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Youth Employment and Training Programs: The YEDPA Years (1985)

Chapter: 2 Youth Employment and Unemployment

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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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Suggested Citation:"2 Youth Employment and Unemployment." National Research Council. 1985. Youth Employment and Training Programs: The YEDPA Years. Washington, DC: The National Academies Press. doi: 10.17226/613.
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2 Youth Employment and Unemployment THE YOUTH EMPLOYMENT PROBLEM: Unemployment Rates ITS NATURE AND DIMENSIONS The United States recently experienced its most serious unemployment problems since the Great Depression of the 1930s. In the depths of this recession, in December 1982, the overall unemployment rate reached a postwar high of 10.8 percent. But the unemployment rate for teenagers was 24.5 percent--more than twice the overall rate--and the unemployment rate for black teenagers was 49.5 percent. Since the trough of the recession, the national employment situation has improved somewhat, so that during 1984 the unemployment rate averaged 7.5 percent. The rate for teenagers was still substantially higher--18.9 percent--and the rate for black teenagers had improved only slightly, to 42.7 percent. The youth employment problem is not due merely to the greater vulnerability of young workers to the swings of the business cycle. There has been a long-term upward trend in youth unemployment rates over the last several decades (Congressional Budget Office, 1982~. Table 2.1a provides statistics for four periods from 1957 to 1984: 1957, 1964, and 1978 were chosen because they were years of relatively high economic activity and had identical unemployment rates for adult white men aged 35-44. Over the period spanned by these statistics, the unemployment rate for all youths climbed steadily. ~ ~ ~ ~ . . . . . . . . . In addition, the gap between Wh' te and nonwhite youths that was evident in 1957 became much larger over these decades. Thus, even among the more "settled" 20- to 24-year-old youths, the 1957 unemployment rate for white males was 7.1 percent while the rate for nonwhites was 12.7 percent; by 1984, this gap had expanded to 9.8 percent for whites and 24.5 percent for nonwhites. For women aged 20-24, the unemployment gap had expanded similarly, from 5.1 percent for whites and 12.2 percent for nonwhites in 1957 to 8.8 percent for whites and 23.5 percent for nonwhites in 1984. Table 2.lb, which compares the unemployment rates for young white males with other youths, shows that nonwhite females aged 20-24 were 1.7 times as likely as white males to be unemployed in 1957; by 1984 they were 2.4 times as likely to be unemployed. In contrast, white females have in most years been less likely to be unemployed than white 34

35 TABLE 2.1a Youth Unemployment Rates in the Civilian Population for Selected Years (in percentages) Year Group 1957 1964 1978 1984 Adult white males 35-44 years old2.52.52.54.6 All youths 16-17 years old12.517.819.321.2 18-19 years old10.914.914.217.4 20-24 years old7.18.39.611.5 White males 16-17 years old11.916.116.919.7 18-19 years old11.213.410.815.0 20-24 years old7.17.47.79.8 Nonwhite males 16-17 years old16.325.939.839.8 18-19 years old20.023.130.738.5 20-24 years old12.712.620.024.5 Hispanic males 16-17 years oldaa27.530.5 18-19 years oldaa13.921.6 20-24 years oldaa9.412.1 White females 16-17 years old11.917.117.117.8 18-19 years old7.913.212.413.6 20-24 years old5.17.18.38.8 Nonwhite females 16-17 years old18.336.541.542.2 18-19 years old21.329.236.336.6 20-24 years old12.218.321.323.5 Hispanic females 16-17 years oldaa29.925.2 18-19 years oldaa16.621.4 20-24 years oldaa13.012.5 NOTE: _ The vears 1957. 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak; 1984 was selected to provide a view of recent youth unemployment. aNo data for persons of Hispanic origin are available for 1957 or 1964. SOURCE: Data from U.S. Department of Labor (1982, 1985b) .

36 TABLE 2.lb Ratios Between Unemployment Rates for Young White Males and Other Groups Year _ 1957 1964 1978 1984 Group White males 16-17 years old1.01.0 1.01.0 18-19 years old1.01.0 1.01.0 20-24 years old1.01.0 1.01.0 Nonwhite males 16-17 years old1.411.61 2.362.02 18-19 years old1.741~72 2.842.57 20-24 years old1.791.70 2.602.50 Hispanic males 16-17 years oldaa 1.631.52 18-19 years oldaa 1.291.44 20-24 years oldaa 2.601.23 White females 16-17 years old1.031.06 1.01.90 18-19 years old.69.99 1.15.91 20-24 years old.72.96 1.08.90 Nonwhite females 16-17 years old1.592.27 2.462.14 18-19 years old1.852.18 3.362.44 20-24 years old1.712.47 2.772.40 Hispanic females 16-17 years oldaa 1.771.28 18-19 years oldaa 1.541.43 20-24 years oldaa 1.691.28 NOTE: The years 1957, 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak; 1984 was selected to provide a view of recent youth unemployment. aNo data for persons of Hispanic origin are available for 1957 or 1964. SOURCE: Data from U.S. Department of Labor (1982, 1985b).

37 males, but between 1957 and 1984 this ratio approached parity: for 20- to 24-year-old white females, the ratio of unemployment rates was 0.7 in 1957 and 0.9 in 1984. (Although comparable historical data are not available for Hispanic youths, the available data indicate that Hispanic males aged 20-24 were 1~2 times as likely as white males to be unemployed in 1984, and Hispanic females were 1.3 times as likely to be unemployed as white males.) These continuing trends in the relative unemployment rates of young Americans were a primary motivation for the launching in the late 1970s of federally funded programs designed to provide employment and training services to disadvantaged youths. Yet, as the last column of Table 2.1a indicates, the gap between white and nonwhite unemployment rates has persisted: in 1984 unemployment among white youths aged 20-24 was 9.8 percent for males and 8.8 percent for females; for nonwhite youths the rates were 24.5 and 23.5 percent, respectively. While the unemployment rates and ratios shown in Tables 2.1a and 2.lb demonstrate that young people's problems have been increasing, the unemployment rate can sometimes be a misleading indicator, particularly when applied to the youngest segment of the labor force (Hahn and Lerman, 1983:2~. To be counted as unemployed a person must indicate in answer to a survey question that (1) she or he is not currently employed and (2) she or he is currently looking for work. People who are not working and who say they are not actively looking for work are counted as "out of the labor force" rather than unemployed. The unemployment rate is calculated by dividing the number of people who are unemployed by the number of people in the labor force (defined as the sum of the employed [E] and unemployed [Ul): unemployment rate = U/(U + E) It can be seen that the unemployment rate can rise even though the number of employed (E) stays constant. And, given the way in which one is defined as being "in the labor force," it is not necessary that there be any change in the number of people who are not working. The unemployment rate may rise simply because more people begin looking for work (or at least say they are looking for work), thereby increasing the size of the labor force. [See Bailar and Rothwell (1984) and National Commission on Employment and Unemployment Statistics (1979) for discussions of this and other aspects of unemployment measurements.] The unemployment rate is particularly ambiguous as an indicator of employment problems in the youth population because it becomes entangled with school attendance. When young people say that they are looking for work even though they are also enrolled in school, they are none- theless counted as unemployed. This method of counting raises serious questions of interpretation since full-time students, it can be argued, already have a full-time though unpaid occupation, attending school. This component of youth unemployment statistics is not insubstantial: for example, almost half of the 1978 teenage unemployment shown in Table 2.1a is generated by youths who were enrolled in school. It is thus necessary to examine other measures to better understand the nature and scope of youth employment problems.

