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A Small-Sample Estimator for the Sample-Selection Model

Amos Golan (), Enrico Moretti and Jeffrey Perloff

Econometric Reviews, 2004, vol. 23, issue 1, 71-91

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: Maximum entropy; Sample selection; Monte Carlo experiments (search for similar items in EconPapers)
Date: 2004
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Handle: RePEc:taf:emetrv:v:23:y:2004:i:1:p:71-91