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A dynamic Mincer equation with an application to Portuguese data

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  • Corrado Andini

Abstract

This article argues in favour of a dynamic specification of the Mincer equation, where the 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 labour-market experience, as suggested by some recent empirical evidence for the United States.

Suggested Citation

  • Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    • Handle: RePEc:taf:applec:v:42:y:2010:i:16:p:2091-2098
    DOI: 10.1080/00036840701765429
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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.
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    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.
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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

    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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