A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY

Lidia Farre, Roger Klein (rogerwklein@gmail.com) and Francis Vella

No 4935, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: An innovation which bypasses the need for instruments when estimating endogenous treatment effects is identification via conditional second moments. The most general of these approaches is Klein and Vella (2010) which models the conditional variances semiparametrically. While this is attractive, as identification is not reliant on parametric assumptions for variances, the non-parametric aspect of the estimation may discourage practitioners from its use. This paper outlines how the estimator can be implemented parametrically. The use of parametric assumptions is accompanied by a large reduction in computational and programming demands. We illustrate the approach by estimating the return to education using a sample drawn from the National Longitudinal Survey of Youth 1979. Accounting for endogeneity increases the estimate of the return to education from 6.8% to 11.2%.

Keywords: return to education; heteroskedasticity; endogeneity (search for similar items in EconPapers)
JEL-codes: C31 J31 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2010-05
New Economics Papers: this item is included in nep-ecm and nep-edu
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Citations: View citations in EconPapers (4)

Published - published in: Empirical Economics, 2013, 44 (1), 111-133

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Related works:
Journal Article: A parametric control function approach to estimating the returns to schooling in the absence of exclusion restrictions: an application to the NLSY (2013)
Working Paper: A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY (2008)
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