38 TABLE 2.2a Civilian Employment-to-Population Rates for Selected Groups (in percentages) Year Group 1957 1964 1978 1984 Adult white males 35-44 years old 95.6 95.1 93.9 91.6 All youths 16-19 years old 43.9 37.3 48.5 43.7 20-24 years old 59.5 60.9 69.6 68.7 White males 16-19 years old 52.4 45.0 56.3 49.0 20-24 years old 80.5 79.3 76.0 78.0 Nonwhite males 16-19 years old 48.0 37.8 29.8 25.2 20-24 years old 78.2 78.1 61.1 58.3 White females 16-19 years old 38.3 32.2 48.7 47.0 20-24 years old 43.4 45.3 60.6 66.1 Nonwhite females 16-19 years old 26.5 21.8 23.5 21.8 20-24 years old 40.9 43.7 45.4 46.3 NOTE: The years 1957, 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak. In 1984 the rate of unemployment among white males aged 35-44 was 4.6 percent. SOURCES: Data from U.S. Department of Labor (1979, 1980a, 1985b); Bureau of Labor Statistics (1983~. Employment-to-Population Rates Table 2.2a presents the employment-to-population rates (the number of employed divided by the total civilian population) for youths in the same years for which the unemployment rates are presented. Over the period 1957 to 1978, the employment rate in the youth population actually ~ slightly increase increased from 52.0 to 59.9 percent, although it then declined to 58.3 percent in 1984 (not shown in the table). The in employment rates between 1957 and 1978 was more marked for

39 TABLE 2.2b Ratio of Civilian Employment-to-Population Rates for Young White Males to Other Young Groups Year Group 1957 1964 1978 1984 White males 16-19 years old 1.0 1.0 1.0 1.0 20-24 years old 1.0 1.0 1.0 1.0 Nonwhite males _ 16-19 years old .92 .84 .53 .51 20-24 years old .97 .98 .80 .75 White females 16-19 years old .73 .72 .87 .96 20-24 years old .54 .57 .80 .85 Nonwhite females 16-19 years old .51 .48 .42 .44 20-24 years old .51 .55 .60 .59 NOTE: The years 1957, 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak. In 1984 the rate of unemployment among white males aged 35-44 was 4.6 percent. SOURCES: Data from U.S. Department of Labor (1979, 1980a, 1985b); Bureau of Labor Statistics (1983~. the older youth group, aged 20-24, than for the younger group, and the decline from 1978 to 1984 was steeper for the younger group. At a more detailed level, the trends for various demographic groups are not homogeneous. For example, there was a large increase in the employment rates of white women aged 20-24 (from 43 percent in 1957 66 percent in 1984), but there was also a substantial decline in the to employment rates for nonwhite men of the same age group (from 78.2 to 58.3 percent). Table 2.2b presents the ratios of the employment rates of each group to the employment rate for white males. From 1957 to 1984 this ratio declined markedly for nonwhite males. For nonwhite females the ratios declined for the younger group, while they increased somewhat for 20- to 24-year-olds. Nonetheless, in all years for both age groups, the likelihood that nonwhite females would be employed was less than 0.6 times the likelihood that white males would be employed. For white females, the ratios showed steady increases from 1964 to 1984, with the ratio for the most recent year approaching parity for 16- to 19-year-olds; however, it was somewhat lower (0.85) for 20- to 24-year-olds.

40 Employment of In-School and Out-of-School Youths Any discussion of employment-to-population rates runs the risk of confusing trends in school attendance with trends in employment. In the present case, this is a particularly worrisome possibility. While the employment rate for nonwhite youths has declined over the last 3 decades (as shown in Table 2.2a), the school enrollment rate for nonwhite youths has increased during these same decades. The rate of high school completion among black men and women aged 25-29 rose from 47.7 percent in 1960 to 65.4 percent in 1970 and to 79.4 percent in 1983. The employment patterns of youths who are enrolled in school are, of course, considerably different from those who are out of school. Table 2.3 provides a breakdown by school enrollment of the employment rates for 1964, 1978, and 1981 for all youths aged 16-24.2 As one would expect, in-school youths are less likely to be employed than out-of-school youths. However, there are significant differences in these rates over time for different groups. For white males, the employment rates increased for in-school youths from 34.0 percent in 1964 to 43.4 percent in 1981, while the rate for out-of-school youths was stable at approximately 87 percent between 1964 and 1978 and then declined slightly during the economic downturn in 1981. In contrast, the employment rates of black males have shown a marked decline for both in-school and out-of-school youths: the rate for those out of school was 80.5 percent in 1964, 67.8 in 1978, and 57.8 in 1981; the rate for those in school dropped from 30 percent in 1964 to 20 percent in 1978 and was still at 20 percent in 1981. 3 iIdeally, one would like to examine trends in employment status broken down by school enrollment, race, sex, age, presence of dependents, and living arrangements. Unfortunately, tabulations of employment statistics (e.g., the Employment and Earnings series and the Handbook of Labor Statistics) do not provide the appropriate detail. Indeed, even with the 60,000+ sample size of the Current Population Survey, we suspect it would be difficult to obtain reliable estimates for all the cells of such a cross-tabulation. Consequently we use the strategy of examining the employment status of older, out-of-school youths as a crude substitute. 2 The years 1964 and 1978 were selected to provide consistency with other tables in this chapter. Appropriate data were not published in 1957 (or earlier years). No data are currently available for 1984; consequently, we have used the most recent published statistics, for 1981. 3 In this discussion of Tables 2.3 and 2.4 we used statistics for black youths rather than for nonwhite youths. This reflects the categorization used in the published statistics. Federal statistics for recent years generally divide the population by black and white and include counts for the total population (so nonwhite statistics can be computed). For earlier years it is often

41 TABLE 2.3 Employment-to-Population Rates for In-School and Out-of-School Youths Aged 16-24 by Sex and Race: 1964-1981 Emp Out-of Group School Youths In-School Youths White males 1964 86.7 34.0 1978 86.9 46.9 1981 81.1 43.4 Black males 1964 80.5 30.0 1978 67.8 20.3 1981 57.8 20.1 White females 1964 47.3 23.3 1978 66.2 45.7 1981 68.3 43.0 Black females 1964 48.0 15.4 1978 46.9 20.6 1981 43.0 17.2 SOURCE: Bureau of Labor Statistics (1982:Table C-42. Comparing the data for young males, one finds that in 1964 the employment rates of both in-school and out-of-school black males were roughly 90 percent as large as those of white males. However, by 1981 this gap had widened enormously: in-school black males were less than 50 percent as likely to be employed as white males, and out-of-school black males were only 71 percent as likely to be employed as white males. For young females, the data for blacks and whites also show very different trends. Both in-school and out-of-school white females registered roughly a 20 percentage point increase in their employment the case that only statistics for whites and nonwhites were published. It is thus impossible to produce long time series (e.g., 1950-1980) that describe the black youth population. Nonetheless, the nonwhite statistics, while less than ideal, do capture much of what is important since blacks constitute the vast majority of the nonwhites in the United States. In 1980 the nonwhite population included: 26.5 million blacks; 3.5 million Asians and Pacific Islanders; 1.4 million American Indians, Eskimos, and Aleuts; and 6.8 million persons whose race was classified as "other."

42 TABLE 2.4 Employment-to-Population Rates for Out-of-School Youths by Age, Race, and Sex: 1964-1981 Age Group 16-17 18-19 20-24 White males 1964 65.6 80.9 90.0 1978 52.2 85.0 89.5 1981 54.3 75.3 84.0 Black males 1964 43.8 73.4 86.6 1978 19.4 44.7 59.4 1981 22.2 39.8 62.8 White females 1964 30.7 51.9 47.3 1978 47.3 64.7 67.7 1981 34.1 62.4 68.3 Black females 1964 35.9 45.1 50.2 1978 21.4 46.7 63.4 1981 5.5 29.5 48.5 SOURCE: Bureau of Labor Statistics (1982:Table C-42. to-population rates between 1964 and 1981. For the in-school group, their employment rate in 1981 was virtually identical to that of white males. For out-of-school females, their employment rates were con- sistently below those of young white males, although they increased significantly between 1964 and the later two years. For black females, there was a slight upward trend in employment while in school during the period 1964 to 1981; for the out-of-school group, the rate declined slightly over the period, from 48 percent in 1964 to 43 percent in 1981. Table 2.4 disaggregates the employment-to-population rates of out-of-school youths by age. This breakdown shows that the aggregate results hold for all age groups of out-of-school youths, including the oldest. Many researchers argue that unemployment among these older, out-of-school~youths is of particular concern because they are more likely to have dependents to support and to be living outside their parental home. This group shows the familiar pattern of rather high employment rates among white males (90.0 percent in 1964, 84.0 percent in 1981) and consistently lower rates for blacks and females. For out-of-school black males aged 20-24, the employment-to-population rate in 1964 (86.6 percent) approaches that of white males, but the rate declines by over 20 percentage points in the following decade. White females in this age group show increasing rates of employment, but they are still less likely to be employed than white males (47.3 percent of

43 TABLE 2.5a Civilian Labor Force Participation Rates by Age, Race, and Sex (in percentages) Year Group 1957 1964 1978 1984 All Youths 16-17 years old 40.2 35.1 48.6 42.4 18-19 years old 60.4 57.2 67.3 64.9 20-24 years old 64.0 66.3 76.8 77.6 White males 16-17 years old 49.6 43.5 55.3 47.0 18-19 years old 71.6 66.6 75.3 70.8 20-24 years old 86.7 85.7 87.3 86.5 Nonwhite males 16-17 years old 47.5 37.3 33.2 27.0 18-19 years old 72.0 67.2 58.9 55.4 20-24 years old 89.6 89.4 77.5 77.2 White females 16-17 years old 32.1 28.5 48.8 44.8 18-19 years old 52.6 49.6 64.6 65.2 20-24 years old 45.8 48.8 69.3 72.5 Nonwhite females 16-17 years old 24.1 19.5 27.7 24.7 18-19 years old 42.S 46.5 48.4 45.8 20-24 years old 46.6 53.6 62.6 60.5 NOTE: The years 1957, 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was at about its peak. In 1984 the rate of unemployment among white males aged 35-44 was 4.6 percent. SOURCE: Data from U.S. Department of Labor (1982, 1985b). white females were employed in 1964 and 68.3 percent in 1981~. For black females aged 20-24, the employment rate rises from 50.2 percent in 1964 to 63.4 percent in 1978 and then declines to 48.5 percent in 1981. Labor Force Participation Rates and Summary of Employment Data Tables 2.5a and 2.5b provide complementary information on the aggregate civilian labor force participation rates of youths by age, sex, and race. (The civilian labor force participation rate is the ratio of employed and unemployed people to the total nonmilitary

