A Small-Sample Estimator for the Sample-Selection Model
AbstractA 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.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 23 (2004)
Issue (Month): 1 ()
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Other versions of this item:
- Golan, Amos & Moretti, Enrico & Perloff, Jeffrey M., 2001. "A Small-Sample Estimator for the Sample-Selection Model," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt4c82d2nv, Department of Agricultural & Resource Economics, UC Berkeley.
- Golan, Amos & Moretti, Enrico & Perloff, Jeffrey M, 2001. "A small-sample estimator for the sample-selection model," CUDARE Working Paper Series 955, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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