Youth: From Classroom to Workplace?

Order Code RL32871 CRS Report for Congress Received through the CRS Web Youth: From Classroom to Workplace? April 20, 2005 Linda Levine Specialist in Labor Economics Domestic Social Policy Division Congressional Research Service ˜ The Library of Congress Youth: From Classroom to Workplace? Summary Much attention has been devoted to the implications of the aging of the U.S. population for the future supply of labor to the nation’s employers, but little of the discourse about remedies has addressed the younger members of the working-age population, who are in part the focus of legislation being considered for reauthorization by the 109th Congress (the Workforce Investment Act, the Perkins Vocational and Technical Education Act, and the Higher Education Act). Specifically, are the youngest replacements for retiring baby-boomers being fully utilized in the sense that most teenagers and young adults successfully transition from the classroom to the workplace? Which 16-24 year olds are, instead, more likely to impose costs on society rather than contribute to the economy as taxpayers? After holding many jobs within the first decade of joining the labor force, most youth settle into fairly stable situations by their mid-twenties. However, a small share of the youth population (perhaps 15% depending upon definition, ages, and years), who number some three to five million, leave the classroom at risk of not making a firm commitment to the formal labor market. They appear to include young single mothers who rely on government benefits, for a time, as well as their families and partners; young males (principally) with criminal records that make it difficult to obtain steady jobs upon release from incarceration; youth sporadically employed in low-wage jobs who also participate in the underground economy; and youth with disabilities. A key attribute of these disengaged or disconnected youth is their limited educational attainment (high school dropouts and graduates), which argues for strategies that encourage youth to continue their studies (e.g., mentoring programs for elementary and secondary school students, and Pell Grants as well as other financial aid for postsecondary school students). Being out-of-school and out-ofwork appears to be more prevalent among young females than males, and among black and Hispanic than white youth. In addition to these personal attributes, other risk factors for a youth’s marginal attachment to the labor force include the characteristics of the neighborhoods in which they live (e.g., area poverty and employment rates); the proximity of those neighborhoods to jobs; and the characteristics of their families (e.g., labor force status and incarceration of parents). These relationships indicate that while education and training policies meant to raise the human capital of youth may play a necessary part in promoting their integration into the labor force, they are not likely sufficient ones. The results of empirical research suggest that a comprehensive youth employment policy would include training programs that provide, among other things, work experience to young students raised in poor inner-city neighborhoods; delinquency prevention measures, particularly for low-income children with incarcerated family and friends; changes to public transportation and to housing patterns to give at-risk youth greater access to areas of job growth; enhanced enforcement of employment and housing discrimination laws; and neighborhood workforce as well as community/economic development initiatives. This report will be updated as warranted. Contents Youth Unemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Factors Contributing to Youth Joblessness: Implications for Public Policy . . . . . 4 School Enrollment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Serving In-School and Out-of-School Youth . . . . . . . . . . . . . . . . . . . . . 8 Educational Attainment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Disconnected or Disengaged Youth . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Other Factors Affecting the Labor Force Status of Youth . . . . . . . . . . . . . . 16 The Neighborhood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Kith and Kin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Place of Residence vis-à-vis Jobs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 List of Tables Table 1. Unemployment Rates by Age, 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Table 2. Labor Force and School Enrollment Status of 16-24 Year Olds by Selected Demographic Characteristics, October 2004 . . . . . . . . . . . . . . . . . . 6 Table 3. Labor Force Status and Educational Attainment of Out-of-School 16-24 Year Olds, October 2004 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Youth: From Classroom to Workplace? Much time and attention has been devoted to the implications of the aging of the U.S. population for the nation’s old-age social insurance system and for its labor market. A good deal of discussion has focused on the tax burden workers could shoulder to support the growth in retirees if Social Security and Medicare are left unchanged, and on the labor shortages employers could face as greater numbers of baby-boomers reach the traditional retirement ages. A part of the discourse about remedies to potential labor shortages has involved older persons themselves and changes in immigration policy. Little consideration has been given to the role that might be played by the younger members of the workingage population, who are in part the focus of legislation being considered for reauthorization by the 109th Congress (the Workforce Investment Act, the Carl D. Perkins Vocational and Technical Education Act, and the Higher Education Act). Specifically, are the youngest replacements for retiring baby-boomers being fully utilized in the sense that most teenagers and young adults successfully transition from the classroom to the workplace? Which 16-24 year olds are, instead, more likely to impose costs on society rather than contribute to the economy as taxpayers?1 This report will examine the experience of youth in the labor force and attempt to shed some light on these matters. Youth Unemployment Some consider the labor force status of youth to be of even greater consequence than that of other age groups because the early experiences of 16-24 year olds (e.g., sporadic employment) could set the tone for their subsequent working lives (e.g., failure to develop good work attitudes and to accumulate skills). The statistic usually cited to support the perspective that young persons have chronically had more difficulties than others in the labor market is the group’s comparatively high unemployment rates. Indeed, absent cyclical fluctuations,2 the unemployment rate 1 According to Andrew Sum, Ishwar Khatiwada, Nathan Pond, and Mykhaylo Trub’skyy (Left Behind in the Labor Market: Labor Market Problems of the Nation’s Out-of-School, Young Adult Populations, Center for Labor Market Studies, Northeastern University, Nov. 2002), one-third of out-of-school and out-of-work 16-24 year olds received assistance through one of the following six government transfer programs during 2001: Medicaid, Food Stamps, cash rental subsidies or public housing, Temporary Assistance for Needy Families, Supplemental Security Income, and Unemployment Insurance. (Hereafter cited as Sum et al., Left Behind in the Labor Market.) 