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Activity Number: 620
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
Sponsor: Government Statistics Section
Abstract #320735 View Presentation
Title: Outliers in the Annual Survey of Public Employment and Payroll - Small Area Estimation Approach
Author(s): Giang Trinh* and Bac Tran
Companies: U.S. Census Bureau and U.S. Census Bureau
Keywords: robust estimation ; small area ; mixture model
Abstract:

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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