44 TABLE 2.Sb Ratio of Civilian Labor Participation Rates for Selected Groups to Rate for White Males Group Year 1957 1964 1978 1984 White males 16-17 years old1.01.0 1.0 1.0 18-19 years old1.01.0 1.0 1.0 20-24 years old1.01.0 1.0 1.0 Nonwhite males 16-17 years old.96.86 .60 .57 18-19 years old1.001.00 .78 .78 20-24 years old1.031.04 .89 .89 White females 16-17 years old.65.66 .88 .95 18-19 years old.73.74 .86 .92 20-24 years old.53.57 .79 .84 Nonwhite females 16-17 years old.43.45 .50 .53 18-19 years old.60.70 .64 .65 20-24 years old.54.63 .72 .70 NOTE: The years 1957, 1964, and 1978 were selected because in each of these years the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was at about its peak. In 1984 the rate of unemployment among white males aged 35-44 was 4.6 percent. SOURCE: Data from U.S. Department of Labor (1982, 1985b). population; as noted above, the labor force statistics exclude persons who are unemployed and not looking for work.) A comparison of the rates in Tables 2.1a through 2.2b and Tables 2.5a and 2.5b suggest that youth unemployment is generated by somewhat different underlying trends for males and females and whites and nonwhites. For that reason it is useful to discuss each group separately. White Males The labor force participation rates for white males fluctuated over the 1957-1984 period. They were up in 1957 and 1978 (particularly for 16- to 17-year-olds) but declined in 1964 and 1984. There was also an upward movement in the employment-to-population rate between 1957 and

45 1978 for youths aged 16-19, but the employment rate for youths aged 20-24 declined from 80 percent to 76 percent in 1978 then rose to 78 percent in 1984. The unemployment rate for the younger group has increased because the labor force participation rate of the group aged 16-17 has increased by more than the employment-to-population rate. Nonwhite Males For nonwhite males the story is stark and consistent. During the period from 1957 to 1984, the labor force participation rates of young nonwhite males of every age group declined considerably, and their employment-to-population rates also dropped markedly. The proportion of those aged 16-19 who were employed declined from 48 to 25.2 percent; for those aged 20-24 it declined from 78.2 to 58.3 percent. Thus the large increases shown in Table 2.1a for the unemployment rates of nonwhite males understate the labor market difficulties faced by this group: had their labor force participation rates not declined from 1957 to 1984, their unemployment rates would have been even higher than shown in Table 2.1a. White Females White females sharply increased their labor force participation from 1957 to 1984. For 20- to 24-year-olds, the rate of participation increased from 45.8 to 72.5 percent, and the gap between white male and female levels of participation decreased substantially. The employment- to-population rates for this group also increased during this period, from 43.4 to 66.1 percent for those aged 20-24, and as a result their unemployment rate increased. The overall picture for white females is one of an improving employment situation, but one that has not improved rapidly enough to keep pace with their increasing desire (and need) to participate in the labor force. Nonwhite Females The labor force participation rates of nonwhite females increased less rapidly than did the rates for white females, although the increase for 20- to 24-year-olds is still quite sharp, from 46.6 percent in 1957 to 60.5 percent in 1984. During the entire period, nonwhite females have had lower labor force participation rates than all other subgroups. The employment-to-population rate for nonwhite females declined for those aged 16-19 and increased for those aged 20-24. For the entire period nonwhite females had lower employment-to-population rates than all other subgroups. Thus, despite some signs of improvement in absolute levels for those aged 20-24, the employment rates reveal the very serious situation of nonwhite females in comparison with other groups of the youth population.

46 Hispanic Youths There are no adequate historical data to perform similar analyses for Hispanic youths, and so we are unable to assess the dynamics that may account for the Hispanic unemployment rates shown in Table 2.1a. Those rates are higher than those for white youths but lower than those for nonwhite youths: as shown, for males aged 20-24, the unemployment rates in 1984 were 9.8 percent for white males, 12.1 percent for Hispanic males, and 24.5 percent for black males. Inactivity Rates The above analyses suggest that when one looks beyond the unemploy- ment rate, a more complex picture of the nature of the youth unemploy- ment problem emerges. The most striking features of this picture are the changing dynamics of female employment (particularly among whites) and the stark contrast between the employment statistics for young black men and women and those faced by other groups. These differences can be seen even more clearly in "inactivity rates," the numbers of youths who are neither in school, nor in the military, nor employed relative to their population. Table 2.6a presents inactivity rates for several demographic groups for the years 1964, 1978, and 1983. For almost every group the inactivity rates were lower in 1978 than they were in 1964; the major exception is for nonwhite males aged 20-24, whose inactivity rate during this period climbed from 10.5 to 15.9 percent. It should also be noted that the inactivity rates for both white and nonwhite women aged 20-24 remained strikingly higher than those for white and nonwhite males. As shown in Table 2.6a, the inactivity rates for nonwhite females in 1978 were 28.0 percent for 18- to 19-year-olds and 33.5 percent for 20- to 24-year-olds. In 1983 the inactivity rates of almost all groups were higher than in 1978. This reflects the depressed state of the national economy in 1983, which is also reflected in the rise in the rate of unemployment for 35- to 44-year-old white males from 2.5 percent in 1978 to 5.2 percent in October 1983. During this period the inactivity rates for nonwhite females took especially large leaps: in 1983 more than 40 percent of nonwhite women aged 18-24 were out of work and out of school. While inactivity rates for all groups rose in 1983, because inactivity rates for white males rose faster than did those of other groups, the situation of nonwhites of both sexes and white females showed some improvement relative to that of white males; see Table 2.6b. For example, among 20- to 24-year-olds, the inactivity rates relative to white males declined from 2.69 to 2.33 for nonwhite males, from 4.08 to 2.16 for white females, and from 5.68 to 3.93 for nonwhite females. However, the inactivity rates for both male and female nonwhites and for white females are still higher than those for white males. Over the entire period 1964 to 1983, the lowest inactivity rates for every age group are those for white males.

47 TABLE 2.6a Inactivity Rates for Youths by Race and Sex Year . Group 19641978 1983a White males 16-17 years old 3.33.6 4.5 18-19 years old 8.04.7 13.1 20-24 years old 6.15.9 11.6 Nonwhite males 16-17 years old 8.43.7 4.7 18-19 years old 14.613.2 29.3 20-24 years old 10.515.9 27.0 White females 16-17 years old 9.64.6 5.7 (5.7) 18-19 years old 31.9 13.218.5 (18.6) 20-24 years old 46.8 24.125.1 (25.3) Nonwhite females 16-17 years old 11.5 6.45.8 (5.9) 18-19 years old 36.2 28.042.2 (42.5) 20-24 years old 45.7 33.545.6 (45.6) NOTE: Inactivity rates are the percentage of the population that is neither employed, serving in the military, nor enrolled in school. The years 1964 and 1978 were selected because the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak. October 1983 is the most recent date for which comparable rates can be computed. In October 1983 the rate of unemployment among white males aged 35-44 was 5.2 percent (not seasonally adjusted). aFor 1983, figures in parentheses are female inactivity rates calculated to take account of military service by females. SOURCES: Data for 1964 and 1978 from Congressional Budget Office (1982~; data for 1983 computed from Bureau of Labor Statistics (1984) and unpublished tabulation of military enrollment by age, race, and sex. (Data for 1984 are not currently available.)

