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Modeling Earnings Measurement Error: A Multiple Imputation Approach

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  • Brownstone, David
  • Valletta, Robert G

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. The authors model the structure of earnings measurement error using data from the Panel Study of Income Dynamics Validation Study (PSIDVS). They then use Donald B. Rubin's (1987) multiple imputation techniques to estimate consistent earnings equations under nonclassical earnings measurement error in the PSID. The authors' 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. Copyright 1996 by MIT Press.

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Bibliographic Info

Article provided by MIT Press in its journal Review of Economics & Statistics.

Volume (Year): 78 (1996)
Issue (Month): 4 (November)
Pages: 705-17

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Handle: RePEc:tpr:restat:v:78:y:1996:i:4:p:705-17

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Web page: http://mitpress.mit.edu/journals/

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Web: http://mitpress.mit.edu/journal-home.tcl?issn=00346535

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Cited by:
  1. Jörg-Peter Schräpler, 2002. "Respondent Behavior in Panel Studies: A Case Study for Income-Nonresponse by Means of the German Socio-Economic Panel (GSOEP)," Discussion Papers of DIW Berlin 299, DIW Berlin, German Institute for Economic Research.
  2. repec:ese:iserwp:2003-08 is not listed on IDEAS
  3. Fernández-Kranz, Daniel & Lacuesta, Aitor & Rodríguez-Planas, Núria, 2010. "Chutes and Ladders: Dual Tracks and the Motherhood Dip," IZA Discussion Papers 5403, Institute for the Study of Labor (IZA).
  4. Florence Arestoff, 2000. "Taux de rendement de l’éducation sur le marché du travail d’un pays en développement Un réexamen du modèle de gains de Mincer," Working Papers DT/2000/11, DIAL (Développement, Institutions et Mondialisation).
  5. Gabriele Durrant, 2006. "Missing data methods in official statistics in the United Kingdom: Some recent developments," AStA Advances in Statistical Analysis, Springer, vol. 90(4), pages 577-593, December.
  6. Javier Escobal & Sonia Laszlo, 2005. "Measurement Error in Access to Markets," Development and Comp Systems 0503008, EconWPA.
  7. Brownstone, David, 1997. "Multiple Imputation Methodology for Missing Data, Non-Random Response, and Panel Attrition," University of California Transportation Center, Working Papers qt2zd6w6hh, University of California Transportation Center.
  8. Keisuke Hirano & Guido W. Imbens & Geert Ridder & Donald B. Rubin, 1998. "Combining Panel Data Sets with Attrition and Refreshment Samples," Tinbergen Institute Discussion Papers 98-033/4, Tinbergen Institute.
  9. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
  10. Emre Ekinci, 2009. "Dealing with Attrition When Refreshment Samples are Available: An Application to the Turkish Household Labor Force Survey," 2009 Meeting Papers 353, Society for Economic Dynamics.
  11. Arestoff, Florence, 2001. "Taux de rendement de l’éducation sur le marché du travail d’un pays en développement. Une analyse micro-économétrique," Open Access publications from Université Paris-Dauphine urn:hdl:123456789/4924, Université Paris-Dauphine.

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