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Persistence Bias and the Wage-Schooling Model

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  • Andini, Corrado

    (University of Madeira)

Abstract

This paper provides an expression for the bias of the OLS estimator of the schooling coefficient in a simple static wage-schooling model where earnings persistence is not accounted for. It is argued that the OLS estimator of the schooling coefficient is biased upward, and the bias is increasing with potential labor-market experience and the degree of earnings persistence. In addition, NLSY data are used to show that the magnitude of the persistence bias is non-negligible, and the bias cannot be cured by increasing the control set. Further, it is shown that disregarding earnings persistence is still problematic for the estimation of the schooling coefficient even if individual unobserved heterogeneity and endogeneity are taken into account. Overall, the findings support the dynamic approach to the estimation of wage-schooling models recently suggested by Andini (2012; 2013).

Suggested Citation

  • Andini, Corrado, 2013. "Persistence Bias and the Wage-Schooling Model," IZA Discussion Papers 7186, IZA Network @ LISER.
    • Handle: RePEc:iza:izadps:dp7186
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    References listed on IDEAS

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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    2. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    3. Francis Vella & Marno Verbeek, 1998. "Whose wages do unions raise? A dynamic model of unionism and wage rate determination for young men," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(2), pages 163-183.
    4. 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.
    5. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
    6. Corrado Andini, 2007. "Returns to education and wage equations: a dynamic approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(8), pages 577-579.
    7. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    8. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    9. Andini, Corrado, 2013. "Earnings persistence and schooling returns," Economics Letters, Elsevier, vol. 118(3), pages 482-484.
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    Cited by:

    1. Marconi, Gabriele, 2015. "Dynamic returns to schooling by work experience," MPRA Paper 88073, University Library of Munich, Germany.
    2. Andini, Corrado, 2014. "Persistence Bias and Schooling Returns," IZA Discussion Papers 8143, IZA Network @ LISER.

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    Keywords

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    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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

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