Estimating unemployment in very small areas
Ugarte, Maria Dolores (Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas)
Goicoa, Tomás (Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas)
Militino, Ana F. (Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas)
Sagaseta-López, Marina (Instituto de Estadística de Navarra)

Date:	2009
Abstract:	In the last few years, European countries have shown a deep interest in applying small area techniques to produce reliable estimates at county level. However, the specificity of every European country and the heterogeneity of the available auxiliary information, make the use of a common methodology a very difficult task. In this study, the performance of several design-based, model-assisted, and model-based estimators using different auxiliary information for estimating unemployment at small area level is analyzed. The results are illustrated with data from Navarre, an autonomous region located at the north of Spain and divided into seven small areas. After discussing pros and cons of the different alternatives, a composite estimator is chosen, because of its good trade-off between bias and variance. Several methods for estimating the prediction error of the proposed estimator are also provided.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Finite population ; Prediction theory ; Labour Force Survey
Published in:	SORT : statistics and operations research transactions, Vol. 33, Núm. 1 (January-June 2009) , p. 49-70, ISSN 2013-8830

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