Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/36815
Authors: 
Farré, Lídia
Klein, Roger
Vella, Francis
Year of Publication: 
2010
Series/Report no.: 
Discussion paper series // Forschungsinstitut zur Zukunft der Arbeit 4935
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%.
Subjects: 
Return to education
heteroskedasticity
endogeneity
JEL: 
J31
C31
Document Type: 
Working Paper

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