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Unresponsive and Unpersuaded: The Unintended Consequences of Voter Persuasion Efforts

  • Bailey, Michael

    (Georgetown University)

  • Hopkins, Daniel J.

    (Georgetown University)

  • Rogers, Todd

    (Harvard University)

Registered author(s):

    Can randomized experiments at the individual level help assess the persuasive effects of campaign tactics? In the contemporary U.S., vote choice is not observable, so one promising research design involves randomizing appeals and then using a survey to measure vote intentions. Here, we analyze one such field experiment conducted during the 2008 presidential election in which 56,000 registered voters were assigned to persuasion in person, by phone, and/or by mail. Persuasive appeals by canvassers had two unintended consequences. First, they reduced responsiveness to the follow-up survey, lowering the response rate sharply among infrequent voters. Second, various statistical methods to address the resulting biases converge on a counterintuitive conclusion: the persuasive canvassing reduced candidate support. Our results allow us to rule out even small effects in the intended direction and illustrate the backlash that attempts at inter-personal persuasion can engender.

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    Paper provided by Harvard University, John F. Kennedy School of Government in its series Working Paper Series with number rwp13-034.

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    Date of creation: Sep 2013
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    Handle: RePEc:ecl:harjfk:rwp13-034
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    1. Kosuke Imai & Gary King & Elizabeth A. Stuart, 2008. "Misunderstandings between experimentalists and observationalists about causal inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 481-502.
    2. Mitali Das & Whitney K. Newey & Francis Vella, 2003. "Nonparametric Estimation of Sample Selection Models," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 33-58, January.
    3. Rogers, Todd & Nickerson, David W., 2013. "Can Inaccurate Beliefs about Incumbents be Changed? And Can Reframing Change Votes?," Working Paper Series rwp13-018, Harvard University, John F. Kennedy School of Government.
    4. Stefano DellaVigna & Matthew Gentzkow, 2009. "Persuasion: Empirical Evidence," NBER Working Papers 15298, National Bureau of Economic Research, Inc.
    5. Siddique, Juned & Belin, Thomas R., 2008. "Using an Approximate Bayesian Bootstrap to multiply impute nonignorable missing data," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 405-415, December.
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