Analysis of panel data models with grouped observations
We present an iterative estimation procedure to estimate panel data models when some observations are missed or grouped with arbitrary classification intervals. The analysis is carried out from the perspective of panel data models, in which the error terms may follow an arbitrary distribution. We pr...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/50487 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/50487 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.2 panel data grouped or missed data mean-based imputations asymptotic results European Community Household Panel Estadística matemática (Matemáticas) 1209 Estadística |
| Sumario: | We present an iterative estimation procedure to estimate panel data models when some observations are missed or grouped with arbitrary classification intervals. The analysis is carried out from the perspective of panel data models, in which the error terms may follow an arbitrary distribution. We propose an easy-to-implement algorithm to estimate all of the model parameters and the asymptotic stochastic properties of the resulting estimate are investigated as the number of individuals and the number of time periods increase. |
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