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Small area estimates of labour force participation under a multinomial logit mixed model

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A new methodology is developed for estimating unemployment or employment characteristics in small areas, based on the assumption that the sample totals of unemployed and employed individuals follow a multinomial logit model with random area effects. The method is illustrated with UK labour force data aggregated by sex–age groups. For these data, the accuracy of direct estimates is poor in comparison with estimates that are derived from the multinomial logit model. Furthermore, two different estimators of the mean-squared errors are given: an analytical approximation obtained by Taylor linearization and an estimator based on bootstrapping. A simulation study for comparison of the two estimators shows the good performance of the bootstrap estimator.

Keywords: Bootstrap; Maximum likelihood; Multinomial logit mixed model; Penalized quasi-likelihood; Small area estimation; Unemployment

Document Type: Research Article


Affiliations: 1: Universidad Carlos III de Madrid, Madrid, Spain 2: University of Southampton, UK 3: Universidad de Santiago de Compostela, Spain

Publication date: October 1, 2007

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