Small area estimation under varying area boundaries using the synthetic estimator
Small area estimation under varying area boundaries using the synthetic estimator
This paper investigates the use of hierarchical models for small area estimation with varying area boundaries, employing the synthetic estimator. The paper shows how area estimates and corresponding MSE estimates can be obtained at a variety of nested and intersecting boundary systems by fitting a model at the lowest possible level. The estimates are obtained by aggregating from the lowest level and are therefore internally consistent. The methodology is illustrated by presenting results of a simulation study that uses hierarchical models built at the lowest area level defined by the UK 1991 census.
hierarchical models, intersecting areas, mse estimation
625-636
Moura, Fernando
6871bafe-2987-439f-923c-f8f4c1eec001
Clarke, Philip
59dff490-5840-4123-bbc3-6df7ae8c9d4a
Pfeffermann, Danny
c7fe07a0-9715-42ce-b90b-1d4f2c2c6ffc
2005
Moura, Fernando
6871bafe-2987-439f-923c-f8f4c1eec001
Clarke, Philip
59dff490-5840-4123-bbc3-6df7ae8c9d4a
Pfeffermann, Danny
c7fe07a0-9715-42ce-b90b-1d4f2c2c6ffc
Moura, Fernando, Clarke, Philip and Pfeffermann, Danny
(2005)
Small area estimation under varying area boundaries using the synthetic estimator.
Statistics in Transition, 7 (3), .
Abstract
This paper investigates the use of hierarchical models for small area estimation with varying area boundaries, employing the synthetic estimator. The paper shows how area estimates and corresponding MSE estimates can be obtained at a variety of nested and intersecting boundary systems by fitting a model at the lowest possible level. The estimates are obtained by aggregating from the lowest level and are therefore internally consistent. The methodology is illustrated by presenting results of a simulation study that uses hierarchical models built at the lowest area level defined by the UK 1991 census.
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Published date: 2005
Keywords:
hierarchical models, intersecting areas, mse estimation
Identifiers
Local EPrints ID: 38505
URI: http://eprints.soton.ac.uk/id/eprint/38505
ISSN: 1234-7655
PURE UUID: 41137acb-ce47-419d-ae71-f82260b14bad
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Date deposited: 19 Jun 2006
Last modified: 11 Dec 2021 15:42
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Contributors
Author:
Fernando Moura
Author:
Philip Clarke
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