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A Structural Analysis of the Correlated Random Coefficient Wage Regression Model with an Application to the OLS-IV Puzzle

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  • Belzil, Christian

    ()
    (Ecole Polytechnique, Paris)

  • Hansen, Jörgen

    ()
    (Concordia University)

Abstract

We estimate a finite mixture dynamic programming model of schooling decisions in which the log wage regression function is set within a correlated random coefficient model and we use the structural estimates to perform counterfactual experiments. We show that the estimates of the dynamic programming model with a rich heterogeneity specification, along with simulated schooling/wage histories, may be used to obtain estimates of the average treatment effects (ATE), the average treatment effects for the treated and the untreated (ATT/ATU), the marginal treatment effect (MTE) and, finally, the local average treatment effects (LATE). The model is implemented on a panel of white males taken from the National Longitudinal Survey of Youth (NLSY) from 1979 until 1994. We find that the average return to experience upon entering the labor market (0.059) exceeds the average return to schooling in the population (0.043). The importance of selectivity based on individual specific returns to schooling is illustrated by the difference between the average returns for those who have not attended college (0.0321) and those who attended college (0.0645). Our estimate of the MTE (0.0573) lies between the ATU and ATT and exceeds the average return in the population. Interestingly, the low average wage return is compatible with the occurrence of very high returns to schooling in some subpopulation (the highest type specific return is 0.13) and the simulated IV estimates (around 0.10) are comparable to those very high estimates often reported in the literature. The high estimates are explained by the positive correlation between the returns to schooling and the individual specific reactions. Moreover, they are not solely attributable to those individuals who are at the margin, but also to those individuals who would achieve a higher grade level no matter what. The structural dynamic programming model with multi-dimensional heterogeneity is therefore capable of explaining the well known OLS/IV puzzle.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 1585.

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Length: 43 pages
Date of creation: May 2005
Date of revision:
Publication status: Published in: Journal of Econometrics, 140 (2), 2007, 333-948
Handle: RePEc:iza:izadps:dp1585

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Keywords: treatment effects; dynamic self-selection; dynamic programming; returns to schooling; random coefficient;

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References

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  1. Stephen V. Cameron & Christopher Taber, 2004. "Estimation of Educational Borrowing Constraints Using Returns to Schooling," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 112(1), pages 132-182, February.
  2. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 62(2), pages 467-75, March.
  3. Meghir, Costas & Palme, Marten, 2001. "The Effect of a Social Experiment in Education," Working Paper Series in Economics and Finance 0451, Stockholm School of Economics.
  4. Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables: With an Application to the Returns to Schooling," Virginia Economics Online Papers 308, University of Virginia, Department of Economics.
  5. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, Elsevier, vol. 56(2), pages 129-133, October.
  6. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects and Econometric Policy Evaluation," NBER Technical Working Papers 0306, National Bureau of Economic Research, Inc.
  7. Magnac & Thesmar, 2002. "Identifying dynamic discrete decision processes," Working Papers 155888, Institut National de la Recherche Agronomique, France.
  8. Christian Belzil & J�rgen Hansen, 2002. "Unobserved Ability and the Return to Schooling," Econometrica, Econometric Society, Econometric Society, vol. 70(5), pages 2075-2091, September.
  9. Michael P. Keane & Kenneth I. Wolpin, 1995. "The career decisions of young men," Working Papers, Federal Reserve Bank of Minneapolis 559, Federal Reserve Bank of Minneapolis.
  10. Wooldridge, Jeffrey M., 2003. "Further results on instrumental variables estimation of average treatment effects in the correlated random coefficient model," Economics Letters, Elsevier, Elsevier, vol. 79(2), pages 185-191, May.
  11. Christian Belzil & Jörgen Hansen, 2007. "A Structural Analysis of the Correlated Random Coefficient Wage Regression Model," Post-Print halshs-00201350, HAL.
  12. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
  13. James Heckman & Edward Vytlacil, 1998. "Instrumental Variables Methods for the Correlated Random Coefficient Model: Estimating the Average Rate of Return to Schooling When the Return is Correlated with Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 974-987.
  14. Robert J. Willis & Sherwin Rosen, 1978. "Education and Self-Selection," NBER Working Papers 0249, National Bureau of Economic Research, Inc.
  15. Pedro Carneiro & James J. Heckman, 2002. "The Evidence on Credit Constraints in Post--secondary Schooling," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 112(482), pages 705-734, October.
  16. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
  17. Belzil, Christian & Hansen, Jörgen, 2003. "Structural Estimates of the Intergenerational Education Correlation," IZA Discussion Papers 973, Institute for the Study of Labor (IZA).
  18. Eckstein, Zvi & Wolpin, Kenneth, 1998. "Youth Employment and Academic Performance in High School," CEPR Discussion Papers, C.E.P.R. Discussion Papers 1861, C.E.P.R. Discussion Papers.
  19. Stephen V. Cameron & James J. Heckman, 1998. "Life Cycle Schooling and Dynamic Selection Bias: Models and Evidence for Five Cohorts of American Males," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 106(2), pages 262-333, April.
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Cited by:
  1. Heckman, James J. & Lochner, Lance John & Todd, Petra E., 2005. "Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond," IZA Discussion Papers 1700, Institute for the Study of Labor (IZA).

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