509 12,131 65.5 11,058 18,554 12,111 65.3 10,895 58.9 1,104 10.6 59.5 1,187 9.9 59.5 1,181 9.9 59.0 1,214 10.2 59.3 1,196 10.0 59.3 1,216 10.1 59.2 1,191 9.9 60.5 1,148 9.4 61.3 1,088 8.8 60.4 1,119 9.2 58.9 1,224 10.2 59.4 1,073 8.9 59.1 1,098 9.1 59.7 1,073 8.8 58.7 1,216 10.0 Hispanic origin Civilian noninstitutional population'............................... Civilian labor force.................... Participation rate ............... Employed .............................. Employment-population ratio2 ............................... Unemployed........................... Unemployment rate............ ' The population tigures are not seasonally adjusted. 2 Civilian employment as a percent of the civilian noninstitutional population. NOTE: Data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under “Employment and Unemployment 5. Data” in the notes to this section. Detail for the above race and Hispanic-origin groups will not sum to totals 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 1994 Selected categories 1993 1994 May June July Aug. 1995 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May CHARACTERISTIC Employed, 16 years and over...... 119,306 123,060 122,703 122,635 122,781 123,197 123,644 124,141 124,403 124,570 124,639 125,125 125,274 125,072 124,319 Men ..................................... 64,700 66,450 66,197 66,255 66,226 66,458 66,682 67,059 67,244 67,483 67,386 67,709 67,811 67,588 67,110 Women ............................ 54,606 56,610 56,506 56,380 56,555 56,739 56,962 57,082 57,159 57,087 57,252 57,416 57,462 57,484 57,208 Married men, spouse present .. 40,869 41,414 41,330 41,313 41,281 41,487 41,557 41,511 41,530 41,608 41,601 42,190 42,132 42,086 41,874 Married women, spouse present............................... 30,512 31,536 31,372 31,193 31,462 31,593 31,905 31,764 31,775 31,723 31,705 31,893 32,135 32,108 32,022 Women who maintain families . 6,764 7,053 7,061 7,008 7,016 6,974 7,029 7,098 7,141 7,074 7,199 7,067 7,071 7,152 7,175 CLASS OF WORKER Agriculture: Wage end salary workers...... Self-employed workers.......... Unpaid family workers........... Nonagricultural industries: Wage and salary workers ...... Government ....................... Private industries................ Private households........... Other .......................... Self-employed workers.......... Unpaid family workers........... 1,637 1,332 105 1,715 1,645 49 1,736 1,637 43 1,675 1,584 46 1,669 1,619 50 1,728 1,654 50 1,712 1,630 63 1,764 1,652 43 1,767 1,677 48 1,738 1,714 49 1,866 1,663 35 1,970 1,684 27 1,987 1,674 57 1,884 1,649 70 1,747 1,560 55 107,011 110,517 110,164 110,215 110,345 110,576 111,100 111,686 111,770 111,960 111,987 112,461 112,649 112,578 112,111 18,504 18,293 18,378 18,294 18,281 18,225 18,306 18,201 18,357 18,340 18,295 18,504 18,685 18,646 18,493 88,507 92,224 91,786 91,921 92,064 92,351 92,794 93,485 93,413 93,620 93,692 93,957 93,964 93,932 93,619 1,105 966 978 966 940 881 903 935 999 1,023 1,075 1,075 1,039 988 913 87,402 91,258 90,808 90,955 91,124 91,470 91,891 92,550 92,414 92,597 92,617 92,882 92,925 92,945 92,705 9,003 9,003 9,049 8,964 8,962 9,021 8,989 8,878 8,915 8,959 9,039 8,904 8,865 8,848 8,763 218 131 129 148 140 131 134 131 120 121 95 118 129 110 125 PERSONS AT WORK PART TIME' All industries: Part time for economic reasons . Slack work or business conditions............................ Could only find part-time work Part time for noneconomic reasons ................................ Nonagricultural industries: Part time for economic reasons . Slack work or business conditions............................ Could only find part-time work Part time for noneconomic reasons ................................ 6,348 4,625 4,792 4,766 4,467 4,348 4,333 4,411 4,411 4,422 4,693 4,460 4,530 4,469 4,476 3,140 2,908 2,432 1,871 2,503 1,981 2,464 1,927 2,431 1,698 2,396 1,618 2,404 1,697 2,394 1,791 2,394 1,736 2,384 1,734 2,504 1,777 2,372 1,739 2,333 1,902 2,517 1,686 2,502 1,720 15,062 17,638 17,441 17,452 17,922 17,955 17,609 17,644 17,756 17,576 17,940 18,041 17,627 18,121 17,666 6,106 4,414 4,583 4,510 4,273 4,173 4,154 4,226 4,246 4,254 4,430 4,187 4,347 4,171 4,289 2,977 2,832 2,311 1,824 2,386 1,942 2,349 1,883 2,318 1,661 2,272 1,583 2,290 1,646 2,257 1,756 2,282 1,689 2,272 1,690 2,359 1,737 2,216 1,687 2,226 1,854 2,328 1,624 2,364 1,698 14,637 17,007 16,841 16,909 17,308 17,314 16,982 16,992 17,101 16,917 17,307 17,381 16,991 17,232 17,034 1 Excludes persons “with a job but not at work” during the survey period for such reasons as vacation, illness, or industrial disputes. NOTE: D a ta f o r 1 9 9 4 a re n o t d ire c tly c o m p a ra b le w ith d a ta fo r 1 9 9 3 a n d e a r lie r y e a rs . the notes to this section. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis F o r a d d itio n a l in fo r m a tio n , s e e th e b o x n o te u n d e r “ E m p lo y m e n t a n d U n e m p lo y m e n t D a t a " in M onthly Labor Review August 1995 93 Current Labor Statistics: 6. Labor Force D ata Selected unemployment indicators, monthly data seasonally adjusted (Unemployment rates) 1994 Annual average 1995 Selected categories 1993 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Total, all workers.............................................. Both sexes, 16 to 19 years............................ Men, 20 years and over................................ Women, 20 years and over............................ 6.8 19.0 6.4 5.9 6.1 17.6 5.4 5.4 6.1 18.1 5.4 5.4 6.1 17.1 5.3 5.4 6.1 17.7 5.5 5.3 6.0 17.5 5.3 5.3 5.8 17.2 5.1 5.2 5.7 17.1 5.0 5.0 5.6 15.8 4.9 5.0 5.4 17.2 4.7 4.7 5.7 16.7 5.0 4.9 5.4 17.6 4.6 4.8 5.5 16.1 4.7 4.9 5.8 17.5 4.9 5.2 5.7 17.6 5.1 4.8 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......................... 6.0 16.2 17.6 14.6 5.6 5.1 5.3 15.1 16.3 13.8 4.8 4.6 5.3 15.5 17.0 13.7 4.7 4.6 5.3 14.3 15.1 13.6 4.7 4.7 5.3 14.7 16.1 13.1 4.8 4.7 5.2 14.6 15.4 13.7 4.6 4.6 5.1 14.8 16.2 13.3 4.4 4.6 5.0 14.4 15.2 13.5 4.4 4.4 4.8 13.5 14.3 12.6 4.3 4.3 4.8 14.7 16.0 13.2 4.2 4.1 4.9 14.1 15.0 13.1 4.4 4.3 4.7 14.7 16.1 13.1 4.0 4.1 4.7 13.6 14.7 12.4 4.2 4.2 5.0 14.6 15.3 13.8 4.4 4.5 5.0 14.8 15.2 14.3 4.6 4.3 Black, 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......................... 12.9 38.9 40.1 37.5 12.1 10.6 11.5 35.2 37.6 32.6 10.3 9.8 11.7 38.2 40.9 35.0 10.3 10.0 11.3 36.1 39.3 32.6 10.0 9.5 11.2 37.3 41.4 32.7 10.4 8.8 11.3 36.1 39.9 31.9 10.2 9.4 10.7 32.1 30.8 33.4 9.8 9.0 11.1 37.5 35.9 39.1 9.5 9.2 10.5 33.0 32.0 34.1 9.2 8.9 9.8 34.6 34.3 35.0 8.3 8.3 10.2 35.5 34.0 37.1 9.2 8.5 10.1 35.7 38.7 32.4 7.9 9.0 9.8 31.2 31.7 30.7 7.8 9.1 10.7 35.6 35.4 35.8 8.9 9.3 9.9 35.1 40.0 30.5 8.8 7.8 Hispanic origin, total..................................... 10.6 9.9 9.9 10.2 10.0 10.1 9.9 9.4 8.8 9.2 10.2 8.9 9.1 8.8 10.0 Married men, spouse present........................ Married women, spouse present.................... Women who maintain families....................... Full-time workers ......................................... Part-time workers ......................................... 4.4 4.6 9.5 7.4 7.4 3.7 4.1 8.9 6.8 7.1 3.7 4.1 8.9 6.1 6.2 3.6 4.2 8.8 6.1 5.9 3,6 4.0 7.9 6.1 6.0 3.5 4.1 8.8 6.0 6.2 3.4 4.0 8.9 5.8 5.8 3.3 4.0 8.9 5.8 5.6 3.2 3.9 8.7 5.6 5.4 3.2 3.7 8.8 5.3 5.9 3.4 3.7 8.9 5.5 6.2 3.0 3.6 8.1 5.3 6.0 3.2 3.9 7.6 5.4 5.8 3.4 4.2 9.0 5.6 6.3 3.4 3.9 8.0 5.6 6.1 7.0 7.3 14.3 7.2 7.1 7.3 5.1 7.8 6.3 5.4 11.8 5.6 5.2 6.0 4.8 7.4 6.4 6.0 11.7 5.6 5.3 5.9 4.9 7.4 6.3 6.1 11.7 5.5 5.2 5.9 4.9 7.2 6.3 6.0 11.1 5.6 5.5 5.8 5.1 7.5 6.1 5.0 10.7 5.3 5.3 5.3 4.8 7.4 6.0 5.1 10.7 5.3 5.3 5.4 4.5 7.0 5.9 4.7 10.7 5.1 4.8 5.6 4.4 7.2 5.9 4.5 10.7 5.1 4.3 6.0 4.6 7.0 5.6 3.9 10.9 4.9 4.6 5.4 4.2 6.7 5.7 5.1 11.7 4.7 4.2 5.4 4.7 6.6 5.5 5.2 10.5 4.4 3.9 5.0 4.5 6.4 5.5 6.1 10.8 4.5 4.2 4.9 4.5 6.2 5.9 4.3 11.8 4.8 4.4 5.4 4.6 6.8 6.0 4.9 12.6 5.5 5.3 6.0 4.0 6.7 4.1 6.5 3.3 11.6 3.6 6.1 3.4 11.3 3.6 6.0 3.5 8.8 3.7 5.9 3.7 8.6 3.7 5.9 3.4 12.1 3.7 5.7 3.6 11.1 4.3 5.5 3.2 11.1 3.4 5.3 3.2 10.3 3.6 5.4 2.7 10.4 2.9 5.2 3.1 11.1 2.9 5.2 3.2 10.7 3.5 5.2 2.8 9.1 3.3 5.3 . 2.7 10.5 3.4 5.6 3.1 11.3 3.7 5.5 2.8 12.5 CHARACTERISTIC INDUSTRY Nonagricultural private wage and salary workers .... Mining......................................................... Construction ................................................ Manufacturing ............................................. Durable goods........................................... Nondurable goods ..................................... Transportation and public utilities ................... Wholesale and retail trade............................ Finance,insurance, and real estate.................................................. Services...................................................... Government workers ......................................... Agricultural wage and salary workers .................. NOTE: Data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under “Employment and Unemployment Data” in the notes to this section. 7. Duration of unemployment, monthly data seasonally adjusted (Numbers in thousands) 1994 Annual average Weeks of unemployment 1995 1993 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May Less than 5 weeks..................................... 5 to 14 weeks ............................................ 15 weeks and over..................................... 15 to 26 weeks ........................................ 27 weeks and over................................... 3,160 2,522 3,052 1,274 1,778 2,728 2,408 2,860 1,237 1,623 2,651 2,461 2,853 1,160 1,693 2,754 2,452 2,740 1,193 1,547 2,768 2,365 2,823 1,234 1,589 2,655 2,572 2,773 1,198 1,575 2,675 2,294 2,768 1,213 1,555 2,434 2,256 2,934 1,344 1,590 2,599 2,163 2,661 1,187 1,474 2,587 2,149 2,456 1,088 1,368 2,937 2,122 2,386 1,033 1,353 2,600 2,165 2,298 1,090 1,207 2,523 2,319 2,266 920 1,347 2,629 2,430 2,505 1,115 1,390 2,598 2,304 2,585 1,282 1,303 Mean duration, in weeks.............................. Median duration, in weeks............................ 18.1 8.4 18.8 9.2 19.4 9.2 18.4 9.1 19.0 9.2 18.9 9.2 18.8 9.5 19.3 10.1 18.2 9.1 17.8 8.7 16.7 7.9 16.9 7.8 17.5 7.9 17.7 8.5 16.9 9.0 NOTE: In the three tables above, data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under M onthly Labor Review 94 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 “Employment and Unemployment Data" in the notes to this section, 8. Unemployed persons by reason for unemployment, monthly data seasonally adjusted (Numbers in thousands) Annual average 1994 1995 Reason for unemployment 1993 Job losers' ....................................................... On temporary layoff........................................ Not on temporary layoff .................................. Job leavers ...................................................... Reentrants ....................................................... New entrants ................................................... 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 4,769 1,104 3,664 946 2,145 874 3,815 977 2,838 791 2,786 604 3,640 811 2,829 796 2,863 611 3,734 931 2,803 788 2,785 498 3,863 1,031 2,832 770 2,766 594 3,706 1,012 2,694 786 2,758 621 3,574 824 2,750 874 2,620 600 3,513 848 2,665 755 2,626 614 3,495 881 2,614 710 2,575 578 3,442 930 2,512 704 2,525 555 3,658 1,061 2,598 694 2,488 597 3,339 1,025 2,314 773 2,474 582 3,352 1,032 2,320 811 2,430 604 3,532 1,145 2,387 817 2,779 637 3,614 958 2,657 870 2,458 522 54.6 12.6 42.0 10.8 24.6 10.0 47.7 12.2 35.5 9.9 34.8 7.6 46.0 10.3 35.8 10.1 36.2 7.7 47.8 11.9 35.9 10.1 35.7 6.4 48.3 12.9 35.4 9.6 34.6 7.4 47.1 12.9 34.2 10.0 35.0 7.9 46.6 10.7 35.9 11.4 34.2 7.8 46.8 11.3 35.5 10.1 35.0 8.2 47.5 12.0 35.5 9.6 35.0 7.9 47.6 12.9 34.8 9.7 34.9 7.7 49.2 14.3 34.9 9.3 33.4 8.0 46.6 14.3 32.3 10.8 34.5 8.1 46.6 14.3 32.2 11.3 33.8 8.4 45.5 14.7 30.7 10.5 35.8 8.2 48.4 12.8 35.6 11.7 32.9 7.0 3.7 .7 1.7 .7 2.9 .6 2.1 .5 2.8 .6 2.2 .5 2.9 .6 2.1 .4 3.0 .6 2.1 .5 2.8 .6 2.1 .5 2.7 .7 2.0 .5 2.7 .6 2.0 .5 2.7 .5 2.0 .4 2.6 .5 1.9 .4 2.8 .5 1.9 .5 2.5 .6 1.9 .4 2.5 .6 1.8 .5 2.7 .6 2.1 .5 2.7 .7 1.9 .4 PERCENT OF UNEMPLOYED Job losers' .................................................... On temporary layoff ..................................... Not on temporary layoff................................ Job leavers.................................................... Reentrants..................................................... New entrants ................................................. PERCENT OF CIVILIAN LABOR FORCE Job losers' ...................................................... Job leavers ...................................................... Reentrants ...................................................... New entrants ................................................... 1 Includes persons who completed temporary jobs. 9. Unemployment rates by sex and age, monthly data seasonally adjusted (Civilian workers) Sex and age Annual average 1993 1994 1994 May June July Aug. 1995 Sept. Oct. Nov. Dec. Jan. Total, 16 years and over ......................................................... 16 to 24 years.................................................. 16 to 19 years ................................................................... 16 to 17 years ................................................................ 18 to 19 years ................................................................ 20 to 24 years ................................................................... 25 years and over................................................................ 25 to 54 years ................................................................ 55 years and over........................................................... 6.8 13.3 19.0 21.3 17.5 10.5 5.6 5.8 4.3 6.1 12.5 17.6 19.9 16.0 9.7 4.8 5.0 4.1 6.1 12.6 18.1 20.4 16.3 9.6 4.8 4.9 4.2 6.1 12.2 17.1 20.1 15.4 9.5 4.8 4.9 4.0 6.1 12.5 17.7 20.3 15.7 9.7 4.8 4.9 4.2 6.0 12.6 17.5 19.9 15.6 9.9 4.7 4.8 4.2 5.8 12.1 17.2 18.8 16.0 9.4 4.6 4.8 3.8 5.7 11.8 17.1 17.8 16.8 9.0 4.5 4.7 3.9 5.6 11.4 15.8 17.2 14.7 9.1 4.5 4.5 3.9 5.4 11.6 17.2 18.1 16.6 8.6 4.3 4.4 3.5 Men, 16 years and over...................................................... 16 to 24 years ............................................................ 16 to 19 years............................................. 16 to 17 years............................................................ 18 to 19 years............................................................ 20 to 24 years......................................... 25 years and over........................................................... 25 to 54 years............................................................ 55 years and over....................................................... 7.1 14.3 20.4 22.8 18.8 11.3 5.8 5.9 4.7 6.2 13.2 19.0 21.0 17.6 10.2 4.8 4.9 4.3 6.2 13.5 19.9 22.4 18.0 10.1 4.7 4.8 4.4 6.0 12.7 18.0 21.6 16.6 9.9 4.8 4.8 4.2 6.3 13.4 19.4 20.9 18.0 10.3 4.9 4.9 4.5 6.1 13.3 18.8 20.7 17.1 10.5 4.7 4.8 4.2 5.8 12.6 18.5 19.4 17.5 9.5 4.5 4.6 3.9 5.7 12.4 18.1 18.2 18.1 9.4 4.5 4.6 4.1 5.5 11.8 16.5 16.5 16.5 9.5 4.4 4.4 4.0 5.5 12.2 18.5 18.8 18.2 9.0 4.3 4.3 3.5 17.4 20.9 14.5 9.1 4.5 4.6 4.0 Women, 16 years and over................................... 16 to 24 years............................................... 16 to 19 years ............................................. 16 to 17 years .......................................................... 18 to 19 years ........................................................... 20 to 24 years ......................................... 25 years and over........................................................... 25 to 54 years .......................................................... 55 years and over ..................................................... 6.5 12.2 17.4 19.6 16.0 9.6 5.4 5.6 3.8 6.0 11.6 16.2 18.7 14.3 9.2 4.9 5.0 3.9 6.1 11.6 16.2 18.3 14.6 9.0 5.0 5.1 3.9 6.1 11.6 16.0 18.5 14.2 9.1 4.9 5.1 3.8 5.9 11.5 15.9 19.7 13.1 9.1 4.8 5.0 3.7 6.0 11.7 16.1 19.0 14.0 9.3 4.8 4.9 4,1 5.8 11.6 15.9 18.2 14.2 9.3 4.7 5.0 3.6 5.7 11.2 16.0 17.4 15.4 8.6 4.6 4.8 3.7 5.6 10.9 15.0 17.9 12.8 8.7 4.6 4.7 3.8 5.4 10.9 15.8 17.4 14.9 8.1 4.3 4.4 3.4 5.6 10.7 15.9 19.1 13.9 7.8 4.6 4.6 3.7 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 5.7 11.4 16.7 20.0 14.2 8.5 4.5 4.6 3.9 5.7 12.0 M onthly Labor Review Feb. 5.4 11.7 17.6 20.7 15.3 8.5 4.2 4.3 3.4 5.4 Mar. 5.5 5.8 5.7 11.8 11.8 16.1 17.5 20.0 20.6 13.0 9.1 4.2 4.3 3.5 15.7 8.7 4.6 4.7 3.8 17.6 21.5 14.7 11.8 19.4 22.6 20.2 16.7 14.6 8.9 4.1 4.2 3.7 8.2 4.0 4.2 3.6 5.5 11.2 15.6 18.7 13.7 8.7 4.3 4.5 3.2 May 11.6 5.4 11.7 17.0 12.1 Apr. 5.5 11.5 15.2 19.8 11.3 9.4 4.3 4.4 3.4 August 1995 5.7 8.6 4.5 4.6 3.8 5.8 12.3 18.4 17.8 21.7 16.1 22.6 4.5 4.5 4.3 15.2 8.9 4.6 4.7 4.0 5.9 11.9 17.2 19.4 15.2 5.5 11.4 16.7 20.4 14.0 8.6 8.8 8.2 4.7 5.0 3.3 4.4 4.6 3.6 95 Current Labor Statistics: 10. Labor Force D ata Unemployment rates by State, seasonally adjusted May 1994 Apr. 1995 May 1995p Alabama.............. Alaska.................. Arizona................ Arkansas ............. California............. 6.1 8.0 6.4 5.5 8.5 5.8 6.7 5.5 5.0 7.9 5.9 6.4 5.6 4.1 8.5 Colorado.............. Connecticut.......... Delaware............. District of Columbia Florida................. 4.4 5.5 5.1 8.1 6.8 4.0 5.2 4.1 8.4 5.6 3.9 5.1 4.3 8.6 5.1 Georgia............... Hawaii................. Idaho................... Illinois.................. Indiana................ 5.2 6.0 5.3 5.8 4.9 4.7 5.2 5.1 5.7 4.8 4.8 5.1 5.1 5.5 4.7 Iowa.................... Kansas................ Kentucky.............. Louisiana............. Maine.................. 3.7 5.2 5.4 8.1 7.0 3.4 4.6 4.8 7.6 5.8 3.3 4.7 5.0 7.1 6.2 Maryland.............. Massachusetts...... Michigan.............. Minnesota............ Mississippi........... Missouri ............... 5.2 5.8 5.9 4.0 6.6 4.9 4.9 5.9 5.8 3.7 5.5 4.9 5.0 5.0 5.7 3.9 6.0 5.1 State May 1994 Apr. 1995 May 1995» Montana............................................ Nebraska........................................... Nevada .............................................. New Hampshire ................................. 4.9 2.8 6.2 4.8 5.3 2.5 5.8 4.0 5.5 2.6 5.9 3.8 New Jersey........................................ New Mexico....................................... New York.......................................... North Carolina.................................... North Dakota..................................... 6.9 6.4 6.5 4.2 3.8 6.3 6.0 6.8 4.7 3.3 6.5 5.7 6.3 4.3 3.3 Ohio.................................................. Oklahoma .......................................... Oregon .............................................. Pennsylvania..................................... Rhode Island...................................... 6.4 6.0 5.5 6.2 7.1 4.5 4.9 4.6 5.8 5.8 4.7 4.6 5.2 5.7 6.4 South Carolina ................................... South Dakota..................................... Tennessee ......................................... Texas ................................................ Utah.................................................. 6.5 3.2 4.9 6.7 3.7 4.9 3.3 4.4 5.9 3.6 4.9 2.3 4.6 6.0 3.7 Vermont ............................................ Virginia .............................................. Washington........................................ West Virginia ...................................... 4.7 4.9 6.7 8.8 4.6 4.2 4.4 6.1 7.3 3.9 3.9 4.5 6.1 7.6 3.9 Wyoming........................................... 5.3 4.4 4.8 State p = preliminary 11. Employment of workers on nonfarm payrolls by State, seasonally adjusted (In thousands) May 1994 Apr. 1995 May 1995p California............................................... 1,746.5 258.2 1,674.2 1,027.4 12,135.5 1,774.6 261.1 1,751.3 1,070.6 12,234.4 1,770.8 261.3 1,752.6 1,069.6 12,243.6 Colorado............................................... Connecticut ........................................... Delaware............................................... District of Columbia................................. Florida .................................................. 1,742.3 1,542.5 353.8 658.9 5,765.6 1,791.2 1,545.8 360.2 647.4 5,967.4 1,787.5 1,545.7 359.7 646.6 5,985.4 Indiana .................................................. 3,242.7 534.0 460.2 5,443.0 2,707.5 3,382.5 534.6 476.7 5,541.1 2,768.0 3,384.1 533.6 474.9 5,526.8 2,762.3 1,313.7 1,159.9 1,592.2 1,705.2 530.7 1,349.8 1,190.9 1,629.0 1,788.7 542.3 1,348.7 1,195.6 1,633.8 1,794.4 541.7 2,142.7 2,888.0 4,125.7 2,304.7 1,051.0 2,456.1 2,162.4 2,951.5 4,255.2 2,361.7 1,055.8 2,545.9 2,160.4 2,948.3 4,258.8 2,361.8 1,056.3 2,535.3 State Alaska .................................................. Kansas .................................................. Maine.................................................... Minnesota............................................. Mississippi............................................. May 1994 Apr. 1995 Nebraska.............................................. 337.8 791.6 730.7 520.0 348.6 812.0 772.1 534.1 349.9 808.4 773.3 533.6 New Jersey .......................................... New Mexico ......................................... New York.............................................. North Carolina ...................... ................ North Dakota ........................................ 3,548.6 651.6 7,804.0 3,347.3 293.3 3,603.3 685.6 7,837.1 3,436.9 301.4 3,604.1 684.2 7,826.0 3,434.8 301.3 Ohio .................................................... 5,067.1 1,272.7 1,356.3 5,184.1 433.2 5,173.9 1,296.6 1,409.5 5,222.8 434.4 5,169.8 1,299.3 1,413.4 5,200.9 431.9 South Carolina...................................... 1,600.6 330.6 2,411.4 7,698.7 853.3 1,626.6 341.6 2 485 8 7,975.8 898.3 1,626.8 341.3 2 487 1 7,975.1 902.7 Vermont............................................... 264.2 2,992.1 2,293.2 682.9 2,471.4 269.0 3,075.2 2,359.4 686.8 2,535.3 267.7 3,073.1 2^360.4 687.9 2,540.4 216.0 220.4 218.7 State Wisconsin............................................. p = preliminary NOTE: Some data in this table may differ from data published elsewhere because of the continual updating of the database. M onthly Labor Review 96 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 May 1995p 12. Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted (In thousands) Annua average 1994 Industry 1993 TOTAL ........................................ PRIVATE SECTOR ...................... GOODS-PRODUCING ..................... Mining1 ............................................. Metal mining .......................... Oil and gas extraction ............. Nonmetallic minerals, except fuels..................................... Construction .................................. General building contractors..... Heavy construction, except building................................ Special trades contractors....... M anufacturing................................ Production workers ............... Durable g o o d s .............................. Production workers ............... Lumber and wood products...... Furniture and fixtures............... Stone, clay, and glass products . Primary metal industries........... Blast furnaces and basic steel products............................... Fabricated metal products........ Industrial machinery and equipment ............................. Computer and office equipment.. Electronic and other electrical equipment ............... Electronic components and accessories..................... Transportation equipment ......... Motor vehicles and equipment... Aircraft and parts................... Instruments and related products Miscellaneous manufacturing industries............................... 1994 May June July Aug. 1995 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr.p Mayp 110,730 114,034 113,638 113,943 114,171 114,510 114,762 114,935 115,427 115,624 115,810 116,123 116,302 116,295 116,194 91,889 94,917 94,545 94,840 95,061 95,327 95,555 95,740 96,152 96,405 96,588 96,882 97,054 97,048 96,969 23,352 610 50 350 23,913 600 49 336 23,837 599 48 336 23,905 602 49 337 102 103 103 103 103 103 103 104 104 104 4,668 1,120 5,010 1,201 4,981 1,192 5,006 1,197 5,029 1,199 5,038 1,206 5,077 1,214 5,088 1,222 5,144 1,234 5,166 1,241 713 2,836 736 3,073 737 3,052 738 3,071 743 3,087 738 3,094 740 3,123 734 3,132 740 3,170 739 3,186 18,075 12,341 18,303 12,615 18,257 12,569 18,297 12,609 18,297 12,610 18,346 12,658 18,355 12,671 18,398 12,709 18,439 12,759 10,221 6,849 10,431 7,092 10,388 7,050 10,426 7,086 10,422 7,088 10,465 7,128 10,481 7,145 10,513 7,175 709 487 517 683 752 502 533 699 748 500 531 692 752 502 532 697 755 504 533 700 757 504 534 699 758 504 535 704 240 1,339 239 1,387 235 1,378 239 1,386 240 1,390 238 1,396 1,931 363 1,985 351 1,981 354 1,989 355 1,983 352 1,526 1,571 1,561 1,570 528 1,756 837 542 896 544 1,749 899 480 863 539 1,741 885 485 867 542 1,746 893 480 863 23,922 596 49 332 23,981 597 49 333 24,030 598 49 336 24,081 595 49 331 24,175 592 49 328 24,230 592 50 326 24,293 590 50 325 24,324 588 51 323 24,370 589 51 323 24,320 583 51 319 24,205 581 51 319 105 105 106 105 104 5,201 1,250 5,213 1,250 5,256 1,258 5,237 1,255 5,180 1,236 742 3,209 740 3,223 747 3,251 743 3,239 730 3,214 18,472 12,785 18,502 12,813 18,523 12,833 18,525 12,832 18,500 12,819 18,444 12,776 10,550 7,218 10,574 7,239 10,596 7,259 10,622 7,288 10,633 7,297 10,629 7,295 10,600 7,269 761 505 537 708 766 507 539 712 766 507 540 715 767 508 542 716 766 509 545 718 767 509 547 718 761 506 546 719 756 504 543 718 239 1,397 239 1,405 240 1,412 240 1,421 239 1,428 240 1,435 240 1,439 240 1,441 241 1 436 1,992 350 1,995 348 1,999 345 2,006 344 2,010 342 2,017 341 2,025 340 2,029 336 2,035 336 2,031 334 1,570 1,581 1,586 1,589 1,595 1,603 1,608 1,613 1,614 1,617 1,618 545 1,736 893 475 859 549 1,751 908 473 859 552 1,753 913 469 857 554 1,761 921 467 854 556 1,764 924 465 854 560 1,764 926 462 853 563 1,764 932 459 850 565 1,766 934 457 849 569 1,767 937 455 847 571 1,765 938 454 845 575 1,758 935 450 844 378 390 389 389 392 392 392 394 395 395 396 396 396 394 392 7,854 5,492 7,872 5,523 7,869 5,519 7,871 5,523 7,875 5,522 7,881 5,530 7,874 5,526 7,885 5,534 7,889 5,541 7,898 5,546 7,906 5,554 7,901 5,545 7,892 5,535 7,871 5,524 7,844 5 ,5 0 7 1,680 44 675 1,680 42 673 1,679 43 673 1,680 42 673 1,681 42 673 1,679 42 674 1,677 41 671 1,677 41 674 1,683 41 674 1,684 41 673 1,690 40 672 1,689 40 671 1,690 39 670 1,687 40 669 1,687 39 664 989 692 1,517 1,081 152 969 691 1,542 1,061 149 973 691 1,537 1,062 149 972 691 1,540 1,061 148 969 692 1,544 1,060 148 972 691 1,547 1,057 150 971 689 1,547 1,056 149 970 692 1,550 1,055 149 963 692 1,551 1,054 149 960 692 1,556 1,054 150 957 693 1,557 1,055 147 951 692 1,561 1,054 148 946 691 1,561 1,053 148 939 692 1,557 1,050 146 932 689 1 554 1,049 145 909 117 952 114 948 114 950 114 953 113 956 113 960 113 965 112 970 112 975 113 982 113 983 112 982 112 980 in 976 109 87,378 90,121 89,801 90,038 90,249 90,529 90,732 90,854 91,252 91,394 91,517 91,799 91,932 91,975 91 989 5,829 3,615 248 6,006 3,775 241 5,994 3,766 239 6,008 3,781 241 6,022 3,794 240 6,045 3,810 237 6,048 3,813 240 6,061 3,821 240 6,092 3,846 242 6,121 3,870 241 6,129 3,886 241 6,156 3,900 242 6,175 3,914 242 6,186 3,921 242 6,182 3,919 242 379 1,698 168 740 18 363 410 1,797 169 748 18 392 405 1,797 172 747 18 388 411 1,808 169 745 18 389 415 1,813 171 744 17 394 425 1,819 168 746 18 397 418 1,824 168 746 18 399 417 1,828 167 748 18 403 421 1,843 165 750 18 407 425 1,857 164 754 18 411 428 1,864 166 754 17 416 431 1,871 165 756 17 418 433 1,877 164 760 17 421 437 1,879 164 761 17 421 441 1,872 163 761 17 423 2,214 1,269 2,231 1,305 2,228 1,298 2,227 1,301 2,228 1,305 2,235 1,314 2,235 1,314 2,240 1,320 2,246 1,325 2,251 1,331 2,243 1,327 2,256 1,343 2,261 1,351 2,265 1,355 2,263 1,357 944 927 930 926 923 921 921 920 921 920 916 913 910 910 906 Wholesale trade ............................. 5,981 6,140 6,118 6,131 6,138 6,163 6,181 6,195 6,210 6,229 6,251 6,275 6,287 6,301 6,292 Retail tra d e ...................................... 19,773 20,437 Building materials and garden supplies................................ General merchandise stores...... Department stores.................... Food stores............................. 20,356 20,408 20,459 20,497 20,565 20,580 20,703 20,759 20,760 20,794 20,760 20,763 20,755 779 2,488 2,140 3,224 828 2,545 2,212 3,289 825 2,532 2,198 3,289 829 2,534 2,201 3,285 833 2,542 2,211 3,292 835 2,551 2,219 3,297 838 2,555 2,225 3,296 840 2,563 2,232 3,298 844 2,598 2,268 3,308 846 2,585 2,256 3,320 851 2,562 2,236 3,325 851 2,545 2,223 3,328 849 2,530 2,207 3,332 Nondurable g o o d s ......................... Production workers................. Food and kindred products....... Tobacco products ................... Textile mill products................. Apparel and other textile products ................................ Paper and allied products......... Printing and publishing ............. Chemicals and allied products .... Petroleum and coal products .... Rubber and miscellaneous plastics products.................... Leather and leather products.... SERVICE-PRODUCING ................... Transportation and public u tilities............................................. Transportation.......................... Railroad transportation ............. Local and interurban passenger transit.................................... Trucking and warehousing........ Water transportation ................ Transportation by air................ Pipelines, except natural gas..... Transportation services............ Communications and public utilities.................................... Communications...................... Electric, gas, and sanitary services................................ See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review 853 2,539 2,218 3,343 | August 1995 850 2,539 2,221 3^334 97 Current Labor Statistics: Labor Force D ata 12. Continued—Employment of workers on nonfarm payrolls by industry, monthly data seasonally adjusted (In thousands) Automotive dealers and service stations .................................. New and used car dealers...... Apparel and accessory stores.... Furniture and home furnishings stores..................................... Eating and drinking places......... Miscellaneous retail establishments........................ Finance, insurance, and real e s ta te ............................................... Finance ................................... Depository institutions .............. Commercial banks.................. Savings institutions................. Nondepository institutions......... Security and commodity brokers ................................. Holding and other investment offices................... Insurance ................................ Insurance carriers.................... Insurance agents, brokers and service ........................... Real estate .............................. Services .......................................... Agricultural services .................. Hotels and other lodging places......................... Personal services ..................... Business services..................... Services to buildings................ Personnel supply services ........ Help supply services ............... Computer and data processing services................ Auto repair services, and parking ............................ Miscellaneous repair services..... Motion pictures ........................ Amusement and recreation services ................................. 1995 1994 Annual average Industry 1993 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr.p Mayp 2,014 908 1,144 2,123 964 1,134 2,112 959 1,133 2,119 964 1,133 2,122 967 1,134 2,135 971 1,132 2,145 975 1,135 2,154 979 1,136 2,165 984 1,130 2,173 989 1,126 2,182 993 1,122 2,191 996 1,118 2,202 998 1,110 2,206 1,000 1,104 2,207 1,001 1,094 828 6,821 890 7,069 877 7,045 883 7,067 893 7,076 899 7,084 906 7,103 915 7,086 926 7,134 927 7,182 933 7,188 936 7,221 943 7,19.1 945 7,171 944 7,181 2,476 2,560 2,543 2,558 2,567 2,564 2,587 2,588 2,598 2,600 2,597 2,604 2,603 2,602 2,606 6,757 3,238 2,089 1,497 324 455 6,933 3,323 2,075 1,492 308 499 6,935 3,328 2,075 1,488 313 507 6,946 3,332 2,075 1,489 310 506 6,947 3,332 2,076 1,492 308 502 6,948 3,329 2,074 1,492 305 499 6,942 3,324 2,072 1,492 303 494 6,935 3,320 2,072 1,496 300 490 6,937 3,319 2,071 1,498 296 485 6,931 3,317 2,070 1,498 295 481 6,927 3,312 2,067 1,497 293 478 6,929 3,312 2,066 1,497 291 475 6,938 3,313 2,066 1,499 289 475 6,919 3,303 2,062 1,493 288 472 6,916 3,307 2,061 1,491 289 476 472 518 516 520 522 524 525 525 528 530 530 532 532 528 528 223 2,197 1,529 231 2,237 1,551 230 2,239 1,555 231 2,240 1,554 232 2,238 1,551 232 2,238 1,549 233 2,236 1,546 233 2,236 1,544 235 2,236 1,542 236 2,232 1,537 237 2,233 1,535 239 2,233 1,534 240 2,238 1,536 241 2,238 1,536 242 2,233 1,533 668 1,322 686 1,373 684 1,368 686 1,374 687 1,377 689 1,381 690 1,382 692 1,379 694 1,382 695 1,382 698 1,382 699 1,384 702 1,387 702 1,378 700 1,376 30,197 519 31,488 565 31,305 560 31,442 563 31,573 567 31,693 571 31,789 574 31,888 578 32,035 584 32,135 588 32,228 575 32,404 580 32,524 584 32,559 589 32,619 567 1,596 1,137 5,735 823 1,906 1.669 1,618 1,139 6,239 855 2,254 2,002 1,621 1,135 6,158 848 2,209 1,960 1,625 1,135 6,219 854 2,250 1,997 1,625 1,135 6,274 858 2,281 2,026 1,620 1,139 6,314 860 2,296 2,040 1,617 1,139 6,358 861 2,321 2,061 1,612 1,140 6,392 861 2,337 2,077 1,605 1,140 6,457 869 2,373 2,107 1,612 1,138 6,487 870 2,386 2,118 1,614 1,148 6,513 868 2,408 2,138 1,614 1,160 6,555 870 2,427 2.152 1,616 1,158 6,570 871 2,399 2,138 1,609 1,157 6,539 865 2,372 2,102 1,613 1,144 6,568 865 2,377 2,103 893 950 938 945 949 958 967 974 984 991 994 1,006 1,017 1,025 1,036 925 349 412 971 334 471 961 333 453 968 333 461 971 333 470 979 334 481 984 334 491 989 335 505 995 337 519 1,000 338 529 1,006 340 545 1,010 342 566 1,014 344 577 1,016 342 598 1,016 341 623 1,258 1,344 1,343 1,355 1,361 1,365 1,354 1,364 1,371 1,375 1,380 1,398 1,434 1,453 1,457 9,055 9,074 9,096 9,121 9,141 9,168 9,197 9,211 9,221 Health services ........................ Offices and clinics of medical doctors...................... Nursing and personal care facilities ......................... Hospitals................................ Home health care services....... Legal services.......................... Educational services ................. Social services......................... Child day care services............ Residential care....................... Museums and botanical and zoological gardens................... Membership organizations.......... Engineering and management services................................ Engineering and architectural services................................ Management and public relations................................ 8,756 9,001 8,970 8,991 9,011 9,037 1,506 1,541 1,535 1,538 1,541 1,549 1,548 1,553 1,557 1,562 1,563 1,570 1,576 1,579 1,580 1,585 3,779 469 924 1,711 2,070 473 567 1,649 3,774 555 927 1,822 2,181 502 602 1,644 3,770 548 926 1,819 2,163 497 597 1,649 3,769 554 923 1,821 2,178 501 600 1,654 3,772 560 925 1,826 2,191 506 603 1,657 3,776 566 927 1,831 2,205 518 606 1,659 3,779 572 928 1,840 2,211 509 610 1,661 3,781 575 928 1,843 2,216 510 613 1,663 3,785 579 930 1,851 2,226 512 617 1,667 3,790 588 930 1,854 2,233 512 620 1,672 3,792 591 931 1,843 2,244 514 623 1,676 3,796 596 932 1,864 2,254 517 626 1,679 3,802 599 933 1,863 2,264 519 629 1,681 3,810 597 932 1,866 2,263 518 631 1,679 3,811 601 930 1,880 2,271 521 633 76 2,035 79 2,059 79 2,059 79 2,060 79 2,058 80 2,060 79 2,065 79 2,066 80 2,066 80 2,062 80 2,062 81 2,060 81 2,059 81 2,056 81 2,056 2,521 2,567 2,554 2,560 2,575 2,578 2,589 2,595 2,606 2,616 2,634 2,648 2,658 2,675 2,678 757 775 770 773 778 780 785 785 787 790 793 795 795 799 798 688 716 709 711 716 719 725 731 737 742 752 762 773 785 792 Government .................................... 18,841 2,915 2,128 4,488 1,834 19,118 2,870 2,053 4,562 1,875 19,093 2,873 2,062 4,548 1,867 19,103 2,866 2,051 4,553 1,868 19,110 2,864 2,045 4,572 1,882 19,183 2,861 2,041 4,594 1,900 19,207 2,863 2,039 4,589 1,891 19,195 2,858 2,031 4,589 1,888 19,275 2,854 2,022 4,596 1,892 19,219 2,853 2,014 4,598 1,891 19,222 2,838 2,004 4,599 1,889 19,241 2,831 1,997 4,610 1,901 19,248 2,828 1,992 4,613 1,904 19,247 2,808 1,969 4,607 1,906 19,225 2,802 1,961 4,602 1,911 2,654 11,438 6,353 2,687 11,685 6,490 2,681 11,672 6,465 2,685 11,684 6,480 2,690 11,674 6,497 2,694 11,728 6,548 2,698 11,755 6,554 2,701 11,748 6,544 2,704 11,825 6,549 2,707 11,768 6,557 2,710 11,785 6,577 2,709 11,800 6,591 2,709 11,807 6,599 2,701 11,832 6,617 2,691 11,821 6,619 5,085 5,195 5,207 5,204 5,177 5,180 5,201 5,204 5,276 5,211 5,208 5,209 5,208 5,215 5,202 Federal.................................... Federal, except Postal Service ... State ...................................... Education .............................. Other State government........................... Local...................................... Education .............................. Other local government........................... ' Includes other industries not shown separately. p = preliminary NOTE: See notes on the data for a description of the most recent benchmark revision. M onthly Labor Review Digitized for98 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 13. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls by industry, monthly data seasonally adjusted Industry Annual average 1993 1994 1994 May June July Aug. 1995 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr.» May» 34.5 34.7 34.7 34.7 34.7 34.6 34.7 34.9 34.6 34.7 34.8 34.6 34.6 34.6 34.3 40.9 41.4 41.4 41.4 41.4 41.4 41.4 41.4 41.4 41.5 41.6 41.4 41.3 40.7 40.7 M IN IN G ....................................................................... 44.3 44.7 44.6 44.9 45.4 44.6 44.9 44.8 44.9 44.7 44.9 44.9 44.6 44.6 44.3 M ANUFACTURING................................................. 41.4 4.1 42.0 4.7 42.0 4.6 42.0 4.7 42.0 4.7 42.0 4.7 42.1 4.8 42.1 4.7 42.1 4.8 42.1 4.8 42.2 4.9 42.1 4.8 42.0 4.7 41.5 4.5 41.5 4.3 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........................... 42.1 4.3 40.8 40.1 42.7 43.7 44.1 42.1 42.8 5.0 41.2 40.4 43.4 44.7 44.9 42.9 42.9 5.0 41.3 40.4 43.5 44.7 44.8 42.8 42.8 5.0 41.4 40.7 43.5 44.5 44.5 42.7 42.7 5.0 41.2 40.5 43.5 44.6 44.8 42.7 42.9 5.0 41.2 40.5 43.4 44.7 45.1 42.9 42.9 5.1 41.0 40.7 43.6 44.9 45.3 42.9 42.9 5.0 41.3 40.7 43.5 44.9 45.5 42.9 43.0 5.1 41.1 40.6 43.5 45.0 45.6 43.0 43.0 5.1 41.2 40.4 43.5 45.0 45.6 43.0 43.0 5.3 41.2 40.8 43.6 44.8 45.7 43.2 43.0 5.2 40.9 40.5 43.3 44.8 45.4 43.1 42.8 5.1 40.7 39.8 43.4 44.5 45.1 42.8 42.3 4.9 40.5 38.7 42.5 43.3 45.0 42.0 42.2 46 40.4 39 1 42.6 44.0 44.3 42.2 Industrial machinery and equipment.............. Electronic and other electrical equipment...... Transportation equipment............................ Motor vehicles and equipment ................... Instruments and related products................. Miscellaneous manufacturing ....................... 43.0 41.8 43.0 44.3 41.1 39.8 43.7 42.2 44.3 46.0 41.7 40.0 43.7 42.2 44.3 45.8 41.7 40.2 43.8 42.2 44.1 45.5 41.6 40.2 43.6 42.2 43.6 44.8 41.9 40.2 43.6 42.2 44.4 45.9 41.8 40.0 43.8 42.0 44.3 45.9 41.8 39.9 43.7 42.2 44.4 45.8 41.9 40.1 43.8 42.1 44.7 46.4 41.8 40.0 43.8 42.0 44.7 46.2 41.7 39.9 44.0 42.1 44.6 46.1 41.8 40.1 44.0 41.9 44.7 46.1 41.7 40.2 43.9 41.8 44.5 45.8 41.7 39.9 43.2 41.5 44.5 43.4 41.4 40.1 43 5 41.3 43.5 44 1 41 4 39.9 Nondurable goods .............................................. Overtime hours ..................................... Food and kindred products ......................... Textile mill products.................................... Apparel and other textile products ............... Paper and allied products........................... 40.6 4.0 40.7 41.4 37.2 43.6 40.9 4.3 41.3 41.6 37.5 43.9 40.9 4.2 41.0 41.7 37.7 43.9 41.0 4.3 41.2 41.8 37.7 44.0 41.1 4.3 41.6 41.7 37.6 44.2 40.9 4.2 41.3 41.6 37.6 44.1 41.0 4.3 41.4 41.6 37.6 43.9 41.0 4.3 41.3 41.8 37.7 44.0 41.0 4.3 41.5 41.5 37.6 43.9 41.1 4.3 41.5 41.6 37.7 44.0 41.0 4.4 41.5 41.8 37.5 44.0 41.0 4.3 41.3 41.9 37.7 43.9 40.9 4.2 41.3 41.8 37.6 43.7 40.4 4.0 40.7 41.0 36.9 43.1 40.5 40 41.1 40.4 37.0 43.1 Printing and publishing ................................ Chemicals and allied products..................... Rubber and miscellaneous plastics products ... Leather and leather products....................... 38.3 43.1 41.8 38.6 38.6 43.2 42.2 38.6 38.8 43.3 42.2 38.5 38.7 43.2 42.2 38.4 38.6 43.3 42.3 38.0 38.6 43.2 42.2 C8.6 38.6 43.2 42.3 38.6 38.7 43.4 42.3 39.0 38.6 43.4 42.3 38.7 38.7 43.2 42.3 38.6 38.5 43.3 42.3 38.0 38.5 43.4 42.3 38.4 38.4 43.4 42.0 38.4 38 3 43 4 41.1 38.1 38.4 42 9 41 8 38.7 SERVICE-PRODUCING............................................ 32.7 32.8 32.9 32.8 32.8 32.7 32 8 33.0 32.7 32.8 32.9 32.7 32.7 32.9 32.5 TRANSPORTATION AND PUBLIC UTILITIES 39.6 39.9 39.9 39.9 39.9 39.7 40.0 40.0 39.8 39.6 39.8 39.7 39.5 39.7 39.4 WHOLESALE TRADE 38.2 38.4 38.4 38.4 38.3 38.2 38.4 38.6 38.4 38.4 38.4 38.4 38.2 38.3 37.9 RETAIL T R A D E ...................................................... 28.8 28.9 28.9 29.0 29.0 28.9 28.9 29.2 28.9 28.9 29.0 28.8 28.8 29.1 28.7 PRIVATE SECTOR .................................. GOODS-PRODUCING ............. Overtime hours ..................................... Durable g o o d s ....................................................... » = preliminary NOTE: See “Notes on the data" for a description of the most recent benchmark adjustment. 14. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls by industry seasonally adjusted Industry An lual average 1993 PRIVATE SECTOR (in current dollars) ....... 1994 1994 May June July Aug. Sept. 1995 Oct. Nov. Dec. Jan. Feb. Mar. Apr.» May» $10.83 $11.13 $11.08 $11.09 $11.13 $11.14 $11.18 $11.25 $11.24 $11.27 $11.29 $11.32 $11.34 $11.40 $11.38 GOODS-PRODUCING ........................................... 12.37 12.71 12.65 12.68 12.72 12.74 12.78 12.81 12.83 12.83 12.84 12.89 12.91 12.94 Mining ....................................................... Construction.............................................. Manufacturing ........................................... Excluding overtime.................................... 14.60 14.38 11.74 11.18 14.89 14.72 12.06 11.42 14.81 14.65 12.00 11.38 14.78 14.84 14.70 14.76 12.03 12.06 11.40 11.42 14.85 14.74 12.09 11.44 14.95 14,82 12.12 11.47 15.04 14.90 12.14 11.49 15.04 14.84 12.17 11.52 15.08 14.81 12.18 11.53 15.08 14.74 12.21 11.56 15.12 14.88 12.24 11.60 15.15 14,90 12.25 11.61 15.15 15.21 14.95 15.01 12.28 12.27 11.72 11.65 SERVICE-PRODUCING......................................... 10.30 13.62 10.57 13.86 10.53 10.54 13.79 13.79 10.57 13.84 10.57 13.87 10.62 13.88 10.70 13.99 10.68 14.02 10.71 14.01 10.74 14.03 10.76 14.00 10.79 14.05 10.87 14.14 10.84 14.07 Wholesale trade......................................... 11.74 Retail trade ............................................... 7.29 Finance, insurance, and real estate.............. 11.35 Services.................................................... 10.78 12.05 7.49 11.83 11.05 12.01 7.47 11.80 11.01 12.03 7.48 11.77 11.02 12.06 7.50 11.82 11.06 12.05 7.51 11.81 11.06 12.08 7.53 11.90 11.11 12.22 12.15 12.20 7.56 7.56 7.60 12.05 11.99 12.01 11.20 11.17 11.21 12.23 7.59 12.06 11.26 12.24 7.60 12.09 11.28 12.27 7.61 12.16 11.30 12.41 7.63 12.28 11.39 12.31 7.68 12.20 11.36 7.39 7.41 7.41 7.39 7.39 7.37 7.38 7.39 7.39 7.38 7.40 Transportation and public utilities ................. PRIVATE SECTOR (in constant (1982) dollars) - uata not available. = Preliminary https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 7.42 7.40 7.40 12.94 - NOTE: See "Notes on the data” for a description of the most recent benchmark revision. M onthly Labor Review August 1995 99 Current Labor Statistics: Labor Force D ata 15. Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls by industry Annual average Industry 1993 1994 1995 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr.p Mayp PRIVATE S E C TO R ..................................................... $10.83 $11.13 $11.09 $11.03 $11.05 $11.05 $11.22 $11.28 $11.27 $11.28 $11.36 $11.36 $11.36 $11.41 $11.39 M IN IN G ......................................................................... 14.60 14.89 14.83 14.74 14.73 14.69 14.92 14.91 14.97 15.09 15.25 15.26 15.24 15.29 15.24 14.97 15.05 14.87 14.83 14.67 14.82 14.84 14.88 14.98 12.14 12.10 12.17 12.26 12.23 12.24 12.25 12.29 12.27 12.83 12.80 9.95 9.98 9.67 9.76 12.25 12.43 14.41 14.78 17.03 17.67 12.05 12.02 12.80 10.03 9.72 12.31 14.48 17.23 12.05 CO NSTRUCTIO N........................................................ 14.38 14.72 14.62 14.59 14.75 14.79 M ANUFACTURING..................................................... 11.74 12.06 12.01 12.03 12.04 12.01 Durable goods ........................................................... 12.33 12.67 12.62 12.63 12.62 12.62 12.76 12.70 12.77 12.87 12.81 12.83 9.84 9.80 9.84 9.87 9.87 9.95 9.96 9.93 9.97 9.95 9.94 Lumber and wood products............................ 9.61 Furniture and fixtures..................................... 9.27 9.55 9.45 9.48 9.54 9.56 9.69 9.70 9.67 9.76 9.67 9.66 Stone, clay, and glass products...................... 11.85 12.13 12.10 12.15 12.17 12.19 12.27 12.22 12.21 12.21 12.19 12.23 Primary metal industries ................................ 13.99 14.33 14.24 14.31 14.40 14.34 14.40 14.37 14.44 14.53 14.54 14.43 Blast furnaces and basic steel products........ 16.36 16.85 16.74 16.79 16.93 16.95 17.05 17.08 17.13 17.16 17.30 17.09 Fabricated metal products ............................. 11.69 11.93 11.89 11.90 11.86 11.87 11.99 11.92 12.03 12.09 12.04 12.03 13.04 11.57 16.71 17.27 12.55 9.71 10.98 11.25 11.19 11.21 11.28 Food and kindred products............................. 10.45 10.66 10.64 10.65 10.68 Tobacco products.......................................... 16.89 19.10 20.27 20.78 20.60 9.12 Textile mill products...................................... 8.88 9.13 9.06 9.11 Apparel and other textile products................... 7.09 7.34 7.28 7.33 7.31 13.68 13.8313.77 13.71 13.42 Paper and allied products.............................. 11.20 10.59 18.91 9.12 7.36 13.80 11.31 11.30 10.64 10.65 18.89 18.71 9.20 9.19 7.44 7.43 13.96 13.89 11.35 11.42 11.44 10.81 10.85 10.85 19.46 18.64 18.71 9.35 9.26 9.31 7.45 7.47 7.53 13.92 13.98 14.01 12.99 11.50 16.48 16.98 12.47 9.66 12.95 11.48 16.41 16.92 12.37 9.60 12.95 11.53 16.42 16.93 12.43 9.60 Nondurable goods .................................................... 13.11 11.54 16.62 17.11 12.55 9.79 13.15 11.59 16.60 17.12 12.54 9.98 12.92 11.52 16.44 16.92 12.48 9.63 12.73 11.24 15.80 16.10 12.23 9.39 13.03 11.51 16.52 16.98 12.54 9.72 13.19 11.59 16.83 17.37 12.63 9.90 12.94 11.56 16.41 16.89 12.46 9.61 Industrial machinery and equipment................ Electronic and other electrical equipment ........ Transportation equipment............................... Motor vehicles and equipment...................... Instruments and related products ................... Miscellaneous manufacturing.......................... 13.15 13.15 11.53 11.54 16.71 16.66 17.26 17.23 12.63 1,2.63 9.94 9.90 13.05 11.48 16.46 17.00 12.68 9.94 13.17 11.54 16.42 16.91 12.66 9.94 11.43 11.45 11.59 11.53 10.83 10.87 10.95 10.94 19.67 20.44 20.03 21.66 9.31 9.30 9.38 9.38 7.62 7.56 7.48 7.51 14.02 14.03 14.27 14.18 Printing and publishing................................... Chemicals and allied products........................ Petroleum and coal products.......................... Rubber and miscellaneous plastics products.... Leather and leather products ......................... 11.93 14.82 18.53 10.57 7.63 12.13 15.14 19.07 10.70 7.98 12.05 15.05 18.76 10.69 7.97 12.08 15.08 18.87 10.72 7.96 12.12 15.16 18.94 10.75 7.98 12.12 15.08 18.76 10.65 7.97 12.26 15.27 19.32 10.65 7.99 12.23 15.30 19.29 10.66 8.03 12.20 15.29 19.25 10.69 8.05 12.26 15.42 19.32 10.79 8.06 12.24 15.40 19.19 10.82 8.13 12.24 15.42 19.55 10.76 8.14 12.26 15.43 19.38 10.80 8.13 12.21 15.72 19.55 10.78 8.33 12.21 15.53 18.83 10.90 8.31 TRANSPORTATION AND PUBLIC U T ILITIE S .... 13.62 13.86 13.74 13.70 13.81 13.84 13.91 14.01 14.07 14.04 14.08 14.04 14.06 14.13 14.01 WHOLESALE T R A D E ............................................... 11.74 12.05 12.03 11.98 12.04 12.00 12.09 12.20 12.15 12.21 12.30 12.28 12.25 12.45 12.32 RETAIL TRADE .......................................................... 7.29 7.49 7.47 7.46 7.46 7.44 7.54 7.57 7.57 7.59 7.64 7.63 7.63 7.65 7.68 FINANCE, INSURANCE, AND REAL ES TA T E .... 11.35 11.83 11.84 11.67 11.72 11.73 11.85 12.02 11.98 12.05 12.17 12.19 12.21 12.32 12.25 SERVICES ................................................................... 10.78 11.05 11.01 10.90 10.90 10.90 11.11 11.20 11.22 11.29 11.39 11.38 11.36 11.40 11.36 p = preliminary NOTE: See “Notes on the data” for a description of the most recent benchmark revision. 100 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 16. Average weekly earnings of production or nonsupervisory workers on private nonfarm payrolls by industry Annual average 1994 Industry 1993 1994 May June July Aug. Sept. 1995 Oct. Nov. Dec. Jan. Feb. Mar. Apr.p Mayp PRIVATE SECTOR Current dollars............................................ $373.64 $386.21 $385.93 $383.84 $386.75 $386.75 $390.46 $394.80 $389.94 $392.54 $390.78 $388.51 $389.65 $391.36 $390.68 Seasonally adjusted.................................. 384.48 384.82 386.21 385.44 387.95 392.63 388.90 391.07 392.89 391.67 392.36 394.44 390.33 Constant (1982) dollars ............................... 254.87 256.96 258.15 255.72 256.98 255.79 257.56 260.25 256.54 258.42 256.25 253.93 253.84 253.96 M IN IN G ......................................................................... 646.78 665.58 659.94 661.83 661.38 661.05 677.37 673.93 679.64 680.56 683.20 677.54 670.56 675.82 675.13 CO NSTRUCTIO N........................................................ 553.63 572.61 580.41 579.22 587.05 588.64 598.80 595.98 572.50 573.92 553.06 546.86 565.40 560.98 576.73 MANUFACTURING Current dollars............................................. Constant (1982) dollars................................. 486.04 506.52 504.42 507.67 500.86 504.42 514.74 511.83 517.23 525.95 513.66 510.41 510.83 496.52 509.21 331.54 337.01 337.40 338.22 332.80 333.61 339.54 337.40 340.28 346.25 336.83 333.60 332.79 322.21 Lumber and wood products............................ Furniture and fixtures..................................... Stone, clay, and glass products...................... Primary metal industries ................................. Blast furnaces and basic steel products........ Fabricated metal products ............................. 519.09 392.09 371.73 506.00 611.36 721.48 492.15 542.28 405.41 385.82 526.44 640.55 756.57 511.80 541.40 407.68 377.06 533.61 637.95 749.95 508.89 543.09 409.34 385.84 537.03 639.66 752.19 510.51 532.56 404.67 383.51 533.05 639.36 766.93 498.12 538.87 410.59 389.09 536.36 636.70 764.45 508.04 549.96 412.93 399.23 542.33 648.00 780.89 517.97 547.37 414.34 399.64 540.12 642.34 772.02 514.94 552.94 409.12 396.47 533.58 652.69 779.42 523.31 563.71 414.75 406.02 528.69 662.57 787.64 531.96 549.55 404.97 392.60 515.64 652.85 787.15 518.92 546.56 397.60 383.50 512.44 643.58 769.05 513.68 546.56 401.98 381.00 520.63 639.80 761.24 512.13 524.80 401.20 367.95 525.79 637.02 795.15 484.41 541.44 408.22 375.19 531.79 638.57 763.29 508.51 Industrial machinery and equipment................ Electronic and other electrical equipment ........ Transportation equipment............................... Motor vehicles and equipment...................... Instruments and related products ................... Miscellaneous manufacturing.......................... 547.39 469.83 679.40 713.23 502.65 373.72 567.66 485.30 730.06 781.08 520.00 386.40 565.92 483.31 731.89 786.78 514.59 384.00 567.21 487.72 729.05 780.47 518.33 384.96 557.71 479.74 697.43 729.65 515.84 379.60 556.85 483.84 725.00 771.55 517.92 384.24 569.85 488.25 748.61 801.33 524.59 389.37 569.41 486.87 735.14 779.38 524.17 394.63 575.53 491.60 747.90 797.33 528.36 398.45 590.91 499.53 767.45 818.13 538.04 399.96 581.23 489.10 735.38 780.67 525.43 397.20 578.60 478.50 741.92 792.23 524.15 395.61 577.29 478.91 741.37 790.86 526.67 395.01 544.19 461.50 696.26 734.40 512.27 386.67 572.90 475.45 719.20 757.57 522.86 394.62 Nondurable g o o d s .................................................... 445.79 425.32 631.69 367.63 263.75 585.11 460.13 440.26 750.63 379.81 275.25 604.50 456.55 433.05 788.50 378.71 274.46 600.50 460.73 437.72 835.36 386.26 278.54 601.92 460.22 444.29 782.80 375.74 272.66 607.14 460.32 442.66 746.95 382.13 278.21 605.82 468.23 450.07 778.27 387.32 281.23 619.82 466.69 445.17 783.95 385.98 282.34 615.33 471.03 456.18 776.45 387.07 283.10 615.26 476.21 457.87 767.97 391.02 284.61 626.30 465.61 445.94 731.56 388.03 280.12 616.44 462.92 438.62 759.26 383.57 279.00 607.07 463.73 441.32 778.76 383.16 280.12 604.69 458.96 435.81 773.16 374.26 270.51 605.05 465.81 446.35 892.39 379.89 280.48 609.74 Durable goods ........................................................... Food and kindred products............................ Tobacco products......................................... Textile mill products...................................... Apparel and other textile products................... Paper and allied products .............................. Printing and publishing................................... Chemicals and allied products........................ Petroleum and coal products.......................... Rubber and miscellaneous plastics products......................................... Leather and leather products ......................... TRANSPORTATION AND PUBLIC U T IL IT IE S ................................................................... 456.92 468.22 462.72 463.87 464.20 469.04 479.37 475.75 477.02 481.82 466.34 466.34 470.78 461.54 463.98 638.74 654.05 650.16 651.46 653.40 646.93 658.14 664.02 668.17 678.48 666.82 666.14 668.12 680.68 666.24 819.03 846.71 821.69 830.28 829.57 816.06 894.52 869.98 854.70 853.94 840.52 868.02 841.09 858.25 798.39 441.83 451.54 452.19 455.60 447.20 448.37 450.50 450.92 455.39 463.97 456.60 451.92 451.44 433.36 455.62 294.52 308.03 306.85 309.64 302.44 307.64 310.81 314.78 313.95 314.34 307.31 309.32 309.75 309.04 321.60 539.35 553.01 549.60 549.37 556.54 556.37 557.79 563.20 559.99 555.98 554.75 551.77 549.75 558.14 553.40 WHOLESALE T R A D E ............................................... 448.47 462.72 464.36 461.23 462.34 459.60 464.26 472.14 466.56 470.09 469.86 467.87 465.50 476.84 469.39 RETAIL TRADE .......................................................... 209.95 216.46 215.88 218.58 222.31 220.97 218.66 220.29 217.26 222.39 215.45 214.40 215.93 221.09 220.42 FINANCE, INSURANCE, AND REAL ESTATE .................................................................... SERVICES ................................................................... 406.33 423.51 427.42 415.45 418.40 416.42 420.68 435.12 425.29 430.19 441.77 435.18 433.46 447.22 432.43 350.35 359.13 358.93 354.25 356.43 356.43 359.96 366.24 362.41 365.80 369.04 367.57 365.79 370.50 365.79 - Data not available. p = preliminary NOTE: See "Notes on the data” for a description of the most recent benchmark revision. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 101 Current Labor Statistics: 17. Labor Force D ata Diffusion indexes of employment change, seasonally adjusted (In percent) Jan. Time span and year Feb. Mar. Apr. June May July Sept. Aug. Nov. Oct. Dec. Private nonfarm payrolls, 356 industries Over 1-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 57.6 60.0 60.3 61.5 63.3 61.7 51.4 65.9 57.6 58.3 62.4 49.6 61.4 58.0 44.4 55.1 63.8 “ 57.7 60.5 ~ 56.3 61.5 “ 61.4 60.7 “ 59.7 61.1 ” 61.1 65.3 “ 60.7 61.1 ” Over 3-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 64.0 68.8 66.4 61.2 70.9 64.9 61.8 69.8 56.6 58.8 67.1 47.5 61.4 66.0 “ 61.8 66.0 ” 59.3 68.4 “ 61.8 68.3 62.6 67.8 “ 66.7 67.3 “ 65.7 68.1 “ 63.6 67.4 ” Over 6-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 63.2 71.2 65.0 63.8 70.2 58.0 62.8 70.5 ” 64.2 69.5 - 60.8 69.8 " 63.9 69.1 ” 64.5 70.5 ” 64.7 70.9 “ 66.2 69.0 67.3 69.0 " 70.8 67.4 ” 70.8 67.0 ” Over 12-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 64.9 68.4 - 63.9 70.8 - 64.0 71.9 “ 65.4 70.2 “ 67.0 69.5 “ 67.6 69.7 “ 67.6 70.4 ” 67.0 70.8 “ 70.2 70.4 ” 69.4 70.2 ” 68.8 65.9 ” 69.4 “ Manufacturing payrolls, 139 industries Over 1-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 52.2 59.4 56.8 57.9 61.2 54.7 52.9 59.4 49.6 44.2 56.5 42.4 51.4 55.0 37.4 46.0 59.0 50.7 54.0 “ 48.6 56.5 " 56.1 53.2 - 54.7 59.4 “ 56.5 59.0 “ 54.3 57.6 Over 3-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 60.8 65.1 61.5 60.4 66.5 56.1 57.2 64.4 45.3 46.4 59.0 35.6 46.4 58.6 “ 50.7 58.3 ” 49.6 61.5 “ 54.3 59.0 ” 53.2 61.5 “ 60.1 60.4 “ 56.1 64.0 ” 57.6 62.2 - Over 6-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 57.6 61.9 55.4 56.5 62.9 46.8 56.1 64.4 “ 55.0 61.5 “ 49.3 60.8 52.2 59.0 “ 55.4 62.2 ~ 57.9 62.6 ~ 56.8 61.5 57.6 64.0 ” 65.1 61.5 “ 62.9 61.5 ” Over 12-month span: 1993 ............................................................ 1994 ............................................................ 1995 ............................................................ 56.8 58.3 “ 57.9 59.7 ” 55.8 61.9 58.6 61.5 “ 57.2 61.5 “ 57.6 61.5 “ 58.6 61.9 ” 59.0 63.3 “ 61.2 61.5 60.4 59.0 ” 60.1 56.1 “ 59.4 - - 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 18. employment. Data for the 2 most recent months shown in each span are preliminary. See the “Definitions” in this section. See “Notes on the data” for a description of the most recent benchmark revision, Annual data: Employment status of the population (Numbers in thousands) Employment status 1986 Civilian noninstitutional population..................... 