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The Causal Effect of High School Employment on Educational Attainment in Canada

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  • Daniel Parent

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Abstract

The objective of this paper is to assess the impact of working in the twelve months preceding the date of leaving high school, either as a graduate or as a dropout, on the probability of graduation. To do so, I use Statistics Canada's 1991 School Leavers Survey and its 1995 Follow-up. Given that both the decision to graduate and the decision to work are endogenous variables, I use local labor market conditions as an exclusion restriction to study the sensitivity of the results to different estimation techniques in a system of endogenous limited-dependent/qualitative variables. While all estimation methods lead to roughly the same qualitative conclusion, relaxing some of the underlying distributional assumptions in favor of semi-parametric (or less restrictive) methods generally leads to larger impacts than what I get with full maximum likelihood techniques. In conclusion, while previous work using U.S. data points towards somewhat ambiguous effects, the results here show a strong negative effect of working while in school on the probability of graduation, especially for men. This negative effect shows up both when I use a dummy for work activity while in school or when I use hours worked directly. L'objectif poursuivi dans cet article est d'évaluer l'effet du travail durant les douze mois précédant la date de sortie des études secondaires, soit comme diplômé soit comme décrocheur, sur la probabilité d'obtenir le diplôme. À cette fin, j'utilise les données de l'Enquête sur les sortants effectuée en 1991 ainsi que celles du Suivi de 1995. Étant donné l'endogénéité des deux variables d'intérêt, la diplômation et le travail pendant les études, j'utilise les conditions du marché du travail local comme instrument afin d'étudier la sensibilité des résultats par rapport à plusieurs techniques d'estimation dans le cadre d'un système de variables dépendantes qualitatives/limitées. Bien que toutes les méthodes d'estimation mènent plus ou moins à la même conclusion du point de vue qualitatif, l'utilisation de méthodes semi-paramétriques tend à accentuer l'impact estimé du travail sur la probabilité d'abandon par rapport aux techniques faisant appel au maximum de vraisemblance. En conclusion, contrairement aux résultats avec des données américaines qui tendent à être quelque peu ambigus, les résultats obtenus ici avec des données canadiennes sont non-équivoques : le travail pendant les études réduit substantiellement la probabilité d'obtenir le diplôme d'études secondaires. Cette constatation s'applique aussi bien lorsque j'utilise les heures travaillées que lorsque j'utilise une variable dichotomique pour le travail.

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Bibliographic Info

Paper provided by CIRANO in its series CIRANO Working Papers with number 2002s-28.

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Date of creation: 01 Apr 2002
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Handle: RePEc:cir:cirwor:2002s-28

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Keywords: High school non-completion; local labour market conditions; system of endogenous binary or limited-dependent variables; semiparametric estimation; abandon scolaire; conditions économiques locales; système d'équations simultanées avec variables dépendantes qualitatives/limitées; estimation semi-paramétrique;

References

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  1. Powell, James L, 1986. "Symmetrically Trimmed Least Squares Estimation for Tobit Models," Econometrica, Econometric Society, vol. 54(6), pages 1435-60, November.
  2. Joshua D. Angrist, 1991. "Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology," NBER Technical Working Papers 0115, National Bureau of Economic Research, Inc.
  3. Joshua D. Angrist, 2000. "Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice," NBER Technical Working Papers 0248, National Bureau of Economic Research, Inc.
  4. Paarsch, Harry J., 1984. "A Monte Carlo comparison of estimators for censored regression models," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 197-213.
  5. Stephen V. Cameron & James J. Heckman, 1993. "Determinants of Young Male Schooling and Training Choices," NBER Working Papers 4327, National Bureau of Economic Research, Inc.
  6. Zvi Eckstein & Kenneth I. Wolpin, 1999. "Why Youths Drop Out of High School: The Impact of Preferences, Opportunities, and Abilities," Econometrica, Econometric Society, vol. 67(6), pages 1295-1340, November.
  7. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
  8. James J. Heckman, 1977. "Dummy Endogenous Variables in a Simultaneous Equation System," NBER Working Papers 0177, National Bureau of Economic Research, Inc.
  9. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  10. Christopher J. Ruhm, 1995. "Is High School Employment Consumption or Investment?," NBER Working Papers 5030, National Bureau of Economic Research, Inc.
  11. Gerald S. Oettinger, 1999. "Does high school employment affect high school academic performance?," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 53(1), pages 136-151, October.
  12. Richard Blundell & James Powell, 2001. "Endogeneity in nonparametric and semiparametric regression models," CeMMAP working papers CWP09/01, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  13. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
  14. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
  15. Alberto Abadie, 2000. "Semiparametric Estimation of Instrumental Variable Models for Causal Effects," NBER Technical Working Papers 0260, National Bureau of Economic Research, Inc.
  16. J.D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
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