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High school completion and future youth unemployment: new evidence from High School and Beyond

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  • Mingliang Li

    (Department of Economics, State University of New York at Buffalo, USA)

Abstract

In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two-limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial variability in returns to education across schools and evidence of diminishing marginal effects of compulsory attendance on high school completion. The simulation results suggest that increasing the compulsory attendance age raises the probability of completing high school and reduces the proportion of time the individuals are unemployed. These effects are much more pronounced for disadvantaged students but less pronounced for advantaged students, suggesting the potential effects of compulsory attendance on reducing the inequality in education and employment. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • Mingliang Li, 2006. "High school completion and future youth unemployment: new evidence from High School and Beyond," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 23-53.
  • Handle: RePEc:jae:japmet:v:21:y:2006:i:1:p:23-53
    DOI: 10.1002/jae.817
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    File URL: http://qed.econ.queensu.ca:80/jae/2006-v21.1/
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    References listed on IDEAS

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    Cited by:

    1. Anderson, D. Mark & Hansen, Benjamin & Walker, Mary Beth, 2013. "The minimum dropout age and student victimization," Economics of Education Review, Elsevier, vol. 35(C), pages 66-74.
    2. Philip Oreopoulos & Kjell G. Salvanes, 2011. "Priceless: The Nonpecuniary Benefits of Schooling," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 159-184, Winter.
    3. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    4. Philip Oreopoulos & Kjell G. Salvanes, 2009. "How large are returns to schooling? Hint: Money isn't everything," NBER Working Papers 15339, National Bureau of Economic Research, Inc.
    5. Li, Mingliang, 2009. "Is there "white flight" into private schools? New evidence from High School and Beyond," Economics of Education Review, Elsevier, vol. 28(3), pages 382-392, June.
    6. Bonin, Holger, 2017. "Report No. 75: The Potential Economic Benefits of Education of Migrants in the EU," IZA Research Reports 75, Institute for the Study of Labor (IZA).
    7. Rainer Winkelmann, 2009. "Copula-based bivariate binary response models," SOI - Working Papers 0913, Socioeconomic Institute - University of Zurich.
    8. Rémi Piatek & Pia Pinger, 2016. "Maintaining (Locus of) Control? Data Combination for the Identification and Inference of Factor Structure Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 734-755, June.

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