JSM 2005 Online Program

Abstract #304124

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	527
Type:	Contributed
Date/Time:	Thursday, August 11, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Survey Research Methods
Abstract - #304124
Title:	Variance Estimation for Small Domains
Author(s):	Julie B. Gershunskaya*+ and Partha Lahiri
Companies:	Bureau of Labor Statistics and University of Maryland
Address:	2 Massachusetts Ave NE, Washington, DC, 20212,
Keywords:	small area estimation ; Empirical Linear Bayes ; Current Employment Statistics Survey
Abstract:	The Bureau of Labor Statistics (BLS) publishes Current Employment Statistics Program employment estimates for many small domains, such as an industry classification within a state or metropolitan statistical area (MSA). To give users a sense of the quality of these estimates, it is important to publish estimates of their associated standard errors. The BLS uses a balanced repeated replication (BRR) technique to produce variance estimates for national industry classification cells and higher levels of aggregation. However, in our limited simulation study, the BRR variance estimator has been found to be unstable, even at the statewide industrial supersector level. In this paper, we propose an empirical linear Bayes (ELB) method for small areas to combine the design-based variance estimator with a suitable model-based estimator. Our preliminary findings are encouraging and motivate further research in this area.

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