Multipurpose small area estimation
Multipurpose small area estimation
Sample surveys are generally multivariate, in the sense that they measure more than one
response variable. In theory, each variable can then be assigned an optimal weight for
estimation purposes. However, it is often a distinct practical advantage to have a single
weight that is used with all variables collected in the survey. This paper describes how
such multipurpose sample weights can be constructed when small area estimates of the
survey variables are required. The approach is based on the model-based direct (MBD)
method of small area estimation described in Chambers and Chandra (2006). Empirical
results reported in this paper show that MBD estimators for small areas based on
multipurpose weights perform well across a range of variables that are often of interest in
business surveys. Furthermore, these results show that the proposed approach is robust to
model misspecification and also efficient for the variables ill-suited to standard methods
of small area estimation (e.g. variables that contain a significant proportion of zeros).
Southampton Statistical Sciences Research Institute, University of Southampton
Chandra, Hukum
20235c19-9d73-47d0-abcc-65d9d8cc716c
Chambers, Ray
96331700-f45e-4483-a887-fef921888ff2
9 June 2006
Chandra, Hukum
20235c19-9d73-47d0-abcc-65d9d8cc716c
Chambers, Ray
96331700-f45e-4483-a887-fef921888ff2
Chandra, Hukum and Chambers, Ray
(2006)
Multipurpose small area estimation
(S3RI Methodology Working Papers, M06/06)
Southampton, UK.
Southampton Statistical Sciences Research Institute, University of Southampton
24pp.
Record type:
Monograph
(Working Paper)
Abstract
Sample surveys are generally multivariate, in the sense that they measure more than one
response variable. In theory, each variable can then be assigned an optimal weight for
estimation purposes. However, it is often a distinct practical advantage to have a single
weight that is used with all variables collected in the survey. This paper describes how
such multipurpose sample weights can be constructed when small area estimates of the
survey variables are required. The approach is based on the model-based direct (MBD)
method of small area estimation described in Chambers and Chandra (2006). Empirical
results reported in this paper show that MBD estimators for small areas based on
multipurpose weights perform well across a range of variables that are often of interest in
business surveys. Furthermore, these results show that the proposed approach is robust to
model misspecification and also efficient for the variables ill-suited to standard methods
of small area estimation (e.g. variables that contain a significant proportion of zeros).
Text
s3ri-workingpaper-m06-06.pdf
- Author's Original
More information
Published date: 9 June 2006
Identifiers
Local EPrints ID: 38464
URI: http://eprints.soton.ac.uk/id/eprint/38464
PURE UUID: fbce6f87-9077-40cd-8b3c-34799abfc431
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Date deposited: 09 Jun 2006
Last modified: 20 Feb 2024 03:21
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Contributors
Author:
Hukum Chandra
Author:
Ray Chambers
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