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Evaluating School-To-Work Programs Using the New NLSY

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  • David Neumark
  • Mary Joyce

Abstract

A critical impediment to research on school-to-work programs has been the absence of large representative data sets with information on such programs. In contrast, the new NLSY (NLSY97) offers researchers opportunities to analyze direct evidence on school-to-work programs. In the NLSY97, individuals are asked a set of survey questions about programs schools offer to help students prepare for the world of work,' and an accompanying survey includes information on school-to-work programs offered by schools attended by the interviewees. These data, coupled with observations on multiple individuals in the same schools, potentially allow researchers to estimate the effects of school-to-work programs on individuals while accounting for possible bias from selection into these programs, although apparent data problems pose some limitations. Because Round One of the NLSY97 covers workers only up to age 17, this paper focuses on the consequences of school-to-work programs for youth employment and schooling decisions while in high school, and students' subjective assessments of the likelihood of future schooling and work behavior. Overall, the evidence does not point to a causal effect of school-to-work program participation on behavior likely associated with future college attendance. On the other hand, school-to-work program participation does appear to have positive effects on educational attainment in terms of respondents' subjective probabilities of obtaining a high-school diploma. More in accordance with the traditional view of school-to-work programs, the data indicate that participation in these programs increases the perceived likelihood of future labor market activity, both for the year following the survey and at age 30. However, school-to-work programs do not appear to boost the probability of current employment.

Suggested Citation

  • David Neumark & Mary Joyce, 2000. "Evaluating School-To-Work Programs Using the New NLSY," NBER Working Papers 7719, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:7719
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    References listed on IDEAS

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    1. David Neumark, 1998. "Youth Labor Markets in the U.S.: Shopping Around vs. Staying Put," NBER Working Papers 6581, National Bureau of Economic Research, Inc.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
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    5. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097, Elsevier.
    6. Rosella Gardecki & David Neumark, 1998. "Order from Chaos? The Effects of Early Labor Market Experiences on Adult Labor Market Outcomes," ILR Review, Cornell University, ILR School, vol. 51(2), pages 299-322, January.
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    Cited by:

    1. van Ours, Jan C. & Williams, Jenny & Ward, Shannon, 2015. "Bad Behavior: Delinquency, Arrest and Early School Leaving," CEPR Discussion Papers 10755, C.E.P.R. Discussion Papers.
    2. Charles L. Baum & Christopher J. Ruhm, 2016. "The Changing Benefits of Early Work Experience," Southern Economic Journal, John Wiley & Sons, vol. 83(2), pages 343-363, October.
    3. Shaun M. Dougherty, 2018. "The Effect of Career and Technical Education on Human Capital Accumulation: Causal Evidence from Massachusetts," Education Finance and Policy, MIT Press, vol. 13(2), pages 119-148, Spring.
    4. Charlene Kalenkoski & Sabrina Pabilonia, 2010. "Parental transfers, student achievement, and the labor supply of college students," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(2), pages 469-496, March.
    5. Kalenkoski, Charlene Marie & Pabilonia, Sabrina Wulff, 2012. "Time to work or time to play: The effect of student employment on homework, sleep, and screen time," Labour Economics, Elsevier, vol. 19(2), pages 211-221.
    6. David Neumark & Donna Rothstein, 2004. "Do School-to-Work Programs Help the "Forgotten Half"?," PPIC Working Papers 2004.16, Public Policy Institute of California.
    7. Sabrina Wulff Pabilonia, 2017. "Teenagers’ risky health behaviors and time use during the great recession," Review of Economics of the Household, Springer, vol. 15(3), pages 945-964, September.
    8. Cellini, Stephanie Riegg, 2006. "Smoothing the transition to college? The effect of Tech-Prep programs on educational attainment," Economics of Education Review, Elsevier, vol. 25(4), pages 394-411, August.
    9. Daniel Kreisman & Kevin Stange, 2020. "Vocational and Career Tech Education in American High Schools: The Value of Depth Over Breadth," Education Finance and Policy, MIT Press, vol. 15(1), pages 11-44, Winter.
    10. Neumark, David & Rothstein, Donna, 2006. "School-to-career programs and transitions to employment and higher education," Economics of Education Review, Elsevier, vol. 25(4), pages 374-393, August.
    11. Boockmann, Bernhard & Nielen, Sebastian, 2016. "Mentoring disadvantaged youths during school-to-work transition: evidence from Germany," VfS Annual Conference 2016 (Augsburg): Demographic Change 145770, Verein für Socialpolitik / German Economic Association.
    12. Robert LaLonde & Daniel Sullivan, 2010. "Vocational Training," NBER Chapters, in: Targeting Investments in Children: Fighting Poverty When Resources Are Limited, pages 323-349, National Bureau of Economic Research, Inc.

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    JEL classification:

    • I2 - Health, Education, and Welfare - - Education
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination

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