180,587 Civilian labor force......................................... 117,834 Labor force participation rate.......................................................... 65.3 1987 1988 1989 1990 1991 1992 1993 1994 182,753 119,865 184,613 121,669 186,393 123,869 188,049 124,787 189,765 125,303 191,576 126,982 193,550 128,040 196,814 131,056 65.6 65.9 66.5 66.4 66.0 66.3 66.2 66.6 Employed ................................................ Employment-population ratio ................... Agriculture......................................... Nonagricultural industries..................... 109,597 60.7 3,163 106,434 112,440 61.5 3,208 109,232 114,968 62.3 3,169 111,800 117,342 63.0 3,199 114,142 117,914 62.7 3,186 114,728 116,877 61.6 3,233 113,644 117,598 61.4 3,207 114,391 119,306 61.6 3,074 116,232 123,060 62.5 3,409 119,651 Unemployed ........................................... Unemployment rate............................... Not in labor force ......................................... 8,237 7.0 62,752 7,425 6.2 62,888 6,701 5.5 62,944 6,528 5.3 62,523 6,874 5.5 63,262 8,426 6.7 64,462 9,384 7.4 64,593 8,734 6.8 65,509 7,996 6.1 65,758 102 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 19. Annual data: Employment levels by industry (In thousands) Industry Total employment.............................. Private sector............................................................... Goods-producing........................................................ Mining....................................... Construction .......................................................... Manufacturing........................................................ Service-producing.......................................... Transportation and public utilities............................ Wholesale trade ............................ Retail trade ................................ Finance, insurance, and real estate........................ Services....................................... Government....................................... Federal......................................... State................................................ Local ............................................... 1986 1987 1988 1989 1990 1991 1992 1993 1994 99,344 101,958 105,210 107,895 109,419 108,256 108,604 110,730 114,034 82,651 84,948 87,824 90,117 91,115 89,854 89,959 91,889 94,917 24,533 24,674 25,125 25,254 24,905 23,745 23,231 23,352 23,913 777 717 713 692 709 689 635 610 600 4,810 4,958 5,098 5,171 5,120 4,650 4,492 4,668 5,010 18,947 18,999 19,314 19,391 19,076 18,406 18,104 18,075 18,303 74,811 5,247 5,761 17,880 6,273 22,957 77,284 5,362 5,848 18,422 6,533 24,110 80,086 5,514 6,030 19,023 6,630 25,504 82,642 5,625 6,187 19,475 6,668 26,907 84,514 5,793 6,173 19,601 6,709 27,934 84,511 5,762 6,081 19,284 6,646 28,336 85,373 5,721 5,997 19,356 6,602 29,052 87,378 5,829 5,981 19,773 6,757 30,197 90,121 6,006 6,140 20,437 6,933 31,488 16,693 2,899 3,893 9,901 17,010 2,943 3,967 10,100 17,386 2,971 4,076 10,339 17,779 2,988 4,182 10,609 18,304 3,085 4,305 10,914 18,402 2,966 4,355 11,081 18,645 2,969 4,408 11,267 18,841 2,915 4,488 11,438 19,118 2,870 4,562 11,685 NOTE: See “Notes on the data” for a description of the most recent benchmark revision. 20. Annual data: Average hours and earnings of production or nonsupervisory workers on nonfarm payrolls, by industry Industry 1986 1987 1988 1989 1990 1991 1992 1993 1994 34.8 8.76 304.85 34.8 8.98 312.50 34.7 9.28 322.02 34.6 9.66 334.24 34.5 10.01 345.35 34.3 10.32 353.98 34.4 10.57 363.61 34.5 10.83 373.64 34.7 11.13 386.21 42.2 12.46 525.81 42.4 12.54 531.70 42.3 12.80 541.44 43.0 13.26 570.18 44.1 13.68 603.29 44.4 14.19 630.04 43.9 14.54 638.31 44.3 14.60 646.78 44.7 14.89 665.58 37.4 12.48 466.75 37.8 12.71 480.44 37.9 13.08 495.73 37.9 13.54 513.17 38.2 13.77 526.01 38.1 14.00 533.40 38.0 14.15 537.70 38.5 14.38 553.63 38.9 14.72 572.61 40.7 9.73 396.01 41.0 9.91 406.31 41.1 10.19 418.81 41.0 10.48 429.68 40.8 10.83 441.86 40.7 11.18 455.03 41.0 11.46 469.86 41.4 11.74 486.04 42.0 12.06 506.52 39.2 11.70 458.64 39.2 12.03 471.58 38.8 12.26 475.69 38.9 12.60 490.14 38.9 12.97 504.53 38.7 13.22 511.61 38.9 13.45 523.21 39.6 13.62 539.35 39.9 13.86 553.01 38.3 9.34 357.72 38.1 9.59 365.38 38.1 9.98 380.24 38.0 10.39 394.82 38.1 10.79 411.10 38.1 11.15 424.82 38.2 11.39 435.10 38.2 11.74 448.47 38.4 12.05 462.72 29.2 6.03 176.08 29.2 6.12 178.70 29.1 6.31 183.62 28.9 6.53 188.72 28.8 6.75 194.40 28.6 6.94 198.48 28.8 7.12 205.06 28.8 7.29 209.95 28 9 7.49 216.46 36.4 8.36 304.30 36.3 8.73 316.90 35.9 9.06 325.25 35.8 9.53 341.17 35.8 9.97 356.93 35.7 10.39 370.92 35.8 10.82 387.36 35.8 11.35 406.33 35.8 11.83 423.51 32.5 8.18 265.85 32.5 8.49 275.93 32.6 8.88 289.49 32.6 9.38 305.79 32.5 9.83 319.48 32.4 10.23 331.45 32.5 10.54 342.55 32.5 10.78 350.35 32 5 11.05 359.13 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 M onthly Labor Review August 1995 103 Current Labor Statistics: 21. C o m pe nsatio n & Industrial Relations Employment Cost Index, compensation,1 by occupation and industry group (June 1989=100) Series Mar. June 1995 1994 1993 Sept. Dec. Mar. June Sept. Dec. Mar. Percent change 3 months ended 12 months ended Mar. 995 Civilian workers 2 .......................................................................... 117.5 118.3 119.5 120.2 121.3 122.1 123.3 123.8 124.8 0.8 2.9 Workers, by occupational group: White-collar workers................................................... Professional specialty and technical............................ Executive, administrative, and managerial.................... Administrative support, including clerical ..................... Blue-collar workers...................................................... Service occupations.................................................... 117.9 120.1 116.9 118.3 116.7 117.9 118.6 120.6 117.5 119.3 117.8 118.7 119.9 122.0 118.6 120.4 118.8 119.9 120.6 122.5 119.4 121.3 119.4 120.5 121.8 123.7 120.6 122.6 120.4 121.6 122.6 124.2 121.6 123.5 121.3 122.1 123.9 125.7 122.9 124.6 122.4 123.5 124.4 126.2 123.6 125.2 122.7 124.3 125.5 127.0 125.2 126.5 123.6 125.0 .9 .6 1.3 1.0 .7 .6 3.0 2.7 3.8 3.2 2.7 2.8 Workers, by industry division: Goods-producing.......................................................... Manufacturing............................................................ Service-producing........................................................ Services............................................................ ....... Health services....................................................... Hospitals.............................................................. Educational services................................................ Public administration 3................................................ Nonmanufacturing........................................................ 118.0 118.6 117.2 120.1 122.3 122.0 120.1 117.6 117.1 119.1 119.7 118.0 120.6 123.2 122.6 120.2 118.0 117.9 120.0 120.6 119.3 122.2 124.4 123.9 122.6 119.3 119.2 120.6 121.3 120.0 122.9 125.4 125.0 122.9 120.0 119.8 121.9 122.5 121.0 123.8 126.1 125.9 123.2 121.5 120.9 123.0 123.5 121.7 124.2 126.6 126.4 123.6 122.2 121.7 123.9 124.4 123.1 125.8 127.8 127.5 126.0 123.7 123.0 124.4 125.1 123.6 126.4 128.5 128.4 126.4 124.2 123.4 125.3 126.2 124.6 127.2 129.4 128.8 126.9 125.4 124.4 .7 .9 .8 .6 .7 .3 .4 1.0 .8 2.8 3.0 3.0 2.7 2.6 2.3 3.0 3.2 2.9 117.1 117.5 118.0 118.5 119.1 119.5 119.8 120.2 121.0 121.4 122.0 122.3 123.0 123.4 123.5 123.9 124.5 125.0 .8 .9 2.9 3.0 117.4 118.3 120.4 116.5 112.9 118.3 119.2 121.3 117.2 113.8 119.4 120.2 122.2 118.1 115.6 120.2 121.0 122.9 118.9 116.5 121.5 122.4 124.6 120.3 117.2 122.5 123.3 125.3 121.3 118.8 123.5 124.4 126.3 122.6 119.2 124.1 125.1 126.8 123.3 119.6 125.3 126.3 127.7 124.9 120.2 1.0 1.0 .7 1.3 .5 3.1 3.2 2.5 3.8 2.6 118.1 119.2 120.3 121.2 122.5 123.5 124.5 125.1 126.5 1.1 3.3 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 .... 116.6 116.6 117.8 113.9 116.8 117.7 117.6 119.0 115.2 117.6 118.7 118.7 120.0 115.9 118.4 119.3 118.9 120.8 117.0 119.1 120.3 120.2 121.3 118.5 120.2 121.2 121.2 122.2 119.1 121.4 122.3 122.5 122.9 120.3 122.7 122.6 122.5 123.4 120.6 122.9 123.5 123.4 124.2 121.8 124.1 .7 .7 .6 1.0 1.0 2.7 2.7 2.4 2.8 3.2 Service occupations.................................................. 117.2 118.0 118.9 119.5 120.6 121.0 121.8 122.9 123.4 .4 2.3 Production and nonsupervisory occupations4............... 116.9 117.9 119.0 119.7 120.7 121.6 122.6 123.1 124.1 .8 2.8 Workers, by industry division: Goods-producing....................................................... Excluding sales occupations................................. White-collar occupations........................................ Excluding sales occupations................................. Blue-collar occupations.......................................... Service occupations.............................................. Construction............................................................ Manufacturing........................................................... White-collar occupations....................................... Excluding sales occupations................................ Blue-collar occupations......................................... Service occupations............................................. Durables................................................................ Nondurables........................................................... 118.0 117.8 118.6 118.1 117.6 120.0 114.9 118.6 118.7 118.0 118.5 120.3 119.0 117.9 119.1 118.8 119.6 119.0 118.7 120.6 116.0 119.7 119.7 118.8 119.6 120.7 120.0 119.0 119.9 119.6 120.5 119.7 119.6 121.5 116.8 120.6 120.5 119.5 120.5 121.7 121.0 119.7 120.6 120.1 121.1 119.9 120.2 122.4 116.5 121.3 121.3 119.9 121.3 122.7 121.9 120.3 121.8 121.4 123.0 121.9 121.1 123.5 118.6 122.5 122.7 121.3 122.3 123.8 122.9 121.7 123.0 122.5 124.3 123.2 122.2 123.8 120.2 123.5 123.9 122.5 123.2 124.1 123.8 122.8 123.9 123.5 125.1 124.1 123.1 126.5 121.4 124.4 124.9 123.6 124.0 127.0 125.1 123.2 124.3 124.0 125.9 125.0 123.4 126.3 120.8 125.1 126.0 124.9 124.5 127.0 125.8 123.8 125.3 124.9 127.2 126.2 124.1 127.3 121.1 126.2 127.4 126.1 125.3 128.0 127.0 124.7 .8 .7 1.0 1.0 .6 .8 .2 .9 1.1 1.0 .6 .8 1.0 .7 2.9 2.9 3.4 3.5 2.5 3.1 2.1 3.0 3.8 4.0 2.5 3.4 3.3 2.5 116.4 117.3 116.9 118.4 114.3 116.8 114.8 112.8 117.4 116.5 118.6 114.7 115.4 115.3 116.0 114.5 115.9 114.1 117.3 118.3 117.8 119.3 115.5 117.7 116.0 114.1 118.3 117.5 119.4 115.9 116.2 116.4 116.8 115.6 117.2 114.7 118.5 119.3 119.0 120.4 116.6 118.6 116.8 114.8 119.2 118.5 120.2 116.4 117.0 116.6 117.6 116.2 117.1 115.5 119.3 120.2 119.8 121.4 117.2 119.1 117.5 115.7 119.9 119.2 120.8 117.1 118.0 117.8 118.7 116.8 118.3 116.3 120.4 121.4 121.0 122.7 118.4 120.2 119.2 117.1 121.7 121.0 122.7 117.6 118.6 117.9 119.3 117.5 119.6 115.3 121.2 122.1 121.9 123.4 119.1 120.7 119.8 117.7 122.6 122.1 123.2 119.4 119.8 119.7 120.3 119.2 120.6 118.0 122.3 123.3 122.9 124.6 120.6 121.3 121.4 119.7 123.6 122.9 124.4 120.5 120.9 120.6 121.3 120.4 120.3 118.7 122.8 123.8 123.4 125.1 120.7 122.5 122.1 120.3 124.4 124.0 124.8 120.6 120.9 121.5 122.0 120.1 120.0 119.3 123.9 125.0 124.6 126.4 122.1 123.0 124.0 122.3 126.1 126.3 125.9 121.7 122.4 123.2 124.4 120.9 120.8 120.1 .9 1.0 1.0 1.0 1.2 .4 1.6 1.7 1.4 1.9 .9 .9 1.2 1.4 2.0 .7 .7 .7 2.9 3.0 3.0 3.0 3.1 2.3 4.0 4.4 3.6 4.4 2.6 3.5 3.2 4.5 4.3 2.9 1.0 4.2 Private industry w o rk e rs .......................................................... Excluding sales occupations...................................... Workers, by occupational group: White-collar workers.................................................. Excluding sales occupations................................... Professional specialty and technical occupations........ Executive, administrative, and managerial occupations Sales occupations................................................... Administrative support occupations, including clerical................................................................. Service-producing ...................................................... Excluding sales occupations................................ White-collar occupations......................................... Excluding sales occupations.................................. Blue-collar occupations.......................................... Service occupations.............................................. Electric, gas, and sanitary services ........................ Excluding sales occupations................................. General merchandise stores................................ See footnotes at end of table. 104 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 21. Continued—Employment Cost Index, compensation,' by occupation and industry group (June 1989=100) 1993 1994 1995 Series Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. Percent change 3 months ended 12 months ended Mar. 1995 Finance, insurance, and real estate............................ Excluding sales occupations................................. Banking, savings and loan, and other credit agencies.................................................... Insurance.............................................................. Services.................................................................. Business services.................................................. Health services ...................................................... Hospitals ............................................................ Educational services .............................................. Colleges and universities...................................... 112.6 114.9 113.1 116.4 115.7 117.5 116.4 118.2 117.7 119.7 117.7 120.3 118.5 121.5 118.9 121.8 120.2 123.7 1.1 1.6 2.1 3.3 114.6 114.3 120.1 116.5 123.0 122.7 120.5 121.5 116.0 116.1 120.9 117.4 124.0 123.4 120.6 121.5 116.9 117.4 122.3 118.1 125.0 124.5 123.8 125.0 117.8 119.7 123.1 118.6 126.0 125.6 124.1 125.3 118.7 119.4 119.9 120.5 124.4 » 124.9 121.3 122.1 126.7 127.1 126.7 127.1 124.5 125.4 125.7 126.0 120.8 121.5 125.9 122.4 127.9 127.7 128.2 128.5 120.5 122.3 126.6 123.0 128.7 128.6 128.4 128.8 123.5 123.5 127.5 124.5 129.7 128.9 128.8 129.3 2.5 1.0 .7 1.2 .8 .2 .3 .4 4.0 3.0 2.5 2.6 2.4 1.7 3.5 2.9 Nonmanufacturing .................................................... White-collar occupations............. .......................... Excluding sales occupations................................ Blue-collar occupations......................................... Service occupations ............................................. 116.3 117.0 118.5 114.6 116.8 117.2 117.9 119.4 115.6 117.7 118.4 119.0 120.4 116.6 118.6 119.0 119.9 121.4 117.1 119.1 120.3 121.1 122.8 118.2 120.2 121.2 122.1 123.6 119.1 120.7 122.3 123.1 124.7 120.5 121.3 122.6 123.5 125.1 120.5 122.4 123.7 124.7 126.4 121.5 123.0 .9 1.0 1.0 .8 .5 2.8 3.0 2.9 2.8 2.3 State and local government workers .................................. 119.3 119.6 121.4 121.9 122.6 123.1 125.0 125.6 126.4 .6 3.1 Workers, by occupational group: White-collar workers.................................................. Professional specialty and technical......................... Executive, administrative, and managerial................. Administrative support, including clerical................... Blue-collar workers................................................... 119.5 119.6 119.0 119.2 118.3 119.6 119.7 119.2 119.6 118.7 121.5 121.7 121.0 121.0 120.5 121.9 122.0 121.6 121.6 121.4 122.6 122.5 122.8 122.7 122.3 122.9 122.7 123.4 123.3 122.7 124.9 125.0 124.7 124.9 124.2 125.5 125.5 125.3 125.6 124.7 126.2 126.0 126.9 126.3 125.4 .6 .4 1.3 .6 .6 2.9 2.9 3.3 2.9 2.5 Workers, by industry division: Services.................................................................. Services excluding schools5.................................... Health services.................................................... Hospitals........................................................... Educational services............................................. Schools............................................................ Elementary and secondary ............................... Colleges and universities.................................. Public administration3................................................ 120.0 119.6 120.2 120.0 120.0 120.2 120.7 118.4 117.6 120.2 120.0 120.7 120.4 120.1 120.3 120.8 118.5 118.0 122.2 121.4 122.2 122.0 122.3 122.5 123.0 120.8 119.3 122.6 121.9 123.1 123.3 122.7 122.9 123.6 120.7 120.0 123.1 122.8 124.2 123.7 122.9 123.2 123.7 121.5 121.5 123.4 123.3 125.2 124.5 123.1 123.4 123.8 122.0 122.2 125.6 124.9 127.2 127.0 125.5 125.9 126.3 124.5 123.7 126.1 125.6 127.7 127.7 126.0 126.3 126.5 125.5 124.2 126.7 126.4 128.4 128.4 126.5 126.8 127.1 126.0 125.4 .5 .6 .5 .5 .4 .4 .5 .4 1.0 2.9 2.9 3.4 3.8 2.9 2.9 2.7 3.7 3.2 1 Cost (cents per hour worked) measured in the Employment Cost Index consists of wages, salaries, and employer cost of employee benefits. 2 Consist of private industry workers (excluding farm and household workers) and State and local government (excluding Federal Government) workers. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 3 Consist of legislative, judicial, administrative, and regulatory activities. 4 This series has the same industry and occupational coverage as the Hourly Earnings Index, which was discontinued in January 1989. 5 Includes, for example, library, social, and health services. M onthly Labor Review August 1995 105 Current Labor Statistics: 22. C o m pe nsatio n & Industrial Relations Employment Cost Index, wages and salaries, by occupation and industry group (June 1989=100) Series Mar. June 1995 1994 1993 Sept. Dec. Mar. June Sept. Dec. Mar. Percent change 3 months ended 12 months ended Mar. 1995 Civilian workers 1 .......................................................................... 114.5 115.2 116.4 117.1 117.8 118.6 119.8 120.4 121.3 0.7 3.0 Workers, by occupational group: White-collar workers................................................... Professional specialty and technical..................... ...... Executive, administrative, and managerial................... Administrative support, including clerical ..................... Blue-collar workers...................................................... Service occupations.................................................... 115.4 117.5 115.0 115.3 112.7 114.5 116.0 118.0 115.5 116.1 113.4 115.2 117.4 119.5 116.5 117.1 114.4 116.1 118.1 120.0 117.3 118.0 115.0 116.6 118.8 120.7 118.1 118.9 115.8 117.5 119.7 121.3 119.0 119.8 116.7 118.1 120.8 122.8 120.2 120.9 117.8 119.4 121.5 123.5 120.8 121.6 118.2 120.4 122.4 124.2 122.2 122.8 119.2 121.2 .7 .6 1.2 1.0 .8 .7 3.0 2.9 3.5 3.3 2.9 3.1 Workers, by industry division: Goods-producing.......................................................... Manufacturing............................................................ Service-producing........................................................ Services.................................................................. Health services...................................................... Hospitals............................................................ Educational services .............................................. Public administration 2 .............................................. Nonmanufacturing....................................................... 113.8 114.7 114.8 117.4 119.5 118.9 117.9 114.4 114.4 114.6 115.5 115.5 117.8 120.3 119.5 118.0 114.9 115.1 115.4 116.3 116.8 119.5 121.4 120.7 120.4 115.9 116.4 116.2 117.3 117.5 120.0 122.2 121.7 120.7 116.6 117.0 117.0 118.0 118.2 120.9 122.8 122.4 121.0 117.9 117.7 118.0 119.0 118.9 121.3 123.4 123.0 121.3 118.5 118.5 119.0 120.0 120.2 122.8 124.4 124.0 123.8 119.9 119.7 119.6 120.8 120.7 123.5 125.4 124.9 124.3 120.6 120.2 120.5 121.9 121.7 124.4 126.1 125.5 125.0 121.9 121.1 .8 .9 .8 .7 .6 .5 .6 1.1 .7 3.0 3.3 3.0 2.9 2.7 2.5 3.3 3.4 2.9 113.9 114.2 114.6 115.0 115.7 115.9 116.4 116.6 117.2 117.5 118.1 118.3 119.1 119.4 119.7 120.0 120.6 121.0 .8 .8 2.9 3.0 114.7 115.7 117.1 115.5 116.4 117.9 116.7 117.4 118.9 117.5 118.2 119.5 118.3 119.0 120.4 119.3 119.9 121.3 120.2 121.0 122.2 120.8 121.7 123.0 121.7 122.8 123.7 .7 .9 .6 2.9 3.2 2.7 114.7 110.5 115.3 111.6 116.2 113.8 117.0 114.7 117.8 114.8 118.8 116.2 120.0 116.5 120.5 116.7 121.9 116.9 1.2 .2 3.5 1.8 115.2 116.1 117.1 118.0 119.0 119.9 120.9 121.6 122.9 1.1 3.3 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............................................................. 112.5 113.2 114.1 114.8 115.6 116.5 117.5 118.0 119.0 .8 2.9 112.4 113.2 110.0 113.2 113.8 111.2 114.2 114.7 111.7 114.7 115.6 112.6 115.5 116.2 113.5 116.5 117.2 114.0 117.8 118.0 115.2 117.9 118.8 115.6 118.8 119.6 117.0 .8 .7 1.2 2.9 2.9 3.1 113.6 114.3 114.9 115.7 116.6 117.3 117.9 118.9 120.1 1.0 3.0 Service occupations............................................... 113.5 114.1 114.9 115.3 116.3 116.8 117.6 118.8 119.4 .5 2.7 Production and nonsupervisory occupations3............. 113.4 114.2 115.3 115.9 116.6 117.5 118.5 119.1 119.9 .7 2.8 Workers, by industry division: Goods-producing..................................................... Excluding sales occupations................................ White-collar occupations........................................ Excluding sales occupations................................. Blue-collar occupations ......................................... Service occupations.............................................. 113.8 113.5 115.4 114.9 112.8 113.9 114.5 114.2 116.4 115.6 113.4 114.4 115.3 114.9 117.3 116.4 114.1 115.7 116.1 115.6 118.2 116.8 114.9 116.9 116.9 116.4 119.1 117.7 115.6 116.4 118.0 117.4 120.3 118.8 116.6 117.7 118.9 118.4 121.1 119.8 117.5 120.1 119.6 119.1 122.0 120.8 118.1 119.7 120.4 119.9 123.0 121.8 118.8 120.6 .7 .7 .8 .8 .6 .8 3.0 3.0 3.3 3.5 2.8 3.6 Construction .......................................................... 109.5 110.4 111.3 111.1 112.2 113.6 114.6 114.7 114.8 .1 2.3 121.9 123.9 122.4 120.4 121.5 121.9 121.9 .9 1.0 .8 .8 .7 .9 .9 3.3 3.7 3.7 3.0 4.0 3.5 3.0 Private industry w o rk e rs ....................................................... Excluding sales occupations.................................... Workers, by occupational group: White-collar workers............................................... Excluding sales occupations................................ Professional specialty and technical occupations..... Executive, administrative, and managerial occupations....................................................... Sales occupations................................................ Administrative support occupations, including clerical............................................................... Manufacturing........................................................ White-collar occupations..................................... Excluding sales occupations............................. Blue-collar occupations...................................... Service occupations........................................... Durables............................................................. Nondurables........................................................ 114.7 116.0 115.3 113.9 114.3 114.4 115.5 115.5 116.9 115.9 114.5 114.5 115.1 116.3 116.3 117.7 116.7 115.2 116.0 115.9 116.9 117.3 118.8 117.2 116.2 117.3 117.2 117.5 118.0 119.5 118.0 116.9 116.8 117.8 118.3 119.0 120.6 119.1 117.8 118.2 118.7 119.5 120.0 121.7 120.2 118.7 120.6 119.8 120.3 120.8 122.7 121.4 119.5 120.6 120.8 120.8 Service-producing.................................................... Excluding sales occupations................................ White-collar occupations........................................ Excluding sales occupations.............................. Blue-collar occupations.......................................... Service occupations.............................................. 113.9 114.8 114.5 116.0 111.9 113.5 114.7 115.6 115.2 116.8 112.9 114.1 115.9 116.6 116.5 117.8 114.1 114.9 116.6 117.4 117.3 118.7 114.6 115.2 117.3 118.3 118.0 119.6 115.5 116.3 118.2 119.0 118.9 120.4 116.2 116.7 119.2 120.2 119.9 121.5 117.5 117.3 119.7 120.7 120.4 122.1 117.6 118.7 120.7 121.8 121.3 123.2 119.2 119.3 .8 .9 .7 .9 1.4 .5 2.9 3.0 2.8 3.0 3.2 2.6 Transportation and public utilities........................... Transportation.................................................... Public utilities...................................................... Communications............................................... Electric, gas, and sanitary services..................... 112.9 110.8 115.4 114.7 116.3 114.0 112.0 116.4 115.6 117.4 114.7 112.6 117.2 116.5 118.2 115.4 113.4 117.9 117.1 118.8 116.4 114.2 119.1 118.4 119.9 117.2 114.8 120.1 119.5 120.9 118.9 116.7 121.4 121.0 121.9 119.6 117.5 122.3 122.1 122.4 121.2 119.0 123.9 124.3 123.4 1.3 1.3 1.3 1.8 .8 4.1 4.2 4.0 5.0 2.9 See footnotes at end of table. 106 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 22. Continued— Employment Cost Index, wages and salaries, by occupation and industry group (June 1989=100) 1993 1994 1995 Percent change 3 months ended Series Mar. June Sept. Dec. Mar. June Sept. Mar. Dec. 12 months ended Mar. 1995 Wholesale and retail trade..................................... Excluding sales occupations............................. Wholesale trade ................................................ Excluding sales occupations............................ Retail trade....................................................... Food stores.................................................... Général merchandise stores............................. 113.0 113.6 113.9 114.7 112.6 114.6 112.4 114.2 114.4 115.1 115.5 113.8 115.4 113.4 114.7 115.2 115.1 116.3 114.5 114.9 114.5 115.4 116.1 116.4 117.5 115.0 115.9 115.0 115.5 116.5 116.2 117.8 115.2 117.0 114.0 117.4 117.8 118.3 118.8 117.0 117.8 116.4 118.3 118.7 118.9 119.6 118.0 117.4 116.5 118.4 118.8 119.9 120.2 117.8 117.3 117.5 119.4 120.2 120.9 122.2 118.7 117.8 117.9 0.8 1.2 .8 1.7 .8 .4 .3 3.4 3.2 4.0 3.7 3.0 .7 3.4 Finance, insurance, and real estate....................... Excluding sales occupations ............................ Banking, savings and loan, and other credit agencies................................................ Insurance.......................................................... 109.3 112.0 109.3 113.1 112.3 114.0 112.9 114.6 113.7 115.5 113.2 116.0 113.8 117.2 114.2 117.4 115.0 119.3 .7 1.6 1.1 3.3 112.1 111.2 112.9 112.9 113.7 113.9 114.5 116.6 114.7 116.0 115.0 116.8 116.5 117.7 116.2 118.6 119.2 119.8 2.6 1.0 3.9 3.3 Services.............................................................. Business services............................................... Health services................................................... Hospitals ......................................................... Educational services ........................................... Colleges and universities................................... 117.0 114.2 119.8 119.3 117.5 118.0 117.6 114.6 120.7 119.9 117.4 117.7 118.9 115.3 121.7 121.0 120.7 121.3 119.6 115.7 122.6 122.0 120.9 121.6 120.8 118.8 123.1 122.8 121.2 122.0 121.3 119.4 123.5 123.3 122.2 122.2 122.2 119.9 124.3 123.9 124.9 124.5 123.0 120.4 125.4 124.8 125.1 124.9 123.9 122.1 126.2 125.4 125.6 125.5 .7 1.4 .6 .5 .4 .5 2.6 2.8 2.5 2.1 3.6 2.9 Nonmanufacturing.................................................. White-collar occupations....................................... Excluding sales occupations................................ Blue-collar occupations......................................... Service occupations ............................................. 113.4 114.4 115.8 111.1 113.4 114.2 115.2 116.6 111.9 114.1 115.4 116.4 117.6 113.0 114.8 116.0 117.2 118.5 113.4 115.1 116.8 117.9 119.4 114.2 116.3 117.7 118.9 120.2 115.1 116.7 118.7 119.7 121.3 116.4 117.3 119.1 120.2 121.8 116.4 118.6 120.0 121.1 122.9 117.5 119.2 .8 .7 .9 .9 .5 2.7 2.7 2.9 2.9 2.5 State and local government workers......................... 117.2 117.4 119.3 119.7 120.4 120.7 122.8 123.4 124.3 .7 3.2 Workers, by occupational group: White-collar workers............................................... Professional specialty and technical....................... Executive, administrative, and managerial............... Administrative support, including clerical................. Blue-collar workers................................................. 