A Small-Sample Estimator for the Sample-Selection Model

Amos Golan, Enrico Moretti and Jeffrey Perloff

No 25047, CUDARE Working Papers from University of California, Berkeley, Department of Agricultural and Resource Economics

Abstract: A semiparametric estimator for evaluating the parameters of data generated under a sample selection process is developed. This estimator is based on the generalized maximum entropy estimator and performs well for small and ill-posed samples. Theoretical and sampling comparisons with parametric and semiparametric estimators are given. This method and standard ones are applied to three small-sample empirical applications of the wage-participation model for female teenage heads of households, immigrants, and Native Americans.

Keywords: Labor and Human Capital; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 41
Date: 2001
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Related works:
Journal Article: A Small-Sample Estimator for the Sample-Selection Model (2004)
Working Paper: A Small-Sample Estimator for the Sample-Selection Model (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:ucbecw:25047

DOI: 10.22004/ag.econ.25047

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