Abstract Details
Activity Number:
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120
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 4, 2014 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #311363
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View Presentation
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Title:
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Using Matched Household and Administrative Data to Measure Response Bias in Earnings
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Author(s):
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Barry Hirsch*+ and Christopher Bollinger and Charles Hokayem and James Ziliak
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Companies:
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Georgia State University and University of Kentucky and U.S. Census Bureau and University of Kentucky
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Keywords:
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non-response bias ;
measurement error ;
earnings ;
CPS ASEC ;
hot deck imputation
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Abstract:
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Earnings non-response in household surveys is widespread, yet there is limited evidence on how response bias affects measured earnings. This paper examines the patterns and consequences of non-response using internal Current Population Survey worker records matched to administrative data on earnings for 2005-2010. Non-response across the earnings distribution, conditional on covariates, is found to be U-shaped for men and women, with left-tail "strugglers" and right-tail "stars" least likely to report earnings. Household surveys report too few low earners and too few very high earners. Non-response is ignorable over much of the distribution, but there exists trouble in the tails.
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