48 TABLE 2.6b Ratio of Inactivity Rates for Other Groups to Those for White Males Year Group 1964 1978 1983a White males 16-17 years old 1.0 1.0 1.0 18-19 years old 1.0 1.0 1.0 20-24 years old 1.0 1.0 1.0 Nonwhite males 16-17 years old 2.55 1.03 1.04 18-19 years old 1.82 2.80 2.24 20-24 years old 1.72 2.69 2.33 White females 16-17 years old 2.91 1.28 1.27 (1.27) 18-19 years old 3.99 2.81 1.41 (1.42) 20-24 years old 7.67 4.08 2.16 (2.18) Nonwhite females 16-17 years old 3.48 1.78 1.29 (1.31) 18-19 years old 4.53 5.96 3.22 (3.24) 20-24 years old 7.49 5.68 3.93 (3.93) NOTE: Inactivity rates are the percentage of the population that is neither employed, serving in the military, nor enrolled in school. The years 1964 and 1978 were selected because the unemployment rate for white males aged 35-44 was an identical 2.5 percent and the business cycle was about at its peak. October 1983 is the most recent date for which comparable rates can be computed. In October 1983 the rate of unemployment among white males aged 35-44 was 5.2 percent (not seasonally adjusted). aFor 1983, figures in parentheses are female inactivity rates calculated to take account of military service by females. SOURCES: Data for 1964 and 1978 from Congressional Budget Office (1982~; data for 1983 computed from Bureau of Labor Statistics (1984) and unpublished tabulation of military enrollment by age, race, and sex. (Data for 1984 are not currently available.)

49 As the ratios presented in Table 2.6b make clear, the disparities in inactivity rates are often quite large. For females, even though the disparities in inactivity declined between 1964 and 1983, inactivity rates for those aged 20-24 were still 2.16 (for whites) and 3.93 (for nonwhites) times as large as those of white males. (It is unfortunate that we are unable to disaggregate this result to determine the portion of female "inactivity" that represents women who are at home with young children. Because some of this female "inactivity" represents child- bearing, readers are advised to interpret the inactivity rates in conjunction with the unemployment rates shown in Table 2.1.) For nonwhite males, the trends across time show increasing disparity for youths aged 18-24. While the ratio of inactivity rates was 1.82 (for those 18-19) and 1.72 (for those 20-24) in 1964, it had increased to 2.24 and 2.33 by 1983, and the disparity was even higher during 1978, a time of increased economic activity. The sole exception to this disturbing picture is found among the youngest group of nonwhite males. Their ratio declined from 2.55 in 1964 to approximate parity in 1978 (a ratio of 1.03) and remained at that level in 1983 (a ratio of 1.04~. This improvement relative to white males is attributable to increased levels of school enrollment and roughly constant rates of military enlistment for young black males. A similar trend can be observed for 16- to 17-year-old females, although in 1983 both white and nonwhite females were still approximately 1.3 times as likely to be out of school and out of work as white males. Entry, Turnover, and Unemployment Another way to understand the nature of the youth employment problem is to study the nature of the events that lead to unemployment. An analysis by Freeman and Medoff (1982) provides some insight into the processes that lead to youth unemployment (see Table 2.77. The salient feature of Table 2.7 is the sizable proportion of young people whose unemployment is associated with entry into the labor force--either for the first time, as new entrants, or reentry after a period out of the labor force. The high proportion of new entrants among youths is not surprising. The high proportion of reentrants reflects the fact that teenagers tend to drop out of the labor force after a period of unem- ployment. As youths get older, however, their unemployment is less likely to be due to entry or reentry into the labor market. Thus, in 1978, for those aged 16-17, entrants into the labor market accounted for the vast majority of the unemployed--39.8 percentage points of the 44.0 percent unemployment rate of blacks and 11.0 percentage points of the 13.8 percent unemployment rate of whites in 1978. Among those aged 18-19 entrants into the labor market accounted for 30.5 percentage points of the 38.0 percent unemployment rate for blacks and 4.5 percentage points of the 9.0 percent rate for whites. By the age of 20-24, most of the unemployed youths have left or lost their jobs: entrants into the labor market account for only 7.9 percentage points of the 18.8 percent black unemployment rate and 2.3 percentage points of the 6.6 percent white unemployment rate.

50 TABLE 2.7 Direct Causes of Youth Unemployment, Males and Females: 1969-1978 Age and Status Black White . 1969 1975 1978 1969 1975 1978 16-17 years old Total unemployment rate24.642.444.0 10.7 17.713.8 losers2.75.63.4 1.4 3.31.5 leavers2.41.80.8 1.0 1.41.3 total entrants19.635.139.8 8.2 13.011.0 reentrants7.719.511.9 3.5 5.04.2 new entrants11.915.628.0 4.7 8.06.8 18-19 years old Total unemployment rate18.536.738.0 5.7 15.99.0 losers5.413.14.8 1.9 7.22.7 leavers4.50.72.7 0.7 1.31.9 total entrants8.622.930.5 3.1 7.44.5 reentrants8.114.117.8 2.5 4.82.9 new entrants0.5a8.812.7 0.6 2.61.6 20-24 years old Total unemployment rate7.128.318.8 4.4 13.66.6 losers2.518.08.7 1.6 8.73.1 leavers2.71.72.2 1.0 1.01.2 total entrants2.08.77.9 1.7 4.02.3 reentrants1.55.85.1 1.5 3.61.8 new entrants0.52.92.9 0.2 0.40.5 NOTE: Regularly published tabulations (e.g., Employment and Earnings) do not provide age breakdowns for 16- to 17- and 18- to 19-year-olds. Thus there are no readily accessible tabulations for years after 1978. aThis rate is reported as .05 in Freeman and Medoff (1982~. This appears to be a typographical error; it has been corrected to 0.5, which would be consistent with the published rates for total entrants and reentrants. SOURCE: Freeman and Medoff (1982~. A second important cause of unemployment as shown in Table 2.7 is the high percentage of job losers; for all but one group (blacks aged 20-24 in 1969), job losers exceed job leavers. In contrast to the usual view that youths have high unemployment rates because they quit jobs more often than adults, these data indicate that their problems arise primarily because they lose jobs or tend to find jobs for which the probability of firing or layoffs is higher.

51 TABLE 2.8 Ratios of the Median Usual Weekly Earnings of Out-of-School Males to Earnings of Male Workers Aged 25 and Older, by Race: 1967-77 Earnings of Full-Time Change Earnings of Full-Time Change Young White Men/ in Young Nonwhite Men/ in Earnings of Full-Time Earnings Earnings of Full-Time Earnings White Men, Age 25+ Ratios White Men, age 25+ Ratios Age 1967 1977 1967-77 1967 1977 1967-77 16 .38 .34 -.04 .33 .32 -.01 17 .49 .39 -.10 .39 .32 -.07 18 .54 .49 -.05 .44 .44 .00 19 .61 .52 -.09 .42 .43 -.01 20 .66 .58 -.08 .63 .52 -.11 21 .73 .61 -.12 .57 .50 -.07 22 .79 .63 -.16 .59 .54 -.05 23 .81 .71 -.13 .59 .54 -.05 24 .87 .75 -.12 .60 .63 -.03 SOURCE: Data from Freeman and Medoff (1982:Table 3.9). In an interesting analysis of the black/white differential in unemployment, Freeman and Medoff (1982) demonstrate that much of the gap is due to the longer time it takes young black men and women to find a job on entry into the labor force. In addition, among youths aged 20-24, the higher black unemployment rate is partly due to a higher job loss rate than for whites. Black youths appear to have both a harder time finding a first job and a greater likelihood of losing a job than whites (Freeman and Medoff, 1982~. Entry and job turnover figures cannot, however, be used to discount the unemployment problem as a whole, since a subset of youths are unemployed for long periods of time and bear a disproportionate share of the burden. Feldstein and Ellwood (1982), using 1976 Current Population Survey data on out-of-school teenagers, estimate that 8.3 percent of the youths were unemployed for more than 26 weeks and account for 52 percent of total unemployment days among that group. Lerman (1980a) estimates, using 1977 data, that 70-80 percent of total youth unemployment (including that of in-school youths) was borne by youths with 15 or more weeks of unemployment. Wages and Earnings While many employment problems can be measured in terms of nonemployment of one type or another, a full picture of the youth employment predicament also requires consideration of wages and earnings. Table 2.8 presents data on the earnings of male youths as a percentage of earnings of white males aged 25 and over. Two features of these data should be noted: First, over the decade from 1967 to 1977, the earnings of young men relative to those of adult men declined.