2 Because there often is an inverse relationship between seniority and who gets laid off and because firms are likely to have made comparatively small investments in their youngest (continued...) CRS-2 of teenagers (16-19 year olds) has for decades been about four times that of adults (age 25 and older), and the unemployment rate of young adults (20-24 year olds) has been about twice that of adults. In addition, youth account for a disproportionate share of all unemployed persons: 16-24 year olds comprise 15.1% of the labor force, but they are twice that share of the unemployed (32.4%).3 The high incidence of youth unemployment is partly related to their comparatively frequent movements into and out of the labor force. In 2004, 37.9% of all unemployed persons versus 63.3% of unemployed 16-24 year olds were seeking their very first jobs or were searching for positions after having been out of the workforce.4 Not surprisingly, such individuals are very likely to encounter some spell of unemployment while they learn how to get a job and gather information on the kinds of jobs available to them. The educational calendar exacerbates the probability of unemployment for young labor force (re)entrants. They typically flood the labor market in May and June searching for summer jobs after the school year has ended or seeking initial jobs upon dropping out or graduating. While the regularly occurring swell in the labor supply of youth coincides with increased demand for workers in some seasonal industries, this is not the case for most firms in the economy. The high unemployment rate of youth also is associated with their relatively frequent job changes, with each transition potentially involving a spell of unemployment. About two-thirds of all job changes occur within the first 10 years of a young person’s working life, during which time he/she works for eight employers on average.5 This initial period of frequent job turnover has been viewed 2 (...continued) workers, youth are among the first let go when employers respond to reduced demand for their goods and services during a recession. The unemployed youths must then compete with experienced laid off adults for the dwindling number of available jobs. Another reaction of firms to recessions is to stop hiring, which presents more of a problem for labor force entrants who are disproportionately young. The unemployment rate of 16-24 year olds thus increases to a greater extent than that of adults during a cyclical downturn. In contrast, good economic times operate to the relative advantage of young workers: when product demand is high and labor is in short supply, firms become more willing to hire those they consider less desirable such as young inexperienced persons. For more information on the 2001 recession’s impact on young workers see Andrew Sum and Robert Taggart, The National Economic Downturn and Deteriorating Youth Employment Prospects: The Case for a Young Adult Jobs Stimulus Program, Center for Labor Market Studies, Northeastern University, Boston, MA, Nov. 2001. 3 Annual average data for 1979, 1989, 2000, and 2004 compiled by the U.S. Bureau of Labor Statistics (BLS) from the monthly Current Population Survey (CPS), available at []. 4 Unpublished BLS data from the CPS. Note: Reasons for unemployment are new labor force entrants, reentrants, job-losers (i.e., persons on temporary layoff and those who have permanently lost their jobs or have completed temporary jobs), and job-leavers. 5 Jonathan R. Veum and Andrea B. Weiss, “Education and the Work Histories of Young (continued...) CRS-3 in both a positive and negative light: a time during which new labor force members try out different positions and work environments until they find the optimal match; a time of employer reluctance to hire inexperienced workers for career ladder positions and of young workers in dead-end jobs having little reason to form a lasting attachment to any particular firm. Analyses of data from the National Longitudinal Survey of Youth generally have found that while the typical young worker does not get a long-term job (of three years duration) immediately after leaving school, he/she does by about age 22.6 Educational attainment appears to greatly influence the length of time it takes for a young school-leaver to find a stable position. Despite high school dropouts joining the workforce several years before graduates, the typical dropout takes much longer to settle into his/her first long-term job (10.8 years versus 5.8 years, or at age 29 versus age 24).7 The typical youth with some postsecondary schooling takes less than one-half the time of a high school graduate to find a good job match (2.7 years). The typical youth with at least a bachelor’s degree takes less than one-fourth the time of a high school graduate, perhaps partly reflecting the greater specific skills already acquired by those with more schooling and their superior knowledge of the job market in their chosen fields. Time—that is to say, getting older and gaining experience and/or education— thus tends to improve a person’s labor market situation. This is further demonstrated in Table 1. The average unemployment rate of 16-24 year olds in 2004 was 11.9%, compared to a much lower rate of 4.4% among adults. Even within the youth labor force, the unemployment rate of young adults (9.4%) approaches one-half that of teenagers (17.0%). The inverse relationship between age and unemployment rate holds true, as well, for older as opposed to younger teenagers and within the agerange of young adults. Further, according a longitudinal survey of 18-27 year olds, the rate of increase in number of unemployment spells diminishes with age and remains fairly constant after reaching 24 years old.8 5 (...continued) Adults,” Monthly Labor Review, Apr. 1993. (Hereafter cited as Veum and Weiss, Education and the Work Histories of Young Adults.) 6 Julie A. Yates, “The Transition from School to Work: Education and Work Experiences,” Monthly Labor Review, Feb. 2005 (Hereafter cited as Yates, The Transition from School to Work); and Jacob Alex Klerman and Lynn A. Karoly, “Young Men and the Transition to Stable Employment,” Monthly Labor Review, Aug. 1994. Note: The National Longitudinal Survey of Youth (NLSY) is one of a number of surveys sponsored and directed by the BLS that follow groups of individuals over time. In 1979, a longitudinal survey of 14-22 year olds was begun. The research discussed above and elsewhere in this report that reference the NLSY are based upon the 1979 cohort. A somewhat younger group (12-17 year olds) began to be surveyed in 1997. Researchers are now analyzing data from the NLSY97. 