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Interpreting Instrumental Variables Estimates of the Returns to Schooling

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  • Kling, Jeffrey R
Abstract
This article synthesizes economic insights from theoretical models of schooling choice based on individual benefits and econometric work interpreting instrumental variables estimates as weighted averages of individual-specific causal effects. Linkages are illustrated using college proximity to instrument for schooling. After characterizing groups differentially affected by the instrument according to family background, 1 directly compute weights underlying estimation of the overall return. In analyzing the level of schooling at which individuals change their behavior in response to the instrument, I demonstrate that this instrument has its greatest impact on the transition from high school to college. Specification robustness is also examined.

Suggested Citation

  • Kling, Jeffrey R, 2001. "Interpreting Instrumental Variables Estimates of the Returns to Schooling," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 358-364, July.
  • Handle: RePEc:bes:jnlbes:v:19:y:2001:i:3:p:358-64
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    References listed on IDEAS

    as
    1. 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.
    2. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
    3. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    4. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
    5. 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.
    6. repec:eee:labchp:v:1:y:1986:i:c:p:525-602 is not listed on IDEAS
    7. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    8. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-161, April.
    9. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
    10. Caroline M. Hoxby, 1997. "How the Changing Market Structure of U.S. Higher Education Explains College Tuition," NBER Working Papers 6323, National Bureau of Economic Research, Inc.
    11. Joshua D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
    12. Stephen Cameron & Christopher Taber, 2000. "Borrowing Constraints and the Returns to Schooling," NBER Working Papers 7761, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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