52 Second, the extent of the decline was greater for white than nonwhite youths and, therefore, the earnings of young black men grew relative to those of young white men. Thus, we see both a general deterioration of earnings of young males and a relative increase in earnings (actually a smaller decrease) for young black males compared with young white males. Moreover, when various individual characteristics are controlled, the average wages for young black males are not significantly different from those of young white males. The observed difference in total earnings is due primarily to the fact that the probability of a young black male with a given set of characteristics obtaining a job is much lower than that of a young white male with similar characteristics (Freeman, 1980~. Unfortunately, there is no comparable analysis for the earnings of young women, and thus we do not know if a similar finding would result. CAUSES AND CONSEQUENCES OF YOUTH EMPLOYMENT PROBLEMS The previous section has documented unemployment rates and other measures of employment for youths and differences among blacks and whites, males and females, and other groups for the past 2 decades. It has also raised a score of questions. What explains the high unemploy- ment rate of youths compared with adults? Why have rates of unemploy- ment been rising? Why has the gap between blacks and whites widened? How do these trends relate to the relative decline in earnings for young full-time workers and the narrowing gap in earnings between young white and black full-time workers? What is the source of the male/ female differences in youth employment experiences? Researchers typically discuss a number of supply and demand factors that might contribute to continuing high unemployment rates for youths (e.g., Ellwood and Wise, 1983~. On the demand side the factors include: poor macroeconomic performance; shifting geographical and industrial distribution of jobs; minimum wage laws and other government interven- tions in the labor market; discrimination in hiring; and demand for military personnel. On the supply side the factors include: the baby boom bulge and other demographic factors; unrealistic expectations of youths and the "reservation" wage; and mismatched jobs and educational qualifications. Each of these factors is discussed in this section, in turn, along with recent empirical evidence and the nature of continuing disagreements among researchers. At the end of this section, we also consider other factors that do not fit neatly into the demand and supply categories. At the outset it should be kept in mind that it is not possible to discriminate accurately among all these causes given the available data. If time-series data are used, there are too many overlapping and correlated trends to distinguish among them: for example, the baby boom bulge coincided with "stagflation" and poor macroeconomic per- formance in the 1970s. It is also very difficult to measure or dis- tinguish between the effects of subjective variables such as discrimination on the demand side or low motivation or lack of general skills on the supply side.

53 Factors Affecting the Demand for Labor Macroeconomic Conditions The unemployment rates of youths are more sensitive to macro- economic conditions than are those of adults. Comprehensive studies of time-series data by the Congressional Budget Office and the Council of Economic Advisors suggest that a 1 percent change in the unemployment rate for adult males is matched by a 1.5 percent change for white youths and a 2.5 percent change for black youths (e.g., Congressional Budget Office, 1978~. Freeman (1982) has argued and we agree that the employment-to-population ratio is a more reliable indicator of youth activity. In both time-series and cross-sectional data, he finds that a 1 percent change in the total male unemployment rate leads to a 1.7 to 2.4 percent change in the employment-to-population ratio for youths aged 16-19 and a 1.5 to 3.4 percent change for those aged 20-24 (Freeman, 1980~. Bowers has reviewed the employment experiences of blacks, teenagers aged 16-19, and women during all business cycles from 1948 to 1980, and he also concludes (Bowers, 1981) that teenagers and blacks, both in the aggregate economy and in key cyclical sectors, suffer a disproportionate share of the decline in employment that occurs during economic recessions. It should be noted that when the adult male unemployment rate was trending upward over the past 2 decades (even from peak to peak in the business cycles), the foregoing relationships imply that there would be an even greater deterioration in the employment situation for the teenage group. Such data provide only a crude indicator, of course, of the complex relationships that exist between the employment problems of teenagers and the evolution of the macroeconomic situation in the nation. Nonetheless, there appears to be substantial agreement among most researchers that a relatively high level of economic activity is essential for any long-term improvement in the youth employment situation. Industrial and Geographical Shifts in the Economy From year to year, the American economy changes. Wealth increases and tastes change, new technologies are discovered and brought on line, old factors of production or natural resources are used up and new ones found, foreign trade opens up opportunities for some U.S. goods and creates intense competition for others. At the same time, broad shifts may occur in where people want to live, from one region to another or from cities to suburbs or from suburbs to rural areas. These changes are very likely to lead to shifts in the demand for young workers over time, although the precise links may be hard to trace. If wage rates or other factors of production were totally flexible--as in classical economic models--supply and demand would quickly adjust, but such is not the case in reality. The decline of agriculture and the movement of black families from southern rural areas to northern cities explains some of the widening

54 black/white youth unemployment gap in the 1950s and early 1960s. Cogan (1982), Lerman (1980a), and Mare and Winship (1983), among others, have pointed out that in 1950 young black men in farm areas of the South experienced minimal unemployment (e.g., 3 percent for 18- to 19- year-olds). At the same time, the unemployment rate for urban young black men was 20 percent, substantially higher than for whites. The large-scale flow of blacks northward and from rural to urban areas would thus, all else being equal, contribute to an increased disparity between the unemployment rates of white and black males (since the black migrants would now, presumably, suffer from unemployment at the higher rate characteristic of black urban residents). However, since 1970 migratory patterns have changed, and the racial differential has been increasing in all regions. Migration alone cannot explain this phenomenon. Another possible cause of a downward shift in demand for youths, particularly for blacks, is the movement of jobs from the inner cities to the suburbs and beyond (a move resulting in large part because land and other costs are lower). This is a matter of some dispute in the economics literature. Leonard (1984) has found, for example, that the ratio of black to total employment in any given firm in Los Angeles or Chicago in the 1970s varied inversely with distance from the black ghetto. Over time, the loss of employment in the cities has resulted in an appreciable loss of jobs for blacks who, apparently because of racial discrimination, do not follow the jobs as they move into the suburbs and nonmetropolitan areas. However, this movement of jobs away from where blacks live cannot explain the black/white differential that persists within inner cities. Ellwood (1983), for example, has shown that in Chicago distance from jobs was a weak predictor of employment: for black and white youths living in adjacent neighborhoods, black youth employment could be as much as 20 percent lower than white youth employment; similarly, blacks in neighborhoods near jobs were no more likely to be employed than blacks in neighborhoods far away from jobs. Minimum Wage Laws and Other Government Interventions Low wages are an unfortunate fact of life for many young workers in America. Since low-wage workers are more likely to have their jobs affected by the statutory minimum wages, much of the concern about the policy implications of minimum wages has focused on the impact of minimum wages on the youth labor market. There have been several comprehensive reviews of the impact of minimum wage laws on the youth labor market (Brown et al., 1982; Freeman, 1982; Report of the Minimum Wage Study Commission, 1981; Welch and Cunningham, 1978; Mincer, 1976; Kosters and Welch, 1972~. Most estimates of the disemployment effects are relatively small. The estimates from time-series data indicate that the disemployment effects for white males resulting from a 10 percent increase in the statutory minimum would reduce the level of employment by 1-3 percent (Freeman, 1980~. For young blacks and women, there are larger estimated effects, and the greatest effects on employment are for the youngest workers. Theoretically, nonwhites

55 should experience greater levels of disemployment, but Brown, Gilroy, and Kohen (1982) could find no convincing evidence that this occurs. Economic researchers have also become interested in the nonemploy- ment influences of a statutory minimum wage. Hashimoto (1982), Lazear and Miller (1981), and Fleisher (1981) have argued that, in addition to whatever disemployment effects are caused, the minimum wage will also prevent young people from being able to engage in on-the-job training. These human capital theorists propose a model in which an employee's full wage has a market wage and an unmeasured component of on-the-job training that shows up in future wage growth. Using the National Longitudinal Survey (NLS) between 1966 and 1969, Hashimoto (1982) estimates that the loss in earnings growth would be between 2.7 and 15 percent of the observed wage of workers. It seems unlikely, however, that the minimum wage could explain the increasing gap in employment between adults and youths (particularly minorities and women) since, in real terms, the minimum wage has been declining in recent years.4 Discrimination Discrimination could contribute to youth employment problems in the form of discrimination on the basis of age or on the basis of race or 4 In addition to whatever disemployment or nonemployment is caused by the minimum wage on the demand side, the existence of income maintenance programs may work (along with minimum wage laws) to provide an alterna- tive to work for children of families receiving income maintenance. Thus, these government interventions might affect the supply of labor. Betsey and Dunson (1981) find that part of the estimated minimum wage impact may be attributable to increases in welfare payments. It is clear that in trying to assess the impact of minimum wages one has to also consider changes in other income maintenance programs. Venti (1984) has estimated the disemployment effects caused by one income maintenance program, using data from the Seattle-Denver Income Maintenance Experiment. This experiment offered benefits well in excess of contemporary welfare programs (e.g., financial support levels for a family of four of $3,800, $4,800, and $5,600 in constant 1971 dollars). Venti finds that this income maintenance program had large disemployment effects, but that when one considers the choice as a joint one with the decision to go to school, almost all of the disemployment is a movement into schooling, not into idleness. Venti and Wise (1984) argue that interpretation of these results requires an allowance for schooling decisions because analysis of "the simple work effect may be an incomplete indicator of the social and economic consequences of an income maintenance program." Of course, in turn, one does not know whether some of this movement into schooling may represent disguised idleness: Are youths using their time to gain real market skills through schooling or simply disguising their problem with unproductive schooling?

