Prediction of a Small Area Mean for an Infinite Population when the Variance Components Are Random

Marius Stefan ()
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Marius Stefan: Polytechnic University of Bucharest, Free University of Brussels

Journal for Economic Forecasting, 2009, vol. 6, issue 3, 22-33

Abstract: In this paper, we propose a new model with random variance components for estimating small area characteristics. Under the proposed model, we derive the empirical best linear unbiased estimator, an approximation to terms of order and an estimator whose bias is of order for its mean squared error, where m is the number of small areas in the population.

Keywords: small areas; direct and indirect estimation; infinite population; empirical best linear unbiased predictor (search for similar items in EconPapers)
JEL-codes: C13 C51 C63 (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:rjr:romjef:v:6:y:2009:i:3:p:22-33

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