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 o(1/ m) and an estimator whose bias is of order o(1/ m) 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
Institutions:	Solvay Brussels School of Economics and Management, Université Libre de Bruxelles
Subject:	Direct and indirect estimation \| Empirical best linear unbiased predictor \| Infinite population \| Small areas

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Series:	ULB Institutional Repository.
Type of publication:	Book / Working Paper
Notes:	SCOPUS: ar.j Published in: Romanian Journal of Economic Forecasting (2009) v.11 n° 3,p.22-33
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011099510