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

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.

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Year of publication:	2009
Authors:	Stefan, Marius
Published in:	Journal for Economic Forecasting. - Institutul de Prognoza Economica. - Vol. 6.2009, 3, p. 22-33
Publisher:	Institutul de Prognoza Economica
Subject:	small areas \| direct and indirect estimation \| infinite population \| empirical best linear unbiased predictor

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Type of publication:	Article
Language:	English
Classification:	C51 - Model Construction and Estimation ; C63 - Computational Techniques ; C13 - Estimation
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008472214