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Activity Number:
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620
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
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Sponsor:
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Government Statistics Section
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Abstract #320719
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View Presentation
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Title:
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The Performance of the Empirical Best Linear Unbiased Predictor in Annual Survey of Local Government Finances
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Author(s):
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Peter Schilling* and Redouane Betrouni and Bac Tran
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Companies:
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U.S. Census Bureau and George Mason University and U.S. Census Bureau
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Keywords:
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Annual Survey of State and Local Government Finances ;
EBLUP ;
Calibration
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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 prediction, Calibration, and Horvitz-Thompson methods to estimate these statistics. These three estimators are evaluated through a Monte Carlo simulation experiment using the two census years data 2007 and 2012. The performance of the three estimators is compared through their mean squared errors and relative bias.
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Authors who are presenting talks have a * after their name.
