A Small-Sample Estimator for the Sample-Selection Model

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.


Issue Date:
2001
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/25047
Total Pages:
41
Series Statement:
CUDARE Working Paper 955




 Record created 2017-04-01, last modified 2017-08-24

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