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The Causal Effect of Schooling : empirical Evidence from Germany

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  • Markus Jochmann

    ()
    (Department of Economics, University of Konstanz)

  • Winfried Pohlmeier

    ()
    (Department of Economics, University of Konstanz)

Abstract

This paper analysis the robustness of the causal relationship between schooling and wages. Different estimators and instruments are compared under the assumption of heterogeneous returns to schooling. A data set from Germany is employed. It is shown that the results depend crucially on the choice of instruments and not so much on the applied estimator.

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Bibliographic Info

Paper provided by Research Group Heterogeneous Labor, University of Konstanz/ZEW Mannheim in its series Working Papers of the Research Group Heterogenous Labor with number 04-05.

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Length: 31 pages
Date of creation: 25 Feb 2004
Date of revision:
Handle: RePEc:knz:hetero:0405

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Related research

Keywords: returns to schooling ; causal effect ; correlated random coefficients ; weak instruments ; robust interference;

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References

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  1. Orley Ashenfelter & Cecilia Rouse, 1998. "Income, Schooling, And Ability: Evidence From A New Sample Of Identical Twins," The Quarterly Journal of Economics, MIT Press, vol. 113(1), pages 253-284, February.
  2. Thomas J. Kane & Cecilia E. Rouse, 1993. "Labor Market Returns to Two- and Four-Year Colleges: Is a Credit a Credit and Do Degrees Matter?," NBER Working Papers 4268, National Bureau of Economic Research, Inc.
  3. Jinyong Hahn & Jerry Hausman, 2002. "A New Specification Test for the Validity of Instrumental Variables," Econometrica, Econometric Society, vol. 70(1), pages 163-189, January.
  4. Pedro Carneiro & James J. Heckman, 2002. "The Evidence on Credit Constraints in Post--secondary Schooling," Economic Journal, Royal Economic Society, vol. 112(482), pages 705-734, October.
  5. Nelson, C. & Startz, R., 1988. "Some Furthere Results On The Exact Small Sample Properties Of The Instrumental Variable Estimator," Discussion Papers in Economics at the University of Washington 88-06, Department of Economics at the University of Washington.
  6. Donald, Stephen G & Newey, Whitney K, 2001. "Choosing the Number of Instruments," Econometrica, Econometric Society, vol. 69(5), pages 1161-91, September.
  7. Vincent Hogan & Roberto Rigobon, 2003. "Using Heteroscedasticity to Estimate the Returns to Education," Working Papers 200301, School Of Economics, University College Dublin.
  8. Joshua Angrist & Alan Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," Working Papers 653, Princeton University, Department of Economics, Industrial Relations Section..
  9. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, vol. 56(2), pages 129-133, October.
  10. Dinardo, J.E. & Pischke, J.S., 1996. "The Returns to Computer Use Revisited: Have Pencils Changed the Wage Structure Too?," Working papers 96-12, Massachusetts Institute of Technology (MIT), Department of Economics.
  11. Michael Maier & Friedhelm Pfeiffer & Winfried Pohlmeier, 2003. "Overeducation and Individual Heterogeneity," Working Papers of the Research Group Heterogenous Labor 03-01, Research Group Heterogeneous Labor, University of Konstanz/ZEW Mannheim.
  12. Omar Arias & Kevin F. Hallock & Walter Sosa Escudero, 1999. "Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression using Twins Data," Department of Economics, Working Papers 016, Departamento de Economía, Facultad de Ciencias Económicas, Universidad Nacional de La Plata.
  13. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 272-306, 06.
  14. Fuller, Wayne A, 1977. "Some Properties of a Modification of the Limited Information Estimator," Econometrica, Econometric Society, vol. 45(4), pages 939-53, May.
  15. Blomquist, Soren & Dahlberg, Matz, 1999. "Small Sample Properties of LIML and Jackknife IV Estimators: Experiments with Weak Instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 69-88, Jan.-Feb..
  16. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-29, October.
  17. Rummery, Sarah & Vella, Francis & Verbeek, Marno, 1999. "Estimating the returns to education for Australian youth via rank-order instrumental variables," Labour Economics, Elsevier, vol. 6(4), pages 491-507, November.
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