Improving Small Area Estimation by Combining Surveys: New Perspectives in Regional Statistics

descriptionPublicationkeyboard_double_arrow_right Article , Research , Other literature type , Preprint 01 Jan 2006 Spain English Publisher:Elsevier BVJournal:SSRN Electronic Journal (eissn: 1556-5068,

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Authors: Costa, Àlex; Satorra, A.; Ventura, Eva;

doi: 10.2139/ssrn.1002507

handle: 10230/46301 , 20.500.11797/RP2301 , 2099/3785 , 10230/455 , 10230/988

Improving Small Area Estimation by Combining Surveys: New Perspectives in Regional Statistics

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Abstract

A national survey designed for estimating a specific population quantity is sometimes used for estimation of this quantity also for a small area, such as a province. Budget constraints do not allow a greater sample size for the small area, and so other means of improving estimation have to be devised. We investigate such methods and assess them by a Monte Carlo study. We explore how a complementary survey can be exploited in small area estimation. We use the context of the Spanish Labour Force Survey (EPA) and the Barometer in Spain for our study.

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Spain

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Keywords

small area, Composite estimator, Classificació AMS::62 Statistics::62H Multivariate analysis, Inference, Anàlisi multivariable, composite estimator, complementary survey, mean squared error, Regional statistics, Official statistics, Classificació AMS::62 Statistics::62J Linear inference, Composite estimator, complementary survey, mean squared error, official statistics, regional statistics, small area, Classificació AMS::62 Statistics::62J Linear inference, regression, regional statistics, :62 Statistics::62H Multivariate analysis [Classificació AMS], official statistics, Small areas, Small area, Multivariate analysis, Inferència, Statistics, Econometrics and Quantitative Methods, :62 Statistics::62J Linear inference, regression [Classificació AMS], Mean squared error, regression, Complementary survey

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