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Peter Schilling

U.S. Census Bureau



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Redouane Betrouni

U.S. Census Bureau



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Bac Tran

U.S. Census Bureau



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662 – State, County, and Local Government Statistics

Outlier Research in the Annual Survey of Local Government Finances

Sponsor: Government Statistics Section
Keywords: robust estimation, small area, mixture models, outliers

Peter Schilling

U.S. Census Bureau

Redouane Betrouni

U.S. Census Bureau

Bac Tran

U.S. Census Bureau

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 Directorate makes thousands of estimates at the state and local levels based on ALFIN, and uses small area methods due to low estimation cell sizes. The presence of outliers in ALFIN data is a concern due to violation of model-based assumptions. In this paper, we evaluate the use of transformations in the small area mixed models to handle outliers. Our research uses a Monte Carlo simulation experiment with data from census years 2007 and 2012 to conduct the evaluation.

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