7 Yates, The Transition from School to Work. 8 Veum and Weiss, Education and the Work Histories of Young Adults. CRS-4 Table 1. Unemployment Rates by Age, 2004 Age All workers (age 16 and older) Unemployment rate 5.5 Youth (16-24 year olds) 11.9 Teenagers (16-19 year olds) 17.0 16-17 20.2 18-19 15.0 Young adults (20-24 year olds) 9.4 20 11.9 21 10.4 22 9.7 23 8.0 24 7.7 Adults (age 25 and older) 4.4 Source: U.S. Bureau of Labor Statistics (BLS) data from the Current Population Survey (CPS). Factors Contributing to Youth Joblessness: Implications for Public Policy The preceding analysis is not meant to imply that youths’ early experiences in the labor market can safely be ignored because most will settle into better circumstances, or even that all youth will participate in the workforce. Indeed, for some 16-24 year olds (e.g., teenage males), employment in the civilian noninstitutional and military sectors of the economy has become less common at the same time that their presence in such institutions as correctional facilities—where they largely are unavailable for work and which depresses their job opportunities after release—has become more common.9 Policymakers therefore may want to determine which individual characteristics incline youth to become less firmly attached than others to the labor market and the kinds of initiatives that could facilitate the transition of these at-risk youth from the classroom to the workplace. 9 U.S. Congressional Budget Office (CBO), What Is Happening to Youth Employment Rates?, Washington, DC, Nov. 2004 (Hereafter cited as CBO, What Is Happening to Youth Employment Rates?); and Jeremy Travis, Amy L. Solomon, and Michelle Waul, From Prison to Home: The Dimensions and Consequences of Prisoner Reentry (Washington, DC: Urban Institute, June 2001). CRS-5 School Enrollment Whether youngsters are enrolled in school has a considerable effect on their connection to the labor market. Young students are employed or actively seeking jobs (i.e., they are in the labor force) less than half as often as non-students. The increased rate of school enrollment over time consequently has reduced work activity among youth from what it otherwise would have been. (Column 4 of Table 2 shows current labor force participation rates by status of school enrollment.) At present, 54.4% of all 16-24 year olds in the civilian noninstitutional population are employed. Despite rising markedly over the years, the employment rate of students (41.1%) remains considerably below that of non-enrolled youth (70.8%). Notably, among out-of-school youth, African American males (62.9%) and females (57.5%) are much less likely to have jobs as are Hispanic females (53.2%). (Column 6 of Table 2 shows the employment-to-population ratio or the employment rate.) More than three of every five young workers who are unemployed are not enrolled in school (1.6 million out of 2.6 million). Blacks are overrepresented among unemployed out-of-school youth: African Americans comprise 27.0% of unemployed non-student youth compared to just 14.6% of all out-of-school youngsters in the labor force. The unemployment rates of youth no longer in school are especially high, at 20.0% among 16-19 year olds and 10.7% among 20-24 year old workers. In contrast, relatively fewer teenagers (14.4%) and young adults (7.0%) who are both in school and in the labor force are unemployed. (Columns 7 and 8 of Table 2 present unemployment data.) CRS-6 Table 2. Labor Force and School Enrollment Status of 16-24 Year Olds by Selected Demographic Characteristics, October 2004 (numbers in thousands) Civilian labor force Characteristic Civilian noninstitutional population Employment Total Labor force as percent of population Number Unemployment Employed as % of population Unemployment rate Number Not in labor force All 16-24 year olds 36,504 22,484 61.6 19,847 54.4 2,637 11.7 14,020 Enrolled 20,173 9,293 46.1 8,283 41.1 1,010 10.9 10,880 16-19 13,047 4,810 36.9 4,116 31.5 694 14.4 8,237 20-24 7,125 4,483 62.9 4,167 58.5 316 7.0 2,643 In high school 9,372 2,982 31.8 2,490 26.6 493 16.5 6,389 10,801 6,331 58.4 5,794 53.6 517 8.2 4,490 —Two-year college 2,684 1,867 69.5 1,673 62.3 193 10.4 818 —Four-year college 8,117 4,444 54.8 4,120 50.8 324 7.3 3,672 —Full-time college students 9,256 4,967 53.7 4,534 44.0 433 8.7 4,289 —Part-time college students 1,545 1,344 87.0 1,260 81.5 84 6.3 201 16,031 13,191 80.8 11,564 70.8 1,627 12.3 3,140 16-19 3,210 2,322 72.4 1,858 57.9 464 20.0 887 20-24 13,121 10,868 82.8 9,705 74.0 1,163 10.7 2,253 In college Not enrolled CRS-7 Civilian labor force Characteristic Civilian noninstitutional population Employment Total Labor force as percent of population Number Unemployment Employed as % of population Number Unemployment rate Not in labor force Males 8,560 7,485 87.4 6,578 76.9 907 12.1 1,075 Females 7,771 5,706 73.4 4,986 64.2 720 12.6 2,066 White 12,842 10,486 81.7 9,441 73.5 1,045 10.0 2,356 —Male 6,855 6,096 88.9 5,476 79.9 621 10.2 758 —Female 5,897 4,390 73.3 3,965 66.2 425 9.7 1,597 Black 2,465 1,923 78.0 1,483 60.2 440 22.9 542 —Male 1,216 977 80.4 764 62.9 213 21.8 238 —Female 1,250 946 75.7 719 57.5 227 24.0 304 3,541 2,737 77.3 2,429 68.6 308 11.2 804 —Male 1,984 1,771 89.3 1,582 79.7 189 10.7 213 —Female 1,487 915 61.5 792 53.2 123 13.5 572 Hispanic origin Source: BLS, College Enrollment and Work Activity of 2004 High School Graduates, USDL 05-487, Mar. 25, 2005, and unpublished BLS tabulations from the Oct. 2004 supplement to the CPS. Note: Subtotals may not add to totals due to rounding. CRS-8 Serving In-School and Out-of-School Youth. Given these figures, it could be argued that government resources should be more focused on out-of-school youth—particularly since they, unlike students, do not have a socially acceptable alternative to participation in the labor force. It was estimated, for example, that time spent out of the workforce by 18-21 year old non-students, and intermittent low-wage employment when they are in the labor force, increases the chance of youth engaging in criminal activities.10 The risk of criminal involvement was found to be lower among students, which perhaps reflects their “making an investment to enhance future stability,” much like the out-of-school youth with good jobs were “occupationally stable” and hence less likely to engage in criminal activities. These results led the researchers to conclude that “it is the stability that goes with good work (or with academic involvement) that inhibits criminality.”11 Positive individual and societal outcomes thus might flow from providing services to both out-of-school and in-school youth. If out-of-school youth receive skills training that enables them to obtain good jobs, they might become more strongly committed to the formal labor market and be less inclined to engage in illegal activities. And, helping youngsters