120 – Using Linked Survey and Administrative Data to Assess Measurement Error in Household Surveys
Using Matched Household and Administrative Data to Measure Response Bias in Earnings
Christopher R. Bollinger
University of Kentucky
Barry T. Hirsch
Georgia State University
Charles M. Hokayem
U.S. Census Bureau
James P. Ziliak
University of Kentucky
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.