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Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching

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Author Info

  • Christopher R. Bollinger

    (University of Kentucky)

  • Barry T. Hirsch

    (Trinity University)

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.

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Bibliographic Info

Article provided by University of Chicago Press in its journal Journal of Labor Economics.

Volume (Year): 24 (2006)
Issue (Month): 3 (July)
Pages: 483-520

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Handle: RePEc:ucp:jlabec:v:24:y:2006:i:3:p:483-520

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