Prediction of a small area mean for an infinite population when the variance components are random
ULB Institutional Repository from ULB -- Universite Libre de Bruxelles
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.
Keywords: Direct and indirect estimation; Empirical best linear unbiased predictor; Infinite population; Small areas (search for similar items in EconPapers)
Note: SCOPUS: ar.j
References: Add references at CitEc
Citations: Track citations by RSS feed
Published in: Romanian Journal of Economic Forecasting (2009) v.11 n° 3,p.22-33
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ulb:ulbeco:2013/184824
Ordering information: This working paper can be ordered from
http://hdl.handle.ne ... lb.ac.be:2013/184824
Access Statistics for this paper
More papers in ULB Institutional Repository from ULB -- Universite Libre de Bruxelles Contact information at EDIRC.
Bibliographic data for series maintained by Benoit Pauwels ().