117.5 118.1 116.5 115.4 116.2 117.6 118.2 116.6 115.9 116.5 119.6 120.4 118.2 117.2 118.4 119.9 120.7 118.8 117.8 119.0 120.6 121.1 119.8 118.9 119.7 120.9 121.3 120.3 119.4 120.1 122.9 123.6 121.6 120.9 121.8 123.6 124.2 122.4 121.7 122.5 124.4 124.8 124.1 122.5 123.1 .6 .5 1.4 .7 .5 3.2 3.1 3.6 3.0 2.8 Workers, by industry division: Services ............................................................... Services excluding schools4.................................. Health services.................................................. Hospitals........................................................ Educational services............................................. Schools............................................................ Elementary and secondary ............................... Colleges and universities.................................. Public administration 2............................................. 118.1 118.4 118.1 117.6 118.0 117.9 118.7 115.5 114.4 118.2 118.7 118.8 118.2 118.1 118.0 118.8 115.6 114.9 120.3 120.1 120.4 119.9 120.3 120.3 121.1 117.8 115.9 120.6 120.4 121.0 120.7 120.6 120.7 121.6 117.7 116.6 121.1 121.3 121.9 121.2 120.9 121.0 121.7 118.6 117.9 121.3 121.9 122.9 122.0 121.1 121.2 121.8 119.2 118.5 123.6 123.2 124.7 124.2 123.6 123.8 124.5 121.5 119.9 124.2 124.0 125.3 125.1 124.2 124.3 124.9 122.5 120.6 124.9 125.0 126.0 125.8 124.8 125.0 125.5 123.2 121.9 .6 .8 .6 .6 .5 .6 .5 .6 1.1 3.1 3.1 3.4 3.8 3.2 3.3 3.1 3.9 3.4 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. 23. 3 This series has the same industry and occupational coverage as the Hourly Earnings Index, which was discontinued in January 1989. 4 Includes, for example, library, social and health services. Employment Cost Index, benefits, private industry workers by occupation and industry group (June 1989 = 100) 1993 1994 1995 Percent change 3 months ended Series Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. 12 months ended Mar. 1995 Private industry workers ............................................... 125.2 126.7 127.7 128.3 130.7 131.7 132.8 133.0 134.5 1.1 2.9 Workers, by occupational group: White-collar workers ................................................... Blue-collar workers...................................................... 124.7 125.5 125.9 127.3 126.8 128.4 127.6 128.9 130.5 130.5 131.6 131.5 132.8 132.7 133.3 132.5 135.2 133.3 1.4 .6 3.6 2.1 Workers, by industry group: Goods-producing........................................................ Service-producing....................................................... Manufacturing ............................................................ Nonmanufacturing...................................................... 127.3 123.4 126.8 124.2 129.0 124.6 128.6 125.5 130.0 125.7 129.7 126.5 130.3 126.7 130.0 127.4 132.7 128.9 132.0 129.9 133.9 129.7 133.0 130.8 134.8 131.2 133.9 132.2 134.8 131.5 134.3 132.3 135.9 133.2 135.4 133.9 .8 1.3 .8 1.2 2.4 3.3 2.6 3.1 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 107 Current Labor Statistics: 24. C o m pe nsatio n & Industrial Relations Employment Cost Index, private nonfarm workers, by bargaining status, region, and area size (June 1989=100) 1993 1994 1995 Series Mar. June Sept. Dec. Mar. June Sept. Dec. Mar. Percent change 3 months ended 12 months ended Mar. 1995 COMPENSATION Workers, by bargaining status’ Union .......................................................................... Goods-producing........................................................ Service-producing....................................................... Manufacturing ............................................................ Nonmanufacturing ...................................................... 117.8 118.7 116.7 119.8 116.3 119.1 120.0 117.7 121.1 117.4 120.0 121.0 118.6 121.9 118.5 120.9 121.9 119.6 123.0 119.3 121.9 122.5 121.0 123.6 120.5 123.0 123.8 121.8 124.8 121.5 123.8 124.4 122.9 125.3 122.6 124.2 124.7 123.6 125.8 123.0 125.1 125.2 124.8 126.3 124.0 0.7 .4 1.0 .4 .8 2.6 2.2 3.1 2.2 2.9 Nonunion..................................................................... Goods-producing........................................................ Service-producing....................................................... Manufacturing............................................................ Nonmanufacturing....................................................... 116.8 117.7 116.3 118.1 116.3 117.7 118.6 117.2 119.0 117.2 118.8 119.4 118.4 120.0 118.3 119.5 119.9 119.2 120.6 119.0 120.7 121.5 120.3 122.0 120.2 121.7 122.6 121.1 122.9 121.1 122.7 123.6 122.2 124.0 122.2 123.2 124.1 122.7 124.8 122.5 124.3 125.2 123.8 126.1 123.6 .9 .9 .9 1.0 .9 3.0 3.0 2.9 3.4 2.8 117.8 116.2 117.9 116.2 119.1 117.0 119.3 116.4 120.2 118.1 120.1 117.8 120.7 118.8 121.2 118.1 121.6 120.0 122.8 119.4 122.8 120.8 123.6 120.5 124.0 121.8 124.6 121.3 124.3 122.5 125.0 121.7 125.6 123.7 125.8 122.6 1.0 1.0 .6 .7 3.3 3.1 2.4 2.7 117.1 117.0 118.1 117.8 119.1 118.7 119.8 119.7 120.9 121.3 121.9 122.5 122.9 123.2 123.4 123.5 124.5 124.8 .9 1.1 3.0 2.9 Union .......................................................................... Goods-producing........................................................ Service-producing....................................................... Manufacturing ............................................................ Nonmanufacturing ...................................................... 113.1 112.2 114.2 113.2 113.0 113.9 113.0 115.1 113.9 113.9 114.8 113.8 116.0 114.6 114.9 115.7 114.8 116.8 115.9 115.5 116.5 115.4 118.0 116.6 116.4 117.6 116.7 118.7 117.8 117.3 118.6 117.5 120.1 118.5 118.6 119.1 117.9 120.6 119.2 119.0 119.8 118.4 121.6 119.8 119.8 .6 .4 .8 .5 .7 2.8 2.6 3.1 2.7 2.9 Nonunion..................................................................... Goods-producing........................................................ Service-producing....................................................... Manufacturing ............................................................ Nonmanufacturing....................................................... 114.1 114.4 113.8 115.4 113.5 114.8 115.2 114.6 116.1 114.3 115.9 116.0 115.9 117.0 115.5 116.6 116.7 116.6 117.9 116.1 117.4 117.6 117.2 118.6 116.9 118.3 118.6 118.1 119.5 117.8 119.2 119.5 119.0 120.5 118.7 119.8 120.3 119.5 121.5 119.1 120.8 121.3 120.5 122.7 120.0 .8 .8 .8 1.0 .8 2.9 3.1 2.8 3.5 2.7 114.6 113.6 113.5 113.6 115.7 114.3 114.6 113.7 116.8 115.3 115.2 115.3 117.3 116.0 116.5 115.7 117.8 116.6 117.5 116.6 118.8 117.4 118.3 117.9 120.0 118.5 119.5 118.1 120.2 119.1 120.1 119.0 121.3 120.0 120.9 119.9 .9 .8 .7 .8 3.0 2.9 2.9 2.8 113.9 113.5 114.7 114.4 115.8 115.0 116.5 115.8 117.2 117.0 118.1 118.1 119.1 118.6 119.7 119.0 120.6 120.5 .8 1.3 2.9 3.0 Workers, by region 1 Northeast..................................................................... South .......................................................................... Midwest (formerly North Central)..................................... West............................................................................ Workers, by area size ’ Metropolitan areas........................................................ Other areas.................................................................. WAGES AND SALARIES Workers, by bargaining status * Workers, by region ' Northeast..................................................................... South .......................................................................... Midwest (formerly North Central)..................................... West............................................................................ Workers, by area size’ Metropolitan areas........................................................ Other areas.................................................................. 1 The indexes are calculated differently from those for the occupation and industry groups. For a detailed description of the index calculation, see the 108 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 M onthly Lab or R eview Technical Note, "Estimation procedures for the Employment Cost Index,” May 1982. 25. Percent of full-time employees participating In employer-provided benefit plans, 1980-91 Small private establish ments2 Medium and large private establishments' Item 1983 1984 1985 1986 1988 1989 9 25 76 25 99 10.0 24 3.8 99 67 11 25 74 25 99 9.8 25 3.7 100 67 9 26 73 26 99 9.8 23 3.6 99 67 10 27 72 26 88 3.2 98 10.1 26 3.7 99 67 10 27 72 26 88 3.2 99 10.0 25 3.7 100 70 11 29 72 26 85 3.2 96 9.4 24 3.3 9e 69 10 26 71 26 84 3.3 97 9.2 22 3.1 97 68 8 30 67 26 80 3.3 92 10.2 21 3.3 96 67 8 37 48 27 47 2.9 84 9.5 11 2.8 88 47 4 17 34 4 58 29 56 3.7 81 10.9 38 2.7 72 97 11 36 56 29 63 3.7 74 13.6 39 2.9 67 95 - - - - - _ 33 16 37 18 37 26 17 8 57 30 51 33 97 97 97 96 97 96 95 90 92 83 69 93 93 58 98 - 60 99 - 62 99 50 37 37 58 99 53 43 46 62 99 61 52 56 67 99 68 61 66 70 99 70 66 76 79 98 80 74 75 80 97 97 96 81 80 98 97 96 79 83 98 97 94 76 78 98 87 86 82 79 99 99 98 26 46 - 27 49 - 44 36 43 47 51 27 33 36 - $10.13 $11.93 $12.05 $12.80 $19.29 $25.31 $26.60 54 58 56 63 64 66 69 51 - $32.51 $35.93 $38.33 $41.40 $60.07 $72.10 $96.97 42 $25.13 67 $109.34 96 96 96 96 96 96 96 92 94 94 64 85 88 69 - 72 64 72 64 72 66 74 64 73 13 62 72 10 59 76 8 49 71 7 42 71 6 44 78 1 19 67 1 55 67 1 45 40 1980 1981 1982 1991 1990 State and local governments3 1987 1990 Tlme-off plans Participants with: Paid lunch time ......................................... 10 10 Average minutes per day.......................... 75 75 Paid rest time........................................... Average minutes per day......................... Paid funeral leave..................................... Average days per occurrence................... 99 99 Paid holidays ............................................ Average days per year............................. 10.1 10.2 20 23 Paid personal leave................................... Average days per year............................. Paid vacations.......................................... 100 99 62 65 Paid sick leave......................................... Unpaid maternity leave .............................. Unpaid paternity leave ............................... - Insurance plans Participants in medical care plans.................. Participants with coverage for: Home health care................................... Extended care facilities............................ Mental health care.................................. Alcohol abuse treatment.......................... Drug abuse treatment .............................. Participants with employee contribution required for: Self coverage ......................................... Average monthly contribution ................. Family coverage...................................... Average monthly contribution5................ Participants in life insurance plans.................. Participants with: Accidental death and dismemberment insurance.......................................... Survivor income benefits .......................... Retiree protection available...................... Participants in long-term disability insurance plans..................................................... Participants in sickness and accident insurance plans..................................................... 35 38 $15.74 $25.53 71 65 $71.89 $117.59 41 43 45 47 48 48 42 45 40 19 31 27 54 50 51 49 51 52 49 46 43 45 26 14 21 Retirement plans Participants in defined benefit pension plans’ .... Participants with: Normal retirement prior to age 65.............. Early retirement available......................... Ad hoc pension increase in last 5 years..... Terminal earnings formula........................ Benefit coordinated with Social Security..... Participants in defined contribution plans......... Participants in plans with tax-deferred savings arrangements ......................................... 84 84 84 82 82 80 76 63 63 59 20 93 90 55 98 53 45 - 56 98 50 43 - 58 97 52 45 - 64 97 51 54 55 - 63 97 47 54 56 - 67 97 41 57 61 7 53 64 98 35 57 62 760 59 98 26 55 62 45 62 97 22 64 63 48 55 98 7 56 54 48 54 95 7 58 49 31 92 90 33 100 18 9 89 88 16 100 8 9 - - - - 26 33 36 41 44 17 28 45 Other benefits Employees eligible for: Flexible benefits plans ............................... Reimbursement accounts........................... - “ - - - 2 5 5 12 9 23 10 36 1 8 5 5 5 31 " ' From 1979 to 1986, data were collected in private sector establishments with a minimum employment varying from 50 to 250 employees, depending upon industry. In addition, coverage in service industries was limited. Begin ning in 1988, data were collected in all private sector establishments employing 100 workers or more in all industries. 2 Includes private sector establishments with fewer than 100 workers. 3 In 1987, coverage excluded local governments employing fewer than 50 workers. In 1990, coverage included all State and local governments. 4 Data exclude college teachers. 5 Data for 1983 refer to the average monthly employee contribution for dependent coverage, excluding the employee. Beginning in 1984, data refer https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis to the average monthly employee contribution for family coverage, which includes the employee. • Prior to 1985, data on participation in defined benefit pension plans included a small percentage of workers participating in money purchase pension plans. Beginning in 1985, these workers were classified as participating in defined contribution plans. 7 Includes employees who participated in Payroll-based Employee Stock Ownership Plans. Beginning in 1987, these plans were no longer available. NOTE: Dash indicates data were not collected in this year. M onthly Labor Review August 1995 109 Current Labor Statistics: C o m pe nsatio n & Industrial Relations 26. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all agreements, private industry collective bargaining agreements covering 1,000 workers or more (in percent) Annual average Quarterly average Measure 1993 1992 1994 1995 1993 II III IV I II III IV lp Rate changes under settlements: Specified total compensation changes, settlements covering 5,000 workers or more: First year of contract.................................... Annual average over life of contract............ 3.0 3.1 3.0 2.4 3.2 2.6 1.0 1.4 3.8 2.5 3.0 2.6 3.4 2.9 0.0 1.4 1.5 2.1 1.4 1.6 Specified wage changes, settlements covering 1,000 workers or more: First year of contract................................ Annual average over life of contract.............. 2.7 3.0 2.3 2.1 2.5 2.5 1.1 1.7 2.8 2.0 3.0 2.4 2.0 2.4 1.0 1.9 2.2 2.5 1.9 1.9 3.1 3.0 .9 .8 .7 .4 .8 .9 .6 .3 .8 1.9 .4 .9 1.9 .2 .2 .7 .1 .1 .6 (2> .5 .2 (2) .1 .3 i2) .2 .6 .1 .1 .7 .1 .2 .3 .1 .0 .2 .0 Wage rate changes under all agreements: Average wage change 1.................................. Source: Current settlements................................... Prior settlements...................................... COLA provisions..................................... 1 Because of rounding, total may not equal sum of parts. 2 More than zero but less than 0.05 percent. M onthly Labor Review Digitized for110 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 » = preliminary. 27. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all agreements, private industry collective bargaining agreements covering 1,000 workers or more during 4-quarter periods (in percent) Average for four quarters endingMeasure II 1995 1994 1993 IV III I» IV III II I Rata changes under settlements: Specified total compensation changes, settlements covering 5,000 workers or more, all industries: First year of contract................................................................. Annual average over life of contract ........................................... 2.9 2.9 2.1 2.4 3.0 2.4 3.0 2.3 3.1 2.4 3.1 2.5 2.3 2.4 2.1 2.3 Specified wage changes, settlements covering 1,000 workers or more: All industries: First year of contract.............................................................. Contracts with COLA clauses ................................................ Contracts without COLA clauses............................................ Contracts with either lump sums, COLA, or both...................... Contracts with neither lump sums nor COLA........................... Annual average over life of contract......................................... Contracts with COLA clauses ................................................ Contracts without COLA clauses............................................ Contracts with either lump sums, COLA, or both...................... Contracts with neither lump sums nor COLA........................... 2.5 2.7 2.5 2.6 2.5 2.7 2.5 2.8 2.7 2.8 2.0 2.5 1.8 2.3 1.7 2.3 2.1 2.4 2.1 2.5 2.3 2.8 2.1 2.6 2.0 2.1 1.4 2.5 1.9 2.5 2.4 2.7 2.3 2.6 2.1 2.1 1.0 2.5 1.8 2.5 2.2 3.0 1.9 2.8 1.5 2.1 1.5 2.4 2.0 2.2 2.3 2.9 2.0 2.7 1.6 2.2 1.7 2.3 2.1 2.2 2.0 2.7 1.8 2.5 1.6 2.3 2.5 2.3 2.3 2.3 1.8 2.5 1.6 2.3 1.5 2.3 2.4 2.2 2.2 2.3 Manufacturing: First year of contract.............................................................. Contracts with COLA clauses ................................................ Contracts without COLA clauses........................................... Contracts with either lump sums, COLA, or both...................... Contracts with neither lump sums nor COLA........................... Annual average over life of contract......................................... Contracts with COLA clauses ................................................ Contracts without COLA clauses............................................ Contracts with either lump sums, COLA, or both...................... Contracts with neither lump sums nor COLA........................... 2.0 2.4 3.0 2.3 3.3 2.6 2.3 2.8 2.2 3.0 2.5 2.6 2.5 2.3 3.1 2.1 1.9 2.5 1.8 2.9 2.7 2.9 2.3 2.7 2.9 1.5 1.3 2.1 1.3 2.5 2.5 2.7 1.9 2.4 2.6 1.3 1.0 1.9 1.0 2.3 2.7 3.0 1.9 2.7 2.6 1.5 1.3 2.0 1.4 2.3 2.6 3.0 1.9 2.7 2.2 1.7 1.5 1.9 1.5 2.0 2.4 3.0 1.8 2.4 2.2 2.3 2.5 2.1 2.3 2.2 2.2 2.6 1.8 2.2 2.2 2.1 2.3 1.9 2.1 2.2 Nonmanufacturing: First year of contract.............................................................. Contracts with COLA clauses ................................................ Contracts without COLA clauses........................................... Contracts with either lump sums, COLA, or both...................... Contracts with neither lump sums nor COLA........................... Annual average over life of contract......................................... Contracts with COLA clauses ................................................ Contracts without COLA clauses........................................... Contracts with either lump sums. COLA, or both...................... Contracts with neither lump sums nor COLA........................... 2.5 3.0 2.4 2.7 2.4 2.8 2.7 2.8 2.9 2.7 1.7 2.5 1.6 2.3 1.5 2.4 2.7 2.4 2.5 2.4 2.1 1.8 2.1 2.4 1.8 2.5 2.3 2.6 2.6 2.5 2.3 1.9 2.3 2.0 2.0 2.6 2.5 2.6 2.7 2.5 2.0 2.9 1.9 2.9 1.3 2.4 2.7 2.4 2.7 2.2 2.0 2.5 2.0 2.8 1.4 2.5 2.7 2.5 2.7 2.3 1.8 2.2 1.8 2.6 1.6 2.3 Construction: First year of contract.............................................................. Annual average over life of contract......................................... 1.8 2.4 2.0 2.4 2.1 2.6 2.4 2.7 1.7 2.5 1.8 2.9 2.6 3.0 2.9 .7 1.8 .4 .6 1.8 .3 .9 1.9 .2 .9 1.8 .2 Wage rate changes under all agreements: Average wage change' ............................................................... Source: Current settlements.................................................................. Prior settlements...................................................................... COLA provisions...................................................................... 2.3 1.6 2.2 1.5 2.4 1.4 2.3 2.6 2.3 2 .4 2 .4 2.3 2.3 2 .6 1.8 2.5 1.5 2.4 2.7 2.9 2.7 2.6 .9 1.7 .2 .8 1.9 .2 .6 1.9 .2 .5 1.9 .3 2 .6 1 Because of rounding, total may not equal sum of parts. p = preliminary. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 111 Current Labor Statistics: Compensation & Industrial Relations 28. Specified changes in the cost of compensation and components annualized over the life of the contract in private industry collective bargaining settlements covering 5,000 workers or more, by quarter, and during 4-quarter periods (in percent) 1993 Measure II III 1994 IV I II 1995 III IV I 0.8 .9 .9 .5 1.2 1.5 1.5 .6 1.1 1.2 1.1 .9 Quarterly average All industries: Compensation......................................... Cash payments..................................... Wages.................................................. Benefits...................................... 1.8 1.7 1.7 1.8 0.9 .8 .7 1.1 1.8 1.4 1.4 2.4 2.0 1.9 1.7 2.1 1.9 1.4 1.4 2.7 Average for four quarters All industries: Compensation................................. Cash payments................................ Wages............................................. Benefits................................................. With contingent pay provisions: Compensation............................................ Cash payments..................................................... Wages........................................................................... Benefits.................................................... Without contingent pay provisions: Compensation......................................................................... Cash payments...................................................................... Wages..................................................... Benefits................................................. 1.9 1.7 1.8 2.3 1.4 1.2 1.3 1.7 1.6 1.3 1.3 2.1 1.6 1.3 1.3 2.0 1.6 1.3 1.3 2.2 1.7 1.4 1.4 2.2 1.6 1.4 1.3 1.8 1.4 1.3 1,3 1.6 2.0 1.7 1.9 2.5 1.4 1.2 1.4 1.8 1.5 1.2 1.4 2.0 1.4 1.2 1.3 1.8 1.7 1.3 1.4 2.3 1.9 1.4 1.6 2.5 2.2 1.8 1.7 3.0 2.1 1.7 1.6 2.8 1.9 1.7 1.7 2.3 1.4 1.3 1.2 1.6 1.7 1.4 1.3 2.1 1.8 1.6 1.4 2.2 1.6 1.3 1.1 2.1 1.5 1.3 1.1 1.8 1.3 1.3 1.2 1.3 1.1 1.1 1.1 1.1 Manufacturing: Compensation..................................................................... Cash payments....................................................................... Wages................................................................................. Benefits................................................................. 1.8 1.3 1.7 2.7 1.1 1.0 1.2 1.4 1.2 .8 1.1 1.6 1.1 .7 .9 1.5 1.3 .9 1.1 1.9 1.5 1.0 1.2 2.1 1.9 1.7 1.6 2.3 1.7 1.6 1.4 2.0 Nonmanufacturing: Compensation......................................................................... Cash payments....................................................................... Wages............................................................................... Benefits............................................................... 2.0 1.8 1.8 2.2 1.5 1.3 1.3 1.8 1.9 1.6 1.5 2.4 2.0 1.8 1.6 2.3 1.8 1.5 1.4 2.4 1.8 1.6 1.5 2.2 1.4 1.3 1.3 1.6 1.3 1.2 1.2 1.5 Goods-producing: Compensation......................................................................... Cash payments....................................................................... Wages................................................................................. Benefits................................................................................. 1.9 1.6 1.8 2.7 1.6 1.4 1.5 2.1 1.4 1.1 1.2 1.9 1.4 1.2 1.2 1.8 1.4 1.1 1.1 1.8 1.4 1.2 1.2 1.8 1.6 1.5 1.4 1.6 1.4 1.3 1.2 1.5 Service-producing: Compensation......................................................................... Cash payments....................................................................... Wages................................................................................. Benefits.................................................................................. 2.0 1.8 1.8 2.2 1.2 1.1 1.0 1.3 1.8 1.5 1.5 2.3 1.8 1.6 1.5 2.2 2.0 1.6 1.5 2.7 2.0 1.6 1.6 2.6 1.5 1.3 1.3 1.9 1.5 1.3 1.3 1.8 112 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis * August 1995 29. Specified compensation and wage rate changes from contract settlements, and wage rate changes under all agreements, State and local government collective bargaining agreements covering 1,000 workers or more (in percent) Annual average Measure 1992 1993 1994 Changes under settlements: Total compensation 1changes, 2 settlements covering 5,000 workers or more: First year of contract ................................................................................................................................ Annual average over life of contract........................................................................................................... 0.6 1.9 0.9 1.8 2.8 3.1 Wage changes, settlements covering 1,000 workers or more: First year of contract ................................................................................................................................ Annual average over life of contract........................................................................................................... 1.1 2.1 1.1 2.1 2.7 3.0 1.9 2.8 3.3 .8 1.1 (4) 1.6 1.1 (4) 1.4 1.9 (4) Wage changes under all agreements: Average wage change 3.............................................................................................................................. Source: Current settlements................................................................................................................................ Prior settlements.................................................................................................................................... COLA provisions.................................................................................................................................... ’ Compensation includes wages, salaries, and employers’ cost of employee benefits when contract is negotiated. 2 Changes are the net result of increases, decreases, and zero change in compensation or wages. 3 Because of rounding, total may not equal sum of parts. 4 Less than 0.05 percent. 30. Work stoppages involving 1,000 workers or more 1995 1994 Annual totals Measure 1993 Number of stoppages: Beginning in period.................. In effect during period.............. 1994 June May July Sept. Aug. Nov. Oct. Apr." Mar» Feb.» Jan.p Dec. 35 36 45 45 4 6 9 11 4 9 5 11 7 14 4 9 1 6 0 4 1 4 1 4 4 7 2 5 Workers involved: Beginning in period (in thousands)............................ In effect during period (in thousands)............................ 18.2 322.2 13.5 38.7 14.3 58.6 32.0 8.0 2.6 .0 37:7 3.0 17.6 32.0 18.4 322.2 18.0 43.2 33.1 88.2 59.4 32.7 26.8 17.2 52.9 18.2 32.8 56.9 Days idle: Number (in thousands)............. Percent of estimated working time' .................................... 3,981.0 5,020.5 133.5 367.0 436.1 678.5 638.5 505.9 420.8 342.2 368.5 306.8 367.8 529.7 .02 .01 .01 .01 .01 .01 .02 .02 .01 .02 ' 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 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis .02 .02 .02 .02 worked is found in "Total economy’ measure of strike idleness." M onthly Labor R e view, October 1968, pp. 54-56. p = preliminary. M onthly Labor Review August 1995 113 Current Labor Statistics: Price D a ta 31. 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 Series 1994 1995 * 1993 1994 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May CONSUMER PRICE INDEX FOR ALL URBAN CONSUMERS: All items..................... All items (1967 = 100) ........ 144.5 148.2 147.5 148.0 148.4 149.0 149.4 149.5 149.7 149.7 150.3 150.9 151.4 151.9 152.2 432.7 444.0 441.9 443.3 444.4 446.4 447.5 448.0 448.6 448.4 450.3 452.0 453.5 455.0 455.8 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................... 141.6 140.9 140.1 156.6 135.5 129.4 159.0 130.5 133.4 130.0 114.6 143.7 143.2 149.6 144.9 144.3 144.1 163.0 137.2 131.7 165.0 135.6 135.2 133.5 123.2 147.5 145.7 151.5 144.1 143.5 143.0 162.3 137.1 132.0 163.2 132.8 135.5 133.4 115.6 147.0 145.3 151.5 144.2 143.5 142.9 163.4 137.2 132.2 161.6 132.9 134.9 133.5 115.8 147.2 145.5 151.7 144.8 144.2 144.0 163.9 136.7 131.8 164.4 135.7 135.2 135.1 122.8 147.6 145.6 151.6 145.3 144.8 144.7 164.7 137.1 131.8 162.8 138.9 135.1 134.1 131.3 148.4 145.9 151.3 145.6 145.0 145.0 164.8 137.3 131.3 163.2 139.4 135.4 134.2 132.1 148.8 146.2 151.4 145.6 145.0 144.8 164.6 136.8 131.5 162.9 139.5 135.6 135.0 132.7 148.5 146.4 151.6 145.9 145.3 145.1 163.7 136.9 131.7 165.7 139.0 134.5 134.3 132.4 148.1 146.8 151.9 147.2 146.8 147.3 164.2 136.4 131.6 180.3 138.8 134.5 134.2 131.7 148.1 147.1 151.8 147.9 147.5 148.2 164.6 137.3 132.7 180.4 140.3 135.5 136.4 133.3 149.4 147.4 152.0 147.8 147.4 147.9 165.8 137.6 132.1 177.1 140.6 135.8 136.8 133.7 149.7 147.6 152.4 147.9 147.4 147.6 165.3 138.4 132.2 174.0 140.7 136.4 136.8 132.9 150.5 148.1 153.1 148.9 148.4 149.2 166.9 137.7 132.1 183.1 140.9 136.7 137.2 132.9 150.6 148.3 153.6 148.7 148.3 148.7 166.6 137.3 132.8 181.0 140.8 137.3 137.1 131.7 151.3 148.6 153.9 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..................................................... 