Correcting for Survey Misreports Using Auxiliary Information with an Application to Estimating Turnout

Caltech Social Science Working Paper No. 1294

29 Pages Posted: 20 Nov 2009

See all articles by Jonathan N. Katz

Jonathan N. Katz

California Institute of Technology - Division of the Humanities and Social Sciences

Gabriel Katz

California Institute of Technology - Division of the Humanities and Social Sciences

Date Written: August 1, 2008

Abstract

Misreporting is a problem that plagues researchers that use survey data. In this paper, we give conditions under which misreporting will lead to incorrect inferences. We then develop a model that corrects for misreporting using some auxiliary information, usually from an earlier or pilot validation study. This correction is implemented via Markov Chain Monte Carlo (MCMC) methods, which allows us to correct for other problems in surveys, such as non-response. This correction will allow researchers to continue to use the non-validated data to make inferences. The model, while fully general, is developed in the context of estimating models of turnout from the American National Elections Studies (ANES) data.

Keywords: misreporting, surveys, MCMC, missing data, discrete choice

JEL Classification: C35, C42

Suggested Citation

Katz, Jonathan N. and Katz, Gabriel, Correcting for Survey Misreports Using Auxiliary Information with an Application to Estimating Turnout (August 1, 2008). Caltech Social Science Working Paper No. 1294, Available at SSRN: https://ssrn.com/abstract=1214733 or http://dx.doi.org/10.2139/ssrn.1214733

Jonathan N. Katz (Contact Author)

California Institute of Technology - Division of the Humanities and Social Sciences ( email )

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HOME PAGE: http://jkatz.caltech.edu

Gabriel Katz

California Institute of Technology - Division of the Humanities and Social Sciences ( email )

1200 East California Blvd.
Pasadena, CA 91125
United States

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