continue their studies (through outreach programs of the Higher Education Act, Pell Grants and other scholarships, and work-study programs for example) might enable them to later enter the workforce better qualified for good jobs. Another analysis, based upon a representative sample of 11-20 year olds from the National Longitudinal Study of Adolescent Health, determined that the relationship between the quality of future job opportunities and violent delinquency begins even earlier in the life course as individuals move through adolescence. It is here that impressions about the future begin to form. When that future does not appear promising, adolescents are more likely to become disinterested in formal education and perhaps seek out alternative sources of status among peer cliques or possibly gangs.12 The estimated effect of a future of low-paying jobs on adolescent delinquency was dampened when school attachment and achievement were taken into account. The result appears to reaffirm the desirability of dropout prevention strategies, particularly 10 Robert D. Crutchfield and Susan R. Pitchford, “Work and Crime: The Effects of Labor Stratification,” Social Forces, vol. 76, no. 1, Sept. 1997. 11 12 Ibid., p. 112. Paul E. Bellair, Vincent J. Roscigno, and Thomas L. McNulty, “Linking Local Labor Market Opportunity to Violent Adolescent Delinquency,” Journal of Research in Crime and Delinquency, vol. 40, no. 1, Feb. 2003, p. 27. Note: The National Longitudinal Study of Adolescent Health (Add Health) is a nationally representative study that examines the causes of health-related behaviors of adolescents in grades 7 through 12 and their outcomes in early adulthood. The study is intended to explore how social contexts (e.g., families, friends, and neighborhoods) affect youths’ health and risk behaviors. The National Institute of Child Health and Human Development issued a grant, co-funded with 17 other federal agencies, in 1994 to begin the study. Information at the individual, family, school, and community level were collected in two waves between 1994 and 1996. A third wave, undertaken in 2001 and 2002, involved the re-interview of 18-26 year old Add Health respondents. CRS-9 for students in low-income families (a factor independently found to be related to delinquency during adolescence). One such federally funded activity for at-risk middle school students (grades 4-8) is the mentoring program administered by the Education Department’s Office of Safe and Drug-Free Schools.13 In addition, The No Child Left Behind Act (Title I, Part H) established another grant program for dropout prevention and re-entry for students in grades 6-12 that includes counseling and mentoring at-risk students among other activities. The importance of intervention early in a child’s life to facilitate subsequent labor force participation is underscored by the findings from a longitudinal analysis of 3-21 year olds in Dunedin, New Zealand. (The researchers noted that the results from their study are applicable to other developed countries based upon crossnational comparisons of social problems.) Holding education variables constant among those in the nationally representative sample at the typical ages of movement from the classroom to the workplace, the authors estimated that the probability of unemployment during the transition was greater if the youth had failed to develop good reading skills, been uninvolved in school, engaged in antisocial behavior, and had grown up in single-parent families. Because these risk factors for unemployment upon entering the labor force were found to span multiple domains (school, home, and society) and to be present early in children’s lives, the authors suggested that the most effective preventive measures are multimodal strategies implemented during the preschool years, such as “Headstart programs that have significant social and economic benefits that can endure through young adulthood.”14 Other studies have shown that working while a student helps to ease the transition to the labor force shortly after leaving high school. The inverse relationship estimated between neighborhood poverty rates and high school students’ employment rates suggests that poor adolescents could have particular difficulty entering the labor market.15 Publicly sponsored work experience programs for students living in low-income communities might consequently enhance their employment prospects upon exiting high school (e.g., the summer employment opportunities program under the Workforce Investment Act). Having a job can be important to students and to the households in which they live for more immediate reasons. Over one-half of students enrolled full-time in twoor four-year colleges also are in the workforce, as are almost nine-tenths of students 13 For more information see CRS Report RL32633, Mentoring Programs Funded by the Federal Government Dedicated to Disadvantaged Youth: Issues and Activities, by Edith Fairman Cooper. (Hereafter cited as CRS Report 32633, Mentoring Programs Funded by the Federal Government Dedicated to Disadvantaged Youth.) 14 Avshalom Caspi, Terrie E. Moffitt, Bradley R. Entner Wright, and Phil A. Silva, “Early Failure in the Labor Market: Childhood and Adolescent Predictors of Unemployment in the Transition to Adulthood,” American Sociological Review, vol. 63, June 1998, p. 445. 15 “Expanding the Number and Quality of the In-School Work Experiences of High School Youth,” in Andrew Sum, Neeta Fogg, and Garth Mangum, Confronting the Youth Demographic Challenge: The Labor Market Prospects of Out-of-School Young Adults, Sar Levitan Center for Social Policy Studies, Institute for Policy Studies, Johns Hopkins University, Policy Issues Monograph 00-01, Oct. 2000. CRS-10 enrolled part-time. The absence of paychecks among the 517,000 unemployed college students might hamper their pursuit of additional education. (See Table 2.) Wage loss due to unemployment among students might impose a hardship on their families as well. Even the fairly small paychecks of teenagers attending school— 694,000 of whom were unemployed in October 2004—might contribute substantially to the economic well-being of single-parent families in which the parents themselves hold low-wage jobs, for example. Although virtually all respondents in a nationally representative sample of high school students surveyed in early 2000 indicated that they worked to get extra spending money, 16% also reported that their families needed their earnings and 59% said their wages were going toward saving for college or other long-term goals.16 Hence, government support of student employment could have short-term and long-term effects that extend beyond the youths themselves. Educational Attainment Typically, the unemployment rate of individuals varies inversely with their educational attainment. In the case of out-of-school youth, unemployment rates range from 20.4% for those with less than a high school diploma to 6.6% for those with at least a bachelor’s