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Testing the Specification of the Mincer Wage Equation

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  • Christian Belzil

    ()
    (GATE - Groupe d'analyse et de théorie économique - CNRS : UMR5824 - Université Lumière - Lyon II - Ecole Normale Supérieure Lettres et Sciences Humaines)

Abstract

Using panel data taken from the NLSY, I perform the joint estimation of i) a reduced-form dynamic model of the transition from one grade level to the next with observed and unobserved heterogeneity, and ii) a flexible version of the celebrated Mincerian wage equation with skill heterogeneity, non linearity in schooling, non-separability between the effects of schooling and experience and heteroskedasticity (after conditionning on unobserved skills). The model rejects all symplifying assumptions common in the empirical literature. In particular, the log wage regression is highly convex, even after conditionning on unobserved and observed skills. Skill heterogeneity is also found to be over-estimated when non-linearity is ignored. After conditioning on skill heterogeneity, schooling has a positive effect on wage growth.

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Paper provided by HAL in its series Post-Print with number halshs-00142542.

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Date of creation: May 2006
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Handle: RePEc:hal:journl:halshs-00142542

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Keywords: heterogeneity ; Mincer regression ; random coefficient models ; return to experience ; returns to education;

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  1. Belzil, Christian & Hansen, Jörgen, 2002. "A Structural Analysis of the Correlated Random Coefficient Wage Regression Model," IZA Discussion Papers 512, Institute for the Study of Labor (IZA).
  2. James Heckman & Edward Vytlacil, 1998. "Instrumental Variables Methods for the Correlated Random Coefficient Model: Estimating the Average Rate of Return to Schooling When the Return is Correlated with Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 974-987.
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  8. Christian Belzil & J�rgen Hansen, 2002. "Unobserved Ability and the Return to Schooling," Econometrica, Econometric Society, vol. 70(5), pages 2075-2091, September.
  9. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
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  15. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, 05.
  16. Christian Belzil, 2006. "The Return to Schooling in Structural Dynamic Models: A Survey," Working Papers 0609, Groupe d'Analyse et de Théorie Economique (GATE), Centre national de la recherche scientifique (CNRS), Université Lyon 2, Ecole Normale Supérieure.
  17. David Card & Thomas Lemieux, 2001. "Can Falling Supply Explain The Rising Return To College For Younger Men? A Cohort-Based Analysis," The Quarterly Journal of Economics, MIT Press, vol. 116(2), pages 705-746, May.
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  21. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute for the Study of Labor (IZA).
  22. Belzil, Christian & Hansen, Jörgen, 2003. "Structural Estimates of the Intergenerational Education Correlation," IZA Discussion Papers 973, Institute for the Study of Labor (IZA).
  23. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  24. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
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