Data/hora: 12/06/2024 14:33:47

Provedor de dados: 	31	
País: 	United States	
Título: 	A Small-Sample Estimator for the Sample-Selection Model	
Autores: 	Golan,   Amos; Moretti,   Enrico; Perloff,   Jeffrey M.	
Data: 	2006-02-06	
Ano: 	2001	
Palavras-chave: 	Maximum entropy; Sample selection; Monte Carlo experiments; Labor and Human Capital; Research Methods/ Statistical Methods.	
Resumo: 	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.	
Tipo: 	Working or Discussion Paper	
Idioma: 	Inglês	
Identificador: 	19794

http://purl.umn.edu/25047	
Editor: 	AgEcon Search	
Relação: 	University of California, Berkeley&gt;Department of Agricultural and Resource Economics&gt;CUDARE Working Papers

CUDARE Working Paper 955	
Formato: 	41

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