An empirical investigation of parametric and semiparametric estimation methods in sample selection models
ABSTRACT: In this paper we analyze empirically different specifications of a sample selection model. We are interested in how the estimates vary across alternative assumptions concerning the joint conditional distribution of the sample selection equation errors, such us the specification of error di...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2010 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/4569 |
| Acceso en línea: | http://hdl.handle.net/10902/4569 |
| Access Level: | acceso abierto |
| Palabra clave: | Sample selection models Distributional assumptions Semiparametric two-step estimation methods Modelos de selección muestral Hipótesis distribucionales Métodos de estimación en dos etapas semiparamétricos |
| Sumario: | ABSTRACT: In this paper we analyze empirically different specifications of a sample selection model. We are interested in how the estimates vary across alternative assumptions concerning the joint conditional distribution of the sample selection equation errors, such us the specification of error distribution, the functional relationship of the index function and heteroskedasticity. To do this, we estimate a wage equation for the Spanish labor market using two different approaches: Maximum Likelihood and Two-Step Methods. For the latter, three alternative semiparametric procedures are used to compute the sample selection mechanism, and thus three alternative two-step estimators of the parameters of the wage equation are obtained. We compare theses estimates with Heckman's approach. |
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