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A Dynamic Mincer Equation with an Application to Portuguese Data

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  • Andini, Corrado

    (University of Madeira)

Abstract

This paper argues in favor of a dynamic specification of the Mincer equation, where past observed earnings play the role of additional explanatory variable for current observed earnings. A dynamic approach offers an explanation why the return to schooling in terms of observed earnings is not independent of labor-market experience, as suggested by some recent empirical evidence for the United States.

Suggested Citation

  • Andini, Corrado, 2007. "A Dynamic Mincer Equation with an Application to Portuguese Data," IZA Discussion Papers 2897, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp2897
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    References listed on IDEAS

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    1. Martins, Pedro S. & Pereira, Pedro T., 2004. "Does education reduce wage inequality? Quantile regression evidence from 16 countries," Labour Economics, Elsevier, vol. 11(3), pages 355-371, June.
    2. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1.
    3. Santiago Budría & Pedro Telhado-Pereira, 2011. "Educational Qualifications And Wage Inequality: Evidence For Europe," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 19(2), pages 5-34, Autumn.
    4. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863, Elsevier.
    5. James J. Heckman & Lance J. Lochner & Petra E. Todd, 2003. "Fifty Years of Mincer Earnings Regressions," NBER Working Papers 9732, National Bureau of Economic Research, Inc.
    6. Heckman, James J. & Lochner, Lance J. & Todd, Petra E., 2006. "Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond," Handbook of the Economics of Education, in: Erik Hanushek & F. Welch (ed.), Handbook of the Economics of Education, edition 1, volume 1, chapter 7, pages 307-458, Elsevier.
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    11. Omar Arias & Walter Sosa-Escudero & Kevin F. Hallock, 2001. "Individual heterogeneity in the returns to schooling: instrumental variables quantile regression using twins data," Empirical Economics, Springer, vol. 26(1), pages 7-40.
    12. Corrado Andini, 2007. "The total impact of schooling on within-groups wage inequality in Portugal," Applied Economics Letters, Taylor & Francis Journals, vol. 15(2), pages 85-90.
    13. Telhado Pereira, Pedro & Silva Martins, Pedro, 2002. "Is there a return-risk link in education?," Economics Letters, Elsevier, vol. 75(1), pages 31-37, March.
    14. Taylor, John B., 1999. "Staggered price and wage setting in macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 15, pages 1009-1050, Elsevier.
    15. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, vol. 8(2), pages 202-229, April.
    16. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    17. Corrado Andini, 2007. "Returns to education and wage equations: a dynamic approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(8), pages 577-579.
    18. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    19. Pedro Telhado Pereira & Pedro Silva Martins, 2004. "Returns to education and wage equations," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 525-531.
    20. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
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    Citations

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    Cited by:

    1. Corrado Andini, 2022. "Tertiary education for all and wage inequality: policy insights from quantile regression," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 50(6), pages 1281-1296, November.
    2. Andini, Corrado, 2009. "How Fast Do Wages Adjust to Human-Capital Productivity? Dynamic Panel-Data Evidence from Belgium, Denmark and Finland," IZA Discussion Papers 4583, Institute of Labor Economics (IZA).
    3. Andersson, Roland & Nabavi Larijani, Pardis & Wilhelmsson, Mats, 2013. "The impact of vocational education and training on income in Sweden," Working Paper Series 13/4, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    4. Corrado Andini, 2009. "Wage Bargaining and the (Dynamic) Mincer Equation," Economics Bulletin, AccessEcon, vol. 29(3), pages 1842-1849.
    5. Savina Finardi & Jakub Fischer, 2017. "The estimation of Mincer function in conditions of the Czech republic [Odhad Mincerovy funkce v podmínkách České republiky]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2017(3), pages 57-68.
    6. Sebastian Kripfganz & Claudia Schwarz, 2019. "Estimation of linear dynamic panel data models with time‐invariant regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(4), pages 526-546, June.
    7. Andini, Corrado, 2014. "Persistence Bias and Schooling Returns," IZA Discussion Papers 8143, Institute of Labor Economics (IZA).
    8. Corrado Andini, 2013. "How well does a dynamic Mincer equation fit NLSY data? Evidence based on a simple wage-bargaining model," Empirical Economics, Springer, vol. 44(3), pages 1519-1543, June.
    9. Andini, Corrado, 2013. "Earnings persistence and schooling returns," Economics Letters, Elsevier, vol. 118(3), pages 482-484.

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    More about this item

    Keywords

    panel data; Mincer equation; return to schooling; wage level;
    All these keywords.

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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