degree. (See Table 3.) Moreover, 16-24 year olds who do not complete high school and those who stop their education upon obtaining a high school diploma (or the equivalent) contribute disproportionately to total youth unemployment: out-of-school youth who lack a high school diploma and those who graduate but do not pursue postsecondary education comprise about one-half of all unemployed 16-24 year olds, which greatly surpasses their representation in the youth labor force at 36.5%.17 Accordingly, dropout prevention programs directed toward elementary and secondary (K-12) school students might lower the incidence of unemployment among youth (e.g., vocational education). Conversely, as shown in Table 3, the employment rate varies directly with educational attainment. A little over half of all out-of-school youth in the civilian noninstitutional population who do not complete high school are employed, compared to at least four of every five youth with some postsecondary education. Although young females’ employment rates are below those of males at each level of schooling, the disparity becomes progressively less as educational attainment rises: for those without a high school diploma (40.7% among young females versus 62.3% among young males), the difference in employment rates is more than four times that of youth with at least a bachelor’s degree (85.2% among young females versus 90.4% among young males).18 16 Ellen Galinsky, Stacy S. Kim, James T. Bond, and Kimberlee Salmond, Youth & Employment: Today’s Students Tomorrow’s Workforce, Families and Work Institute, NY, NY, undated. 17 The 10.6% of out-of-school youth in the labor force without high school diplomas account for 18.4% of all unemployed youth. The 25.9% of out-of-school youth in the labor force whose education stopped at high school graduation account for 31.1% of all unemployed youth. 18 Unless indicated otherwise, data in this report are based on published and unpublished BLS tabulations of responses to the Oct. 2004 supplement to the CPS. CRS-11 Similarly, the equalizing effect of educational attainment is evident in the narrowed gap in the employment rates of out-of-school youth by race. Among high school dropouts, 57.8% of white youths have jobs compared to just 35.2% of black youths. The gulf is half that among young high school graduates, at 73.9% for whites and 62.3% for African Americans. The difference in employment rates of 16-24 year old whites (89.1%) and blacks (81.0%) no longer attending school diminishes further for those with at least a bachelor’s degree. This pattern is repeated when educational attainment data from the CPS are further disaggregated by geographic location. For example, the employment rate of out-of-school youth who lack a high school diploma is lower, on average, for those living in central cities (67.9%) versus suburbs (73.2%); yet, regardless of place of residence, there is near equality of employment rates among 16-24 year olds with at least a bachelor’s degree (86%-87%). CRS-12 Table 3. Labor Force Status and Educational Attainment of Out-of-School 16-24 Year Olds, October 2004 (numbers in thousands) Civilian labor force Employment Characteristic Civilian noninstitutional population Total Percent of population Number Unemployment Percent of population Number Rate Not in labor force All 16-24 year olds 36,504 22,484 61.6 19,847 54.4 2,637 11.7 14,020 All out-of-school 16-24 year olds 16,031 13,191 80.8 11,564 70.8 1,627 12.3 3,140 Less than a high school diploma 3,552 2,385 67.1 1,899 53.5 486 20.4 1,167 High school graduate only 7,133 5,831 81.8 5,012 70.3 819 14.1 1,302 Some college or associate degree 3,391 3,023 89.1 2,749 81.1 274 9.9 367 At least a bachelor’s degree 1,828 1,687 92.3 1,575 86.2 112 6.6 141 Source: BLS, College Enrollment and Work Activity of 2004 High School Graduates, USDL 05-487, Mar. 25, 2005, and unpublished BLS tabulations from the Oct. 2004 supplement to the CPS. CRS-13 Trends. The employment rate of out-of-school 16-24 year olds by gender has moved in opposite directions over the past two decades. It has trended downward among males and upward among females, with the divergence especially notable among less educated African American youth. Surprisingly, the employment rate of young out-of-school black males with a high school diploma or less fell more sharply during the 1990s boom than it had during the 1980s (from 62% in 1979 to 59% in 1989 to 52% in 2000, approximate peaks in the business cycle).19 After estimating that changes over time in personal characteristics and in labor market conditions explain little of the decline in employment among young less educated black males, the researchers postulated that ! greater efforts in recent years to establish paternity and to enforce court- ordered child support may have deterred their participation in the formal economy, as could have ! high rates of incarceration and the criminal records that then attach to the individuals (with possible spillover effects on the employment of African American males more generally). Indeed, the paternity establishment and child support enforcement provisions in the Personal Responsibility and Work Opportunity Reconciliation Act reportedly are imposing a substantial “tax” on the paychecks of those ex-offender non-custodial parents who are able to obtain jobs.20 In contrast, the employment rate of less educated young black females no longer in school rose during the 1990s to such an extent that it surpassed the (albeit low) employment rate of their Hispanic counterparts. “Welfare reform, an expanded Earned Income Tax Credit, and other policy changes likely contributed to this trend, in addition to the strong prevailing economic conditions.”21 The still low employment rates of young less educated minority females could be partly accounted for by comparatively high birth rates. Disconnected or Disengaged Youth. The terms “disconnected youth” and “disengaged youth” have been used to describe young persons who are marginally attached to such societal institutions as the labor market. There is no universally agreed upon definition of the group. Educational Attainment. Educational attainment is closely linked with a youth’s probability of being included in this group, however it is defined. According to one analysis of October 2000 CPS data, for example, almost 800,000 or 4.5% of 19 Paul Offner and Harry Holzer, Left Behind in the Labor Market: Recent Employment Trends Among Young Black Men (Washington, DC: The Brookings Institution, Apr. 2002). (Hereafter cited as Offner and Holzer, Left Behind in the Labor Market.) See also Elise Richer, Abbey Frank, Mark Greenberg, Steve Savner, and Vicki Turetsky, Boom Times A Bust: Declining Employment Among Less-Educated Young Men (Washington, DC: Center for Law and Social Policy, July 2003). 20 Maria L. Buck, Getting Back to Work: Employment Programs for Ex-Offenders (Philadelphia, PA: Public/Private Ventures, fall 2000). 