An empirical evaluation of five small area estimators
This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated we...
| Autores: | , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2003 |
| País: | España |
| Recursos: | Universitat Autònoma de Barcelona |
| Repositório: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglês |
| OAI Identifier: | oai:ddd.uab.cat:93736 |
| Acesso em linha: | https://ddd.uab.cat/record/93736 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Regional statistics Small areas Root mean square error Direct Indirect and composite estimators |
| Resumo: | This paper compares five small area estimators. We use Monte Carlo simulation in the context of both artificial and real populations. In addition to the direct and indirect estimators, we consider the optimal composite estimator with population weights, and two composite estimators with estimated weights: one that assumes homogeneity of within area variance and squared bias and one that uses area-specific estimates of variance and squared bias. In the study with real population, we found that among the feasible estimators, the best choice is the one that uses area-specific estimates of variance and squared bias. |
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