56 sex. That employers prefer older workers to younger workers seems to be well established. However, whether this preference constitutes discrimination depends on whether there are in fact differences in productivity, costs of training, and turnover associated with younger workers (Freeman, 1980~. There have been few attempts to establish such relationships empirically. Discrimination studies have con- sistently shown black adult workers to have lower earnings than whites after the measured individual characteristics have been controlled for; a large part of this earnings differential is associated with the probability of employment rather than differences in wages. With respect to wages and earnings (net of weeks worked) and common capital variables (e.g., education), economists have generally human found substantial evidence of discrimination in wages prior to the mid-1960s, but in more recent years the available evidence suggests that discrimination in wage rates by race has been narrowed 1983) or effectively ended (Osterman, 1980; Freeman, 1973~. workers, however, the situation is quite different. year-round workers, the earnings of women average less than 60 percent of those of men, and young women (age 20-24 years) earn approximately 87 percent as much as young men. A National Research Council review of discrimination in wage-setting found that the evidence "suggests that only a small part of the earnings differences between men and women can be accounted for by differences in education, labor force experience, labor force commitment, or other human capital type factors believed to contribute to productivity differences among workers" (Treiman and Hartman, 1981~. A major confounding factor is the substantial occupa- tional segregation of the work force--with women being concentrated in occupations that are low paying. With respect to employment--in contrast to wages--efforts have been reported by Osterman (1980b) to account for the disparity in unemploy- ment rates between whites and blacks on the basis of standard human capital variables. He found that about one-half of the gap in unemploy- ment rates between young black and white workers could be accounted for: if one followed the convention used in the earnings literature, the residual gap would be attributed to discrimination (Osterman, 1980b). The actual mechanics by which this discrimination operates are difficult to specify. Culp and Dunson (1983) present findings from a pilot study suggesting that treatment of job applicants with the same backgrounds and qualifications may depend in many crucial ways on the - ~~ ~ ~ There is also evidence (Ross) and Ornstein, Among full-time, (Reimers, For women race of the applicant. 1973) suggesting that the social networks and friendships used to find jobs are segregated by race, resulting in some disadvantage to nonwhite youths. While discrimination may account for differences between blacks and whites at a aiven Point in time, it is more difficult to establish that increases in discrimination in the late 1960s and the 1970s were an important factor in explaining the increasing differential in employment between young blacks and young whites.

57 Antidiscrimination Laws and Enforcement The three key pieces of statutory and administrative policy that affect the level of discrimination in society--Title VII of the 1964 Civil Rights Act, Executive Order 11246, and the Equal Pay Act of 1962--emphasize the job market opportunities of entrants or reentrants into the job market. All three were enacted or issued before the employment problems of young people were generally viewed as central issues in the society. Analysts disagree on how effective Title VII (and other measures) can be for young minority and female workers. The statute exempts many small employers from the statutory scheme. When the act became effective on July 2, 1965, it applied only to employers of 100 workers or more. The current limit is 15 workers, which still excludes coverage for many young people employed in small stores and restaurants. More than one-third of all youths aged 16-24 work in retail trade, including restaurants, and many of these are small operations not covered by Title VII. In addition to jobs not being covered by Title VII or corresponding limitations in Executive Order 11246, many young workers may find the cost of litigation to be too great, given their lack of commitment to a particular job. In order to bring pressure on a recalcitrant employer, someone must be willing to complain and involve himself or herself in the expensive and time-consuming process of enforcing the statute Is prohibitions against discrimination. One would expect the willingness to finance and bring suits to be positively related to expected length of job tenure and the relative attractiveness of that job in comparison with other possible job opportunities for the potential complainant. Both of these factors tend to be lacking in many jobs that young people have. Questions have sometimes been raised about potential disemployment effects of antidiscrimination laws and affirmative action programs. By raising black youths' wages, have they reduced employment? Freeman and Holzer (1985) reply to this question by noting that the laws and pro- grams are intended to change the demand for labor, not wages: they assume nondiscrimination in wage setting and attempt to increase the demand for minority and female workers. According to Freeman and Holzer (1985) the most reliable assessments of the effects of affirma- tive action programs indicate that the programs do increase employment of these groups, although this claim has been disputed in the economics literature. Demand for Military Personnel Service in the military has long been an important employment experience for young males, although the proportion of youths serving in the armed forces has been declining since the late 1960s. Despite this decline, the availability of employment in the military is impor- tant for some groups of the youth population. In 1984, 9 percent of nonwhite males aged 18-24 were in military service; the total number of

58 approximately 224,000 is quite substantial when viewed in perspective with the number of nonwhite male youths of the same age who were employed in civilian occupations (1.1 million). Changing patterns of military service by different racial groups masked some of the differ- ential in civilian employment between black and white youths. During the 1970s white youths' participation in the military declined sub- stantially while black youths' participation remained approximately constant (Ellwood and Wise, 1983~. If, after 1972, the proportion of black youths in the military had declined in proportion to the white decline, the proportion of black youths without work in 1982 would have have risen by about 3 percent (Mare and Winship, 1983~. (Participation in military service by females involved only 0.6 percent of white females and 1.4 percent of nonwhite females in 1984.) Factors Affecting the Supply of Labor Demographic Trends During the 1970s several demographic trends might have affected youth employment. First, and most prominent, was the entry of the massive baby-boom generation into the labor force. Theory suggests that as the supply of young workers rises relative to the supply of both older workers and other factors of production, youth wages or employment will fall relative to that of older workers. Indeed, in a cross-sectional analysis of standard metropolitan statistical areas, Freeman (1982) found that as the youth share of the population increased, employment prospects declined by a moderate amount, particularly for those aged 16-17. However, analysis by Wachter and Kim (1982) suggests that, at a national level and over time, the primary effect appears to have been on wages. For example, as shown in Tables 2.2a and 2.2b, during the period of rapid expansion of the youth labor force, 1957 to 1978, the employment-to-population rate for white youths stabilized or actually increased. In contrast, Table 2.8 shows that during the 1970s the wages of white youths declined relative to adult wages. Whatever the effects of this large demographic bulge, it did not overcome other factors tending to raise the employment-to- population rate for white youths, but it may have played a role in lowering their relative wages. Among black youths, however, the pattern appears different: relative wages over those years declined by less than those of white youths, but unemployment rose and employment rates fell substantially. Two other factors increased the supply of labor during the same period: the sharp and continuing rise in the labor force participation of adult women (see Hahn and Lerman, 1983) and the influx of immigrant workers into the United States. Each of those groups might draw jobs away from youths if they enter the labor market in part-time or low- skill jobs (particularly if employers prefer to discriminate in their favor or can pay lower wages to these groups). It is possible that increased numbers of women in the labor force may have worsened the employment prospects and lowered the wage rates of youths (Borjas,

59 1983), although there have been few studies of such effects. Estimating the employment interactions between youths and immigrants has been difficult because of the lack of reliable data on the illegal component of the immigrant work force. However, Freeman and Holzer (1985) report that there is no evidence to support the view that increases in the Hispanic population (which accounts for a substantial number of immigrants) have hurt job opportunities for black youths, since black youth unemployment rates are similar in cities with large and small Hispanic populations. A fourth demographic development of considerable importance is the change in childbearing and marital patterns in the youth population. During the 1970s there was both a decline in the rate of marriage among youths and an increase in divorce among those who did marry. It is possible that these changes might increase the supply of female labor. While childbearing declined sharply among young married women, it did not decline among unmarried women. Births to unmarried women tripled as a share of all births between 1960 and 1979 (although their number did not rise). In 1983 among married and unmarried women aged 18-24, there were 965 births per 1,000 female high school dropouts and 506 births per 1,000 female high school graduates who did not attend college (U.S. Bureau of the Census, 1984:Table 43. Since young, unmarried women with children have disproportionately lower incomes and consequently may have difficulty obtaining affordable child care, they may have more difficulty in finding and holding jobs than other young people. However, while the magnitude of this effect has not been estimated for youths, there is evidence that lack of satisfactory child care is a restraint on women's employment (Presser and Baldwin, 1980~. (As noted in Chapter 1, research on this important topic should be encouraged.) As we noted above, there has been a substantial expansion of the youth labor supply over the last several decades, resulting from changes in birth rates during the immediate postwar period and sub- stantial increases in the number of young women who entered the labor market. To the extent that an excess of "supply" is (by definition) a prerequisite for unemployment, it is prudent to ask whether this growth in the supply of young workers will continue in the next decade. Since one aspect of such a forecast involves making assumptions about the future decisions of millions of young women, any answer would be quite speculative. It may not be unreasonable to expect the rate of female participation in the labor force to approximate that of men, but it may also not be unreasonable to speculate that traditional patterns will die hard, thus restraining further large jumps in the rate of female participation in the labor market. There is, however, one aspect of a forecast about which we do have some "hard" evidence: the l990s "supply" of teenagers has already been born, and barring massive changes in death rates or patterns of migra- tion, one can venture a prospective count of their numbers. Figure 2.1 shows the actual and projected size of the older teenage population for 1960-2000. For the period 1960 through 1982, this segment of the population grew from roughly 13 million to more than 21 million in 1980 and then began to decline. In 1982 the population aged 15-19 totaled

