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Why Does the American National Election Study Overestimate Voter Turnout?

Published online by Cambridge University Press:  05 November 2018

Simon Jackman  and
Bradley Spahn
Simon Jackman
Affiliation:
Professor of Political Science and Chief Executive Officer of the United States Studies Centre, University of Sydney, NSW 2006, Australia. Email: [email protected]
Bradley Spahn*
Affiliation:
PhD candidate, Department of Political Science, Stanford University, Stanford, CA, USA. Email: [email protected]
*
*Email: [email protected]
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Abstract

Surveys are a key tool for understanding political behavior, but they are subject to biases that render their estimates about the frequency of socially desirable behaviors inaccurate. For decades the American National Election Study (ANES) has overestimated voter turnout, though the causes of this persistent bias are poorly understood. The face-to-face component of the 2012 ANES produced a turnout estimate at least 13 points higher than the benchmark voting-eligible population turnout rate. We consider three explanations for this overestimate in the survey: nonresponse bias, over-reporting and the possibility that the ANES constitutes an inadvertent mobilization treatment. Analysis of turnout data supplied by voter file vendors allows the three phenomena to be measured for the first time in a single survey. We find that over-reporting is the largest contributor, responsible for six percentage points of the turnout overestimate, while nonresponse bias and mobilization account for an additional 4 and 3 percentage points, respectively.

Keywords

survey designmeasurement errortreatment effects
Type
Articles
Information
Political Analysis , Volume 27 , Issue 2 , April 2019 , pp. 193 - 207
Copyright
Copyright © The Author(s) 2018. Published by Cambridge University Press on behalf of the Society for Political Methodology. 

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Footnotes

Contributing Editor: Jonathan N. Katz

Authors’ note: We thank Matthew DeBell (Senior Research Scientist, ANES Stanford), Patricia Luevano (ANES Michigan) and Kyle Dropp for valuable research assistance and recognize support from the National Science Foundation (SES-0937715). Earlier versions of this paper were presented at the summer meetings of the Society for Political Methodology (University of Georgia, July 2014) and the University of Michigan’s Interdisciplinary Seminar in Quantitative Methods. We thank Bob Erikson, Don Green and two anonymous reviewers for valuable comments. An anonymized replication archive is available in Jackman & Spahn (2018).

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