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Activity Number: 519
Type: Contributed
Date/Time: Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
Sponsor: Section on Survey Research Methods
Abstract - #305897
Title: Empirical Evaluation of Imputation Methods on Quarterly Census of Employment and Wages Data
Author(s): Marek Kaminski*+ and Vinod Kapani
Companies: Bureau of Labor Statistics and Bureau of Labor Statistics
Address: , , ,
Keywords: employment imputation ; wages imputation ; ratio method ; nearest neighbor method ; simluation of missing data ; influential observations
Abstract:

The U.S. Bureau of Labor Statistics' Quarterly Census of Employment and Wages (QCEW) program currently uses each establishment's year-ago trend in imputing missing employment and wages data without using an established imputation method; therefore, an empirical evaluation of well established methods, namely ratio and nearest-neighbor, is undertaken. This paper presents the analytical evaluation of these methods using current trends in the data. The reported data is simulated for imputing employment and wages on a random sample from QCEW Longitudinal Database (LDB). Both methods utilize exclusion criterion for removing influential observations from the computations. Finally, we offer comparisons of both methods, at stratum and aggregate levels, percentage relative errors.


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