60 20 ~ 15 o . _ . _ . _ - O o cat 5 o 15-19 Year Olds f ~ - 1 I I 1 1 1 1 1960 1970 1980 YEAR 1 990 2000 FIGURE 2.1 Actual and projected trends in the youth population aged 15-19, 1960-2000. NOTE: The 1970 and 1980 figures are population counts from decennial censuses reported in U.S. Department of Commerce (1985:Table 30~. The 1960 figures are population counts from the 1960 decennial census as reprinted in Bureau of the Census {1973:Table 189~. The 1975, 1981, and 1982 figures are estimates based on Current Population Survey sample surveys of population as reported in Bureau of the Census (1979, 1982~. The 1985-2000 figures are population projections (middle series) made by and reported in Bureau of the Census (1982~. 19.8 million. When the size of this population group is projected to later years, it shows continuing declines through 1995; at that time it is roughly 80 percent of its peak (1980) size. Thus, on the supply side, the demographic projections indicate that there will be a steady decline in the number of potential participants in the labor market through 1995. Enrollment in School Changes in school enrollment patterns could have a direct effect on the measured extent of unemployment problems among youths (Hahn and Lerman, 1983~. During the 1960s and 1970s, the enrollment rates for white males declined somewhat and those for white women and blacks of

61 TABLE 2.9 Percentage of Persons Aged 16-24 Enrolled in School, by Race and Sex Group 1964 1974 1983 White males 51.0 45.8 44.7 Nonwhite males 39.4 48.5 45.4 White females 36.4 39.1 40.7 Nonwhite females 34.1 38.6 40.9 SOURCE: Data from Bureau of Labor Statistics (1982, 1984). both sexes increased (see Table 2.9~. The difference in the patterns of school enrollment between blacks and whites contributed in part to the growing differential in employment-to-population ratios between black and white youths (Freeman, 1980~. The declining school enroll- ment rate of whites would tend to increase their employment rates since the employment rate for those out of school is generally higher than that for those in school. However, most of the increased employment for young whites in the past two decades came from rising employment rates for in-school youths. More interesting than the question of enrollment status is the degree to which educational attainment has an effect on the labor market experiences of youths. Many studies indicate that dropouts have a more difficult time in the labor market than do high school graduates. These effects are seen in difficulties in obtaining the first job, in duration of unemployment between jobs, and in wage rates. Academic performance appears to be positively related to both number of weeks employed and wage rates for youths. Other studies find that vocational training in high school appears to be unrelated to employment and wage rates, while there are some indications that vocational training after nlgn school may nave some positive ettects (Freeman and Wise, 1982). These findings on the effects of education on employment experi- ences may help to explain the distribution of employment and unemploy- ment among youth groups, but they do not appear to help to explain the growing differential between black and white youths. One explanation that has been put forward is that differences in the quality of educa- tion are responsible for the growing differential. The validity of this explanation is difficult to test. Studies of functional literacy than among whites, do show that literacy rates are lower amona ~4 arks but there is no indication that this gap has widened over recent years. Similarly, while there has been some overall decline in the Scholastic Aptitude Test (SAT) and other test scores, there is no indication that racial differentials in test scores have increased over time {Hahn and Lerman, 1983~. _ ~

62 Youths' Expectations and the Reservation Wage The "reservation wage" of a person is defined as the lowest wage at which that person would be willing to take a job. It has been suggested that some of the employment problems of youths may be related to a reservation wage that is too high. In addition, some analysts argue that increasing incomes throughout the society have caused the level of the reservation wage to rise over time to a greater degree than warranted by the increasing skills of the labor force. Data on reservation wages have not been collected over long enough periods of time for conclusions to be drawn as to whether rising reservation wages have been a major cause of increased unemployment for younger workers. On the whole, recent studies find (e.g., Freeman and Holzer, 1985) that the reservation wages of unemployed younger workers appear on average to be quite realistic: both white and black youths appear to have reservation wages that are quite close to the prevailing federal minimum wage. While the reservation wages of white and black male youths are about the same, Freeman and Holzer suggest that the fact that the employment prospects for blacks are worse means that their reservation wages are higher relative to the actual wages they are likely to be able to obtain. And reservation wages for specific low-wage jobs are generally lower for blacks than for whites. Reservation wages of young blacks appear to have the effect of lengthening the period of nonemploy- ment but also of increasing subsequent wages. The reservation wages of young whites have somewhat less effect on the duration of nonemployment but greater effects on their subsequent wages. Summing Individual Effects Thus far we have been serially reviewing possible causes of the trends in youth employment problems within a framework of demand and supply factors. Two sets of researchers, Ellwood and Wise (1983) and Mare and Winship (1983), have independently sought to bring together most of the factors covered above in a consistent accounting framework in order to see what proportion of the growth in the gap in black/white youth employment rates can be explained by the sum of the individual effects of all the factors. Though their accounting frameworks are quite different, both sets of researchers conclude that they can account for only about 50 percent of the diverging racial employment patterns among youths in the 1970s. In discussing each factor separately we have also not touched upon possible (nonadditive) interactions among factors; such interactions might yield results that are different from the simple sum of each individual factor. Two hypothetical examples can illustrate such interactions. It was previously noted that increases in the supply of young workers seem to be related to increases in employment rates and decreases in wages (relative to adults) for young white males, but they seem to be related to sharp decreases in employment rates and smaller relative wage decreases for young black males. These differences might -

63 be due to the interaction of the increased supply of labor and the existence of minimum wage rates and increased civil rights enforcement and affirmative action programs. The wages of young black males were already closer to the minimum wage than were those of young whites, so when the youth labor supply increased employers had less room to compress black wages than white wages. [Hall (1982) suggests this possibility in his commentary on the research of Wachter and Kim (1982~.] A second possible interaction is between the demographic increase in supply and employer discrimination. Even if the desire to discrimi- nate on the part of employers was not increasing during recent decades, the increase in the supply of both young whites and blacks may have increased the scope for the exercise of discriminatory hiring by employers.5 This theoretical possibility was emphasized in the earliest exposition of an economic theory of discrimination by Becker (1957) While these higher-order interactions generate interesting hypotheses, they are extraordinarily difficult to assess empirically, particularly when they involve such factors as the minimum wage or discrimination, which have proved challenging to assess even as singular first-order factors. Other Influences on Youth Employment Several research findings do not fit neatly into the supply and demand framework we have used in the preceding sections of this chapter. We note several of these briefly and then turn to a dis- cussion of social context. Family Influences and Teenage Experiences Family background has a positive relationship to the probability that a young person is employed, and Meyer and Wise (1982) find that an increase of $5,000 in parental income is associated with an increase of more than three weeks in the number of weeks worked by teenagers. Other family structure factors do seem to affect employment probabilities (see Rees and Gray, 1982; Corcoran, 1982~. Youths with siblings working are more likely to be working themselves, suggesting the importance of family connections for information or role models. sSimilarly, in the increasing concern with civil rights and affirmative action there may have been greater pressure for equal wage treatment, leading employers to make more of their adjustment to increased supply by decreased hiring of blacks. Freeman {1985) rejects this hypothesis, arguing that affirmative action increases relative employment of blacks by punishing discrimination in employment as well as in wage setting.

64 Youths from female-headed families or families on welfare have slightly lower probabilities of being employed. A somewhat surprising and potentially important finding in several studies (e.g., Meyer and Wise, 1982; Stevenson, 1980) is that there is a strong relationship between hours worked while in high school and later employment and wage rates. Whether the relationship is really causal or simply correlative (i.e., due to a common underlying factor such as motivation) remains unclear. Obviously, for those interested in the potential benefits from employment and training programs for in-school youths, this finding is intriguing. A final finding that has drawn the attention of many analysts is that the long-term (i.e., 4-5 years later) effects of unemployment during younger years appear to be rather less than had been previously suggested. Once individual characteristics have been controlled for, the experience of early unemployment does not appear to raise the probability of unemployment in the following 4-5 years. This result appears to hold for both young men and young women (Ellwood, 1982; Corcoran, 1982~. In addition, once individual characteristics are held constant, initial wage levels seem to have little relationship to wage levels 4-5 years later. These relatively encouraging findings about the limited effects of early unemployment and wages are, however, counterbalanced by another finding: early unemployment experience does seem to affect wage levels 4-5 years later, and this effect appears to be stronger and more substantial for youths with lower levels of education. Social Context We conclude by noting a final factor that may strongly influence the employment experiences of young minority youths: the social context that has formed their perceptions and responses. We have chosen to discuss this issue of social context in the final part of this section because it affects both the supply and the demand for labor and because the effects may be strong. The residue of past and current discrimination finds its expression on the demand side in diminished opportunities for minority youths in the labor market (because of the attitudes of employers); and, to the extent that the social context affects the perceptions, attitudes, and responses of youths, it can have a quite fundamental impact on the supply of labor. The long history of the exclusion of blacks from social and economic power, government, and prestigious occupations affects youths in many ways. As Ogbu (1985a, 1985b) has observed in his study of minority youths in Stockton, California, there is a racial or castelike stratification between blacks and whites that historically found expression in such things as job ceilings for black workers. A pilot project by Culp and Dunson (1983) finds evidence of such stratification in the treatment of matched young black and white "auditors n who applied for jobs at firms in the Newark, New Jersey, area. The auditors were recent high school graduates who were trained to make systematic observations of their treatment. Although the study was