141.2 155.7 165.0 150.3 190.3 160.2 160.5 146.9 130.6 135.0 124.6 121.3 111.2 90.3 118.5 147.0 119.3 109.5 130.7 135.8 144.8 160.5 169.4 154.0 196.3 165.5 165.8 152.3 130.8 134.5 125.8 122.8 111.7 88.8 119.2 150.2 121.0 111.0 132.3 138.5 144.1 159.6 168.5 153.3 194.9 164.5 164.8 150.8 131.0 135.0 125.7 122.2 110.6 88.7 118.0 150.4 121.1 111.4 131.9 138.1 144.9 160.1 169.6 153.4 198.9 164.8 165.1 151.9 131.5 135.4 126.2 124.2 113.9 87.7 122.1 150.4 121.4 111.6 132.4 138.4 145.4 160.8 171.0 153.9 203.2 165.3 165.5 153.2 131.3 135.4 125.9 124.3 114.1 87.1 122.3 150.4 121.5 111.8 132.2 138.6 145.9 161.7 172.1 154.5 205.9 166.1 166.4 154.0 131.2 135.4 125.6 124.3 114.0 86.8 122.2 150.6 121.4 111.5 132.2 138.9 145.8 161.6 169.4 155.0 193.5 167.1 167.3 154.3 131.6 135.8 126.0 124.2 113.8 86.8 122.1 150.3 121.4 111.2 132.6 139.3 145.7 162.0 169.8 155.2 194.0 167.5 167.8 154.5 130.8 135.9 123.8 122.4 110.8 87.0 118.5 150.4 121.4 110.9 133.7 139.4 145.5 162.1 168.9 155.6 189.2 167.9 168.2 155.0 131.2 136.4 124.3 121.8 109.9 87.7 117.3 150.5 121.1 110.8 132.6 139.1 145.4 161.8 168.2 155.7 186.2 167.8 168.1 155.4 132.7 137.0 126.8 122.0 110.1 88.4 117.4 150.6 120.8 110.3 132.9 139.1 146.4 162.9 170.7 156.1 195.0 168.4 168.7 155.9 133.1 137.3 127.5 122.9 110.7 89.4 118.0 152.1 121.8 110.5 133.8 142.4 147.0 163.8 172.9 156.4 202.9 168.9 169.1 156.1 133.8 137.9 128.2 122.6 110.4 89.6 117.6 151.8 122.4 111.1 134.6 142.8 147.4 164.5 174.6 156.7 208.7 169.2 169.5 157.1 134.2 138.8 128.2 122.3 109.8 89.0 117.1 151.9 122.6 111.2 135.7 142.9 147.4 164.7 174.1 157.0 206.0 169.6 169.9 157.2 134.2 139.0 127.6 122.1 109.3 88.4 116.6 152.2 122.6 111.2 135.9 142.9 147.6 164.8 173.7 157.2 203.4 170.0 170.3 157.4 134.6 139.4 128.1 122.5 109.8 88.3 117.2 152.3 122.7 111.0 136.4 143.3 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....................... 133.7 133.4 131.0 130.4 127.5 126.4 132.6 130.9 127.1 128.1 125.9 126.0 145.6 149.5 151.7 155.4 135.6 132.8 127.4 135.1 125.2 128.5 149.9 155.0 133.8 130.8 125.9 131.6 128.4 127.3 149.7 155.5 130.9 131.1 134.2 127.6 127.8 131.2 124.9 125.7 128.4 125.7 125.5 131.1 129.2 128.6 129.5 125.0 124.5 125.1 150.6 152.4 152.3 155.7 155.9 156.3 135.2 132.3 128.9 133.4 128.6 125.5 151.4 156.4 134.2 131.1 129.2 130.5 131.2 125.7 150.8 156.3 130.5 127.2 125.3 125.7 131.3 123.6 146.5 156.4 129.4 131.1 126.0 127.7 124.0 125.6 123.0 125.9 129.0 126.8 124.0 124.8 150.1 150.4 157.0 157.3 134.4 131.3 127.2 131.5 127.1 125.9 155.0 157.6 134.8 131.7 127.0 132.2 127.1 127.2 154.4 157.7 133.4 130.2 127.9 129.6 123.6 126.6 150.3 157.7 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........................ 130.4 134.3 132.8 133.8 134.6 135.9 127.5 131.4 130.0 131.0 131.8 133.0 132.7 137.6 137.2 137.4 137.4 137.3 131.5 136.0 135.7 135.8 135.8 135.6 133.9 141.7 137.9 140.9 142.6 144.0 98.0 98.5 96.0 98.2 100.5 104.1 97.7 98.2 95.6 97.9 100.4 104.1 145.9 150.2 149.7 149.8 150.0 150.7 156.8 162.1 160.8 161.3 161.5 162.0 103.4 103.5 103.4 103.4 103.3 103.3 169.1 175.8 174.0 174.8 175.1 175.7 167.0 172.0 169.9 169.9 171.4 173.2 135.9 133.1 137.5 135.7 145.4 103.7 103.6 151.2 162.1 103.2 175.8 171.7 136.1 133.6 138.4 136.6 147.7 101.8 101.7 151.7 164.1 103.1 178.4 168.4 137.1 134.8 139.4 137.7 150.1 102.7 102.6 151.8 166.2 104.0 180.7 167.2 137.1 137.3 134.9 134.9 140.1 140.6 138.5 139.0 151.5 152.4 100.4 98.7 100.2 984 151.9 152.0 167.6 168.8 104.3 104.2 182.4 184.0 165.6 168.4 137.5 135.0 140.7 139.1 153.3 98.0 97.7 152.5 169.4 104.6 184.6 169.9 138.0 139.1 135.2 136.2 140.7 141.1 139.0 139.3 154.8 156.7 97.5 99.5 97.2 99.3 152.7 153.2 170.2 170.9 104.6 104.5 185.6 186.5 174.5 176.7 140.3 137.5 141.1 139.3 157.7 104.2 104.2 153.8 170.5 104.7 185.9 176.7 Medical care.................................. Medical care commodities ........................ Medical care services............................. Professional services...................... Hospital and related services........................... 201.4 195.0 202.9 184.7 231.9 211.0 200.7 213.4 192.5 245.6 209.7 200.1 212.0 191.7 243.5 210.4 200.5 212.6 192.3 244.1 211.5 201.3 213.8 193.0 246.1 212.2 201.7 214.7 193.5 247.3 212.8 201.7 215.4 194.0 248.1 214.0 202.2 216.8 195.1 249.8 214.7 202.7 217.5 195.5 250.6 215.3 202.9 218.2 196.0 251.3 216.6 203.1 219.8 197.2 253.2 217.9 203.5 221.3 198.5 254.7 218.4 203.7 221.8 199.1 254.7 218.9 203.6 222.4 199.5 255.3 219.3 203.4 223.0 200.2 255.6 Entertainment .................................... Entertainment commodities ......................... Entertainment services............................... 145.8 133.4 160.8 150.1 136.1 166.8 149.9 136.2 166.2 149.8 136.1 166.3 150.2 136.5 166.7 150.2 136.5 166.6 150.7 137.0 167.1 151.0 136.9 167.7 151.6 137.3 168.6 151.2 136.8 168.3 152.1 137.5 169.4 152.5 137.4 170.2 152.6 137.3 170.7 153.3 138.1 171.3 153.6 138.1 171.8 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.................................... 192.9 228.4 141.5 139.0 144.0 210.7 197.6 211.9 198.5 220.0 144.6 141.5 147.9 223 2 205.5 224.8 197.1 220.6 144.4 141.7 147.2 220.4 204.1 221.9 197.6 220.6 145.2 141.8 148.8 220.9 204.6 222.4 198.0 221.3 145.0 141.9 148.3 221.6 205.1 223.0 199.4 221.7 145.0 141.9 148.3 223.9 205.8 225.5 201.4 220.8 145.1 141.8 148.7 228.0 208.4 229.7 201.9 221.3 145.3 142.0 148.7 228.8 207.7 230.6 202.3 221.4 145.7 142.3 149.2 229.2 207.7 231.1 202.4 222.0 145.8 142.6 149.2 229.2 207.4 231.1 203.0 222.2 145.7 142.2 149.4 230.2 211.9 231.8 204.1 222.7 146.2 142.6 150.1 232.0 212.5 233.6 204.0 222.5 146.0 142.2 150.2 232.0 212.6 233.6 204.3 223.0 146.3 142.2 150.7 232.1 212.7 233.8 204.9 225.3 146.6 142.9 150.6 232.3 212.2 234.0 See footnotes at end of table. M onthly Labor Review Digitized for114 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 31. 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 1993 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......................................................................... 1994 144.5 148.2 131.5 133.8 141.6 144.9 125.3 126.9 128.1 128.4 131.0 130.4 129.6 130.3 121.3 124.8 1995 1994 Annual average May June July Aug. 147.5 133.4 144.1 126.8 128.5 132.8 129.3 124.4 148.0 133.5 144.2 126.9 128.4 130.8 130.2 124.9 148.4 133.7 144.8 126.8 128.1 127.6 131.3 125.1 149.0 134.3 145.3 127.5 129.2 127.8 132.8 125.1 Services.............................................................................. Rent of shelter (12/82-100).............................................. Household services less rent of’ shelter (12/82=100)........... Transportation services...................................................... Medical care services......................................................... Other services .................................................................. 157.9 163.1 162.0 162.8 162.0 167.0 166.0 166.6 134.2 136.3 135.7 137.7 162.9 168.6 167.1 167.5 202.9 213.4 212.0 212.6 177.0 185.4 183.9 184.3 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....................................................... Nondurabies 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.......................................................... 145.1 141.4 146.0 141.2 126.3 129.3 130.7 135.1 164.8 153.6 104.2 150.0 152.2 135.2 97.3 161.9 149.0 144.8 149.5 144.7 127.9 129.7 131.6 136.8 170.7 158.4 104.6 154.1 156.5 137.1 97.6 167.6 148.3 144.2 148.9 144.0 127.8 129.8 130.6 136.5 169.5 157.4 102.9 153.5 156.0 137.5 95.4 166.6 Purchasing power of the consumer dollar: 1982-84-$1.00................................................................. 1967 —$1.00...................................................................... 69.2 23.1 67.5 22.5 67.8 22.6 Oct. 149.4 149.5 134.8 134.9 145.6 145.6 128.1 128.3 130.3 130.2 131.2 132.3 132.8 132.2 125.1 125.7 Nov. Dec. Jan. Feb. Mar. Apr. May 149.7 135.2 145.9 128.6 130.1 131.1 132.5 126.5 149.7 135.1 147.2 127.6 128.1 127.2 131.5 126.9 150.3 135.1 147.9 127.4 127.5 126.0 131.2 127.2 150.9 135.4 147.8 127.9 128.1 127.7 131.3 127.6 151.4 135.9 147.9 128.6 129.2 131.3 131.1 127.7 151.9 136.6 148.9 129.2 129.9 131.7 132.0 128.1 152.2 136.9 148.7 129.7 130.8 130.2 134.2 128.1 163.4 164.2 164.4 164.6 164.7 164.7 165.9 166.7 167.3 167.5 167.7 167.3 168.2 168.2 168.6 168.6 168.3 169.4 170.4 171.2 171.3 171.5 137.9 138.0 137.9 136.3 135.8 135.9 137.2 137.0 136.9 136.7 137.1 168.1 168.9 168.8 169.5 170.5 171.1 172.6 173.4 175.0 176.1 175.9 213.8 214.7 215.4 216.8 217.5 218.2 219.8 221.3 221.8 222.4 223.0 184.7 185.8 187.8 188.5 189.0 188.9 189.7 190.9 191.1 191.4 191.7 148.8 149.1 144.6 144.9 149.4 149.8 144.5 144.8 127.9 127.8 129.7 129.4 131.4 132.4 136.5 136.6 170.5 171.0 158.2 158.7 105.7 106.8 153.7 154.0 156.2 156.4 137.3 136.8 97.2 99.2 167.1 167.7 67.6 22.6 Sept. 67.4 22.5 149.8 150.2 150.4 145.5 146.0 146.1 150.4 150.6 150.7 145.5 145.8 145.9 128.4 129.0 129.3 130.4 131.4 131.4 133.7 133.7 133.2 137.4 138.1 138.1 171.7 172.2 172.2 159.4 159.6 159.7 108.5 108.2 105.8 154.6 155.0 155.5 157.0 157.5 158.0 136.8 137.7 138.3 102.4 102.0 100.4 168.5 168.8 169.3 67.1 22.4 66.9 22.3 66.9 22.3 150.6 146.3 150.9 146.1 129.5 131.2 133.5 138.2 172.4 159.8 105.7 155.7 158.2 138.4 101.2 169.6 150.2 146.3 150.8 146.0 128.5 129.5 132.6 137.8 172.7 159.7 104.7 155.7 157.9 137.6 99.2 169.6 150.8 146.8 151.5 146.6 128.3 128.9 132.4 137.8 174.0 160.9 104.2 156.5 158.7 137.7 97.9 170.8 151.5 147.2 152.1 147.1 128.8 129.5 132.5 138.1 174.7 161.6 103.7 157.2 159.6 138.4 97.2 171.7 66.8 22.3 66.8 22.3 66.5 22.2 66.3 22.1 152.1 152.5 147.7 148.3 152.7 153.2 147.6 148.1 129.5 130.1 130.5 131.3 132.4 133.3 138.7 139.6 175.1 175.5 162.2 162.4 103.2 103.9 157.8 158.3 160.4 160.7 139.4 139.7 96.7 98.4 172.4 172.7 152.9 148.6 153.4 148.4 130.6 132.1 135.2 139.9 175.8 162.6 106.3 158.3 160.8 139.6 102.6 172.9 65.8 22.0 65.7 21.9 66.0 22.0 CONSUMER PRICE INDEX FOR URBAN WAGE EARNERS AND CLERICAL WORKERS: All items ............................................................................... All items (1967-100) ............................................................. 142.1 423.1 145.6 144.9 145.4 145.8 146.5 146.9 147.0 147.3 147.2 147.8 148.3 148.7 149.3 149.6 433.8 431.7 433.2 434.3 436.4 437.5 437.8 438.6 438.6 440.2 441.7 443.0 444.6 445.6 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........................................................... 141.2 140.5 139.6 156.3 135.4 129.1 158.2 130.4 133.1 129.9 115.1 143.5 143.1 149.3 144.4 143.9 143.4 162.7 137.0 131.5 164.2 135.3 135.2 133.5 122.9 147.2 145.5 151.0 143.7 143.1 142.4 162.0 137.0 131.7 162.3 132.7 135.4 133.4 116.1 146.7 145.2 150.9 143.8 143.2 142.4 163.1 137.0 132.1 161.1 132.7 134.7 133.4 116.2 146.9 145.4 151.3 144.4 143.8 143.4 163.6 136.4 131.6 163.8 135.4 135.1 135.1 122.4 147.4 145.5 151.1 144.9 144.4 144.1 164.4 136.9 131.6 162.3 138.3 135.1 134.0 130.2 148.1 145.8 150.7 145.1 144.6 144.4 164.6 137.2 131.0 162.6 138.8 135.4 134.2 130.9 148.5 146.1 150.9 145.1 144.6 144.1 164.3 136.6 131.2 162.0 139.0 135.7 135.0 131.5 148.2 146.3 151.1 145.3 144.8 144.3 163.5 136.7 131.4 164.5 138.5 134.5 134.1 131.1 147.8 146.7 151.3 146.6 146.2 146.3 163.9 136.0 131.4 178.8 138.3 134.4 134.1 130.6 148.0 147.0 151.4 147.2 146.9 147.2 164.3 137.1 132.4 178.8 139.7 135.5 136.3 132.2 149.1 147.3 151.6 147.3 146.9 147.1 165.6 137.4 131.8 175.8 140.2 135.8 136.7 132.9 149.5 147.5 152.0 147.3 146.8 146.8 165.1 138.1 131.9 172.7 140.3 136.4 136.7 132.2 150.2 147.9 152.7 148.3 147.9 148.2 166.7 137.3 131.8 182.1 140.4 136.6 137.1 132.1 150.3 148.2 153.2 148.1 147.7 147.8 166.3 136.9 132.5 179.8 140.4 137.3 136.9 131.0 151.0 148.5 153.4 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........................................................ 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..................................................... 138.5 151.6 144.7 150.0 190.2 146.1 146.3 134.4 130.9 138.6 120.7 121.1 110.7 90.2 118.0 147.7 118.0 108.3 131.1 137.4 142.0 156.2 148.5 153.7 196.6 150.9 151.1 139.7 130.8 138.1 121.1 122.5 111.1 88.7 118.7 150.8 119.7 109.6 132.5 140.6 141.3 155.3 147.7 153.0 194.9 150.0 150.2 138.1 130.9 138.8 120.6 121.9 110.0 88.6 117.4 151.0 119.7 109.9 132.2 140.2 142.1 155.8 148.4 153.1 199.1 150.3 150.5 139.1 131.5 139.1 121.4 124.0 113.5 87.6 121.5 151.1 120.0 110.1 132.7 140.3 142.5 156.4 149.5 153.6 204.2 150.7 150.9 140.5 131.4 139.1 121.1 124.0 113.6 87.0 121.7 150.9 120.1 110.3 132.5 140.6 143.0 157.2 150.3 154.2 206.7 151.5 151.7 141.4 131.3 139.1 120.9 124.0 113.5 86.6 121.6 151.1 120.0 110.1 132.5 140.9 143.0 157.4 148.9 154.7 194.1 152.3 152.6 141.7 131.8 139.4 121.6 123.9 113.3 86.7 121.5 150.9 120.0 109.8 132.9 141.5 142.8 157.7 149.2 154.9 194.4 152.8 153.0 141.9 131.0 139.5 120.0 122.0 110.2 86.9 117.8 150.9 120.1 109.5 133.9 141.7 142.7 157.9 148.8 155.4 189.6 153.1 153.3 142.4 131.4 140.0 120.2 121.5 109.3 876 116.7 150.9 119.8 109.5 133.0 141.4 142.7 157.7 148.5 155.4 187.2 153.1 153.3 142.9 132.4 140.3 121.9 121.6 109.5 88.3 116.8 151.1 119,7 109.1 133.3 141.5 143.5 158.6 149.9 155.7 195.3 153.6 153.8 143.2 132.8 140.5 122.5 122.5 110.1 89.3 117.4 152.4 120.5 109.2 134.1 145.6 144.0 159.3 151.3 156.1 202.9 154.0 154.2 143.4 133.2 140.8 123.0 122.2 109.7 89.5 116.9 152.2 121.2 109.9 134.8 146.0 144.3 159.9 152.3 156.4 208.5 154.3 154.5 144.2 133.7 141.7 123.1 121.9 109.1 88.9 116.3 152.3 121.4 109.9 135.9 146.1 144.4 160.1 152.1 156.7 205.8 154.7 154.9 144.5 133.7 141.9 122.9 121.6 108.4 88.3 115.6 152.7 121.4 109.9 136.2 145.9 144.6 160.3 152.0 156.9 203.8 155.1 155.3 144.6 134.1 142.3 123.2 122.0 109.1 88.2 116.3 152.8 121.5 109.8 136.6 146.2 ... . See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 115 Current Labor Statistics: Price D ata 31. Continued— Consumer Price indexes for All Urban Consumers and for Urban Wage Earners and Clerical Workers: U.S. city average, by expenditure category and commodity or service group (1982-84 = 100, unless otherwise indicated) Annual average Series 1994 1995 Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. 129.8 130.2 126.7 127.2 124.6 125.3 124.2 124.5 130.8 129.9 125.8 125.3 148.3 151.5 155.1 155.4 133.1 130.2 127.8 129.4 131.1 126.0 151.3 155.9 133.9 131.1 128.1 131.7 130.3 126.3 149.9 156.0 133.0 130.1 128.4 129.1 133.2 126.1 149.1 155.8 129.3 126.1 124.5 124.0 132.9 124.2 144.1 155.9 128.3 125.0 123.5 121.2 130.3 124.4 149.1 156.5 130.0 126.8 125.2 124.3 127.0 125.3 149.7 156.8 133.2 130.3 126.7 129.8 127.4 126.8 154.6 157.1 133.6 132.1 130.7 129.1 126.5 127.8 130.6 128.1 127.7 123.9 127.9 127.4 153.5 146.9 157.2 157.1 133.9 132.0 138.3 135.6 143.3 100.5 100.4 150.8 157.5 102.6 171.0 167.1 135.3 135.6 136.7 133.5 133.9 135.1 138.4 139.2 140.1 135.4 136.3 137.3 146.1 148.4 150.8 103.7 101.7 102.6 103.7 101.5 102.5 151.9 152.4 152.5 158.0 160.0 162.0 102.4 102.4 103.2 171.8 174.3 176.6 167.6 164.8 163.8 136.7 136.9 135.2 135.2 140.9 141.2 138.1 138.6 152.1 153.0 100.2 98.5 100.0 98.3 152.6 152.7 163.4 164.7 103.5 103.4 178.4 180.0 162.5 164.8 137.1 135.4 141.4 138.7 154.0 97.8 97.5 153.3 165.4 103.8 180.9 166.5 137.6 135.7 141.5 138.7 155.5 97.3 97.0 153.5 166.3 103.8 181.9 170.1 138.7 136.8 141.9 139.0 157.4 99.5 99.3 154.0 166.9 103.7 182.8 172.3 140.1 138.3 141.9 138.9 158.4 104.2 104.3 154.6 166.5 103.9 182.2 172.5 214.0 200.6 217.1 196.5 247.7 214.6 200.8 217.7 196.9 248.5 215.9 200.9 219.3 198.1 250.5 217.3 201.3 220.9 199.4 252.1 217.7 201.5 221.4 200.0 252.2 218.2 201.3 222.0 200.5 252.8 218.7 201.0 222.6 201.2 253.1 149.0 136.2 167.5 149.6 136.6 168.5 149.2 136.1 168.3 150.1 136.8 169.2 150.4 136.8 170.1 150.6 136.7 170.6 151.3 137.5 171.2 151.5 137.5 171.8 198.9 221.1 145.4 142.6 148.6 223.6 209.8 225.0 199.4 221.6 145.5 142.8 148.6 224.4 208.8 225.9 199.8 221.7 145.9 143.1 149.1 224.9 208.8 226.5 200.0 222.2 146.1 143.5 149.2 224.9 208.5 226.5 200.5 222.4 146.0 143.1 149.5 226.0 213.4 227.2 201.5 222.9 146.4 143.4 150.1 227.5 213.4 228.9 201.4 222.6 146.1 142.9 150.2 227.7 213.6 229.0 201.7 223.1 146.5 143.1 150.7 227.8 213.7 229.2 202.5 225.4 146.8 143.7 150.6 228.0 213.2 229.5 146.9 134.6 145.1 128.1 129.9 130.2 132.8 124.4 147.0 134.7 145.1 128.2 129.7 131.1 132.0 125.1 147.3 135.0 145.3 128.6 129.7 130.1 132.4 126.0 147.2 134.8 146.6 127.6 127.7 126.1 131.3 126.5 147.8 134.9 147.2 127.4 127.0 125.0 130.9 126.8 148.3 135.3 147.3 127.9 127.6 126.8 130.8 127.2 148.7 135.7 147.3 128.6 128.5 130.3 130.6 127.5 149.3 136.5 148.3 129.3 129.4 130.7 131.7 128.0 149.6 136.9 148.1 130.0 130.5 129.1 134.2 128.1 1993 1994 May June July 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...................... 132.4 129.8 126.8 130.4 128.9 126.5 145.4 151.2 132.2 129.4 125.8 129.2 129.3 126.9 148.7 154.9 134.3 131.6 126.5 132.7 126.2 129.5 151.3 154.5 132.4 129.6 125.3 129.5 129.6 128.2 148.3 155.0 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................................................ 129.4 133.4 131.8 132.9 127.4 131.4 129.8 131.0 133.3 138.3 138.0 138.2 131.2 135.7 135.4 135.6 134.6 142.4 138.6 141.5 97.9 98.4 96.0 98.2 97.6 98.2 95.6 97.9 146.5 150.9 150.5 150.5 152.9 157.9 156.6 157.3 102.8 102.8 102.8 102.8 165.0 171.5 169.8 170.7 163.0 167.7 166.4 165.9 Medical care........................................................... Medical care commodities................................................. Medical care services........................................... Professional services.................................................. Hospital and related services ........................................... 200.9 210.4 209.1 209.7 210.8 211.5 212.0 213.4 193.2 198.6 198.2 198.7 199.0 199.5 199.3 199.9 202.7 213.0 211.5 212.2 213.4 214.2 214.9 216.4 185.2 193.4 192.5 193.1 193.9 194.4 194.9 196.0 229.2 242.7 240.5 241.3 243.2 244.4 245.2 246.9 Entertainment ............................................................. Entertainment commodities ................................................ Entertainment services....................................................... 144.1 132.9 160.5 148.2 135.5 166.7 148.1 135.7 166.1 148.0 135.6 166.2 148.4 136.0 166.5 148.3 135.9 166.5 148.6 136.0 167.0 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.................................... 192.2 228.3 141.6 139.6 143.9 206.9 199.2 207.8 196.4 220.1 144.8 142.2 147.9 219.2 207.1 220.4 195.3 220.6 144.7 142.4 147.3 216.6 205!9 217.7 195.8 220.7 145.3 142.3 149.0 217.2 206.4 218.4 196.3 221.4 145.1 142.5 148.2 217.9 206.9 219.0 197.5 222.1 145.2 142.6 148.2 220.2 207.5 221.5 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......................................................................... 142.1 131.2 141.2 125.0 127.7 129.8 129.7 120.1 145.6 133.4 144.4 126.6 127.9 129.4 130.1 123.8 144.9 132.9 143.7 126.3 127.9 131.6 129.0 123.1 145.4 133.2 143.8 126.6 127.9 129.6 130.0 123.8 145.8 133.4 144.4 126.7 127.8 126.7 131.2 124.2 146.5 134.1 144.9 127.5 129.1 127.2 133.0 124.3 Services........................................................ Rent of shelter (12/84 = 100).............................................. Household services less rent of shelter (12/84 = 100)............ Transportation services...................................................... Medical care services....................................................... Other services ............................................................ M onthly Labor Review Digitized 116 for FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 135.2 133.3 138.2 135.3 144.7 104.2 104.3 151.4 157.8 102.6 171.5 168.7 155.5 160.6 159.6 160.4 160.9 161.6 161.9 162.1 162.3 162.4 145.8 150.3 149.4 149.9 150.5 151.3 151.4 151.8 151.9 151 7 123.5 125.4 124.8 126.7 126.8 126.9 126.9 125.2 124.7 124.9 160.0 165.7 164.3 164.8 165.2 165.9 166.0 167.2 168.4 169.2 202.7 213.0 211.5 212.2 213.4 214.2 214.9 216.4 217.1 217.7 174.1 182.4 181.0 181.5 181.8 182.9 184.7 185.3 185.9 185.9 Special indexes: All items less food ............................................................. 142.3 145.9 All items less shelter ......................................................... • 139.7 143.0 All items less homeowners’ costs (12/84 = 100).................... 133.9 137.0 All items less medical care................................................. 139.2 142.6 Commodities less food....................................................... 125.9 127.6 Nondurables less food ....................................................... 128.9 129.2 Nondurables less food and apparel ..................................... 130.7 131.2 Nondurables..................................................................... 134.7 136.4 Services less rent of shelter (12/84 = 100)........................... 147.0 152.1 Services less medical care................................................. 151.4 156.1 Energy.............................................................................. 103.6 104.1 All items less energy ......................................................... 147.5 151.5 All items less food and energy ............................................ 149.3 153.5 Commodities less food and energy...................................... 134.3 136.2 Energy commodities .......................................................... 97.5 97.8 Services less energy.......................................................... 159.7 165.3 Purchasing power of the consumer dollar: 1982-84 -$1 00 ................................................................. 1967 = $1.00...................................................................... Aug. 70.4 23.6 68.7 23.1 145.2 142.3 136.4 141.9 127.3 129.2 130.3 136.1 151.0 155.1 102.3 150.9 152.9 136.4 95.6 164.3 145.8 142.8 136.9 142.4 127.6 129.2 131.2 136.1 152.1 155.9 105.1 151.1 153.2 136.3 97.5 164.7 146.1 143.1 137.3 142.7 127.7 129.1 132.2 136.4 152.5 156.4 106.3 151.4 153.4 135.9 99.6 165.3 146.8 143.8 137.9 143.4 128.4 130.3 133.7 137.3 153.0 157.1 108.2 151.9 153.9 136.1 102.9 166.0 69.0 23.2 68.8 23.1 68.6 23.0 68.3 22.9 147.2 147.4 144.2 144.3 138.1 138.2 143.8 143.8 128.9 129.1 131.1 130.9 133.6 133.0 137.8 137.7 153.5 153.4 157.3 157.4 107.8 105.3 152.4 152.9 154.4 155.0 136.9 137.5 102.4 100.6 166.4 167.0 68.1 22.9 68.0 22.8 May 163.4 164.1 164.6 164.8 165.1 152.5 153.3 153.8 154.0 1542 126.1 125.8 125.6 125.4 125.9 170.6 171.5 172.8 173.8 173.6 219.3 220.9 221.4 222.0 222.6 186.6 187.7 188.0 188.3 188.6 147.7 144.6 138.4 144.1 129.4 130.8 133.3 137.8 153.7 157.6 105.3 153.2 155.3 137.7 101.5 167.4 147.4 144.6 138.4 144.0 128.5 129.0 132.4 137.4 154.0 157.6 104.2 153.3 155.1 137.1 99.4 167.5 147.9 145.0 139.0 144.6 128.3 128.4 132.0 137.4 155.2 158.6 103.6 154.0 155.8 137.1 98.0 168.5 67.9 22.8 67.9 22.8 67.7 22.7 148.5 149.0 145.5 145.9 139.4 139.9 145.0 145.5 128.8 129.5 129.0 129.9 132.0 131.9 137.7 138.2 155.8 156.1 159.3 159.7 103.1 102.5 154.6 155.2 156.6 157.3 137.9 138.8 97.3 96.8 169.3 169.9 67.4 22.6 67.2 22.6 149.5 146.5 140.4 146.0 130.2 130.7 132.9 139.1 156.4 160.0 103.3 155.7 157.7 139.3 98.7 170.3 149.9 146.9 140.7 146.3 130.9 131.8 135.1 139.6 156.7 160.2 106.0 155.7 157.8 139.1 103.1 170.5 67.0 22.5 66.8 22.4 32. 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 Area' Pricing schedule2 1994 Apr. U.S. city average................ May Jan. Feb. Mar. Apr. May Apr. May Jan. Feb. Mar. Apr. May 144.7 144.9 147.8 148.3 148.7 149.3 149.6 M 147.4 147.5 150.3 150.9 151.4 151.9 152.2 154.4 154.2 157.1 157.6 158.0 158.3 158.5 151.8 151.7 154.8 155.2 155.5 155.8 156.1 M 155.0 154.7 157.7 158.3 158.7 159.0 159.2 151.4 151.1 154.3 154.8 155.1 155.4 155.7 M 153.3 152.8 155.4 155.7 155.9 156.3 156.4 151.1 150.8 153.3 153.7 153.9 154.2 154.3 153.9 139.8 154.2 140.2 157.4 143.0 157.6 143.6 158.1 144.2 158.6 145.0 158.8 145.2 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 C - 50,000 to 330 000 Size classes: A (12/86-100)................. B..................................... C .................................... D .................................... M M 152.6 M 142.9 152.7 143.3 155.7 146.1 156.0 146.7 156.6 157.0 147.3 148.1 157.1 148.3 M 144.1 144.5 147.3 148.0 148.5 149.0 149.0 140.3 140.7 143.5 144.2 144.7 145.3 145.2 M 142.2 142.0 144.4 145.2 146.1 146.9 147.3 138.5 138.4 140.9 141.8 142.6 143.4 143.9 M 143.7 144.4 147.4 147.7 148.3 149.5 150.0 141.2 141.9 144.9 145.2 145.6 146.9 147.5 M 137.9 M 143.8 138.8 144.3 141.5 146.7 142.3 147.4 142.7 148.0 143.9 148.4 144.6 148.8 136.4 142.2 137.3 142.8 139.8 145.3 140.4 145.9 141.0 146.5 142.2 147.0 142.9 147.4 M 144.4 144.7 146.6 147.3 148.0 148.3 148.7 142.4 142.8 144.8 145.4 146.1 146.4 147.1 M 146.3 148.9 149.6 150.4 150.9 150.8 141.8 142.8 145.6 146.3 146.9 147.4 147.4 147.8 145.5 M 142.9 143.1 145.7 146.2 146.6 147.3 147.6 142.6 142.8 145.7 146.1 146.5 147.3 M 141.3 M 148.9 142.3 148.8 145.2 152.0 146.1 152.4 146.6 152.8 147.1 153.2 148.0 153.5 141.4 145.9 142.5 146.0 145.6 149.2 146.4 149.4 146.7 149.8 147.3 150.3 148.2 150.6 M 150.4 150.4 152.9 153.1 153.6 154.0 154.2 145.8 146.0 148.5 148.7 149.1 149.6 149.7 M 148.6 147.8 154.1 155.1 155.2 155.9 156.4 146.3 145.7 151.4 152.2 152.2 152.8 153.8 M 133.9 M 146.8 M 145.8 M 142.1 133.9 147.0 146.0 143.0 136.2 149.9 149.3 145.9 136.7 137.2 150.5 151.1 149.8 150.2 146.6 147.1 137.5 151.6 151.0 147.7 137.7 132.7 132.9 151.8 144.1 144.4 151.4 144.9 145.2 148.5 141.4 142.3 135.3 147.3 148.6 145.2 135.7 147.9 149.0 145.8 136.2 136.6 136.8 148.5 148.9 149.1 149.3 150.2 150.7 146.3 147.0 147.9 147.9 147.6 151.8 152.3 152.6 153.1 153.0 143.3 143.1 147.1 147.5 147.8 148.3 148.2 M 152.0 151.4 154.3 154.5 154.6 154.7 155.1 146.6 146.2 149.0 149.2 149.3 149.5 149.8 M 157.7 M 153.1 157.3 153.2 159.9 156.6 160.3 157.8 160.9 158.0 161.4 157.8 161.8 157.8 153.9 153.6 152.6 152.7 156.3 156.4 156.6 157.5 157.1 157.5 157.5 157.4 158.0 157.4 M 148.0 148.3 150.3 150.5 151.1 151.5 151.3 145.6 146.1 148.2 148.3 148.9 149.4 149.0 149.1 156.9 139.7 146.6 143.9 152.4 _ 149.4 156.5 139.9 146.8 144.2 152.3 - 144.5 143.6 137.6 142.6 Selected local areas Chicago, IL-Northwestern IN ... Los Angeles-Long Beach, Anaheim, CA.......... New York, NYNortheastern NJ ................. Philadelphia, PA-NJ.............. San FranciscoOakland, CA....................... M Miami, FL........................... St. Louis, MO-IL.................. Washington, DC-MD-VA ....... 1 1 1 1 1 1 Dallas-Ft. Worth, TX............. Detroit, Ml.......................... Houston, TX ....................... Pittsburgh, PA .................... 2 2 2 2 Boston, MA ........................ 1995 1994 1995 _ _ _ - 140.3 142.6 136.8 143.9 145.8 148.7 153.6 158.0 143.7 146.6 143.3 147.3 140.0 142.9 151.4 153.8 _ _ - - _ _ _ 143.3 147.3 139.3 147.3 150.3 158.4 147.3 148.7 144.5 155.1 _ " _ 145.0 148.1 138.0 148.9 150.4 157.7 147.4 148.6 144.6 154.7 - ~ _ - 139.3 137.9 136.2 137.4 144.9 152.2 136.1 141.2 139.2 149.2 147.7 157.0 139.0 145.3 142.3 151.2 - ~ _ “ 142.7 142.7 138.9 141.1 " “ " ' 1 Area definitions are those established by the Office of Manage ment and Budget in 1983, except for Boston-Lawrence-Salem, MA-NH, Area (excludes Monroe County); and Milwaukee, Wl, Area (includes only the Milwaukee MSA). Definitions do not include revisions made since 1983. Excludes farms and the military. 2 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. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 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. M onthly Labor Review August 1995 117 Current Labor Statistics: Price Data 33. Annual data: Consumer Price Index, U.S. city average, all Items and major groups (1982-84=100) Series Consumer Price Index for All Urban Consumers: All Items: Index............................... Percent change................................ Food and beverages: Index............................... Percent change............................... Housing: Index........................................ Percent change.............................. Apparel and upkeep: Index.................................. Percent change............................. Transportation: Index........................................ Percent change........................... Medical care: Index................................... Percent change........................... Entertainment: Index........................................... Percent change............................. Other goods and services: Index............................................ Percent change........................................ Consumer Price Index for Urban Wage Earners and Clerical Workers: All items: Index........................................... Percent change........................................... M onthly Labor Review Digitized for118 FRASER https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 1986 1987 1988 1989 1990 1991 1992 1993 1994 109.6 1.9 113.6 3.6 118.3 4.1 124.0 4.8 130.7 5.4 136.2 4.2 140.3 3.0 144.5 3.0 148.2 2.6 109.1 3.3 113.5 4.0 118.2 4.1 124.9 5.7 132.1 5.8 136.8 3.6 138.7 1.4 141.6 2.1 144.9 2.3 110.9 3.0 114.2 3.0 118.5 3.8 123.0 3.8 128.5 4.5 133.6 4.0 137.5 2.9 141.2 2.7 144.8 2.5 105.9 .9 110.6 4.4 115.4 4.3 118.6 2.8 124.1 4.6 128.7 3.7 131.9 2.5 133.7 1.4 133.4 -.2 102.3 -3.9 105.4 3.0 108.7 3.1 114.1 5.0 120.5 5.6 123.8 2.7 126.5 2.2 130.4 3.1 134.3 3.0 122.0 7.5 130.1 6.6 138.6 6.5 149.3 7.7 162.8 9.0 177.0 8.7 190.1 7.4 201.4 5.9 211.0 4.8 111.6 3.4 115.3 3.3 120.3 4.3 126.5 5.2 132.4 4.7 138.4 4.5 142.3 2.8 145.8 2.5 150.1 2.9 121.4 6.0 128.5 . 