Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data

41 Pages Posted: 27 Oct 2000

See all articles by Omar Arias

Omar Arias

World Bank

Kevin F. Hallock

Cornell University; National Bureau of Economic Research (NBER)

Walter Sosa-Escudero

Universidad Nacional de La Plata - Faculty of Economics

Abstract

Considerable effort has been exercised in estimating mean returns to education while carefully considering biases arising from unmeasured ability and measurement error. Some recent work has also attempted to determine whether there are variations from the "mean" return to education across the population with mixed results. In this paper, we use recent extensions of instrumental variables techniques to quantile regression on a sample of twins to estimate an entire family of returns to education at different quantiles of the conditional distribution of wages while addressing simultaneity and measurement error biases. We test whether there is individual heterogeneity in returns to education against the alternative that there is a constant return for all workers. Our estimated model provides evidence of two sources of heterogeneity in returns to schooling. First, there is some evidence of a differential effect by which more able individuals become better educated perhaps due to lower marginal costs and higher marginal benefits of schooling. Second, once this endogeneity bias is accounted for, our results provide some evidence of the existence of actual heterogeneity in market returns to education consistent with a non-trivial interaction between schooling and unobserved abilities in the generation of earnings. The evidence is consistent with the fact that higher ability individuals (those further to the right in the conditional distribution of wages) have higher returns to schooling but that returns vary significantly only along the lower quantiles to middle quantiles. However, once we fully control for measurement error and ability bias, tests of the differences in returns across quantiles become less precise. In this final approach, the resulting estimated returns are never lower than 9 percent and can be as high as 13 percent at the top of the conditional distribution of wages. Our findings may have meaningful implications for the design of educational policies.

Keywords: returns to education, human capital, heterogeneity, quantile treatment effects, instrumental variables

JEL Classification: C14, I2, J24, J31

Suggested Citation

Arias, Omar and Hallock, Kevin F. and Sosa-Escudero, Walter, Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile Regression Using Twins Data. Available at SSRN: https://ssrn.com/abstract=238898 or http://dx.doi.org/10.2139/ssrn.238898

Omar Arias (Contact Author)

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Kevin F. Hallock

Cornell University ( email )

Ithaca, NY 14853
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Walter Sosa-Escudero

Universidad Nacional de La Plata - Faculty of Economics ( email )

1900 La Plata
Argentina
(541) 553-9983 (Phone)

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