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Author ORCID Identifier
Open Access Dissertation
Doctor of Philosophy (PhD)
Year Degree Awarded
Month Degree Awarded
Brian F. Schaffner
Tatishe M. Nteta
Seth K. Goldman
Stephen D. Ansolabehere
American Politics | Models and Methods | Social Psychology
American politics scholarship has in great measure dedicated itself to the study of
democratic participation in elections. Texts that are considered the cannon on electoral
participation have extended our knowledge of the factors that increase/decrease turnout,
however, this work has relied on self-reports of turnout in surveys. The use of selfreported
turnout is problematic because a non-trivial proportion of survey respondents
say they went out to vote when they actually did not, meaning they overreport turnout.
Overreports of voter turnout are false reports of participation in elections by nonvoters
when responding to political surveys.
Appropriately, scholars of voting behavior have dedicated a great deal of research
to the study of this phenomenon by conducting vote validation studies. This work has
engendered important questions about the study of overreporting and how it affects the
study of voter turnout. There are four major questions in the literature which I address
throughout the dissertation: 1) How accurate is vote validation?, 2) Do overreports bias
statistical models of turnout?, 3) What is the correct way to measure and model
overreporting?, and 4) What is the cognitive mechanism through which overreports
The first chapter describes the phenomenon of voter turnout overreports in
surveys and how they affect estimations of turnout in political polling, and derives a
social desirability theory of overreporting from the vote validation literature. Chapter 2
presents analysis of the persistence and prevalence of overreporting in the Cooperative
Congressional Election Study of 2008 2010, 2012, and 2014. Also, a comprehensive look
at the demographic, social and political characteristics of voters, nonvoters and overreporters
using data from the 2014 and 2012 CCES. Chapter 3 constitutes the first
original contribution to the study of overreporting by proposing a new way of modeling
the likelihood of overreporting through multinomial logistic regression analysis. Most
Importantly, in Chapter 4, I test the social desirability theory of overreporting, namely
analysis of response latency data from the 2014 and 2012 CCES studies. Finally, the
conclusion of this dissertation summarizes the main findings of previous chapters and
presents analysis of the bias induced by overreports in statistical models of turnout.
Cuevas-Molina, Ivelisse, "Voter Turnout Overreports: Measurement, Modeling and Deception" (2017). Doctoral Dissertations. 958.