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Interpreting Instrumental Variables Estimates of the Returns to Schooling

  • Henry S. Farber
  • Jeffrey R. Kling
  • Alan Krueger

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.

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File URL: http://arks.princeton.edu/ark:/88435/dsp01xd07gs69b
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Paper provided by Princeton University, Department of Economics, Industrial Relations Section. in its series Working Papers with number 794.

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Date of creation: Jan 1999
Date of revision:
Handle: RePEc:pri:indrel:dsp01xd07gs69b
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  1. Angrist, Joshua D & Krueger, Alan B, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, MIT Press, vol. 106(4), pages 979-1014, November.
  2. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
  3. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-61, April.
  4. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
  5. Stephen Cameron & Christopher Taber, 2000. "Borrowing Constraints and the Returns to Schooling," NBER Working Papers 7761, National Bureau of Economic Research, Inc.
  6. 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.
  7. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  8. 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.
  9. 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.
  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. J.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.
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