JSM 2004 - Toronto

Abstract #300120

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Activity Number: 140
Type: Invited
Date/Time: Monday, August 9, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #300120
Title: Mean Square Error Approximation in Small-area Estimation by Use of Nonparametric Bootstrap
Author(s): Danny Pfeffermann*+ and Hagit Glickman*+
Companies: Central Bureau of Statistics Israel and Hebrew University and University of Southampton
Address: Department of Social Statistics, Southampton, SO17 IBJ, United Kingdom 66 Kanfey Nesharim St., Jerusalem, 96190, Israel
Keywords: small-area estimation ; mean square error ; nonparametric bootstrap
Abstract:

The computation of reliable MSE estimators is a complicated process in small-area estimation problems. This is so because of the models in use and the small sample sizes within the areas that requires accounting for the contribution to the error resulting from hyper-parameter estimation. Pfeffermann and Tiller (2001) developed a general parametric bootstrap method for MSE approximation of correct order in the context of state-space models but basically the same procedure can be applied for small-area estimation problems. The use of this procedure requires, however, the specification of the parametric distributions of the model error terms. We study the use of nonparametric bootstrap methods for MSE approximations, which use the empirical residuals. The performance of the proposed method will be illustrated empirically and compared to other methods of MSE estimation in common use.

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