21 Offner and Holzer, Left Behind in the Labor Market, p. 4. CRS-14 23-27 year olds in the civilian noninstitutional population are not in school, not in the labor force, not disabled, and not married. Social isolation, based on this conceptualization, is most prevalent among young adults who fail to complete high school, at 11.0%. The likelihood of disconnection is more than halved, to 5.2%, among young high school graduates. For youth with some postsecondary education, the share falls further to 3.3%. Disconnection is rarest among young adults with at least a bachelor’s degree (2.2%).22 The importance of educational attainment to successfully transitioning to adulthood is further demonstrated by its explicit inclusion in the Annie E. Casey Foundation’s definition of disconnected youth in the Kids Count book. The definition is 18-24 year olds not enrolled in school and not working who have obtained, at most, a high school diploma. In 2002, over 3.8 million youth—15% of the age group in the civilian noninstitutional population—fit this definition of disengagement.23 Gender and Race/Ethnicity. Gender and race/ethnicity appear to be associated with the probability of disconnection as well. For example, a larger share of 23-27 year old women than men at each level of educational attainment up to but not including a bachelor’s degree are estimated to be out-of-school, out-of-work, not disabled, and unmarried.24 Examination of a younger age group—16-24 year olds— and based upon a broader definition of detachment—not in school and not working —similarly reveals disconnection is somewhat more prevalent among females than males (15% and 11%, respectively, in 2003). Black (20%) and Hispanic (18%) youth also are much more likely to be out-of-school and out-of-work than the average 1624 year old (13%). And, poor youth (28%) as well as high school dropouts (44%) and graduates (25%) experience detachment at well above-average rates.25 Incarceration. All the definitions of disconnection discussed above are limited to the civilian noninstitutional population. They therefore omit such persons as inmates of prisons and jails, the majority of whom are minority males (nonHispanic blacks and Hispanics).26 Another study that added residents of institutions and active-duty personnel in the Armed Forces to October 2000 CPS data found the rate of disconnection among 16-19 year old males rose from 8% to 10%, and among 22 Brett Brown, Kristin Moore, and Sharon Bzostek, A Portrait of Well-Being in Early Adulthood: A Report of the William and Flora Hewlett Foundation (Washington, DC: Child Trends, Oct. 2003). (Hereafter cited as Brown, Moore, and Bzostek, A Portrait of WellBeing in Early Adulthood.) 23 The Annie E. Casey Foundation, 2004 Kids Count Data Book, available at []. 24 Brown, Moore, and Bzostek, A Portrait of Well-Being in Early Adulthood. 25 J. Wirt, S. Choy, P. Rooney, S. Provasnik, A. Sen, and R. Tobin, The Condition of Education: 2004 (Washington, DC: U.S. Govt. Print. Off., 2004), Indicator 13: Youth Neither Enrolled Nor Working. 26 U.S. Department of Justice, Bureau of Justice Statistics, Prison and Jail Inmates at Midyear 2003, May 2004. CRS-15 20-24 year old males, from 11% to 13%.27 In contrast, inclusion of these population groups had no effect on the incidence of detachment among females, which remained at 9% for teenagers and 18% for young adults. Thus, according to this conceptualization, the incidence of detachment remains highest among young females, many of whom could be single mothers who depend on their families (e.g., parents and partners) and government (e.g., benefits under the Temporary Assistance for Needy Families, TANF, program) to support them while raising their children. Another analysis included as disconnected youth those 18-24 year olds confined in local jails and in state or federal prisons after being convicted of a crime as well as unmarried 18-24 year olds with a high school degree or less who had been unemployed for one or more years. At any point during the 1997-2001 period, the researchers estimated that 7% or almost 1.8 million young adults experienced long spells of unemployment (1.7 million) or were incarcerated (420,000).28 A small majority were male (59% or 1 million), who accounted for 8% of the 18-24 year old male population. The 728,000 disengaged females accounted for 6% of the 18-24 year old female population. Almost one-fourth of the disconnected males were incarcerated compared to just 3% of females. Unexpectedly, the share of mothers among disconnected females did not exceed that of non-mothers until age 22, with two out of five living with their minor child. Nearly all the mothers had their first child between 14 and 20, and half of them reported welfare receipt. Many more of these detached males than females reported having a disability that prevented them from working (21% and 10%, respectively).29 The early onset of disabilities (before age 22) appears to hamper attachment to the labor market both directly and indirectly, through a lesser likelihood of completing high school.30 More specifically, 13% of the difference in employment rates of young adults with and without disabilities was estimated to be due to differences in the groups’ educational attainment; the remainder, to the existence of the disability itself and all other variables. Yet a third study expanded the concept of disconnection to include incarcerated young males. It estimated that in 2001, some 5.2 million out of 35.0 million 16-24 year olds in the civilian noninstitutional population (or 14.8%) were neither in school nor working. The researchers then added the nearly 400,000 males age 18-24 in U.S. jails and prisons to their estimate of out-of-school out-of-work youth and surmised that 5.6 million might be a more complete count of detached youth.31 27 CBO, What Is Happening to Youth Employment Rates?. 28 Michael Wald and Tia Martinez, Connected by 25: Improving the Life Chances of the Country’s Most Vulnerable 14-24 Year Olds, Menlo Park, CA, William and Flora Hewlett Foundation Working Paper, Nov. 2003. 29 Ibid. 30 Pamela Loprest and Elaine Maag, The Relationship between Early Disability Onset and Education and Employment (Washington, DC: The Urban Institute, Sept. 2003). 