Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching
Christopher Bollinger and
Barry Hirsch ()
Journal of Labor Economics, 2006, vol. 24, issue 3, 483-520
Abstract:
This article examines match bias arising from earnings imputation. Wage equation parameters are estimated from mixed samples of workers reporting and not reporting earnings, the latter assigned earnings of donors. Regressions including attributes not used as imputation match criteria (e.g., union) are severely biased. Match bias also arises with attributes used as match criteria but matched imperfectly. Imperfect matching on schooling (age) flattens earnings profiles within education (age) groups and creates jumps across groups. Assuming conditional missing at random, a general analytic expression correcting match bias is derived and compared to alternatives. Reweighting a respondent-only sample proves an attractive approach.
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (98)
Downloads: (external link)
http://dx.doi.org/10.1086/504276 main text (application/pdf)
Access to the online full text or PDF requires a subscription.
Related works:
Working Paper: Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching (2005) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ucp:jlabec:v:24:y:2006:i:3:p:483-520
Access Statistics for this article
More articles in Journal of Labor Economics from University of Chicago Press
Bibliographic data for series maintained by Journals Division ().