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The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers

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  • Abowd, John M.
  • Vilhuber, Lars

Abstract

In this paper, we describe the sensitivity of small-cell flow statistics to coding errors in the identity of the underlying entities. Specifically, we present results based on a comparison of the U.S. Census Bureau’s Quarterly Workforce Indicators (QWI) before and after correcting for such errors in SSN-based identifiers in the underlying individual wage records. The correction used involves a novel application of existing statistical matching techniques. It is found that even a very conservative correction procedure has a sizable impact on the statistics. The average bias ranges from 0.25 percent up to 15 percent for flow statistics, and up to 5 percent for payroll aggregates.
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  • Abowd, John M. & Vilhuber, Lars, 2005. "The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 133-152, April.
    • Handle: RePEc:bes:jnlbes:v:23:y:2005:p:133-152
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