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Micro- and Macroeconomic Implications of Heterogeneity in the Production of Human Capital

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  • Solomon W. Polachek
  • Tirthatanmoy Das
  • Rewat Thamma-Apiroam

Abstract

We derive a tractable nonlinear earnings function that we estimate separately individual by individual using NLSY79 data. We obtain three ability measures, a rate of skill depreciation, a time discount rate, and a population-wide estimate of the human capital rental rate. We utilize these parameters to verify a number of heretofore untested theorems based on the life cycle model. We show how these human capital production function parameters relate to cognitive ability, personality traits, and family background. Finally, we show that accounting for individual-specific heterogeneity dramatically reduces estimates of population-wide persistence of permanent and transitory shocks by over 50 percent.

Suggested Citation

  • Solomon W. Polachek & Tirthatanmoy Das & Rewat Thamma-Apiroam, 2015. "Micro- and Macroeconomic Implications of Heterogeneity in the Production of Human Capital," Journal of Political Economy, University of Chicago Press, vol. 123(6), pages 1410-1455.
  • Handle: RePEc:ucp:jpolec:doi:10.1086/683989
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    References listed on IDEAS

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    1. Philipp Eisenhauer & James J. Heckman & Stefano Mosso, 2015. "Estimation Of Dynamic Discrete Choice Models By Maximum Likelihood And The Simulated Method Of Moments," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 331-357, May.
    2. Audra J. Bowlus & Chris Robinson, 2012. "Human Capital Prices, Productivity, and Growth," American Economic Review, American Economic Association, vol. 102(7), pages 3483-3515, December.
    3. James Heckman & Lance Lochner & Christopher Taber, 1998. "Explaining Rising Wage Inequality: Explanations With A Dynamic General Equilibrium Model of Labor Earnings With Heterogeneous Agents," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(1), pages 1-58, January.
    4. Sologon, Denisa Maria & O'Donoghue, Cathal, 2010. "Earnings Dynamics and Inequality among Men in Luxembourg, 1988-2004: Evidence from Administrative Data," IZA Discussion Papers 5014, Institute of Labor Economics (IZA).
    5. R. F. Engle & D. McFadden (ed.), 1986. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 4, number 4, January.
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    Cited by:

    1. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
    2. Nicholas W. Papageorge & Kevin Thom, 2017. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Upjohn Working Papers and Journal Articles 17-273, W.E. Upjohn Institute for Employment Research.
    3. Eric Nielsen, 2019. "Test Questions, Economic Outcomes, and Inequality," Finance and Economics Discussion Series 2019-013, Board of Governors of the Federal Reserve System (US).
    4. Papageorge, Nicholas W. & Thom, Kevin, 2016. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," IZA Discussion Papers 10200, Institute of Labor Economics (IZA).
    5. repec:pal:easeco:v:43:y:2017:i:3:d:10.1057_s41302-017-0096-z is not listed on IDEAS
    6. Ian Fillmore & Trevor Gallen, 2019. "Heterogeneity in Talent or in Tastes? Implications for Redistributive Taxation," 2019 Meeting Papers 94, Society for Economic Dynamics.
    7. Das, Tirthatanmoy & Polachek, Solomon W., 2017. "Estimating labor force joiners and leavers using a heterogeneity augmented two-tier stochastic frontier," Journal of Econometrics, Elsevier, vol. 199(2), pages 156-172.

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