31 Sum, et. al., Left Behind in the Labor Market. CRS-16 Place of Residence. A substantial share (40%) of the out-of-school out-ofwork youth in the civilian noninstitutional population live in the nation’s 50 most populous metropolitan areas.32 A slight majority of disengaged youth in these metropolitan areas are African American and Hispanic (51%) compared to their lesser presence on a national basis (40%). When the focus narrows to the composition of detached youth in the 10 most populous metropolitan areas, the minority composition rises to 71%. The chance of disconnection is greater for outof-school youth living in the central cities compared to suburbs of metropolitan areas. Other Factors Affecting the Labor Force Status of Youth The foregoing discussion suggests that in addition to personal attributes (school enrollment, educational attainment, race/ethnicity, and gender) there are other factors (student work experience, future job quality, incarceration, and place of residence) that affect a youth’s commitment to the labor market. The probability of a youth successfully transitioning from the classroom to the workplace might be mediated by: ! the characteristics of the neighborhoods in which they live (e.g., area employment and poverty rates), ! the proximity of those neighborhoods to jobs (referred to as spatial mismatch), and ! the characteristics of their families (e.g., labor force status and incarceration of parents). Accordingly, while education and training policies directed at raising the human capital of youth may be a necessary step in promoting their integration in the labor force, it is not likely a sufficient one. The Neighborhood. An analysis that utilized data from the National Longitudinal Survey of Youth (NLSY) and U.S. census tract information for 1980 and 1990 estimated that 14-22 year olds who grow up in metropolitan areas with relatively high poverty rates have a lesser likelihood as adults of being employed in the civilian economy or in the Armed Forces and a greater likelihood of not being in the labor force. Being raised in a poor neighborhood appears to more adversely affect young males, especially those in poor families, than females.33 Other research similarly shows neighborhood effects can vary according to the characteristics of youths. For example, another study based on NLSY data estimated that the adverse impact on labor market attachment of young out-of-school males living in disadvantaged metropolitan areas was harsher for those with less than 12 years of schooling.34 32 Ibid. 33 Steven R. Holloway and Stephen Mulherin, “The Effect of Adolescent Neighborhood Poverty on Adult Employment,” Journal of Urban Affairs, vol. 26, no. 4, 2004. (Hereafter cited as Holloway and Mulherin, The Effect of Adolescent Neighborhood Poverty on Adult Employment.) 34 Bruce A. Weinberg, Patricia B. Reagan, and Jeffrey J. Yankow, “Do Neighborhoods (continued...) CRS-17 The labor market disadvantage from growing up in impoverished inner-city neighborhoods, even among those who subsequently move, appears to partly operate through limited accumulation of work experience. This finding led the researchers to suggest that training programs might enable these youth to gain experience and acquire “both the skills needed to accomplish work tasks and the more intangible soft skills needed for effective relationships with employers, other employees, and perhaps clients and/or customers.”35 Further, the provision of mentors might compensate for the paucity of adult inner-city residents with jobs who can serve as role models to youngsters in poor communities, and the provision of labor market information might compensate for the dearth of job referral channels that rely on personal contacts. These strategies might most benefit young females because more of the neighborhood’s negative impact on employment outcomes was estimated to function through work experience for them than for males. The analysts speculated that the labor market disadvantages of 14-22 year old males growing up in impoverished inner cities might more often operate through such other channels as place/race discrimination by employers and encounters with the criminal justice system. Kith and Kin. Ethnographic research illustrates that the nature of youth’s personal contacts can influence their participation in the informal rather than formal labor market. A juvenile’s membership in a gang may extend into an adulthood of illegal activities or of joblessness due, in part, to the stigma of their own criminal records and a lack of family- or community-based networks to steer them toward opportunities in the legal rather than underground economy. While noting that studies of the relationship between crime and social networks in the United States “often are empirically and ideologically confounded by issues of race,” researchers who utilized panel data on male adolescents (8-21 year olds) in a poor non-minority neighborhood of London estimated that early embeddedness among delinquent friends and in continuing delinquent behaviors leads to adult unemployment. It indicates, further, that parental criminality plays a more salient role in the development of early adult unemployment than parental unemployment.36 Statistics for the United States similarly show “criminal behavior has a strong family connection,” with more than one in ten 18-24 year old male prisoners having a parent who served time and some three in ten having a sibling who served time.37 Two out 34 (...continued) Affect Hours Worked? Evidence from Longitudinal Data,” Journal of Labor Economics, vol. 22, no. 4, 2004. (Hereafter cited as Weinberg, Reagan, and Yankow, Do Neighborhoods Matter?.) 35 Holloway and Mulherin, The Effect of Adolescent Neighborhood Poverty on Adult Employment, p. 449. 36 John Hagan, “The Social Embeddedness of Crime and Unemployment,” Criminology, vol. 31, no. 4, 1993, pp. 486-487. 37 Richard B. Freeman, “Disadvantaged Young Men and Crime,” in David G. Blanchflower and Richard B. Freeman (eds.), Youth Employment and Joblessness in Advanced Countries (continued...) CRS-18 of three young prison inmates also report having friends who engaged in illegal activities. Since Congress time-limited participation in the Temporary Assistance for Needy Families (TANF) program, many custodial parents (primarily mothers) of adolescent welfare beneficiaries have obtained jobs. The above study’s results imply that increased maternal employment might not accomplish as much as had been hoped toward enhancing the labor market prospects of their offspring if parents have criminal records and/or adolescents have delinquent friends. Its findings suggest a role in increasing youth commitment to the workforce for programs aimed at thwarting the development of anti-social behavior among children of incarcerated parents (e.g., the Mentoring Children of Prisoners program of the Administration of Children and Families in the Department of Health and Human Services).38 Further, the reduced arrest rates of male participants in Job Corps’ residential as opposed to nonresidential program suggests that part of the program’s success may be related to temporarily removing young males from possibly harmful networks of family and friends.39 Place of Residence vis-à-vis Jobs. In addition to social isolation from work due to a dearth of role models and job referral networks, geographic isolation from fast-growing job-rich areas has been shown to affect youths’ employment outcomes. Some analyses estimated that limited social access has a more adverse impact than transport access. Nonetheless, the proximity of jobs to youths’ place of residence still was found to affect their labor market involvement independent of other factors.40 Consequently, forging closer connections between suburban labor markets and inner cities—such as through changes to public transportation and housing patterns—might raise the workforce participation of at-risk youth. Implicit in this prescription, however, is the assumption that once minority workers gain physical access to suburban employment centers, they will be on an equal footing with white workers. Racial employment discrimination may in fact be more severe in suburban job markets, where a larger percentage of a firm’s clientele is white and a relatively lower share of businesses are minorityowned, than in the inner city. Any benefit to minority workers from improving physical accessibility may be offset by intensified employment discrimination. 