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Vote Self-Prediction Hardly Predicts Who Will Vote, and Is (Misleadingly) Unbiased

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  • Rogers, Todd

    (Harvard University and Analyst Institute, Washington, DC)

  • Aida, Masa

    (Greenberg Quinlan Rosner Research)

Abstract

Public opinion researchers, campaigns, and political scientists often rely on self-predicted vote to measure political engagement, allocate resources, and forecast turnout. Despite its importance, little research has examined the accuracy of self-predicted vote responses. Seven pre-election surveys with post-election vote validation from three elections (N = 29,403) reveal several patterns. First, many self-predicted voters do not actually vote (flake-out). Second, many self-predicted nonvoters do actually vote (flake-in). This is the first robust measurement of flake-in. Third, actual voting is more accurately predicted by past voting (from voter file or recalled) than by self-predicted voting. Finally, self-predicted voters differ from actual voters demographically. Actual voters are more likely to be white (and not black), older, and partisan than actual nonvoters (i.e., participatory bias), but self-predicted voters and self-predicted nonvoters do not differ much. Vote self-prediction is "biased" in that it misleadingly suggests that there is no participatory bias.

Suggested Citation

  • Rogers, Todd & Aida, Masa, 2013. "Vote Self-Prediction Hardly Predicts Who Will Vote, and Is (Misleadingly) Unbiased," Working Paper Series rwp13-010, Harvard University, John F. Kennedy School of Government.
  • Handle: RePEc:ecl:harjfk:rwp13-010
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    File URL: https://research.hks.harvard.edu/publications/workingpapers/citation.aspx?PubId=8971&type=WPN
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    References listed on IDEAS

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    8. Rogers, Todd T, 2011. "Motivating Voter Turnout by Invoking the Self," Scholarly Articles 8052150, Harvard Kennedy School of Government.
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