5.8 137.0 6.6 147.7 7.8 159.0 7.7 171.6 7.9 183.3 6.8 192.9 5.2 198.5 2.9 108.6 1.6 112.5 3.6 117.0 4.0 122.6 4.8 129.0 5.2 134.3 4.1 138.2 2.9 142.1 2.8 145.6 2.5 34. Producer Price Indexes, by stage of processing (1982 = 100) 1993 Finished g o o d s .............................................. Finished consumer goods ..................... Finished consumer foods.................... Finished consumer goods excluding foods .............................................. Nondurable goods less food ............. Durable goods ................................ Capital equipment................................ Intermediate materials, supplies, and com ponents................................................... 1994 1995 1994 Annual average Grouping June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 126.9 128.3 128.3 126.9 128.5 128.5 127.6 128.5 128.5 128.0 127.9 127.9 124.7 125.7 125.7 125.5 126.8 126.8 125.6 125.9 125.9 126.0 126.2 126.2 126.5 126.6 126.6 125.6 126.3 126.3 125.8 126.1 126.1 126.1 126.9 126.9 126.2 128.6 128.6 126.6 127.9 127.9 121.7 117.6 128.0 78.0 121.6 116.2 130.9 77.0 122.0 116.9 130.8 78.3 122.5 117.5 130.9 79.6 123.4 118.7 131.0 81.4 122.2 117.8 129.2 79.6 122.0 116.3 132.1 77.1 122.3 116.7 132.1 77.7 121.8 115.9 132.2 75.9 122.4 116.7 132.6 76.6 122.6 116.9 132.6 76.6 122.7 117.1 132.4 76.4 123.8 118.7 132.4 78.8 124.7 120.0 132.4 80.4 116.2 118.5 118.2 118.7 119.5 120.1 120.0 120.9 121.1 122.5 123.3 123.7 124.7 125.3 Materials and components for manufacturing .................................... Materials for food manufacturing.......... Materials for nondurable manufacturing . Materials for durable manufacturing...... Components for manufacturing............ 118.9 115.6 115.5 119.1 123.0 122.1 118.5 119.2 125.2 124.3 121.2 118.0 117.1 124.2 124.2 121.7 116.2 118.1 125.1 124.4 122.5 117.8 119.7 126.0 124.3 123.7 118.5 122.3 127.4 124.5 124.5 116.8 124.3 128.5 124.6 125.5 118.0 125.4 130.6 124.8 126.2 117.5 126.7 131.8 124.9 128.1 117.8 129.7 134.6 125.7 129.1 118.5 131.5 136.1 125.9 129.5 119.0 132.4 136.5 125.9 130.6 117.1 135.7 136.8 126.2 130.8 116.5 136.5 136.5 126.3 Materials and components for construction........................................ Processed fuels and lubricants.............. Containers........................................... Supplies.............................................. 84.6 123.8 135.8 125.0 83.0 127.1 137.1 127.0 84.2 126.3 137.1 126.9 85.8 126.7 137.1 126.9 87.3 127.3 137.2 126.9 86.5 128.3 136.4 127.2 83.0 129.2 137.8 127.5 83.4 130.2 137.8 127.9 82.2 130.9 138.1 128.4 82.2 132.6 138.7 129.5 82.4 133.6 139.0 129.8 82.3 134.1 139.1 130.4 83.9 135.2 139.4 131.2 85.6 135.5 139.7 131.3 102.4 108.4 76.7 101.8 106.5 72.1 103.2 107.8 75.2 102.2 103.6 75.3 101.9 101.8 75.6 99.7 101.3 71.3 98.2 98.9 70.2 99.1 100.4 69.3 100.5 101.6 69.9 101.5 102.2 69.8 102.7 104.0 69.8 102.3 103.2 69.2 103.9 101.9 72.9 103.5 99.5 74.1 124.4 78.0 132.9 133.5 135.8 125.1 77.0 134.2 134.2 137.1 125.4 78.3 133.9 133.8 137.1 125.8 79.6 134.0 133.9 137.1 126.4 81.4 134.2 134.1 137.2 125.3 79.6 133.6 133.6 136.4 125.6 77.1 134.5 134.4 137.8 125.8 77.7 134.7 134.7 137.8 125.5 75.9 135.4 135.5 138.1 126.2 76.6 135.7 135.6 138.7 126.4 76.6 136.0 135.9 139.0 126.4 76.4 136.1 136.1 139.1 127.3 78.8 136.3 136.3 139.4 128.0 80.4 136.3 136.3 139.7 138.5 139.0 138.9 138.9 139.0 138.2 139.6 139.7 140.0 140.5 140.8 141.0 141.3 141.7 147.0 147.4 148.2 Crude materials for further processing ... Foodstuffs and feedstuffs .................... Crude nonfood materials...................... 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 ........................................ Intermediate materials less foods and feeds ................................................ Intermediate foods and feeds................ Intermediate energy goods.................... Intermediate goods less energy ............. Intermediate materials less foods and energy............................................... Crude energy materials......................... Crude materials less energy.................. Crude nonfood materials less energy...... https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 146.1 144.4 144.3 144.2 144.4 144.6 144.7 144.8 145.2 145.9 146.3 116.4 112.7 84.6 123.2 118.7 114.8 83.0 126.3 118.3 115.5 84.2 125.6 119.0 113.4 85.8 125.9 119.8 113.6 87.3 126.5 120.4 113.9 86.5 127.5 120.4 112.2 83.0 128.2 121.3 112.1 83.4 129.1 121.6 111.5 82.2 129.7 123.0 111.8 82.2 131.4 123.9 111.8 82.4 132.4 124.3 112.7 82.3 132.9 125.4 111.7 83.9 133.8 126.0 110.7 85.6 134.0 123.8 127.1 126.3 126.7 127.3 128.3 129.2 130.2 130.9 132.6 133.6 134.1 135.2 135.5 76.7 116.3 140.2 72.1 119.3 156.2 75.2 119.1 152.4 75.3 117.0 155.6 75.6 116.4 157.9 71.3 116.4 159.2 70.2 114.6 159.3 69.3 117.0 164.1 69.9 119.1 168.4 69.8 121.0 174.1 69.8 123.1 177.0 69.2 122.9 178.3 72.9 122.6 180.7 74.1 120.6 179.8 M onthly Labor Review August 1995 119 Current Labor Statistics; 35. Price D ata Producer price indexes for the net output of major industry groups (December 1984=100 unless otherwise indicated) Annual average SIC Industry 1993 Total mining Industries......... Metal mining........... Coal mining (12/85 = 100) .. Oil and gas extraction (12/85=100) ... Mining and quarrying of nonmetallic minerals, except fuels ................ Total manufacturing industries................ Food and kindred products...... Tobacco manufactures ........... Textile mill products ............ Apparel and other finished products made from fabrics and similar materials................ Lumber and wood products, except furniture................. Furniture and fixtures......................... Paper and allied products ............... Printing, publishing, and allied industries.......................... Chemicals and allied products................. Petroleum refining and related products . Rubber and miscellaneous plastic products Leather and leather products .................. Stone, clay, glass, and concrete products .. Primary metal industries .............. Fabricated metal products, except machinery and transportation equipment .................................... Machinery, except electrical.................... Electrical and electronic machinery, equipment, and supplies....................... Transportation equipment...................... Measuring and controlling instruments; photographic, medical, optical goods; watches, clocks................................... Miscellaneous manufacturing industries (12/85=100).................................... 1994 June 1994 July Aug. Sept. 1995 Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 10 12 13 76.4 69.7 93.3 76.2 73.3 81.4 93.2 71.1 74.9 81.4 92.0 73.5 74.3 84.9 92.1 72.4 75.0 84.4 92.7 73.3 72.4 87.6 94.3 69.2 71.0 88.3 95.0 67.1 70.5 91.1 94.9 66.2 72.0 94.2 92.0 68.6 72.1 101.9 88.4 68.7 71.4 99.0 88.5 67.9 70.9 101.8 91.5 66.4 73.5 105.0 94.4 69.4 74.3 99.1 92.1 71.2 14 118.8 120.5 120.5 120.5 120.4 120.5 120.7 120.8 120.9 122.4 123.3 123.3 123.1 123.1 119.1 20 118.7 21 218.0 22 113.6 120.7 120.1 187.8 113.6 120.4 119.8 187.7 113.5 120.9 121.5 119.7 120.1 187.7 187.7 113.6 113.8 121.1 119.9 187.9 113.8 121.5 119.6 187.6 113.9 121.9 119.6 188.1 114.2 121.7 119.4 187.9 114.3 122.6 120.2 188.1 114.7 123.0 123.2 120.9 121.0 188.8 190.6 115.5 115.7 124.0 124.5 120.2 120.2 190.8 195.3 116.0 116.6 23 119.2 119.7 119.5 119.8 119.7 119.7 119.8 119.7 119.8 120.0 120.1 120.3 120.6 120.5 24 25 26 148.3 125.4 120.2 154.4 129.7 123.7 153.7 130.1 121.6 152.7 130.2 122.1 153.3 130.1 123.3 154.1 130.3 125.5 153.9 130.5 128.2 155.9 130.9 130.4 155.5 131.0 132.8 155.7 131.5 136.0 155.5 131.9 138.8 155.7 132.1 140.8 155.0 132.5 143.7 154.6 132.9 145.6 27 28 29 30 31 32 33 145.6 127.2 77.6 115.4 129.0 115.4 111.4 149.7 130.0 74.8 117.1 130.6 119.6 117.0 149.2 149.4 128.4 129.2 74.7 78.0 116.4 116.7 130.1 130.3 119.8 120.1 116.0 117.0 149.6 150.3 150.8 151.7 152.4 130.3 132.0 133.6 134.4 136.1 82.5 79.5 76.2 77.8 73.5 117.0 117.9 118.8 119.5 120.1 130.6 131.3 131.7 132.1 132.5 120.4 120.7 121.1 121.4 121.6 117.5 118.7 119.7 121.7 122.9 154.7 138.4 74.3 121.3 133.3 122.4 126.6 155.2 140.3 74.7 121.4 133.8 122.8 128.2 156.0 141.0 74.3 122.4 133.9 123.6 129.1 157.0 143.3 80.6 123.1 134.1 124.6 129.4 157.4 145.0 84.4 123.2 134.4 124.8 129.1 34 118.2 120.3 120.0 120.3 120.6 121.8 122.6 123.8 124.2 124.6 124.7 35 116.8 117.5 117.5 117.6 117.6 117.7 117.7 117.7 117.8 118.3 118.8 118.9 119.0 119.0 36 37 112.0 126.3 112.7 130.1 112.7 129.9 112.8 130.1 112.7 130.1 112.6 128.2 112.6 131.5 112.6 131.2 112.7 131.6 113.1 132.2 113.4 132.2 113.1 131.9 113.1 132.0 113.4 131.8 38 120.8 122.1 122.1 122.3 122.2 122.0 122.3 122.6 122.6 122.9 123.1 123.4 123.7 123.6 39 121.5 123.3 123.3 123.5 123.5 123.6 123.6 123.8 124.0 125.0 125.1 125.2 125.5 125.6 42 43 44 45 46 119.8 99.7 105.6 96.6 101.9 119.8 100.0 108.5 102.6 101.9 119.8 99.1 109.1 101.0 102.1 119.8 99.5 109.0 102.3 102.2 102.3 119.8 119.8 100.1 100.3 109.0 108.5 102.9 103.0 102.7 119.8 102.9 108.3 103.7 102.7 119.8 101.4 108.1 106.5 102.9 119.8 101.6 107.9 107.0 103.1 132.1 102.6 108.1 110.9 104.1 132.1 102.6 109.7 110.9 104.4 132.1 102.6 110.7 110.9 104.6 104.5 132.1 132.1 101.9 102.2 110.1 113.6 110.9 110.9 120.8 121.2 121.6 Service industries: Motor freight transportation and warehousing (06/93 = 100) .......... U.S. Postal Service (06/89 = 100)............ Water transportation (12/92 = 100).......... Transportation by air (12/92=100) .......... Pipelines, except natural gas (12/86=100) - Data not available. 36. Annual data: Producer Price Indexes, by stage of processing (1982=100) index 1986 1987 1988 1989 1990 1991 1992 1993 1994 103.2 107.3 63.0 110.6 105.4 109.5 61.8 113.3 108.0 112.6 59.8 117.0 113.6 118.7 65.7 122.1 119.2 124.4 75.0 126.6 121.7 124.1 78.1 131.1 123.2 123.3 77.8 134.2 124.7 125.7 78.0 135.8 125.5 126.8 77.0 137.1 99.1 102.2 72.6 104.9 101.5 105.3 73.0 107.8 107.1 113.2 70.9 115.2 112.0 118.1 76.1 120.2 114.5 118.7 85.5 120.9 114.4 118.1 85.1 121.4 114.7 117.9 84.3 122.0 116.2 118.9 84.6 123.8 118.5 122.1 83.0 127.1 87.7 93.2 71.8 103.1 93.7 96.2 75.0 115.7 96.0 106.1 67.7 133.0 103.1 111.2 75.9 137.9 108.9 113.1 85.9 136.3 101.2 105.5 80.4 128.2 100.4 105.1 78.8 128.4 102.4 108.4 76.7 140.2 101.8 106.5 72.1 156.2 Finished goods: Total ........................................................... Foods ...................................................... Energy..................................................... Other....................................................... Intermediate materials, supplies, and components: Total ........................... Foods ....................... Energy............................ Other ....................... Crude materials for further processing: Total ............................. Foods Energy ............. Other .................... 120FRASER M onthly Labor Review Digitized for https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 37. U.S. export price indexes by Standard International Trade Classification (1990 = 100, unless otherwise indicated) Category Food and live anim als....................................................... ,.............................. Meat and meat preparations............................................................ Cereals and cereal preparations...................................................... Vegetables, fruit, and nuts, prepared fresh or dry............................... Crude materials, Inedible, except fu e ls ....................................................... Hides, skins, and furskins, raw......................................................... Oilseeds and oleaginous fruits ........................................................ Crude rubber (including synthetic and reclaimed) ............................... Cork and wood ............................................................................. Pulp and waste paper..................................................................... Textile fibers and their waste .......................................................... Crude fertilizers and crude minerals................................................. Metalliferous ores and metal scrap .................................................. 1995 1994 SITC Rev. 3 June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. 0 01 04 05 103.9 107.3 101.8 109.6 102.7 105.3 95.7 116.7 102.6 105.9 93.7 117.5 102.4 107.7 96.1 109.6 103.9 108.8 99.6 106.6 105.2 112.4 100.8 109.2 106.7 109.0 103.9 113.3 105.7 109.3 102.8 109.9 106.6 108.7 104.6 109.2 108.3 112.4 103.1 116.8 111.2 113.6 106.7 122.5 2 21 22 23 24 25 26 27 28 108.1 94.4 112.9 96.1 149.4 94.6 105.0 95.6 91.2 109.7 97.9 104.0 99.3 149.6 109.6 102.7 95.4 95.9 109.4 101.0 96.0 100.8 149.9 110.5 102.1 95.8 98.7 108.9 103.9 96.2 99.3 149.1 105.0 101.8 96.2 100.2 108.9 107.2 87.4 102.0 149.0 108.6 100.2 95.4 104.3 112.7 109.9 89.5 104.5 151.0 118.5 103.8 96.4 108.9 116.8 110.4 91.9 104.7 151.5 126.8 110.5 96.4 116.5 120.4 111.2 91.9 109.6 154.6 135.5 116.2 97.5 119.9 124.3 110.7 92.0 115.8 157.8 145.9 122.8 97.2 124.4 127.4 109.6 93.7 117.0 157.3 155.8 132.9 98.4 124.7 130.2 108.3 96.5 121.1 159.4 169.6 131.0 98.5 125.0 Coal, coke, and briquettes.............................................................. Petroleum, petroleum products, and related materials................................................................................... 3 32 87.4 93.9 89.5 93.4 91.0 93.1 87.6 93.3 87.5 93.6 88.2 93.9 89.3 94.1 89.3 94.0 89.4 94.7 88.9 94.7 90.5 96.0 33 80.3 84.2 87.0 81.1 80.6 81.1 82.8 82.8 82.4 81.8 83.6 Animal and vegetable oils, fats, and w a x e s ............................................... 4 110.0 107.4 109.0 116.2 118.1 119.1 132.1 134.7 124.2 121.8 116.1 Chemicals and related products, n.e.s.......................................................... 5 54 55 57 58 59 99.0 108.4 109.2 106.5 99.5 108.7 100.0 107.7 109.5 109.8 99.8 108.5 101.5 107.9 109.4 113.8 100.2 108.9 103.8 107.9 109.7 121.5 101.4 109.0 106.6 107.6 109.5 129.5 104.6 109.2 108.1 107.5 109.7 132.5 104.2 109.7 109.2 107.5 109.4 134.0 104.8 110.9 112.4 107.5 109.7 137.0 105.7 113.1 113.8 107.7 110.1 138.6 106.0 114.3 115.1 108.0 110.4 141.5 106.5 113.1 116.3 108.1 110.4 143.3 108.1 114.3 6 62 104.4 109.2 105.3 109.0 106.1 109.3 106.6 110.2 108.0 110.7 109.3 110.3 110.9 110.5 112.1 111.6 113.1 112.6 113.8 114.6 115.1 114.0 64 66 68 96.2 107.3 92.5 98.5 107.3 95.6 100.3 107.4 97.6 101.8 107.6 98.7 105.9 107.6 102.5 108.2 107.4 107.1 111.0 108.6 111.4 115.6 108.6 113.8 117.1 108.5 116.1 118.5 109.3 115.2 123.7 109.3 116.2 7 71 72 104.1 112.8 109.8 104.1 113.1 109.4 103.8 113.5 109.3 103.7 113.7 109.9 103.7 113.6 109.9 103.8 114.5 109.9 103.7 114.6 109.9 104.0 115.1 110.6 104.2 115.3 111.1 104.2 114.4 111.6 104.3 114.5 112.1 74 75 110.1 81.0 110.1 80.8 110.3 78.8 110.5 78.8 110.5 78.5 110.5 78.4 110.5 78.1 111.2 77.6 111.8 77.2 111.8 76.9 111.9 77.0 76 77 78 107.3 103.2 106.3 107.5 103.0 106.5 107.3 103.1 106.5 106.8 101.8 106.6 106.7 101.9 107.2 106.7 101.7 107.2 106.4 101.5 107.3 107.1 101.8 107.4 107.1 101.5 107.7 106.4 102.3 107.8 105.9 102.5 107.8 87 111.6 111.9 111.9 112.5 112.2 113.1 112.6 113.5 113.4 113.2 113.0 Mineral fuels, lubricants, and related p rodu cts......................................... Medicinal and pharmaceutical products............................................ Essential oils; polishing and cleaning preparations............................. Plastics in primary forms (12/92—100) ............................................ Plastics in nonprimary forms (12/92—100)....................................... Chemical materials and products, n.e.s.............................................. Manufactured goods classified chiefly by m aterials............................................................................................................. Rubber manufactures, n.e.s.............................................................. Paper, paperboard, and articles of paper, pulp, and paperboard............................................................................ Nonmetallic mineral manufactures, n.e.s............................................ Nonferrous metals......................................................................... Machinery and transport equ ipm ent............................................................ Power generating machinery and equipment ..................................... Machinery specialized for particular industries.................................... General industrial machines and parts, n.e.s., and machine parts....................................................................... Computer equipment and office machines........................................ Telecommunications and sound recording and reproducing apparatus and equipment............................................ Electrical machinery and equipment................................................. Road vehicles ............................................................................... Professional, scientific, and controlling instruments and ap p aratu s........................................................................ https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 121 Current Labor Statistics: 38. Price D a ta U.S. import price indexes by Standard international Trade Classification (1990=100, unless otherwise indicated) SITC Rev.3 Category Food and live anim als................................... Meat and meat preparations..................... Fish and crustaceans, mollusks, and other aquatic invertebrates...................... Cereals and cereal preparations................. Vegetables and fruit, prepared fresh or dried ............... Sugars, sugar preparations, and honey........................ Coffee, tea. cocoa, spices, and manufactures thereof ................................. Beverages and to b a c c o .......................................... Beverages.......................................... Crude materials, Inedible, except fu e ls ......................... Crude rubber (including synthetic and reclaimed)................... Cork and wood ........................... Pulp and waste paper...................... Crude fertilizers................................... Metalliferous ores and metal scrap....................... Crude animal and vegetable materials, n.e.s.................................... Mineral fuels, lubricants, and related produ cts......................... Petroleum, petroleum products, and related materials.................................... Gas, natural and manufactured....................................... Electrical energy................................... Animal and vegetable oils, fats, and w a x e s ....................................... Chemicals and related products, n.e.s.................................................... Inorganic chemicals....................................... Dyeing, tanning, and coloring materials .......................................... Medicinal and pharmaceutical products....................................... Essential oils; polishing and cleaning preparations........................... Fertilizers ........................................ Plastics in primary forms (12/92=100)................................ Plastics in nonprimary forms (12/92=100)............................ Chemical materials and products, n.e.s.................................. Manufactured goods classified chiefly by material ................................. Rubber manufactures, n.e.s.............................................. Paper, paperboard, and articles of paper pulp, paper, or paperboard ............................................ Nonmetallic mineral manufactures, n.e.s...................................... Nonferrous metals..................................................... Manufactures of metals, n.e.s.................................................... Machinery and transport equipment .................................................. Machinery specialized for particular industries................................. General industrial machinery and equipment, n.e.s., and machine parts........................................................ Computer equipment and office machines...................................... Telecommunications and sound recording and reproducing apparatus and equipment......................................... Electrical machinery and equipment............................................... Road vehicles .................................................................. Footwear........................................................... Photographic apparatus, equipment, and supplies, and optical goods, n.e.s............................................................. M onthly Labor Review 122 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 1994 1995 Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May 0 01 118.0 90.7 118.8 91.9 120.6 91.0 118.4 90.9 118.7 91.7 120.1 90.3 116.9 89.7 120.6 88.6 116.0 86.6 117.9 85.1 03 04 05 06 123.6 101.7 99.9 98.8 123.5 100.5 100.1 96.8 126.1 102.5 99.4 97.1 126.5 101.9 100.6 96.7 127.9 101.9 112.6 97.2 125.7 101.6 120.3 98.3 125.6 101.5 110.0 98.8 127.7 102.0 114.4 98.1 127.0 93.3 104.1 99.6 126.0 99.4 111.6 98.4 07 195.9 202.2 212.0 194.5 172.3 172.2 168.6 183.7 176.6 178.1 1 11 113.6 113.1 113.4 113.5 113.6 113.6 113.7 113.8 113.5 113.6 114.0 114.2 113.4 113.6 114.4 114.5 115.0 114.7 114.6 114.7 2 23 24 25 27 28 29 107.2 119.6 154.8 76.7 82.4 90.2 118.6 108.5 121.0 155.4 80.1 82.3 92.3 118.3 110.4 134.0 151.3 86.4 86.0 92.8 117.4 113.9 135.7 157.2 90.0 86.1 94.3 126.6 114.6 143.8 149.6 90.7 86.6 97.2 139.2 118.9 159.8 152.7 97.4 87.9 98.6 142.8 121.6 164.8 150.0 97.4 87.9 101.1 166.3 121.3 165.6 143.3 104.7 89.6 106.6 140.1 123.1 170.4 141.1 108.1 91.8 105.8 154.7 123.5 167.3 139.2 109.5 97.2 105.8 160.9 3 79.2 73.5 73.9 76.9 75.3 76.0 77.8 79.1 82.3 84.9 33 34 35 78.6 86.9 92.4 72.6 87.4 88.8 73.1 86.0 86.2 76.1 87.5 83.3 74.5 88.3 83.5 75.4 84.8 82.3 77.5 81.7 79.9 79.0 79.1 78.0 82.4 79.2 77.4 85.0 81.4 81.1 4 136.9 140.0 141.6 144.1 155.0 152.2 145.4 151.8 153.6 157.3 5 52 53 54 55 56 57 58 59 103.9 100.7 102.7 120.3 110.7 101.0 103.1 99.4 103.1 105.7 102.7 102.5 119.7 110.5 102.1 101.6 102.8 105.2 106.6 105.6 102.9 120.2 111.8 105.0 101.4 102.1 103.1 107.8 106.8 103.2 121.4 112.7 107.0 102.1 105.8 103.4 108.8 107.6 102.9 120.5 113.4 107.2 102.9 107.1 103.7 109.1 108.5 102.4 120.2 114.5 108.2 107.3 110.0 102.6 110.1 109.4 103.3 120.7 115.3 109.7 107.3 112.8 103.4 110.8 113.1 106.4 121.4 116.8 112.0 106.8 115.5 103.8 111.2 112.2 110.9 124.6 120.1 113.1 109.0 116.5 105.0 113.3 113.2 109.1 128.9 124.1 112.8 110.3 119.9 105.7 6 62 102.4 102.2 103.0 101.5 103.9 102.5 105.4 102.6 106.4 102.3 107.4 102.4 108.8 102.1 109.2 102.8 110.6 103.7 112.0 105.2 64 66 68 69 97.9 108.9 90.0 105.7 99.4 109.8 91.0 106.0 99.2 109.6 95.6 106.2 101.3 109.9 99.1 107.0 105.2 110.5 103.1 106.4 108.6 110.4 105.6 106.3 109.9 110.7 110.8 107.0 114.3 110.8 106.1 108.5 119.4 111.1 105.6 110.0 125.2 111.3 106.0 110.6 7 72 107.4 111.5 107.4 111.5 108.1 112.0 108.2 112.8 108.0 112.5 107.9 112.3 108.2 113.2 108.5 114.0 109.5 116.0 110.2 117.1 74 75 110.5 86.0 110.3 86.0 110.9 85.7 111.6 84.5 111.6 84.8 112.1 84.7 112.8 84.6 113.0 84.0 115.8 84.2 116.5 84.1 76 77 78 97.8 106.8 113.4 97.5 106.6 113.5 97.6 106.9 115.0 97.7 106.7 115.3 97.7 106.5 115.1 97.4 106.4 115.0 97.6 106.6 115.3 97.7 106.9 115.8 98.8 107.6 116.3 99.8 108.9 116.8 85 101.0 101.0 101.0 101.3 101.1 100.7 101.0 101.1 101.5 101.7 88 110.6 110.8 111.1 110.8 110.6 109.9 110.7 111.0 113.4 115.6 39. U.S. export price indexes by end-use category (1990 = 100 unless otherwise indicated) 1995 1994 Category Aug. Sept. Oct. Nov. Jan. Dec. Apr. Mar. Feb. May ALL CO M M O DITIES............................................................................... 103.6 103.8 104.4 105.1 105.8 106.7 107.3 107.9 108.9 109.2 Foods, feeds, and beverages ................................................ Agricultural foods, feeds, and beverages.............................. Nonagricultural (fish, beverages) food products......................................................................... 101.1 100.1 101.3 100.3 101.5 100.1 102.9 101.5 104.7 103.4 103.8 102.5 104.5 102.8 106.0 103.9 108.7 106.8 109.5 107.7 108.2 107.9 112.1 112.8 113.0 113.5 117.1 122.1 123.3 122.6 Industrial supplies and materials............................................ 103.5 104.3 106.0 107.9 109.9 112.5 114.1 115.3 117.1 117.8 Agricultural industrial supplies and materials ................................................................. 105.7 107.1 107.7 109.7 114.4 117.7 118.7 122.0 120.6 120.3 92.9 90.3 90.0 90.6 91.4 91.5 91.6 91.0 92.7 94.1 114.2 153.3 115.5 153.4 117.9 153.5 119.0 151.0 Fuels and lubricants .......................................................... Nonagricultural supplies and materials, excluding fuel and building materials.................................. Selected building materials................................................. 104.9 147.3 107.1 148.6 109.2 149.7 103.7 103.6 103.7 103.6 103.9 104.0 104.2 104.6 104.7 106.6 100.8 106.7 100.6 106.8 100.8 106.4 100.6 106.9 100.9 107.0 100.9 107.2 101.0 108.1 101.4 107.9 101.5 106.6 106.7 107.2 107.2 107.3 107.4 107.7 107.4 107.4 107.5 Consumer goods, excluding automotive.................................. Nondurables, manufactured................................................ Durables, manufactured..................................................... Nonmanufactured consumer goods...................................... 107.9 109.9 106.0 99.3 108.1 110.1 106.3 98.4 108.2 110.1 106.5 99.3 108.3 110.2 106.6 98.9 108.2 110.0 106.3 100.7 108.3 110.3 106.3 - 108.8 110.9 106.9 - 109.0 111.3 106.9 99.9 109.3 111.6 107.2 .0 109.5 111.8 107.3 .0 Agricultural commodities....................................................... Nonagricultural commodities................................................. 101.2 104.0 101.7 104.2 101.6 104.9 103.2 105.5 105.7 106.0 105.6 107.0 106.1 107.7 107.7 108.1 109.7 108.9 110.3 109.2 101.2 147.4 102.6 147.2 Capital goods...................................................................... Electric and electrical generating equipment................................... .................................. Nonelectrical machinery..................................................... 103.7 106.5 101.0 Automotive vehicles, parts, and engines................................. 112.2 151.4 - Data not available. 40. U.S. import price indexes by end-use category (1990 = 100) 1995 1994 Category Aug. Sept. Oct. Nov. Jan. Dec. Feb. Mar. Apr. May ALL CO M M O DITIES............................................................................... 103.3 102.8 103.5 104.2 104.1 104.4 105.1 105.7 106.7 107.8 Foods, feeds, and beverages ................................................ Agricultural foods, feeds, and beverages .............................. Nonagricultural (fish, beverages) food products......................................................................... 119.0 117.2 120.0 118.5 121.8 120.2 120.1 117.7 120.2 117.6 121.1 119.4 118.7 116.2 121.9 119.9 118.8 115.7 120.2 118.0 123.2 123.5 125.3 125.7 126.7 125.1 125.0 126.7 126.3 125.5 Industrial supplies and materials............................................ 92.5 90.6 91.5 93.8 93.7 94.8 96.6 97.7 99.8 101.7 Fuels and lubricants ............................................................ Petroleum and petroleum products ...................................... 80.0 78.1 74.5 72.2 74.8 72.8 77.7 75.8 76.1 74.2 77.0 75.1 78.7 77.1 80.3 78.6 83.5 81.9 86.1 84.4 Paper and paper base stocks................................................ Materials assiciated with nondurable supplies and materials ................................................................. Selected building materials............................... .................... Unfinished metals associated with durable goods.................... Nonmetals associated with durable goods .............................. 90.9 93.0 94.7 96.8 100.1 104.7 107.2 112.2 117.1 121.3 104.6 128.4 93.9 98.7 106.4 128.6 95.3 98.0 107.5 126.5 98.1 100.4 109.4 129.8 100.1 100.5 110.3 125.7 102.5 100.7 111.5 125.7 103.8 100.8 112.7 125.2 107.5 101.2 113.3 123.1 106.2 103.0 113.8 122.4 106.8 104.4 115.3 122.0 106.7 107.5 105.1 109.2 103.7 105.2 109.6 103.8 106.3 110.9 104.9 107.2 112.2 105.8 Capital goods...................................................................... Electric and electrical generating equipment......................... Nonelectrical machinery..................................................... Transportation equipment, excluding motor vehicles and spacecraft (12/92 = 100) ............................. Automotive vehicles, parts and engines.................................. 