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 #320735
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View Presentation
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Title:
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Outliers in the Annual Survey of Public Employment and Payroll - Small Area Estimation Approach
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Author(s):
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Giang Trinh* and Bac Tran
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Companies:
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U.S. Census Bureau and U.S. Census Bureau
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Keywords:
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robust estimation ;
small area ;
mixture model
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Abstract:
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The presence of outliers in the Small Area Estimation (SAE) raises serious concerns in the design-based part of population parameters prediction due to the violation of model-based assumptions. Various techniques have been introduced to mitigate the effect of outliers in the unit-level and area-level models in the SAE in the literature. In this paper, we introduced the square root transformation into the mixture models from [9, 10] in order to deal with those outliers and estimate the total number of employees in the Annual Survey of Public Employment & Payroll (ASPEP) data. We then compared the research method to the existing methods being used in the estimation of the ASPEP at the Census Bureau. The two Public Employment census data of 2007 and 2012 were used for the evaluation of this research.
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Authors who are presenting talks have a * after their name.