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College Education and Wages in the U.K.: Estimating Conditional Average Structural Functions in Nonadditive Models with Binary Endogenous Variables

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  • Klein, T.J.

    (Tilburg University, Center for Economic Research)

Abstract

Recent studies debate how the unobserved dependence between the monetary return to college education and selection into college can be characterized. This paper examines this question using British data. We develop a semiparametric local instrumental variables estimator for identified features of a flexible correlated random coefficient model. These identified features are directly related to the marginal and average treatment effect in policy evaluation. Our results indicate that returns to college systematically differ between actual college graduates and actual college non-graduates. They are on average higher for college graduates and positively related to selection into college for 96 percent of the individuals. The dependence between selection into college and returns to college education is strongest for individuals with low math test scores at the age of 7, individuals with less educated mothers, and for working-class individuals.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2009-88.

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Date of creation: 2009
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Handle: RePEc:dgr:kubcen:200988

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Web page: http://center.uvt.nl

Related research

Keywords: Returns to college education; correlated random coefficient model; local instrumental variables estimation;

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References

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  1. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, 07.
  2. Carneiro, Pedro & Meghir, Costas & Parey, Matthias, 2007. "Maternal Education, Home Environments and the Development of Children and Adolescents," CEPR Discussion Papers 6505, C.E.P.R. Discussion Papers.
  3. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, October.
  4. Carneiro, Pedro & Lee, Sokbae, 2009. "Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality," Journal of Econometrics, Elsevier, vol. 149(2), pages 191-208, April.
  5. Frölich, Markus, 2002. "Nonparametric IV Estimation of Local Average Treatment Effects with Covariates," IZA Discussion Papers 588, Institute for the Study of Labor (IZA).
  6. Klein, Tobias J., 2007. "Heterogeneous Treatment Effects: Instrumental Variables without Monotonicity?," IZA Discussion Papers 2738, Institute for the Study of Labor (IZA).
  7. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
  8. James J. Heckman & Sergio Urzua & Edward J. Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," NBER Working Papers 12574, National Bureau of Economic Research, Inc.
  9. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  10. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-60, September.
  11. 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.
  12. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4 National Bureau of Economic Research, Inc.
  13. Goldberger, Arthur S, 1989. "Economic and Mechanical Models of Intergenerational Transmission," American Economic Review, American Economic Association, vol. 79(3), pages 504-13, June.
  14. Heckman, James J. & Vytlacil, Edward J., 2000. "The relationship between treatment parameters within a latent variable framework," Economics Letters, Elsevier, vol. 66(1), pages 33-39, January.
  15. Janet Currie & Enrico Moretti, 2003. "Mother'S Education And The Intergenerational Transmission Of Human Capital: Evidence From College Openings," The Quarterly Journal of Economics, MIT Press, vol. 118(4), pages 1495-1532, November.
  16. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March.
  17. Robert Haveman & Barbara Wolfe, 1995. "The Determinants of Children's Attainments: A Review of Methods and Findings," Journal of Economic Literature, American Economic Association, vol. 33(4), pages 1829-1878, December.
  18. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
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Cited by:
  1. Klein, T.J., 2008. "Heterogeneous Treatment Effects: Instrumental Variables Without Monotonicity?," Discussion Paper 2008-45, Tilburg University, Center for Economic Research.
  2. Bernd Fitzenberger & Michael Lechner & Jeffrey Smith, 2013. "Estimation of treatment effects: recent developments and applications," Empirical Economics, Springer, vol. 44(1), pages 1-11, February.

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