SMALL AREA PREDICTION UNDER ALTERNATIVE MODEL SPECIFICATIONS

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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

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VOLUME 17 , ISSUE 1 (March 2016) > List of articles

SMALL AREA PREDICTION UNDER ALTERNATIVE MODEL SPECIFICATIONS

Andreea L. Erciulescu / Wayne A. Fuller

Keywords : unit level model, parametric bootstrap, double bootstrap, measurement error, auxiliary information

Citation Information : Statistics in Transition New Series. Volume 17, Issue 1, Pages 9-24, DOI: https://doi.org/10.21307/stattrans-2016-003

License : (CC BY 4.0)

Published Online: 06-July-2017

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ABSTRACT

Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical double bootstrap procedure with the same number of samples.

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