Estimates of the Returns to Schooling from Sibling Data: Fathers, Sons and Brothers

34 Pages Posted: 26 Aug 2000 Last revised: 10 Oct 2022

See all articles by Orley Ashenfelter

Orley Ashenfelter

Princeton University - Industrial Relations Section; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

David J. Zimmerman

Williams College

Date Written: October 1993

Abstract

In this paper we use data on brothers, and fathers and sons, to estimate the economic returns to schooling. Our goal is to determine whether the correlation between earnings and schooling is due, in part, to the correlation between family backgrounds and schooling. The basic idea is to contrast the differences between the schooling of brothers, and fathers and sons, with the differences in their respective earnings. Since individuals linked by family affiliation are more likely to have similar innate ability and family backgrounds than randomly selected individuals our procedure provides a straightforward control for unobserved family attributes. Our empirical results indicate that in the sample of brothers the ordinary least squares estimates of the return to schooling may be biased upward by some 25% by the omission of family background factors. Adjustments for measurement error, however, imply that the intrafamily estimate of the returns to schooling is biased downward by about 25% also, so that the ordinary least squares estimate suffers from very little overall bias. Using data on fathers and sons introduces some ambiguity into these findings, as commonly used specification tests reject our simplest models of the role of family background in the determination of earnings.

Suggested Citation

Ashenfelter, Orley C. and Zimmerman, David J., Estimates of the Returns to Schooling from Sibling Data: Fathers, Sons and Brothers (October 1993). NBER Working Paper No. w4491, Available at SSRN: https://ssrn.com/abstract=227320

Orley C. Ashenfelter (Contact Author)

Princeton University - Industrial Relations Section ( email )

Princeton, NJ 08544-2098
United States
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National Bureau of Economic Research (NBER)

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IZA Institute of Labor Economics

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David J. Zimmerman

Williams College ( email )

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United States
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