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Why Bother Asking? The Limited Value of Self-Reported Vote Intention

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  • Rogers, Todd

    (Harvard University and Analyst Institute, Washington, DC)

  • Aida, Masa

    (Greenberg Quinlan Rosner Research, Washington, DC)

Abstract

How accurate are people when predicting whether they will vote? These self-predictions are used by political scientists to proxy for political motivation, and by public opinion researcher to predict election outcomes. Phone surveys from three elections, including one survey experiment, are analyzed to compare respondents' pre-election vote intention with their actual voting behavior using administrative records (N=29,403). Unsurprisingly, many who predict that they will vote actually do not vote. More surprisingly, many who predict that they will not vote actually do vote (29% to 56%). Records of past voting behavior predicts turnout substantially better than self-prediction. Self-prediction inaccuracy is not caused by lack of cognitive salience of past voting, or by inability to recall past voting. Moreover, self-reported recall of turnout in one past election predicts future turnout just as well as self-prediction. We discuss implications for political science research, behavioral prediction, election administration policy, and public opinion.

Suggested Citation

  • Rogers, Todd & Aida, Masa, 2012. "Why Bother Asking? The Limited Value of Self-Reported Vote Intention," Working Paper Series rwp12-001, Harvard University, John F. Kennedy School of Government.
    • Handle: RePEc:ecl:harjfk:rwp12-001
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    Cited by:

    1. Ronald McDonald & Xuxin Mao, 2015. "Forecasting the 2015 General Election with Internet Big Data: An Application of the TRUST Framework," Working Papers 2016_03, Business School - Economics, University of Glasgow.

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