Modeling Earnings Measurement Error: A Multiple Imputation Approach

David Brownstone and Robert G. Velletta

University of California Transportation Center, Working Papers from University of California Transportation Center

Abstract: Recent survey validation studies suggest that measurement error in earnings data is pervasive and violates classical measurement error assumptions, and therefore may bias estimation of cross-section and longitudinal earnings models. We model the structure of earnins measurements error using data from the Panel Study of Income Dynamics Validation Study (PSIDVS). We then use Rubin's (1987) multiple imputation techniques to estimate consistent earnings equations under non-classical earnings measurement error in PSID. Our technique is readily generalized, and the empirical results demonstrate the potential importance of correcting for measurement error in earnings and related data, particularly during recessions.

Keywords: Architecture (search for similar items in EconPapers)
Date: 1996-06-01
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Citations: View citations in EconPapers (23)

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Journal Article: Modeling Earnings Measurement Error: A Multiple Imputation Approach (1996)
Working Paper: Modeling Earnings Measurement Error: A Multiple Imputation Approach (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:cdl:uctcwp:qt2t08s22q

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