JSM 2004 - Toronto

Abstract #301144

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Activity Number: 215
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Survey Research Methods
Abstract - #301144
Title: Small-area Estimation Errors in SAIPE Using GLMM vs. FH Models
Author(s): Eric V. Slud*+
Companies: U.S. Census Bureau
Address: 4700 Silver Hill Road, Washintgon, DC, 20233-9100,
Keywords: small-area estimation ; SAIPE ; Fay-Herriot model ; GLMM models ; loss functions
Abstract:

The Small Area Income and Poverty Estimation (SAIPE) program produces county-level estimates of child-poverty rates and counts of poor school-aged children, using census and administrative-records (CPS, IRS, food stamp) data. The author has for several years studied the properties--and discrepancies from both the "internal" standard of CPS direct estimates and the "external" standard of census-based estimates--of small-area estimators in this setting, based upon competing versions of the aggregate-level Fay-Herriot (FH) model used in SAIPE production or based upon Generalized Linear Mixed Model (GLMM) unit-level models. Recently, Slud (2003) has compared and assessed the fit of various FH models tracked over several years of SAIPE data since the program's original model choices and evaluations were made, and has found that augmentations to the SAIPE production model are needed for the 2000 data. In this paper, an overall summary and assessment is made of the relative strengths and weaknesses of the FH versus GLMM county child poverty rate estimators.

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