An Empirical Evaluation of Five Small Area Estimators

Alex Costa, Albert Satorra and Eva Ventura
Additional contact information
Alex Costa: Idescat
Eva Ventura: UPF

General Economics and Teaching from University Library of Munich, Germany

Abstract: 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)
Pages: 23 pages
Date: 2003-12-15
Note: Type of Document - pdf; prepared on Win2000; to print on Hewlett Packard Laserjet; pages: 23; figures: 7
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://econwpa.ub.uni-muenchen.de/econ-wp/get/papers/0312/0312003.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpgt:0312003

Access Statistics for this paper

More papers in General Economics and Teaching from University Library of Munich, Germany
Bibliographic data for series maintained by EconWPA ( this e-mail address is bad, please contact ).