37 (...continued) (Chicago, IL: University of Chicago Press, 2000), p. 237. 38 For further information see CRS Report RL32633, Mentoring Programs Funded by the Federal Government Dedicated to Disadvantaged Youth, by Edith Fairman Cooper. 39 John Burghardt, Peter Z. Schochet, Sheena McConnell, et al., Does Job Corps Work? Summary of the National Job Corps Study (Washington, DC: Mathematica Policy Research, Inc., June 2001). Note: The arrest rates of females who participated in either Job Corps’ residential or nonresidential program was reduced. 40 See for example Weinberg, Reagan, and Yankow, Do Neighborhoods Matter?; Katherine M. O’Regan and John M. Quigley, “Where Youth Live: Economic Effects of Urban Space on Employment Prospects,” Urban Studies, vol. 35, no. 7, 1998; and Steven Raphael, “Interand Intra-Ethnic Comparisons of the Central City-Suburban Youth Employment Differential,” Industrial & Labor Relationship Review, vol. 51, no. 3, Apr. 1998. CRS-19 If this is the case, residential integration or public transportation improvements may be less effective in boosting minority youth employment than policies that focus on rooting out discrimination or investing in the skills of minority youths.41 Further, the urban/suburban distinction may understate the isolation from the labor market that some youth experience. A study estimated that the average African American 16-21 year old gains less than the average Latino, Asian, and white youngster from proximity to fast-growing job centers in the suburbs. In addition, the researchers determined that the suburban neighborhood in which the average black youth lives has more poverty, a higher proportion of minority residents, lower educational attainment, and a higher youth dropout rate compared to the suburban neighborhoods of the average Latino, Asian, and white adolescent.42 Accordingly, residential mobility programs that encourage poor families to move from the inner core of sprawling metropolitan areas to improve their children’s educational and employment opportunities may be stymied by housing segregation within the suburbs. Better enforcement of policies to eliminate discrimination in the suburban housing market and in mortgage lending might thus be considered part of a comprehensive approach to improving the connection of at-risk youth to the workplace. The success of residential mobility programs also is likely to depend upon a sufficient supply of affordable housing in higher income communities. The federal government has tested ways to deconcentrate poverty through the Section 8 voucher housing program (e.g., the Moving to Opportunity Fair Housing Demonstration and the Moving to Work Demonstration).43 Given the imbalance between the supply of and demand for affordable housing in higher income communities as well as the reluctance of municipalities to lose population, neighborhood workforce development and community/economic development policies might be brought to bear as well. For example, the U.S. Department of Housing and Urban Development helps to fund YouthBuild, an initiative featuring numerous community-based programs that train largely lowincome 16-24 year olds with limited educations in construction skills while they gain work experience by building affordable housing and take classes to obtain a high school (or equivalent) diploma. Some YouthBuild programs also receive support from AmeriCorps. Other workforce and community/economic development programs that do not have youth as their focus could nonetheless mitigate the adverse neighborhood effects previously discussed. But, improvements to an area that increase its attractiveness as a business location might not lead to greater employment of area residents regardless of age. Consequently, at the federal level, an income tax credit is available to businesses that hire (among other hard-to-employ groups such as 41 Ibid., p. 519. 42 Ibid. 43 For more information see CRS Report RL31930, Section 8 Housing Choice Voucher Program: Funding and Related Issues, by Maggie McCarty. CRS-20 members of families receiving TANF benefits) young residents of empowerment zones, enterprise communities, and renewal communities.44 Concluding Remarks Many of the youth employment and training programs that have been evaluated show limited positive long-lasting effects on the subsequent employment and earnings experiences of their participants.45 If graduation from high school is considered the minimal prerequisite for successful integration into the labor market, then the K-12 educational system also seems to be failing a substantial share of the youth population. Human capital development appears to be only a partial, albeit an important, strategy in ameliorating youths’ classroom-to-workplace transition however. Policies to directly or indirectly address the different dimensions of youth development tend to operate in comparative isolation from one another. Some analysts support training initiatives over educational initiatives and vice versa, with both groups contending that improvements to youths’ skills could lead to fewer pregnancies among unwed teenagers, fewer juveniles with criminal records, and more youth contributing to the nation’s revenue base. Others are more supportive of, for example, delinquency and pregnancy prevention programs which they argue could lead to greater educational attainment and enhanced employment outcomes for youth. As “[m]ost young people grow up in families, spend much of their time in schools, and are surrounded by communities,” it would seem that “incorporating opportunities for developmental outcomes into their lives demand coordinated efforts among these stakeholders.”46 44 For additional information see CRS Report RL30089, The Work Opportunity Tax Credit (WOTC) and the Welfare-to-Work (WtW) Tax Credit, by Linda Levine. 45 See for example Public/Private Ventures, Serving High-Risk Youth: Lessons from Research and Programming, Philadelphia, PA, Sept. 2002; and Susan Jekielik, Stephanie Cochran, and Elizabeth Hair, Employment Programs and Youth Development: A Synthesis (Washington, DC: Child Trends, May 2002). 46 Jacquelynne Eccles and Jennifer Appleton Gootman (eds.), Community Programs to Promote Youth Development (Washington, DC: National Academy of Sciences Press, 2002), p. 137.