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Candidate Choice Without Party Labels:

New Insights from Conjoint Survey Experiments

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Abstract

In the absence of party labels, voters must use other information to determine whom to support. The institution of nonpartisan elections, therefore, may impact voter choice by increasing the weight that voters place on candidate dimensions other than partisanship. We hypothesize that in nonpartisan elections, voters will exhibit a stronger preference for candidates with greater career and political experience, as well as candidates who can successfully signal partisan or ideological affiliation without directly using labels. To test these hypotheses, we conducted conjoint survey experiments on both nationally representative and convenience samples that vary the presence or absence of partisan information. The primary result of these experiments indicates that when voters cannot rely on party labels, they give greater weight to candidate experience. We find that this process unfolds differently for respondents of different partisan affiliations: Republicans respond to the removal of partisan information by giving greater weight to job experience while Democrats respond by giving greater weight to political experience. Our results lend microfoundational support to the notion that partisan information can crowd out other kinds of candidate information.

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Notes

  1. Another critical feature of nonpartisan elections is that they may decrease the ability of political machines to influence election outcomes (Bridges 1997). We will focus our attention here on the information channel by which nonpartisan rules may affect outcomes, as the reforms occurred throughout the entire US, including municipalities that did not experience machine politics.

  2. YouGov uses sample matching techniques to construct a nationally representative sample from their panel of respondents. For more information about YouGov’s sampling procedures, see Vavreck and Rivers (2008).

  3. For a deep exploration of this dataset, please see Kirkland (2016).

  4. See the online appendix for descriptive statistics by sample.

  5. Indeed, when we analyze our MTurk experiment using their estimator, both our point estimates and standard errors differ only in the third or fourth decimal place. The implementation of the AMCE estimator provided in the cjoint package for R (Strezhnev et al. 2015) cannot as of this writing accommodate survey weights. Because the vote choice dependent variable is binary, some analysts would opt for a binary choice model such as logit or probit, but this is unnecessary in our setting because, as shown by Hainmueller et al. (2014), OLS is a consistent estimator of the AMCE. As it happens, the estimated marginal effects from a logit model correspond almost exactly to the OLS estimates and none of our substantive interpretations depend on this choice.

  6. For female candidates, the level was “Stay-at-Home Mom” while it was “Stay-at-Home Dad” for male candidates.

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Acknowledgements

The authors thank Justin Phillips, Don Green, Robert Shapiro, Winston Lin, Benjamin Goodrich, Shigeo Hirano, Jeffrey Lax, and Yotam Margalit for helpful comments and feedback. This research was supported by a Dissertation Development Grant from the Department of Political Science at Columbia University.

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Authors and Affiliations

  1. Department of Political Science, Columbia University, New York, NY, USA

    Patricia A. Kirkland

  2. Department of Political Science, Yale University, New Haven, CT, USA

    Alexander Coppock

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  1. Patricia A. Kirkland
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Correspondence to Patricia A. Kirkland.

Additional information

Replication Materials: The data, code, and additional materials required to replicate all analyses in this article are available on the Political Behavior Dataverse within the Harvard Dataverse Network.

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Kirkland, P.A., Coppock, A. Candidate Choice Without Party Labels:. Polit Behav 40, 571–591 (2018). https://doi.org/10.1007/s11109-017-9414-8

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