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Missing data and small area estimation in the UK Labour Force Survey

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Author Info
Nicholas T. Longford
Abstract

We apply multivariate shrinkage to estimate local area rates of unemployment and economic inactivity by using UK Labour Force Survey data. The method exploits the similarity of the rates of claiming unemployment benefit and the unemployment rates as defined by the International Labour Organisation. This is done without any distributional assumptions, merely relying on the high correlation of the two rates. The estimation is integrated with a multiple-imputation procedure for missing employment status of subjects in the database (item non-response). The hot deck method that is used in the imputations is adapted to reflect the uncertainty in the model for non-response. The method is motivated as a development (improvement) of the current operational procedure in which the imputed value is a non-stochastic function of the data. An extension of the procedure to subjects who are absent from the database (unit non-response) is proposed. Copyright 2004 Royal Statistical Society.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1046/j.1467-985X.2003.00728.x
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Publisher Info
Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society Series A.

Volume (Year): 167 (2004)
Issue (Month): 2 ()
Pages: 341-373
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Handle: RePEc:bla:jorssa:v:167:y:2004:i:2:p:341-373

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  1. Albert Satorra & Eva Ventura & Alex Costa, 2006. "Improving small area estimation by combining surveys: new perspectives in regional statistics," Economics Working Papers 969, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
  2. Nicholas Longford, 2008. "Small-area estimation with spatial similarity," Economics Working Papers 1105, Department of Economics and Business, Universitat Pompeu Fabra, revised Sep 2009. [Downloadable!]
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