An Empirical Evaluation of Five Small Area Estimators
Albert Satorra and
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Alex Costa: Idescat
Eva Ventura: UPF
General Economics and Teaching from University Library of Munich, Germany
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.
Keywords: Regional statistics; small areas; root mean square error; direct; indirect and composite estimators. (search for similar items in EconPapers)
JEL-codes: C15 C51 (search for similar items in EconPapers)
Note: Type of Document - pdf; prepared on Win2000; to print on Hewlett Packard Laserjet; pages: 23; figures: 7
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpgt:0312003
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