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Testing the Specification of the Mincer Wage Equation

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  • Belzil, Christian

    (Ecole Polytechnique, Paris)

Abstract

I perform the joint estimation of a reduced-form dynamic model of the transition from one grade level to the next, and a Mincer wage equation, using panel data taken from the NLSY. A very high degree of flexibility is achieved by approximating the distributions of idiosyncractic grade transition shocks and wage shocks with high dimensional normal mixtures. The model rejects all simplifying assumptions common in the empirical literature. In particular, the log wage regression is highly convex, even after conditioning on unobserved and observed skills. Skill heterogeneity is also found to be over-estimated when non-linearity is ignored. After conditioning on skill heterogeneity, I also find evidence of non-separability between the effect of schooling and experience (schooling has a positive effect on wage growth). Finally, the variance of the idiosyncratic wage shock is reduced by obtaining higher education.

Suggested Citation

  • Belzil, Christian, 2007. "Testing the Specification of the Mincer Wage Equation," IZA Discussion Papers 2650, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp2650
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    Cited by:

    1. Belzil, Christian, 2007. "The return to schooling in structural dynamic models: a survey," European Economic Review, Elsevier, vol. 51(5), pages 1059-1105, July.
    2. Belzil, Christian & Poinas, François, 2010. "Education and early career outcomes of second-generation immigrants in France," Labour Economics, Elsevier, vol. 17(1), pages 101-110, January.
    3. Belzil, Christian & Hansen, Jörgen & Kristensen, Nicolai, 2008. "Estimating Complementarity between Education and Training," IZA Discussion Papers 3882, Institute of Labor Economics (IZA).
    4. Haefke, Christian & Sonntag, Marcus & van Rens, Thijs, 2013. "Wage rigidity and job creation," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 887-899.
    5. Fabio Sánchez & Alexis Munari & Tatiana Velasco & María Camila Ayala & Xiomara Pulido, 2016. "Beneficios económicos y laborales de la educación media y acceso a la educación superior," Documentos de trabajo 17660, Escuela de Gobierno - Universidad de los Andes.
    6. Éva Polgár & Julia Wörz, 2010. "No risk and some fun? Trade and wages in the enlarged European Union," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(2), pages 127-163, May.
    7. Eva Katalin Polgar & Julia Woerz, 2011. "Trade With Central and Eastern Europe: Is It Really a Threat to Wages in the West?," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 1, pages 1-31, March.
    8. repec:onb:oenbwp:y:2009:i:1:b:1 is not listed on IDEAS
    9. Belzil, Christian & Hansen, Jörgen, 2008. "Calibration and IV Estimation of a Wage Outcome Equation in a Dynamic Environment," IZA Discussion Papers 3528, Institute of Labor Economics (IZA).
    10. Belzil, Christian & Hansen, Jörgen, 2010. "The Distinction between Dictatorial and Incentive Policy Interventions and its Implication for IV Estimation," IZA Discussion Papers 4835, Institute of Labor Economics (IZA).
    11. Pauline Charnoz & Elise Coudin & Mathilde Gaini, 2014. "Forty Years of Decreasing Wage Inequality in France : The Role of Supply and Hidden Skill-Biased Technical Change," Working Papers 2014-20, Center for Research in Economics and Statistics.
    12. Oancea, Bogdan & Pospisil, Richard & Dragoescu, Raluca, 2017. "The return to higher education: evidence from Romania," MPRA Paper 81720, University Library of Munich, Germany.
    13. Tyrowicz, Joanna, 2011. "What distinguishes entrepreneurs? Evidence on the motives for self-employment," Economics Letters, Elsevier, vol. 112(3), pages 226-229, September.
    14. Lucas Van Der Velde & Joanna Tyrowicz & Karolina Goraus, 2013. "What is the true gender wage gap? A comparative analysis using data from Poland," Working Papers 2013-28, Faculty of Economic Sciences, University of Warsaw.

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    More about this item

    Keywords

    returns to schooling; random coefficient models; heterogeneity; Mincer regressions; returns to experience;
    All these keywords.

    JEL classification:

    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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