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Activity Number: 57
Type: Topic Contributed
Date/Time: Sunday, August 6, 2006 : 4:00 PM to 5:50 PM
Sponsor: Social Statistics Section
Abstract - #306127
Title: Small-Area Estimation for Business Surveys
Author(s): Hukum Chandra*+
Companies: University of Southampton
Address: Southampton Statistical Sciences Research Institute, Southampton, SO1 71BJ, UK
Keywords: skewed data ; model calibration ; expected value model ; MBD approach
Abstract:

In business surveys, data typically are skewed and the standard approach for SAE based on linear mixed models leads to inefficient estimates. In this paper, we discuss SAE techniques for skewed data that are linear following a suitable transformation. In this context, implementation of the EBLUP approach under transformation to a linear mixed model is complicated. However, this is not the case with the model-based direct (MBD) approach (Chambers and Chandra, 2005), which is based on weighted linear estimators. We extend the MBD approach to skewed data using sample weights derived via model calibration based on a lognormal model with random area effects. Our results show this estimator is both efficient and robust with respect to the distribution of these random effects. An application to real data demonstrates the satisfactory performance of the method.

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