104.9 107.7 103.7 104.8 107.4 103.7 105.1 107.7 103.9 105.0 108.3 103.7 104.9 108.1 103.6 104.7 107.9 103.4 104.7 111.5 105.2 111.6 105.7 112.9 105.8 113.2 105.3 113.0 - - - - - 112.9 113.2 113.6 114.3 115.0 Consumer goods, excluding automotives................................ Nondurables, manufactured................................................ Durables, manufactured ..................................................... Nonmanufactured consumer goods...................................... 105.9 105.8 105.5 110.0 106.0 106.0 105.6 110.3 106.2 106.2 105.6 110.6 106.4 106.5 105.6 112.0 106.4 106.4 105.6 113.4 106.3 106.1 105.6 114.0 106.8 106.4 106.0 117.2 106.8 106.9 106.2 112.1 107.3 107.1 106.6 114.1 107.9 107.7 107.4 114.8 - Data not available. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis M onthly Labor Review August 1995 123 Current Labor Statistics: 41. Price a n d Productivity D ata U.S. international price indexes for selected categories of services (1990 = 100 unless otherwise indicated)) 1995 1994 1993 Category Mar. June Sept. Mar. Dec. Sept. June Air freight (inbound) ..................................................... Air freight (outbound).................................................... 100.1 97.3 106.4 96.6 106.6 95.6 106.1 96.4 105.9 96.5 108.1 96.2 Air passenger fares (U.S. carriers) ................................. Air passenger fares (foreign carriers).............................. Ocean liner freight (inbound)......................................... 109.8 108.0 104.0 117.2 115.7 103.5 119.0 117.0 103.3 111.4 107.2 102.1 113.1 108.1 103.4 119.7 114.6 106.3 42. Mar. Dec. 108.6 96.2 110.4 97.3 115.4 98.1 121.4 118.1 106.2 113.8 110.0 106.6 116.1 113.8 106.6 Indexes of productivity, hourly compensation, and unit costs, quarterly data seasonally adjusted (1982 = 100) Quarterly Indexes Item 1992 1994 1993 III IV 115.8 156.0 106.8 134.7 145.8 138.3 116.8 157.7 107.1 135.1 150.2 140.1 116.2 158.7 107.0 136.6 149.5 140.8 113.9 154.7 105.9 135.8 147.1 139.5 115.0 156.4 106.2 136.1 152.1 141.2 119.1 151.5 103.7 124.9 127.2 119.0 171.0 128.8 127.7 127.6 148.3 101.6 116.3 I III IV 116.3 159.9 107.0 137.5 149.6 141.4 117.0 160.6 107.0 137.3 150.5 141.6 118.4 161.3 106.6 136.2 154.0 142.1 118.9 163.3 107.4 137.3 153.4 142.6 114.3 157.2 105.9 137.4 151.5 142.0 114.5 158.1 105.8 138.1 151.8 142.5 115.3 158.7 105.7 137.7 153.6 142.8 116.5 159.3 105.3 136.8 156.3 143.1 120.6 153.1 104.0 123.8 127.0 115.7 191.2 129.9 127.9 119.9 153.9 103.7 125.0 128.3 116.8 183.7 129.4 128.7 121.2 154.4 103.3 124.1 127.3 115.8 199.4 131.5 128.7 122.2 154.8 103.1 123.6 126.7 115.8 202.5 132.1 128.5 129.1 150.7 102.3 116.8 130.8 149.9 101.0 114.6 131.3 151.7 101.5 115.5 132.1 152.5 101.6 115.4 II 1995 III IV 118.5 163.6 106.9 138.1 155.6 143.8 119.5 164.9 106.8 138.0 157.8 144.5 120.7 166.4 107.2 137.8 159.0 144.8 121.4 168.0 107.4 138.4 159.5 145.3 117.0 161.2 106.0 137.8 155.5 143.5 116.6 161.8 105.7 138.8 158.3 145.1 117.3 162.9 105.5 138.8 160.9 145.9 118.6 164.4 105.9 138.7 161.8 146.1 119.4 166.2 106.2 139.2 162.3 146.7 123.4 155.0 102.5 122.6 125.7 114.8 220.9 134.8 128.7 124.0 156.5 102.9 123.5 126.2 116.6 218.2 135.7 129.4 123.8 156.8 102.4 123.4 126.7 115.2 228.7 136.6 129.9 124.3 157.9 102.3 124.0 127.1 116.2 228.8 137.4 130.5 125.3 159.1 102.5 123.8 127.0 115.9 230.3 137.4 130.4 125.9 160.6 102.7 124.3 127.6 116.1 224.9 136.6 130.5 133.6 153.3 101.4 114.7 135.4 154.3 101.4 113.9 136.8 153.6 100.3 112.2 138.0 154.5 100.0 111.9 139.3 155.9 100.4 112.0 140.4 157.7 100.8 112.3 I II I 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............................................. Digitized for124 FRASER M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 43. Annual indexes of multifactor productivity and related measures, selected years (1987=100) Item 1960 1970 1973 1980 1986 1987 1988 1989 1990 1991 1992 1993 Private business: Productivity: Output per hour of all persons....................... Output per unit of capital services.................. Multifactor productivity........................ Output............................................ Inputs: Labor input................ Capital services ............................ Combined units of labor and capital input....... Capital per hour of all persons......................... 53.5 116.0 70.5 37.8 74.8 115.1 87.2 57.4 83.0 120.1 95.3 67.9 89.1 105.8 96.0 79.9 99.6 99.7 99.8 96.7 100.0 100.0 100.0 100.0 100.9 101.4 100.5 104.3 101.0 101.3 100.3 107.0 101.9 99.8 100.0 107.9 102.9 96.8 99.0 106.5 105.9 97.9 100.5 109.3 106.6 98.8 101.1 112.5 66.7 32.6 53.4 46.3 74.2 49.8 65.7 64.9 78.7 56.6 71.1 69.2 86.8 75.5 83.1 84.2 96.8 97.0 96.8 99.8 100.0 100.0 100.0 100.0 104.2 102.9 103.7 99.6 107.2 105.6 106.7 99.7 107.8 108.2 107.8 102.1 106.5 110.0 107.5 106.1 107.5 111.6 108.6 107.9 110.1 113.8 57.7 122.6 74.9 37.4 77.3 120.5 89.9 57.4 85.6 125.3 98.1 68.3 90.6 108.2 97.7 80.2 99.8 100.0 100.0 96.7 100.0 100.0 100.0 100.0 100.9 101.3 100.5 104.5 100.7 100.9 99.9 107.1 101.3 99.1 99.4 107.8 102.5 96.0 98.5 106.4 105.1 96.8 99.6 108.9 105.9 97.8 100.3 112.4 61.4 30.5 49.7 47.1 72.0 47.7 63.8 64.0 76.9 54.5 69.4 68.3 85.7 74.2 82.0 83.8 96.6 96.7 96.6 99.8 100.0 100.0 100.0 100.0 104.4 103.2 103.9 99.6 107.6 106.1 107.1 99.9 108.3 108.8 108.4 102.3 106.8 110.8 107.9 106.6 108.0 112.6 109.2 108.5 110.9 115.0 - - Private nonfarm business: Productivity: Output per hour of all persons ....................... Output per unit of capital services.................. Multifactor productivity............................... Output.................................... Inputs: Labor input................................................... Capital services ................................ Combined units of labor and capital input....... Capital per hour of all persons......................... - Data not available. NOTE: Productivity and output in this table have not been revised for 44. - - consistency with the December 1991 comprehensive revisions to the National Income and Product Accounts. Annual indexes of productivity, hourly compensation, unit costs, and prices, selected years (1982 = 100) Item 1960 1970 1973 1983 1985 1987 1988 1989 1990 1991 1992 1993 1994 Output per hour of all persons......................... Compensation per hour................................... Real compensation per hour........................... Unit labor costs ..................... Unit nonlabor payments .................................. Implicit price deflator ...................................... 65.6 21.1 68.8 32.2 33.6 32.6 87.0 36.7 91.3 42.2 42.7 42.4 95.1 45.1 98.1 47.5 52.1 49.0 102.3 103.8 100.6 101.5 107.5 103.4 106.3 113.2 101.5 106.5 120.8 111.2 109.6 123.1 104.6 112.3 125.5 116.6 110.7 128.5 104.8 116.0 130.6 120.8 109.9 133.0 103.5 121.0 136.6 126.1 110.7 140.6 103.8 127.1 139.8 131.2 112.1 147.4 104.4 131.5 144.9 135.9 115.5 154.9 106.6 134.2 148.3 138.8 117.0 160.1 106.9 136.9 150.9 141.5 119.7 165.1 107.5 137.9 156.3 143.9 69.9 22.2 72.4 31.8 33.3 32.3 88.5 37.0 92.0 41.8 43.0 42.2 96.4 45.4 98.7 47.1 49.6 47.9 102.5 104.0 100.8 101.5 109.2 104.0 105.6 112.8 101.1 106.8 121.6 111.6 108.6 122.5 104.1 112.8 126.6 117.2 109.6 127.7 104.2 116.5 131.8 121.4 108.6 132.0 102.7 121.5 137.1 126.5 109.1 139.2 102.8 127.6 140.6 131.8 110.7 146.2 103.6 132.1 146.5 136.7 113.7 153.7 105.7 135.2 149.7 139.9 115.2 158.3 105.7 137.5 153.4 142.6 117.7 163.1 106.2 138.6 159.1 145.2 75.3 23.6 77.0 29.5 31.4 24.8 75.1 34.2 32.3 90.3 38.4 95.4 40.5 42.5 35.5 69.5 41.9 42.3 95.0 46.6 101.2 46.5 49.0 40.2 87.9 49.2 49.1 103.8 103.4 100.2 99.5 99.6 99.3 135.9 106.2 101.8 106.5 112.0 100.4 103.7 105.2 100.1 168.1 112.9 107.7 111.2 120.9 102.7 107.0 108.8 102.5 172.1 115.6 111.0 113.3 125.9 102.7 109.8 111.1 106.4 183.5 120.9 114.3 111.5 130.2 101.3 115.7 116.8 112.9 168.5 123.3 119.0 112.7 137.1 101.3 120.1 121.7 116.3 167.5 125.9 123.1 115.0 143.8 101.9 123.7 125.0 120.5 164.7 128.8 126.3 118.5 150.4 103.5 124.4 126.9 118.0 177.2 129.1 127.7 121.8 154.6 103.3 123.8 127.0 115.8 201.9 132.0 128.6 124.8 158.2 103.0 123.7 126.7 116.0 226.5 136.8 130.0 102.2 102.7 99.5 100.5 113.5 103.8 106.7 111.3 99.8 104.2 120.1 108.2 116.6 118.4 100.6 101.6 134.5 109.8 119.2 123.1 100.4 103.2 147.4 114.3 119.9 127.9 99.5 106.7 153.3 118.4 122.1 134.7 99.5 110.4 153.7 121.2 124.9 141.9 100.5 113.7 157.0 124.5 127.5 147.9 101.7 116.0 157.0 126.3 132.0 152.0 101.5 115.1 160.8 126.5 137.4 154.5 100.6 112.5 Business: 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 M onthly Labor Review August 1995 125 Current Labor Statistics: 45. P roductivity D ata Annual indexes of output per hour for selected industries (1987= 100) Industry SIC 1973 1979 1985 1986 1987 1988 1989 1990 1991 Iron mining, usable ore ............................... Copper mining, recoverable metal................. Coal mining................................................ Crude petroleum and natural gas.................. Nonmetallic minerals, except fuels................ 101 102 12 131 14 1 51.7 142.4 1 68.9 1 173.5 1 86.5 1 51.8 148.5 1 54.5 1 110.3 1 92.6 1 76.6 1 93.6 1 85.1 1 83.0 1 95.1 1 79.6 1 109.7 1 92.4 1 90.3 1 95.1 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 103.7 1 109.8 1 110.6 1 101.0 1 102.2 1 99.5 1 107.8 1 116.5 1 98.1 1 101.9 1 90.0 1 104.5 1 118.5 1 97.0 1 108.3 187.0 1 102.9 1 122.1 1 98.1 1 103.6 Meatpacking plants..................................... Sausages and other prepared meats............. Poultry dressing and processing................... Cheese, natural and processed.................... Fluid milk................................................... Canned fruits and vegetables....................... Frozen fruits and vegetables........................ Flour and other grain mill products............... Cereal breakfast foods................................ Rice milling ................................................ Wet corn milling ......................................... 2011 2013 2015 2022 2026 2033 2037 2041 2043 2044 2046 165.1 167.2 1 58.0 1 56.6 1 49.5 1 66.0 1 80.1 1 68.5 1 65.6 1 59.3 1 24.1 ’ 75.0 192.8 181.7 1 79.8 162.7 1 74.0 ’ 86.6 180.5 1 74.2 169.3 1 47.1 1 98.3 1 97.8 1 100.5 1 94.7 1 88.3 193.0 197.0 195.8 1 97.1 1 68.6 1 74.6 1 98.7 1 98.6 1 95.6 1 101.1 1 94.0 1 98.4 1 104.9 195.9 1 98.6 1 72.7 197.3 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 99.5 1 105.6 1 95.9 1 106.4 1 103.9 1 100.2 1 95.1 1 102.0 1 98.6 183.8 1 96.6 1 92.2 1 99.8 1 101.2 1 104.3 ’ 106.7 1 92.5 1 98.9 1 101.6 1 96.0 1 98.6 1 103.0 1 92.9 1 93.6 1 107.7 1 101.1 1 108.0 1 96.2 1 92.3 1 107.0 1 102.0 1 106.9 1 104.7 1 94.9 1 90.8 1 114.2 1 98.9 1 110.7 1 103.4 1 98.7 1 107.4 1 105.3 1 101.1 1 100.1 Prepared feeds for animals and fowls........... Bakery products......................................... Raw and refined cane sugar........................ Beet sugar ................................................ Malt beverages........................................... Bottled and canned soft drinks..................... Fresh or frozen fish and seafood.................. Cigarettes, chewing and smoking tobacco..... 2047,48 2051,52 2061,62 2063 2082 2086 2092 211,3 1 51.6 1 82.3 ' 76.7 1 75.9 143.3 149.2 1 93.2 1 79.4 1 66.5 1 83.8 1 96.4 1 78.3 1 63.8 1 64.4 ’ 93.8 190.3 1 96.9 1 95.6 196.6 1 73.4 173.7 1 85.2 188.0 193.5 1 95.2 1 100.1 1 96.9 1 80.8 1 85.1 1 91.4 1 91.2 1 95.3 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 101.2 1 93.8 1 97.5 1 95.3 1 99.1 1 109.9 1 99.2 1 106.8 1 103.1 1 93.2 1 97.4 1 87.9 1 102.0 1 119.3 1 92.9 1 107.3 1 106.6 1 96.2 1 100.9 1 91.1 1 110.9 1 126.7 187.1 1 112.9 1 107.2 1 92.9 1 101.3 1 93.4 1 110.1 r 135.1 1 84.8 1 119.2 Cotton and synthetic broadwoven fabrics...... Hosiery ..................................................... Yarn spinning mills...................................... Men’s and boys’ suits and coats.................. 221,2 2251,52 2281 231 1 58.1 1 63.2 1 55.9 1 75.6 1 75.6 1 93.3 168.3 1 95.9 193.4 1 100.9 1 89.6 1 106.3 1 99.0 1 102.5 1 93.2 1 103.5 1 100.0 1 100.0 1 100.0 1 100.0 1 100.3 1 107.0 1 98.6 1 102.5 1 104.5 1 108.4 1 103.6 1 101.9 1 109.3 1 106.0 1 106.7 1 98.8 1 115.2 1 111.3 ’ 106.3 1 91.3 Sawmills and planing mills, general .............. Hardwood dimension and flooring................. Millwork .................................................... Wood kitchen cabinets................................ Hardwood veneer and plywood .................... Softwood veneer and plywood ..................... Wood containers........................................ Wood household furniture ........................... Upholstered household furniture................... Metal household furniture............................ Mattresses and bedsprings .......................... Wood office furniture................................... Office furniture, except wood....................... Pulp, paper, and paperboard mills................. Corrugated and solid fiber boxes .................. Folding paperboard boxes........................... Paper and plastic bags ............................... 2421 2426 2431 2434 2435 2436 244 2511,17 2512 2514 2515 2521 2522 261,2,3 2653 2657 2673,74 1 68.3 1 84.0 ’ 104.2 1 80.5 1 80.2 1 67.7 1 91.2 1 71.9 1 75.6 1 71.6 1 82.5 1 70.6 1 67.1 1 70.3 1 86.4 1 90.7 1 73.3 1 83.0 1 95.4 1 89.1 1 79.6 1 65.6 1 72.9 1 90.4 182.8 172.5 1 86.2 1 117.0 1 76.7 1 77.3 1 87.2 1 90.7 1 94.1 1 93.5 1 95.1 1 97.4 187.1 184.5 188.3 1 99.6 1 93.3 1 98.6 1 98.8 1 77.2 1 99.4 1 96.9 1 87.6 1 99.6 190.0 1 99.7 1 102.3 1 98.8 1 102.2 1 85.2 1 83.2 1 90.4 1 98.7 1 100.2 1 100.6 1 101.7 1 83.1 1 96.2 1 100.6 1 93.3 1 102.8 1 88.5 1 101.8 1 100.0 ’ 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 101.7 1 97.4 1 98.3 1 97.8 1 98.3 1 100.3 1 103.4 1 101.0 1 99.8 1 100.6 1 99.2 1 94.8 1 96.0 ’ 102.9 1 99.6 1 99.6 1 97.4 1 101.0 1 96.5 1 97.7 1 91.0 ’ 97.4 1 102.0 1 108.9 ' 100.1 1 101.0 1 100.0 1 105.0 1 94.2 1 99.0 1 103.2 1 97.7 1 101.1 193.6 1 101.5 1 95.4 1 97.9 193.7 1 90.2 1 107.3 1 112.0 1 98.8 1 98.5 1 103.9 1 105.7 1 95.8 1 95.7 1 102.1 1 100.3 1 99.4 1 91.4 1 105.0 1 98.2 1 95.8 1 92.6 1 90.7 1 113.0 ' 114.2 1 100.2 1 103.4 1 107.3 1 110.3 1 99.1 1 93.0 1 101.5 1 100.0 1 102.8 1 88.6 Alkalies and chlorine ................................... Inorganic pigments ..................................... Industrial inorganic chemicals, not elsewhere classified................................... Synthetic fibers........................................... Soaps and detergents................................. Cosmetics and other toiletries ...................... Paints and allied products........................... Industrial organic chemicals, not elsewhere classified................................... Nitrogenous fertilizers.................................. Phosphatic fertilizers ................................... Fertilizers, mixing only................................. Agricultural chemicals, not elsewhere classified.................................. 2812 2816 1 38.4 ’ 72.6 1 50.8 1 67.8 1 70.8 1 84.4 1 97.7 1 88.6 1 100.0 1 100.9 1 92.6 1 90.7 1 84.0 1 100.0 1 101.2 1 107.3 1 102.5 1 96.3 2819 pt. 2823,24 2841 2844 285 1 90.6 1 38.4 1 89.1 1 88.6 163.2 1 91.5 1 70.9 1 91.0 1 93.6 1 79.8 187.3 1 79.3 1 91.5 1 90.3 1 96.9 188.6 ’ 90.8 1 92.3 1 96.6 1 98.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 96.8 1 102.7 1 103.4 1 105.0 1 103.0 1 104.3 1 103.5 1 110.7 1 101.6 1 106.6 1 106.8 ’ 98.3 1 132.1 1 100.8 1 111.4 1 99.0 1 97.1 1 131.7 1 103.4 1 111.2 2869 2873 2874 2875 1 73.1 1 65.4 1 62.4 1 90.5 1 93.0 1 72.7 1 68.3 1 110.9 1 87.8 1 100.7 1 84.2 1 100.8 1 92.3 1 90.5 1 79.6 195.1 1 100.0 1 100.0 1 100.0 1 100.0 1 110.7 1 101.7 1 93.4 1 103.4 1 109.9 1 105.4 1 85.6 1 110.8 1 99.5 1 108.9 1 104.5 1 108.7 1 93.2 1 110.1 1 114.5 1 109.3 2879 1 74.3 1 83.6 1 92.9 1 93.2 1 100.0 1 108.4 1 108.9 1 106.2 1 102.8 Petroleum refining....................................... Tires and inner tubes .................................. Rubber and plastics hose and belting........... Miscellaneous plastic products, not elsewhere classified.................................. Footwear................................................... Glass containers ........................................ Cement, hydraulic....................................... Clay construction products........................... Clay refractories......................................... Concrete products ...................................... Ready-mixed concrete ................................ 291 301 3052 1 84.0 1 56.0 1 79.3 182.6 1 63.9 1 80.6 1 84.7 1 94.9 1 100.0 1 105.3 1 109.6 1 109.1 1 106.7 1 89.3 1 92.6 1 100.0 1 104.6 1 107.2 1 108.3 1 109.5 1 100.5 1 102.2 1 100.0 1 107.3 1 96.3 1 100.9 1 93.0 308 314 3221 324 3251,53,59 3255 3271,72 3273 1 72.8 1 89.9 1 75.2 1 71.3 1 78.5 180.1 1 92.5 1 99.1 1 74.3 1 94.5 1 83.8 1 68.7 1 79.0 1 93.9 1 91.3 1 96.2 ' 88.2 1 99.9 ' 93.4 1 91.8 1 94.2 1 94.9 1 99.5 ’ 93.7 1 88.9 1 101.7 1 98.5 1 97.1 1 95.5 1 100.8 1 104.4 196.1 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 98.4 1 102.4 1 101.1 ' 103.3 1 103.9 1 101.3 1 102.3 1 100.3 ' 97.5 1 101.4 1 104.8 1 110.1 1 96.7 1 97.3 1 105.2 1 101.0 1 100.4 1 93.0 1 112.5 1 112.5 1 100.5 1 102.2 1 104.6 1 99.7 1 100.9 1 93.3 1 114.9 1 108.3 1 95.1 1 96.2 1 105.9 196.1 Steel ......................................................... Gray and ductile iron foundries..................... Steel foundries ........................................... Primary copper........................................... Primary aluminum........................................ Copper rolling and drawing .......................... Aluminum rolling and drawing...................... 331 3321 3324,25 3331 3334 3351 3353,54,55 164.2 1 91.3 1 105.8 132.8 1 73.6 1 77.5 1 79.0 165.9 1 92.4 1 104.5 141.1 ' 74.7 1 82.0 1 84.3 1 85.8 1 96.9 199.5 1 73.8 1 97.6 186.2 1 85.7 1 89.7 1 99.3 1 104.9 ’ 88.7 1 102.7 1 92.3 1 95.8 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 113.4 1 106.8 1 95.3 1 103.7 1 102.2 1 100.0 1 96.9 1 108.5 1 104.1 1 96.6 1 96.8 1 104.6 1 94.1 1 91.2 1 110.5 ' 104.1 1 95.9 1 86.3 1 106.3 1 93.9 1 92.4 1 108.1 1 99.3 1 93.2 184.7 1 110.3 ’ 96.9 192.0 See footnotes at end of table. Digitized for126 FRASER M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 45. Continued—Annual indexes of output per hour for selected industries (1987= 100) Industry Metal cans....................................... Hand and edge tools, not elsewhere classified........................................ Heating equipment, except electric............... Fabricated structural metal........................... Metal doors, sash, and trim.......................... Bolts, nuts, rivets, and washers ..................... Automotive stampings............................... Metal stampings, not elsewhere classified................................. SIC 1973 1979 1985 1986 1987 3411 159.2 1 75.2 199.2 1 95.9 1 100.0 1 107.4 1 109.0 1 119.1 1 126.0. 3423 3433 3441 3442 3452 3465 1 108.6 ’ 78.0 198.1 1 90.5 1 75.8 1 74.9 1 111.6 ' 86.2 186.0 192.6 1 78.9 1 81.4 ' 98.8 1 91.9 1 98.6 1 104.8 188.8 194.5 197.1 1 96.2 1 98.8 1 102.0 191.0 1 95.7 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 196.8 1 100.2 1 88.6 1 93.9 1 100.0 1 99.6 3469 1988 1 100.9 1 112.7 198.9 1 102.4 1 97.0 1 104.5 1989 1990 1991 1 102.1 1 103.2 1 94.7 1 101.5 1 93.8 1 104.7 196.4 1 111.2 1 96.8 1 97.0 1 93.7 1 100.8 ' 95.0 1 115.4 1 98.3 194.7 1 96.2 1 104.2 198.3 1 95.1 1 96.3 Valves and pipe fittings............................... Fabricated pipe and fittings.......................... Internal combustion engines, not elsewhere classified................................ Farm machinery and equipment................... Lawn and garden equipment........................ Construction machinery............................... Mining machinery....................................... Oil and gas field machinery.......................... 3491,92,94 3498 3519 3523 3524 3531 3532 3533 1 83.1 1 108.6 1 70.0 1 87.9 1 102.2 1 105.9 186.4 1 112.6 1 83.3 1 91.5 1 89.3 1 100.6 1 92.0 1 101.6 1 82.4 1 92.2 1 93.7 192.3 1 98.5 1 95.7 1 93.2 1 99.1 1 95.1 195.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 105.1 1 112.5 1 97.2 1 107.2 1 102.2 1 99.3 1 110.9 1 123.1 1 91.9 1 109.7 1 107.3 1 104.6 1 105.0 1 130.6 193.4 1 108.9 1 99.0 1 107.4 1 98.9 1 123.6 1 94.5 1 98.2 1 90.7 1 109.2 Metal-cutting machine tools ........................ Metal-forming machine tools........................ Machine tool accessories............................ Pumps and pumping equipment................... Ball and roller bearings............................... Air and gas compressors............................. Refrigeration and heating equipment............. Carburetors, pistons, rings, and valves.......... 3541 3542 3545 3561,94 3562 3563 3585 3592 ’ 101.4 1 112.5 1 105.9 1 84.0 1 108.0 1 87.6 1 100.3 1 102.9 1 100.9 1 98.5 1 100.6 191.4 1 110.2 1 86.1 1 98.8 182.0 189.9 1 93.1 1 92.3 1 91.9 1 91.6 1 92.2 1 98.1 1 98.9 1 92.0 1 93.7 1 95.0 192.7 1 94.1 1 96.0 1 95.8 195.7 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 196.1 1 113.8 1 99.3 1 107.3 1 102.4 1 104.1 1 103.5 1 108.8 1 101.2 1 109.9 1 104.6 1 101.4 1 98.2 1 106.1 1 105.7 1 117.1 1 103.1 1 100.6 1 107.4 1 103.4 1 92.1 1 109.2 1 104.6 1 110.9 1 100.2 1 91.9 1 109.2 1 102.6 1 88.3 1 111.8 1 102.6 1 110.7 Transformers, except electronic ................... Switchgear and switchboard apparatus.......... Motors and generators................................ Household cooking equipment...................... Household refrigerators and freezers ............ Household laundry equipment....................... Household appliances, not elsewhere classified................................................. Electric lamps............................................ Lighting fixtures and equipment.................... Household audio and video equipment.......... Motor vehicles and equipment...................... Aircraft............................................... Instruments to measure electricity................. Photographic equipment and supplies........... 3612 3613 3621 3631 3632 3633 1 100.2 188.2 189.0 161.8 1 70.1 1 72.3 1 109.8 1 87.5 189.7 1 79.1 ’ 86.8 1 84.7 1 97.0 ’ 95.1 1 94.9 1 90.3 1 104.1 1 93.8 1 99.3 1 95.9 1 96.8 1 104.6 1 101.2 1 97.4 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 102.9 1 109.5 1 103.3 1 116.4 1 103.1 1 106.6 1 103.9 1 106.6 1 103.8 1 99.4 1 106.9 1 100.8 1 107.8 1 107.8 1 102.4 1 100.1 1 107.4 1 104.8 1 111.4 1 105.7 1 106.4 1 106.2 1 112.3 1 111.4 1 63.7 161.3 184.1 1 22.3 1 68.7 1 79.2 1 63.7 1 58.9 1 76.1 1 76.1 1 86.2 139.1 1 77.7 198.6 1 70.8 179.0 1 86.3 ’ 94.2 1 96.7 1 96.3 1 95.3 1 94.2 1 95.4 1 86.1 1 89.1 1 91.5 1 103.0 1 106.9 1 95.1 1 93.5 1 90.4 1 94.1 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 101.0 1 101.1 1 98.3 1 107.3 1 103.2 1 104.8 1 106.6 1 106.8 1 98.4 1 86.2 1 97.2 1 122.3 1 103.3 1 108.2 1 109.6 1 115.7 1 91.9 1 91.4 1 96.5 1 128.4 1 102.5 1 109.8 1 108.2 1 111.7 1 81.1 1 97.0 1 94.7 1 142.0 1 96.9 1 126.7 1 111.5 1 115.6 Railroad transportation, revenue traffic.......... 4011 Bus carriers, class 1 ................................... 411,13,14 pts. Trucking, except local ................................. 4213 Air transportation ....................................... 4512,13,22 pts. Petroleum pipelines .................................... 4612,13 Telephone communications.......................... 481 Electric utilities ........................................... 491,493 pt. Gas utilities................................................ 492,493 pt. Scrap and waste materials........................... 5093 1 49.3 1 116.8 1 69.5 1 54.3 1 93.2 146.2 1 88.4 1 145.5 - 154.0 1 108.3 183.9 1 75.5 1 96.9 168.7 195.3 1 141.4 1 81.1 1 79.8 1 96.1 1 93.8 1 92.0 1 99.9 1 92.6 1 93.0 1 111.9 1 93.4 1 86.1 1 95.6 1 96.8 1 93.8 1 102.0 1 98.1 1 95.2 1 102.1 ' 97.7 ' 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 109.3 1 107.9 1 105.2 1 99.5 1 104.8 1 107.8 1 104.9 1 105.5 1 94.3 1 115.4 1 104.6 1 109.4 1 95.1 1 103.2 1 113.4 1 107.7 1 103.6 1 87.8 1 122.6 _ 192.2 1 102.5 1 115.1 1 110.0 1 95.0 1 92.2 1 128.1 _ _ 1 92.5 1 99.1 1 121.8 1 113.3 1 94.2 1 93.1 Hardware stores......................................... Department stores...................................... Variety stores ............................................ Grocery stores............................................ Retail bakeries............................................ New and used car dealers ........................... Auto and home supply stores...................... Gasoline service stations............................. Men’s and boys’ clothing stores................... Women’s clothing stores............................. Family clothing stores ................................. Shoe stores ............................................. Furniture and homefurnishings stores............ Household appliance stores......................... Radio, television, and computer stores..................................................... 525 531 533 541 546 551 553 554 561 562 565 566 571 572 183.3 ' 60.8 1 148.9 1 109.1 1 125.6 1 85.1 1 71.1 1 59.5 1 77.6 1 58.9 1 76.2 1 81.3 1 83.9 1 59.8 ' 97.5 1 74.0 1 123.3 1 106.8 1 112.3 1 86.3 180.1 1 73.7 1 82.3 1 72.8 1 75.4 1 90.9 1 91.0 1 72.9 195.6 192.6 1 129.2 1 105.7 187.6 199.8 194.5 193.5 198.3 199.8 1 103.1 1 97.6 194.8 194.9 1 101.6 1 97.4 1 106.7 1 103.8 1 93.6 1 101.6 1 94.3 1 101.8 1 100.7 1 107.0 1 103.3 1 105.5 1 101.2 1 106.5 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 108.7 199.4 197.3 198.6 1 94.2 1 102.7 1 106.5 1 102.4 1 102.6 1 99.4 1 101.3 1 102.7 1 99.5 1 101.1 1 115.4 1 97.4 1 113.7 1 95.8 1 87.3 1 103.8 1 108.9 1 104.0 1 102.3 1 102.9 1 103.2 1 107.3 1 102.6 1 108.7 1 110.5 1 94.8 1 132.1 1 94.8 1 84.8 1 107.1 1 114.2 1 101.0 1 101.6 1 106.7 1 101.5 1 106.3 1 104.3 1 111.2 1 102.5 1 99.2 1 130.2 1 94.0 1 90.0 1 105.6 1 114.6 1 102.0 1 102.0 1 110.1 1 102.3 1 105.5 1 104.2 1 117.4 573 145.6 1 53.0 189.3 1 94.1 1 100.0 1 122.2 1 122.0 1 131.4 1 146.2 Eating and drinking places ........................... Drug and proprietary stores.......................... Liquor stores.............................................. Commercial banks...................................... Hotels and motels....................................... Laundry, cleaning, and garment services....... Beauty shops............................................. Automotive repair shops.............................. 581 591 592 602 701 721 723 753 1 110.3 1 92.2 1 95.0 181.2 1 102.4 1 110.8 185.9 1 109.3 1 106.6 1 101.8 1 90.2 1 84.1 1 109.7 1 109.9 1 89.4 1 105.0 196.2 1 102.5 1 101.9 194.3 1 101.2 1 103.3 196.1 1 99.4 1 99.3 1 101.6 1 93.8 1 96.2 1 98.9 1 100.8 1 96.9 1 96.1 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 100.0 1 Revised. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 3639 3641 3645,46,47,48 3651 371 3721 3825 386 1 93.6 1 95.7 1 94.4 1 93.9 1 100.0 1 101.3 1 101.0 1 101.9 1 101.2 1 140.8 1 116.0 1 120.0 1 121.4 1 100.0 1 99.2 1 101.7 1 106.5 1 113.3 1 102.6 1 102.0 1 99.9 1 103.4 1 95.8 1 97.1 1 93.3 1 105.6 1 101.9 1 102.8 1 104.7 1 102.2 1 91.4 1 98.6 1 96.0 1 107.8 1 103.1 1 104.1 1 110.6 1 108.6 1 90.6 1 99.0 1 91.3 1 106.3 1 104.5 1 105.5 1 112.3 1 112.3 1 91.3 1 96.6 1 87.6 1 99.9 - Data not available. M onthly Labor Review August 1995 127 Current Labor Statistics: International Comparisons D ata 46. Unemployment rates, approximating U.S. concepts, in nine countries, quarterly data seasonally adjusted Annual average 1993 Country 1993 1994 III 1994 IV I II 1995 III IV I United States' ................................ Canada .......................................... Australia........................................ Japan ............................................ 6.8 11.2 10.9 2.5 6.1 10.4 9.7 2.9 6.7 11.4 10.9 2.6 6.5 11.2 10.8 2.8 6.6 11.0 10.4 2.8 6.2 10.6 10.0 2.9 6.0 10.2 9.5 3.0 5.6 9.8 9.1 2.9 5.5 9.7 8.9 3.0 France........................................... Germany ....................................... Italy2.............................................. Sweden3........................................ United Kingdom .............................. 11.8 5.8 10.3 9.3 10.4 12.3 6.5 11.4 7.8 9.5 12.0 5.9 10.5 9.2 10.5 12.2 6.2 11.0 8.2 10.1 12.3 6.4 11.0 8.2 9.9 12.3 6.5 11.6 7.6 9.7 12.3 6.5 11.1 8.4 9.5 12.3 6.5 11.8 7.2 9.0 12.1 6.4 12.2 7.7 8.7 ’ Data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under “Employment and Unemployment Data” in the notes to this section. 2 Quarterly rates are for the first month of the quarter. Break in series beginning in 1993. 3 Break in series beginning in 1993. Data for 1993 on- 128 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 ward are not seasonally adjusted. 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. See “Notes on the data” for information on breaks in series. 