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Activity Number:
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662
- State, County, and Local Government Statistics
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Type:
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Contributed
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Date/Time:
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Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
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Sponsor:
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Government Statistics Section
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Abstract #324422
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Title:
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A Hierarchical Bayesian Approach to Estimation for the Annual Survey of Local Government Finances
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Author(s):
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Noah Bassel* and Bac Tran
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Companies:
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US Census Bureau and US Census Bureau
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Keywords:
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: Annual Survey of State and Local Government Finances ;
EBLUP ;
Hierarchical Bayes ;
Small Area Estimation
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Abstract:
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The Annual Survey of Local Government Finances (ALFIN) is conducted by the U.S. Census Bureau and provides statistics about the financial activities of state and local governments across the nation. The Economic Statistical Methods Division currently uses a combination of Empirical Best Linear Unbiased Predictor (EBLUP), and Horvitz-Thompson (HT) methods to estimate these statistics. In this paper we explore a linear mixed model Hierarchical Bayes estimator. All three estimators are then evaluated through a Monte Carlo simulation experiment using data from the 2007 and 2012 Census of Governments. The performance of the three estimators is compared through their mean squared errors and relative bias, as well as other diagnostics.
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Authors who are presenting talks have a * after their name.
