The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers
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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Volume (Year): 23 (2005)
Issue (Month): (April)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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