47. Annual data: Employment status of the working-age population, approximating U.S. concepts, 10 countries (Numbers in thousands) Employment status and country 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 Civilian labor force United States' ................................................. Canada ........................................................... Australia.......................................................... Japan .................................................... France............................................................ Germany......................................................... Italy ....................................................... Netherlands..................................................... Sweden........................................................... United Kingdom....................................... 115,461 117,834 119,865 121,669 123,869 124,787 125,303 126,982 128,040 131,056 13,123 13,378 13,631 13,900 14,151 14,329 14,408 14,482 14,663 14,832 7,300 7,588 7,758 7,974 8,228 8,444 8,490 8,562 8,619 8,776 58,820 59,410 60,050 60,860 61,920 63,050 64,280 65,040 65,470 65,780 23,620 23,760 23,890 23,980 24,170 24,300 24,490 24,560 24,630 24,890 28,020 28,240 28,390 28,610 28,840 29,410 29,760 30,040 29,960 29,840 21,800 22,290 22,350 22,660 22,530 22,670 22,940 22,910 22,570 22,450 6,250 6,380 6,500 6,530 6,640 6,770 6,870 6,970 7,070 4,418 4,443 4,437 4,494 4,552 4,597 4,591 4,520 4,443 4,418 27,210 27,380 27,720 28,150 28,420 28,540 28,400 28,230 28,150 - Participation rate2 United States' ................................................. Canada ........................................................... Australia.......................................................... Japan ........................................................ France............................................................ Germany......................................................... Italy .................................................... Netherlands..................................................... Sweden.................................................. United Kingdom................................................ 64.8 65.8 61.6 62.3 56.9 54.7 47.2 55.5 66.9 62.2 65.3 66.3 62.8 62.1 56.9 54.9 47.8 56.0 67.0 62.2 65.6 66.7 63.0 61.9 56.7 55.0 47.6 56.3 66.4 62.6 65.9 67.2 63.3 61.9 56.4 55.1 47.4 56.1 66.9 63.4 66.5 67.5 64.0 62.2 56.1 55.2 47.3 56.5 67.3 63.8 66.4 67.3 64.6 62.6 55.6 55.0 47.2 56.8 67.0 63.9 66.0 66.7 64.1 63.2 55.6 55.4 48.6 57.5 66.6 63.4 66.2 65.5 63.6 63.3 55.6 54.5 48.3 58.6 64.2 62.6 66.3 65.9 63.9 63.4 55.8 55.1 48.5 57.9 65.3 62.8 66.6 65.3 63.9 63.1 55.9 - 48.0 _ 63.6 - Employed United States' ................................................ Canada ........................................................... Australia.......................................................... Japan ............................................................. France ............................................................ Germany......................................................... Italy ................................................................ Netherlands..................................................... Sweden........................................................... United Kingdom................................................ 107,150 109,597 112,440 114,968 117,342 117,914 116,877 117,598 119,306 123,060 11,742 12,095 12,422 12,819 13,086 13,165 12,916 12,842 13,015 13,292 6,697 6,974 7,129 7,398 7,720 7,859 7,676 7,637 7,680 7,921 57,260 57,740 58,320 59,310 60,500 61,710 62,920 63,620 63,810 63,860 21,150 21,240 21,320 21,520 21,850 22,100 22,140 22,010 21,720 21,830 26,010 26,380 26,590 26,800 27,200 27,950 28,480 28,660 28,220 27,900 20,490 20,610 20,590 20,870 20,770 21,080 21,360 21,230 20,240 19,890 5,650 5,740 5,850 5,920 6,070 6,260 6,380 6,470 6,450 4,293 4,326 4,340 4,410 4,480 4,513 4,447 4,265 4,028 3,992 24,150 24,300 24,860 25,730 26,350 26,580 25,910 25,410 25,220 - Employment-population ratio3 United States' ................................................. Canada ........................................................... Australia.......................................................... Japan ............................................................. France ............................................................ Germany......................................................... Italy ................................................................ Netherlands..................................................... Sweden........................................................... United Kingdom................................................ 60.1 58.9 56.5 60.6 51.0 50.7 44.4 50.1 65.0 55.2 60.7 59.9 57.7 60.4 50.8 51.3 44.2 50.3 65.2 55.2 61.5 60.8 57.9 60.1 50.6 51.5 43.8 50.7 65.0 56.2 62.3 62.0 58.7 60.4 50.6 51.6 43.7 50.8 65.7 57.9 63.0 62.4 60.1 60.8 50.7 52.0 43.6 51.7 66.2 59.1 62.7 61.9 60.1 61.3 50.5 52.2 43.9 52.5 65.8 59.5 61.6 59.8 57.9 61.8 50.3 53.0 45.3 53.4 64.5 57.8 61.4 58.4 57.0 62.0 50.0 52.6 44.9 53.8 61.7 56.5 61.6 58.2 56.6 61.7 49.0 51.3 43.3 53.4 58.2 56.1 62.5 58.5 57.7 61.3 49.1 42.5 _ 57.4 - 8,312 1,381 603 1,560 2,470 2,010 1,310 600 125 3,060 8,237 1,283 613 1,670 2,520 1,860 1,680 640 117 3,080 7,425 1,208 629 1,730 2,570 1,800 1,760 650 97 2,860 6,701 1,082 576 1,550 2,460 1,810 1,790 610 84 2,420 6,528 1,065 508 1,420 2,320 1,640 1,760 570 72 2,070 6,874 1,164 585 1,340 2,200 1,460 1,590 510 84 1,960 8,426 1,492 814 1,360 2,350 1,280 1,580 490 144 2,490 9,384 1,640 925 1,420 2,550 1,380 1,680 500 255 2,820 8,734 1,649 939 1,660 2,910 1,740 2,330 620 415 2,930 7,996 1,541 856 1,920 3,060 1,940 2,560 _ 426 - 7.2 10.5 8.3 2.6 10.5 7.2 6.0 9.6 2.8 11.2 7.0 9.6 8.1 2.8 10.6 6.6 7.5 10.0 2.6 11.2 6.2 8.9 8.1 2.9 10.8 6.3 7.9 10.0 2.2 10.3 5.5 7.8 7.2 2.5 10.3 6.3 7.9 9.3 1.9 8.6 5.3 7.5 6.2 2.3 9.6 5.7 7.8 8.6 1.6 7.3 5.5 8.1 6.9 2.1 9.1 5.0 7.0 7.5 1.8 6.9 6.7 10.4 9.6 2.1 9.6 4.3 6.9 7.1 3.1 8.8 7.4 11.3 10.8 2.2 10.4 4.6 7.3 7.2 5.6 10.0 6.8 11.2 10.9 2.5 11.8 5.8 10.3 8.8 9.3 10.4 6.1 10.4 9.7 2.9 12.3 6:5 11.4 _ 9.6 9.5 Unemployed United States' ................................................. Canada ........................................................... Australia.......................................................... Japan ............................................................. France ............................................................ Germany......................................................... Italy ................................................................ Netherlands..................................................... Sweden........................................................... United Kingdom................................................ Unemployment rate United States' ................................................. Canada ........................................................... Australia.......................................................... Japan ............................................................. France ............................................................ Germany......................................................... Italy ................................................................ Netherlands..................................................... Sweden........................................................... United Kingdom................................................ 1 Data for 1994 are not directly comparable with data for 1993 and earlier years. For additional information, see the box note under “Employment and Unemployment Data” in the notes to this section. 2 Labor force as a percent of the working-age population. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 3 Employment as a percent of the working-age population. - Data not available. NOTE: See “Notes on the data” for information on breaks in series for Italy and Sweden. M onthly Labor Review August 1995 129 Current Labor Statistics: 48. International Comparisons D ata Annual indexes of manufacturing productivity and related measures, 12 countries (1982 = 100) 1960 1970 1973 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 51.6 18.5 24.1 32.4 29.6 37.1 29.1 26.5 46.4 36.1 50.3 76.9 50.3 44.0 57.2 58.6 66.4 54.6 52.9 73.0 69.0 72.1 91.9 64.4 57.4 72.7 69.4 77.9 65.2 67.3 85.4 81.2 86.2 103.5 116.3 107.9 117.5 104.3 103.9 109.0 115.7 115.0 112.2 111.9 112.4 106.7 119.8 114.9 119.6 105.0 107.9 113.4 122.3 118.7 115.8 113.6 116.4 109.5 117.9 113.0 121.4 98.9 109.7 114.2 123.7 120.1 114.7 115.4 120.6 116.6 119.0 122.4 123.8 98.4 111.6 112.7 127.2 120.7 120.4 117.6 126.9 119.2 119.5 129.6 128.9 102.1 119.3 116.7 130.0 124.4 119.5 119.3 133.5 119.9 120.0 138.7 134.5 105.6 125.4 120.5 134.0 128.5 125.3 123.1 138.4 122.1 122.0 149.1 134.1 105.5 127.6 125.6 139.3 130.1 129.3 125.0 140.1 124.9 122.9 156.9 137.0 105.5 128.0 130.1 143.8 131.4 130.3 126.1 145.3 127.5 128.0 156.8 142.2 107.7 130.9 128.0 150.8 132.2 132.5 132.8 152.4 131.6 130.9 157.3 146.4 113.9 132.3 130.0 159.2 133.8 135.3 141.5 159.7 44.1 15.1 37.6 45.4 35.1 51.0 28.0 42.7 56.0 51.8 82.9 78.5 55.1 70.4 75.7 72.7 87.0 58.4 80.3 88.4 91.1 110.5 100.0 71.8 86.3 88.5 87.0 96.4 70.7 91.2 101.3 98.7 121.9 111.3 120.2 113.2 109.9 111.7 98.7 104.6 105.4 107.9 105.0 113.6 105.9 114.0 127.0 121.2 111.8 115.3 99.1 108.4 108.9 111.1 108.8 115.7 108.9 115.2 127.9 117.9 111.9 115.3 99.1 110.1 111.5 113.8 108.8 117.1 110.3 123.5 134.1 126.5 112.3 110.6 98.9 108.1 116.3 115.4 110.8 120.0 115.5 130.0 140.9 138.2 118.0 112.3 104.6 111.5 125.0 119.7 105.5 123.7 123.6 131.2 142.1 149.3 125.0 113.6 110.3 115.4 129.7 125.2 103.8 125.1 129.1 130.6 136.8 160.6 126.5 112.4 112.4 121.7 132.3 129.3 104.5 124.3 128.9 128.2 127.5 170.8 125.9 111.1 110.6 126.2 132.1 129.9 102.3 117.4 121.9 130.1 128.3 167.7 125.8 112.5 109.8 123.3 132.4 129.0 104.2 113.3 121.1 135.4 134.7 160.7 120.5 113.2 106.3 113.8 129.6 125.8 105.9 115.1 122.8 94.1 85.5 81.7 156.2 140.0 118.5 137.2 96.2 160.9 120.9 143.7 164.9 106.5 102.1 109.6 159.9 132.3 123.9 131.1 107.0 152.0 121.1 132.0 153.3 112.6 108.8 111.5 150.3 121.8 125.3 123.7 108.3 135.6 118.7 121.6 141.4 107.6 103.3 104.9 93.6 107.1 95.0 96.0 91.1 93.8 93.5 101.5 94.2 106.8 106.0 105.5 93.5 109.8 91.8 95.6 89.0 93.6 94.0 101.9 93.5 105.2 108.5 104.3 92.2 116.6 90.3 96.4 90.1 94.8 94.8 101.5 91.5 106.0 112.7 103.4 90.7 112.4 88.6 95.9 91.4 95.6 92.0 102.0 91.0 109.0 117.9 106.7 91.5 110.0 87.7 95.6 96.1 96.2 88.3 103.6 92.6 109.4 118.4 107.6 93.0 107.6 88.0 95.7 96.8 97.4 82.9 101.6 93.3 107.0 112.2 107.7 94.3 106.6 88.1 96.9 95.0 99.4 80.9 99.4 92.0 102.6 103.7 108.8 91.9 105.3 86.4 97.0 91.8 98.9 78.5 93.1 83.9 102.0 100.3 106.9 88.4 104.4 83.8 96.3 87.8 97.6 78.6 85.4 79.5 102.9 102.9 102.2 82.3 99.4 80.3 87.6 81.4 94.0 78.3 81.4 76.9 United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France ......................................................................... Germany...................................................................... Italy ............................................................................. Netherlands.................................................................. Norway ........................................................................ Sweden........................................................................ United Kingdom............................................................. 16.4 6.6 9.1 7.7 7.6 13.5 3.9 8.9 9.9 9.3 7.1 28.7 25.0 23.2 22.3 18.5 34.5 11.6 27.8 24.6 24.4 14.7 35.9 40.7 35.5 34.5 26.2 48.2 17.7 43.4 35.3 34.3 22.6 106.0 111.1 105.8 114.8 113.0 119.6 110.0 134.3 106.6 120.9 119.6 114.6 111.3 116.8 110.1 122.0 120.6 129.6 116.3 150.9 111.5 132.2 131.8 125.1 115.8 121.3 115.6 127.0 123.1 135.1 121.2 157.1 115.4 145.0 142.4 135.4 118.4 125.0 118.6 130.0 134.6 140.0 126.9 166.0 118.8 165.6 151.9 149.8 123.1 130.5 120.6 132.7 139.4 145.4 131.8 172.5 119.5 175.7 161.8 159.4 127.9 135.4 128.2 139.7 147.3 153.2 138.2 189.5 120.1 183.4 179.0 174.7 134.7 143.0 138.3 147.5 156.5 161.3 147.9 210.8 123.3 193.7 197.5 180.6 141.9 151.7 146.2 156.8 162.2 168.3 157.8 233.1 129.2 202.8 215.1 199.4 147.9 158.1 153.0 164.9 167.2 174.1 165.6 249.7 136.6 208.4 225.0 219.7 152.8 159.0 157.1 171.2 171.4 179.8 177.8 266.1 140.5 210.4 221.6 236.1 Unit labor costs: National currency basis United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France......................................................................... Germany...................................................................... Italy............................................................................. Netherlands.................................................................. Norway........................................................................ Sweden........................................................................ United Kingdom............................................................. 31.9 35.5 38.0 23.8 25.7 36.4 13.5 33.4 21.3 25.8 14.2 37.3 49.7 52.6 39.0 31.5 51.9 21.3 52.7 33.7 35.4 20.4 39.1 63.2 61.8 47.4 37.7 61.9 27.1 64.5 41.4 42.2 26.3 102.4 95.5 98.1 97.7 108.3 115.2 101.0 116.1 92.7 107.8 106.9 101.9 104.2 97.6 95.8 102.0 114.9 120.2 102.6 123.4 93.9 114.2 116.1 107.5 105.8 102.9 102.4 104.7 124.5 123.2 106.2 127.1 96.1 126.4 123.4 112.3 101.6 105.0 96.8 105.0 136.8 125.5 112.6 130.5 98.4 137.5 129.1 118.0 103.2 109.2 93.1 103.0 136.5 121.8 113.0 132.6 96.0 147.1 135.6 119.4 106.7 112.8 92.4 103.8 139.5 122.2 114.6 141.4 93.5 146.3 145.4 126.2 110.4 117.2 92.7 110.0 148.3 126.4 117.8 151.3 94.7 149.8 158.0 128.9 113.7 123.4 93.2 114.4 153.8 131.5 121.3 162.1 98.3 155.6 170.6 137.2 116.0 123.5 97.5 115.9 155.1 133.0 129.4 165.6 103.3 157.3 169.5 144.2 116.1 121.4 99.9 117.0 150.5 135.9 136.8 167.2 105.1 155.5 156.6 147.8 Unit labor costs: U.S. dollar basis United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France ......................................................................... Germany...................................................................... Italy ............................................................................. Netherlands.................................................................. Norway ........................................................................ Sweden....................................................................... United Kingdom............................................................ 40.6 24.6 34.9 28.8 34.4 21.2 29.5 23.7 19.3 31.4 22.8 44.1 34.6 48.5 43.4 37.5 34.6 46.0 38.9 30.4 42.8 28.0 48.2 58.1 72.8 65.7 55.9 56.8 63.1 62.0 46.5 60.9 36.8 102.4 91.0 102.9 77.5 87.3 86.7 86.2 89.5 77.2 85.3 81.2 77.9 104.2 88.2 100.1 78.7 90.4 88.0 84.7 87.5 75.6 85.8 84.8 79.8 105.8 91.4 151.5 107.3 128.3 117.0 118.8 115.4 104.8 110.3 108.8 94.3 101.6 97.8 166.8 128.7 166.7 137.3 152.1 136.3 129.8 131.7 127.8 110.7 103.2 109.5 180.9 128.1 169.0 134.5 156.1 137.9 129.8 145.5 138.8 121.6 106.7 117.6 166.7 120.6 159.0 126.0 148.0 139.5 117.7 136.6 141.5 118.3 110.4 124.0 159.3 150.7 200.0 152.7 176.9 170.9 138.9 154.7 167.6 131.6 113.7 132.9 172.5 153.2 200.4 153.2 177.3 176.8 140.3 154.8 177.1 138.7 116.0 126.2 191.6 165.1 214.4 165.3 201.2 182.0 157.0 163.4 182.8 145.7 116.1 116.2 223.9 154.8 193.6 157.8 200.8 143.8 151.0 141.5 126.3 127.0 Item and country Output per hour United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France ......................................................................... Germany...................................................................... Italy ............................................................................. Netherlands.................................................................. Norway ........................................................................ Sweden........................................................................ United Kingdom............................................................. Output United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France ......................................................................... Germany...................................................................... Italy ............................................................................. Netherlands.................................................................. Norway ........................................................................ Sweden........................................................................ United Kingdom............................................................ Total hours United States................................................................ Canada ........................................................................ Japan .......................................................................... Belgium........................................................................ Denmark...................................................................... France ......................................................................... Germany...................................................................... Netherlands.................................................................. Norway ........................................................................ Sweden........................................................................ United Kingdom............................................................. Compensation per hour - Data not available. 130 M onthly Labor Review https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis August 1995 49. Occupational injury and illness incidence rates by industry,1 United States Incidence rates per 100 full-time workers3 1985 1986 1987 1988 1989' 1990 1991 1992 19934 PRIVATE SECTOR5 Total cases............................................................................... Lost workday cases ....................................................................... Lost workdays............................................................................... 7.9 3.6 64.9 7.9 3.6 65.8 8.3 3.8 69.9 8.6 4.0 76.1 8.6 4.0 78.7 8.8 4.1 84.0 8.4 3.9 86.5 8.9 3.9 93.8 8.5 3.8 - Agriculture, forestry, and fishing5 Total cases................................................................ Lost workday cases....................................................................... Lost workdays............................................................................... 11.4 5.7 91.3 11.2 5.6 93.6 11.2 5.7 94.1 10.9 5.6 101.8 10.9 5.7 100.9 11.6 5.9 112.2 10.8 5.4 108.3 11.6 5.4 126.9 11.2 5.0 - Mining Total cases................................................................................. Lost workday cases.................................................................... Lost workdays............................................................................... 8.4 4.8 145.3 7.4 4.1 125.9 8.5 4.9 144.0 8.8 5.1 152.1 8.5 4.8 137.2 8.3 5.0 119.5 7.4 4.5 129.6 7.3 4.1 204.7 6.8 3.9 - 15.2 6.8 128.9 15.2 6.9 134.5 14.7 6.8 135.8 14.6 6.8 142.2 14.3 6.8 143.3 14.2 6.7 147.9 13.0 6.1 148.1 13.1 5.8 161.9 12.2 5.5 15.2 6.8 120.4 14.9 6.6 122.7 14.2 6.5 134.0 14.0 6.4 132.2 13.9 6.5 137.3 13.4 6.4 137.6 12.0 5.5 132.0 12.2 5.4 142.7 11.5 5.1 Construction Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... General building contractors: Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... Heavy construction, except building: Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... Special trade contractors: Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... 14.5 6.3 127.3 14.7 6.3 132.9 14.5 6.4 139.1 15.1 7.0 162.3 13.8 6.5 147.1 13.8 6.3 144.6 12.8 6.0 160.1 12.1 5.4 165.8 11.1 5.1 15.4 7.0 133.3 15.6 7.2 140.4 15.0 7.1 135.7 14.7 7.0 141.1 14.6 6.9 144.9 14.7 6.9 153.1 13.5 6.3 151.3 13.8 6.1 168.3 12.8 5.8 - Manufacturing Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... 10.4 4.6 80.2 10.6 4.7 85.2 11.9 5.3 95.5 13.1 5.7 107.4 13.1 5.8 113.0 13.2 5.8 120.7 12.7 5.6 121.5 12.5 5.4 124.6 12.1 5.3 - Durable goods: Total cases................................................................................. Lost workday cases .................................................................... Lost workdays............................................................................. 10.9 4.7 82.0 11.0 4.8 87.1 12.5 5.4 96.8 14.2 5.9 111.1 14.1 6.0 116.5 14.2 6.0 123.3 13.6 5.7 122.9 13.4 5.5 126.7 13.1 5.4 18.5 9.3 171.4 18.9 9.7 177.2 18.9 9.6 176.5 19.5 10.0 189.1 18.4 9.4 177.5 18.1 8.8 172.5 16.8 8.3 172.0 16.3 7.6 165.8 15.9 7.6 15.0 6.3 100.4 15.2 6.3 103.0 15.4 6.7 103.6 16.6 7.3 115.7 14.8 6.6 128.4 14.6 6.5 13.9 6.7 127.8 13.6 6.5 126.0 14.9 7.1 135.8 16.0 7.5 141.0 15.5 7.4 149.8 15.4 7.3 160.5 14.8 6.8 156.0 13.6 6.1 152.2 13.8 6.3 12.6 5.7 113.8 13.6 6.1 125.5 17.0 7.4 145.8 19.4 8.2 161.3 18.7 8.1 168.3 19.0 8.1 180.2 17.7 7.4 169.1 17.5 7.1 175.5 17.0 7.3 - 16.3 6.9 110.1 16.0 6.8 115.5 17.0 7.2 121.9 18.8 8.0 138.8 18.5 7.9 147.6 18.7 7.9 155.7 17.4 7.1 146.6 16.8 6.6 144.0 16.2 6.7 - 10.8 4.2 69.3 10.7 4.2 72.0 11.3 4.4 72.7 12.1 4.7 82.8 12.1 4.8 86.8 12.0 4.7 88.9 11.2 4.4 86.6 11.1 4.2 87.7 11.1 4.2 - 6.4 2.7 45.7 6.4 2.7 49.8 7.2 3.1 55.9 8.0 3.3 64.6 9.1 3.9 77.5 9.1 3.8 79.4 8.6 3.7 83.0 8.4 3.6 81.2 8.3 3.5 - 9.0 3.9 71.6 9.6 4.1 79.1 13.5 5.7 105.7 17.7 6.6 134.2 17.7 6.8 138.6 17.8 6.9 153.7 18.3 7.0 166.1 18.7 7.1 186.6 18.5 7.1 - 5.2 2.2 37.9 5.3 2.3 42.2 5.8 2.4 43.9 6.1 2.6 51.5 5.6 2.5 55.4 5.9 2.7 57.8 6.0 2.7 64.4 5.9 2.7 65.3 5.6 2.5 9.7 4.2 73.2 10.2 4.3 70.9 10.7 4.6 81.5 11.3 5.1 91.0 11.1 5.1 97.6 11.3 5.1 113.1 11.3 5.1 104.0 10.7 5.0 108.2 10.0 4.6 - 9.6 10.0 11.1 11.4 11.6 11.7 11.5 11.3 10.7 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............................................................................. Industrial machinery and equipment: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Electronic and other electrical 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............................................................................. Nondurable goods: Total cases................................................................................. See footnotes at end of table. https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 16.1 7.2 16.9 7.8 15.9 7.2 - - - M onthly Labor Review - - - - - - August 1995 131 Current Labor Statistics: Injury a n d Illness D ata 49. Continued— Occupational injury and illness incidence rates by industry,1 United States Incidence rates per 100 full-time workers3 Industry and type of case2 1985 Lost workday cases ..................................................................... Lost workdays............................................................................. Food and kindred products: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Tobacco products: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Textile mill products: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Apparel and other textile products: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Paper and allied products: Total cases................................................................................. 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............................................................................. Rubber and miscellaneous plastics products: Total cases................................................................................. Lost workday cases ..................................................................... Lost workdays............................................................................. Leather and leather products: Total cases........................... ..................................................... Lost workday cases ..................................................................... Lost workdays............................................................................. 1986 1991 1992 19934 5.4 101.7 5.5 107.8 5.6 116.9 5.5 119.7 5.3 121.8 5.0 16.7 8.1 138.0 16.5 8.0 137.8 17.7 8.6 153.7 18.5 9.2 169.7 18.5 9.3 174.7 20.0 9.9 202.6 19.5 9.9 207.2 18.8 9.5 211.9 17.6 8.9 7.3 3.0 51.7 6.7 2.5 45.6 8.6 2.5 46.4 9.3 2.9 53.0 8.7 3.4 64.2 7.7 3.2 62.3 6.4 2.8 52.0 6.0 2.4 42.9 5.8 2.3 7.5 3.0 57.4 7.8 3.1 59.3 9.0 3.6 65.9 9.6 4.0 78.8 10.3 4.2 81.4 9.6 4.0 85.1 10.0 4.4 88.3 9.9 4.2 87.1 9.7 4.1 6.7 2.6 44.1 6.7 2.7 49.4 7.4 3.1 59.5 8.1 3.5 68.2 8.6 3.8 80.5 8.8 3.9 92.1 9.2 4.2 99.9 9.5 4.0 104.6 9.0 3.8 10.2 4.7 94.6 10.5 4.7 99.5 12.8 5.8 122.3 13.1 5.9 124.3 12.7 5.8 132.9 12.1 5.5 124.8 11.2 5.0 122.7 11.0 5.0 125.9 9.9 4.6 6.3 2.9 49.2 6.5 2.9 50.8 6.7 3.1 55.1 6.6 3.2 59.8 6.9 3.3 63.8 6.9 3.3 69.8 6.7 3.2 74.5 7.3 3.2 74.8 6.9 3.1 6.0 2.8 64.2 5.9 2.7 6.2 2.9 68.2 5.9 2.8 71.2 5.2 2.5 16.2 7.8 151.3 15.1 7.2 150.9 14.5 6.8 153.3 13.9 6.5 12.1 5.4 128.5 12.1 5.5 5.1 2.3 38.8 5.1 2.4 49.9 13.4 6.3 107.4 6.3 2.7 49.4 7.1 3.2 67.5 14.0 6.6 118.2 7.0 3.1 58.8 7.3 3.1 65.9 15.9 7.6 130.8 7.0 3.3 59.0 7.0 3.2 68.4 16.3 8.1 142.9 7.0 3.2 63.4 6.6 3.3 68.1 16.2 8.0 147.2 6.5 3.1 61.6 6.6 3.1 77.3 6.4 3.1 62.4 " - ■ - - " - “ - - 10.3 4.6 88.3 10.5 4.8 83.4 12.4 5.8 114.5 11.4 5.6 128.2 13.6 6.5 130.4 12.1 5.9 152.3 12.5 5.9 140.8 8.6 5.0 107.1 8.2 4.8 102.1 8.4 4.9 108.1 8.9 5.1 118.6 9.2 5.3 121.5 9.6 5.5 134.1 9.3 5.4 140.0 9.1 5.1 144.0 9.5 5.4 7.4 3.2 50.7 7.7 3.3 54.0 7.7 3.4 56.1 7.8 3.5 60.9 8.0 3.6 63.5 7.9 3.5 65.6 7.6 3.4 72.0 8.4 3.5 80.1 8.1 3.4 7.2 3.5 59.8 7.2 3.6 62.5 7.4 3.7 64.0 7.6 3.8 69.2 7.7 4.0 71.9 7.4 3.7 71.5 7.2 3.7 79.2 7.6 3.6 82.4 7.8 3.7 7.5 3.1 47.0 7.8 3.2 50.5 7.8 3.3 52.9 7.9 3.4 57.6 8.1 3.4 60.0 8.1 3.4 63.2 7.7 3.3 69.1 8.7 3.4 79.2 8.2 3.3 “ 2.0 .9 15.4 2.0 .9 17.1 2.0 .9 14.3 2.0 .9 17.2 2.0 .9 17.6 2.4 1.1 27.3 2.4 1.1 24.1 2.9 1.2 32.9 2.9 1.2 5.4 2.6 45.4 5.3 2.5 43.0 5.5 2.7 45.8 5.4 2.6 47.7 5.5 2.7 51.2 6.0 2.8 56.4 6.2 2.8 60.0 7.1 3.0 68.6 6.7 2.8 Finance, insurance, and real estate Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... Services Total cases................................................................................... Lost workday cases....................................................................... Lost workdays............................................................................... 1 Data for 1989 and subsequent years are based on the S tandard 1987 Edition. For this reason, they are not strictly comparable with data for the years 1985-88, which were based on the S tand ard Industrial Classification M anual, 1972 Edition, 1977 Supplement. 2 Beginning with the 1992 survey, the annual survey measures only nonfatal injuries and illnesses, while past surveys covered both fatal and nonfatal incidents. To better address fatalities, a basic element of workplace safety, BLS implemented the Census of Fatal Occupational Injuries. 3 The Incidence rates represent the number of injuries and illnesses or lost workdays per 100 full-time workers and were calculated as: (N/EH) X 200,000, where: August 1995 1990 5.1 93.5 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............................................................................... M onthly Labor Review' 132 https://fraser.stlouisfed.org Federal Reserve Bank of St. Louis 1989’ 4.6 82.3 Wholesale and retail trade Industrial C lassification M anual, 1988 4.4 77.6 Transportation and public utilities Total cases................................................................................... Lost workday cases....................................................................... Lost workdays ............................................................................. 1987 " " - - N = number of injuries and illnesses or lost workdays. EH = total hours worked by all employees during the calendar year. 200,000 = base for 100 full-time equivalent workers (working 40 hours per week, 50 weeks per year). 4 Beginning with the 1993 survey, lost workday estimates will not be generated. As of 1992, BLS began generating percent distributions and the median number of days away from work by industry and for groups of workers sustaining similar work disabilities. 5 Excludes farms with fewer than 11 employees since 1976. - Data not available. REVIEW U.S. Department of Labor Bureau of Labor Statistics We provide the pieces. Putting you in touch with the raw data is our mission. We help you put them together. Each issue also brings you our insights on employment and unemployment, wages and benefits, prices and productivity, and the rest of the economic puzzle. You get the picture. Order Processing Code: Superintendent of Documents Order Form *5551 □ YES, Charge your order, It's easy! jf t WS4' ---------- To fax your orders (202) 512-2233 send m e ____ subscription(s) to Monthly Labor Review at □ $25 per year or □ $50 for 2 years. International customers please add 25% . The total cost of my order is $ _______ . (Includes regular shipping and handling.) 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