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Persistence Bias and Schooling Returns

Author

Listed:
  • Andini, Corrado

    (University of Madeira)

Abstract
A well-established empirical literature suggests that individual wages are persistent. Several theoretical arguments support this empirical finding. Yet, the standard approach to the estimation of schooling returns does not account for this fact. This paper investigates the consequences of disregarding earnings persistence. In particular, it shows that the most commonly used static-model estimators of schooling coefficients are subject to an omitted-variable bias which can be named "persistence bias".

Suggested Citation

  • Andini, Corrado, 2014. "Persistence Bias and Schooling Returns," IZA Discussion Papers 8143, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp8143
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    File URL: https://docs.iza.org/dp8143.pdf
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    References listed on IDEAS

    as
    1. Andini, Corrado, 2013. "Persistence Bias and the Wage-Schooling Model," IZA Discussion Papers 7186, Institute of Labor Economics (IZA).
    2. Lillard, Lee A & Willis, Robert J, 1978. "Dynamic Aspects of Earning Mobility," Econometrica, Econometric Society, vol. 46(5), pages 985-1012, September.
    3. 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.
    4. 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.
    5. Baltagi, Badi H. & Blien, Uwe & Wolf, Katja, 2009. "New evidence on the dynamic wage curve for Western Germany: 1980-2004," Labour Economics, Elsevier, vol. 16(1), pages 47-51, January.
    6. 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.
    7. Belzil, Christian, 2007. "The return to schooling in structural dynamic models: a survey," European Economic Review, Elsevier, vol. 51(5), pages 1059-1105, July.
    8. Farber, Henry S, 1994. "The Analysis of Interfirm Worker Mobility," Journal of Labor Economics, University of Chicago Press, vol. 12(4), pages 554-593, October.
    9. Luigi Guiso & Luigi Pistaferri & Fabiano Schivardi, 2005. "Insurance within the Firm," Journal of Political Economy, University of Chicago Press, vol. 113(5), pages 1054-1087, October.
    10. Storesletten, Kjetil & Telmer, Christopher I. & Yaron, Amir, 2004. "Consumption and risk sharing over the life cycle," Journal of Monetary Economics, Elsevier, vol. 51(3), pages 609-633, April.
    11. Corrado Andini, 2010. "A dynamic Mincer equation with an application to Portuguese data," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2091-2098.
    12. L. Hospido, 2012. "Modelling heterogeneity and dynamics in the volatility of individual wages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 386-414, April.
    13. Buchinsky, Moshe, 1994. "Changes in the U.S. Wage Structure 1963-1987: Application of Quantile Regression," Econometrica, Econometric Society, vol. 62(2), pages 405-458, March.
    14. Webbink, Dinand & Hartog, Joop, 2004. "Can students predict starting salaries? Yes!," Economics of Education Review, Elsevier, vol. 23(2), pages 103-113, April.
    15. Ana Rute Cardoso & Miguel Portela, 2009. "Micro Foundations for Wage Flexibility: Wage Insurance at the Firm Level," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(1), pages 29-50, March.
    16. Corrado Andini, 2009. "Wage Bargaining and the (Dynamic) Mincer Equation," Economics Bulletin, AccessEcon, vol. 29(3), pages 1842-1849.
    17. Bell, Brian & Nickell, Stephen & Quintini, Glenda, 2002. "Wage equations, wage curves and all that," Labour Economics, Elsevier, vol. 9(3), pages 341-360, July.
    18. Peter J. Klenow & Mark Bils, 2000. "Does Schooling Cause Growth?," American Economic Review, American Economic Association, vol. 90(5), pages 1160-1183, December.
    19. Abowd, John M & Card, David, 1989. "On the Covariance Structure of Earnings and Hours Changes," Econometrica, Econometric Society, vol. 57(2), pages 411-445, March.
    20. Philip A. Trostel, 2005. "Nonlinearity in the return to education," Journal of Applied Economics, Universidad del CEMA, vol. 8, pages 191-202, May.
    21. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    22. Anabela Carneiro & Paulo Guimarães & Pedro Portugal, 2012. "Real Wages and the Business Cycle: Accounting for Worker, Firm, and Job Title Heterogeneity," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(2), pages 133-152, April.
    23. 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.
    24. Fatih Guvenen, 2009. "An Empirical Investigation of Labor Income Processes," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(1), pages 58-79, January.
    25. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    26. Hungerford, Thomas & Solon, Gary, 1987. "Sheepskin Effects in the Returns to Education," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 175-177, February.
    27. 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.
    28. Anastasia Semykina & Jeffrey M. Wooldridge, 2013. "Estimation of dynamic panel data models with sample selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 47-61, January.
    29. 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.
    30. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
    31. Corrado Andini, 2007. "Returns to education and wage equations: a dynamic approach," Applied Economics Letters, Taylor & Francis Journals, vol. 14(8), pages 577-579.
    32. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    33. 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.
    34. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
    35. Andini, Corrado, 2013. "Earnings persistence and schooling returns," Economics Letters, Elsevier, vol. 118(3), pages 482-484.
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    Cited by:

    1. Rietveld, Cornelius A. & Webbink, Dinand, 2016. "On the genetic bias of the quarter of birth instrument," Economics & Human Biology, Elsevier, vol. 21(C), pages 137-146.

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    More about this item

    Keywords

    schooling; wages; dynamic panel-data models;
    All these keywords.

    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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