65 only a pilot project and the samples were too small for statistical testing, the results suggested that black youths may be treated with less courtesy and may be less likely to be informed of job prospects (Culp and Dunson, 1983~. Other independent anthropological studies (e.g., Ogbu, 1985b) have found evidence of negative stereotyping of low-income blacks. The collective adaptation of black youths to this and other features of a stratification system may be a source of the disproportionate rates of black school failure and unemployment. In the face of bleak future prospects, diligence in school may not appear to be adaptive to social reality, but rather may be seen as "doing the white man's thing" (Ogbu 1985a; Anderson, in this volume; and Foster, 1974~. The castelike stratification of minorities has effects beyond those of youths' perceptions. The historic exclusion of minorities from some occupations deprives them of the chance to learn the requirements of such employment and to undertake the necessary preparation. Minority children will be limited in their opportunity to observe role models pursuing such occupations, and parents, having been excluded by past discrimination, will often be unable to guide and advise their children on the preparations required for such occupations. This may result in a dearth of knowledge on the part of the child and entirely inappro- priate preparation for desired "mainstream" occupations. In one study (Ogbu, 1985a), it was reported that black high school students desiring to become doctors, engineers, and teachers were as likely to take shop courses as those desiring office work. Similarly, minority youths who aspired to be engineers took no more mathematics courses in high school than youths wishing to become physical education teachers. What such findings make clear is not only that children did not learn about the requirements of those occupations in their home environment, but also that the schools did little, if anything, to convey crucial information. Anderson (in this volume) emphasizes the increasing significance of class factors in determining the social context in which black and other minority inner-city youths are raised. The substantial increase in the size of the black middle and upper classes in recent years has resulted in greater residential dispersion of higher-income blacks within the metropolitan area: black inner-city communities have experienced a loss of leadership and important role models that has contributed to the problems faced by the remaining youths. DEVELOPMENTS S INCE 19 8 0 As the Youth Employment and Demonstration Projects Act (YEDPA) programs ended in 1981, the U.S. economy had begun its descent into the worst recession since the 1930s. The economy bottomed out at the end of 1982 with overall unemployment at a post-World War II high of 10.8 percent. The unemployment rate of youths aged 16-19 was more than double that at 24.5 percent. The greater sensitivity of youth employment to the business cycle noted previously can be seen for this period as well in the data on employment-to-population rates given in Table 2.10. In 1978 the

66 TABLE 2.10 Employment-to-Population Rates for Total Civilian Population and for All Civilian Youths Aged 16-19, 1977-1984 Employment-to-Population Rate All Civilian All Youths Workers Aged 16-19 Ratio Year (1) (2) (1~/~2) 1977 1978 1982 1984 57.9 59.3 57.8 59.5 46.1 48.3 41.5 43.7 .796 .814 .718 .734 SOURCE: U.S. Department of Labor (1985:Table B-12~. workers (column 3). . , _ employment-to-population rates for all civilian workers (column 1) was 59.3, while the employment-to-population rate for youths aged 16-19 was 48.3 (column 2~; hence, the youth rate was 81.4 percent of that for all ' ~ ~' By 1982 the employment-to-population rate for all wormers nag fallen sharply, to 57.8, but the rate for youths had fallen even more precipitously, to 41.5, so that the youth rate was only 71.8 percent of the rate for all workers. It is also of some interest to note that in 1982 the employment-to-population rate for all workers was at about the same level as in 1977 (57.8 and 57.9), but the youth rate was considerably lower in 1982 than in 1977 (41.5 compared with 46.1~. For black youths the employment situation in 1982 was disastrous: their employment-to-population rate was only 19.0 percent. The economic recovery began in 1983 and continued through 1984. On the upswing youth employment again showed greater sensitivity so that by 1984 the youth employment-to-population rate had recovered more than that for all workers: it was 73.4 percent of the rate for all workers (compared with 71.8 percent at the bottom of the recession in 1982~. However, if one compares the situation in 1984 with that in 1978, it is clear that, despite the recovery, the youth employment-to-population situation has deteriorated both absolutely--from 48.3 in 1978 to 43.7 in 1984--and relative to the rest of the labor force--from 81.4 percent of the rate for all workers in 1978 to 73.4 percent in 1984. If one looks back to Tables 2.2a and 2.2b, it is apparent that the employment-to-population rate for nonwhite males (both those aged 16-19 and 20-24) is not only worse in 1984 than it was in 1978 but has further deteriorated relative to white male youths, while the employment-to- population rates of nonwhite females remain the lowest of the youth groups. These very summary data indicate both that, as would be expected, the recession hurt youth employment seriously and also that even with the economic recovery youth employment problems remain very serious.

67 Compared either with 1977, just before YEDPA started, or 1978, the first year of the program, the youth employment problem in 1984 was as bad, or worse. Even more disturbing, the employment situation of black youths, particularly males, has worsened even more relative to white youths, apparently continuing the long-term trend observed up to 1978. While our committee has not tried to assess systematically the economic outlook for the future and its implications for youth employ- ment problems, we do wish to comment on one feature that has sometimes been pointed to as a possibly important sensitive development, namely, the decline in the absolute size of the youth cohort. In the previous section, it was noted that one of the possible causes of youth employ- ment problems was the massive, unprecedented rise in the size of the youth cohort, both absolutely and relative to the adult worker popula- tion (shown in Figure 2.1~. Over the 15 years from 1980, when the size of the youth population reached its absolute peak, to 1995, the youth cohort will decline from 21 million to about 17 million. It has been suggested that this decline will significantly improve the employment situation for youths. We have two observations to make about this suggestion. First, while there are some indications that the youth demographic bulge may have contributed to youth employment problems, the evidence is by no means overwhelming. If it is hard to find the effects of this dramatic bulge in relative supply on youth employment problems, it seems unwise to count on the decline in relative supply of youths to have over- whelming effects in reducing youth employment problems over the next decade. Second, by 1985 two-thirds of the total projected decline in the size of the youth population will have occurred. The figures just reviewed above give no indication that this relative supply effect is currently having a substantial impact on youth employment problems. If reductions in relative supply of youths have been having some positive effect, they have not been substantial enough to overcome other negative factors. POSTSCRIPT When focusing on the youth unemployment problem, there is a tendency to lose sight of the fact that the majority of teenagers find jobs relatively easily and that, when they leave or lose one job, they often find another without a long period of unemployment. As Freeman and Wise (1982) observe: Constant references to the youth employment problem, as if all or the majority of young persons had trouble obtaining jobs, appear to misinterpret the nature of the difficulty. Youth joblessness is in fact concentrated among a small group who lack work for extended periods of time. n The vexing problem about the "youth unemployment problem" is that for some groups of youths--disproportionately black youths--finding any job, remaining employed, and finding a new job when necessary is a major and continuing difficulty. Throughout this chapter, it has become apparent that blacks suffer inordinately from unemployment. But while table after table has shown a widening gap between white and

68 black unemployment, inactivity, etc., it is not only the black population among whom unemployment is concentrated. In 1978 Hispanics experienced long-term unemployment at 1.3 times the rate of the population as whole, children from poverty families at 1.6 times the national rate, and those living in inner cities at 1.4 times the national rate (Congressional Budget Office, 1982~. It was against this background that Congress enacted YEDPA in 1977. This act instructed the Secretary of Labor "to establish a variety of employment and training programs to explore the methods of dealing with the structural unemployment problems of the Nation's youth. n In the following chapters we review the implementation and effects of these programs. In Chapter 3 we describe the YEDPA programs and their implementation. In Chapters 4 through 9 (and related appendixes), we review the effectiveness of those programs and the scientific adequacy of the research which was conducted to evaluate them.

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Do government-sponsored youth employment programs actually help? Between 1978 and 1981, the Youth Employment and Demonstration Projects Act (YEDPA) funded extensive programs designed to aid disadvantaged youth. The Committee on Youth Employment Programs examined the voluminous research performed by YEDPA and produced a comprehensive report and evaluation of the YEDPA efforts to assist the underprivileged. Beginning with YEDPA's inception and effective lifespan, this report goes on to analyze the data it generated, evaluate its accuracy, and draw conclusions about which YEDPA programs were effective, which were not, and why. A discussion of YEDPA strategies and their perceived value concludes the volume.

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