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The Effectiveness of a Neighbor-to-Neighbor Get-Out-the-Vote Program: Evidence from the 2017 Virginia State Elections

Published online by Cambridge University Press:  10 May 2021

Cassandra Handan-Nader*
Affiliation:
Department of Political Science, Stanford University, Stanford, CA, USA
Daniel E. Ho
Affiliation:
Department of Political Science, Stanford University, Stanford, CA, USA Stanford Law School, Stanford, CA, USA, Twitter: @DanHo1
Alison Morantz
Affiliation:
Stanford Law School, Stanford, CA, USA, Twitter: @DanHo1
Tom A. Rutter
Affiliation:
Department of Economics, London School of Economics, London, UK
*
*Corresponding author. Email: slnader@stanford.edu

Abstract

We analyze the results of a neighbor-to-neighbor, grassroots get-out-the-vote (GOTV) drive in Virginia, in which unpaid volunteers were encouraged to contact at least three nearby registered voters who were likely co-partisans yet relatively unlikely to vote in the 2017 state election. To measure the campaign’s effectiveness, we used a pairwise randomization design whereby each volunteer was assigned to one randomly selected member of the most geographically proximate pair of voters. Because some volunteers unexpectedly signed up to participate outside their home districts, we analyze the volunteers who adhered to the original hyper-local program design separately from those who did not. We find that the volunteers in the original program design drove a statistically significant 2.3% increase in turnout, which was concentrated in the first voter pair assigned to each volunteer. We discuss implications for the study and design of future GOTV efforts.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Experimental Research Section of the American Political Science Association

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Footnotes

The design of the randomized controlled trial reported herein was developed by D.E.H. and A.M. as unpaid consultants, working in their personal capacity, and by C.H. and T.A.R. in their consulting capacity, independent of Plus3. For full disclosure, A.M. is the spouse of the founder of Plus3, but the evaluation was structured to be independent. The authors otherwise declare no conflicts of interest related to the research described in this paper. We are grateful to David Nickerson, Donald Green and Aaron Strauss for their helpful comments and suggestions. We are also grateful to Plus3 for their willingness to collaborate. The data, code, and any additional materials required to replicate all analyses in this article are available at the Journal of Experimental Political Science Dataverse within the Harvard Dataverse Network, at: https://doi.org/10.7910/DVN/QPRZD4. All errors remain our own.

References

Athey, S. and Imbens, G. W.. 2017. “The Econometrics of Randomized Experiments,” In Handbook of Economic Field Experiments, eds. Banerjee A. V. and Duflo E., vol. 1 of Handbook of Field Experiments, North-Holland, 73140.CrossRefGoogle Scholar
Bedolla, L. G. and Michelson, M. R.. 2012. Mobilizing Inclusion: Transforming the Electorate through Get-Out-the-Vote Campaigns. New Haven, CT: Yale University Press.CrossRefGoogle Scholar
Benjamini, Y. and Hochberg, Y.. 1995. “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing,” Journal of the Royal Statistical Society. Series B (Methodological) 57(1): 289300.CrossRefGoogle Scholar
Bhatti, Y., Dahlgaard, J. O., Hansen, J. H., and Hansen, K. M.. 2017. “How voter mobilization from short text messages travels within households and families: Evidence from two nationwide field experiments,” Electoral Studies 50: 3949.CrossRefGoogle Scholar
Blevins, C. and Mullen, L. A.. 2015. “Jane, John … Leslie? A historical method for algorithmic gender prediction,” Digital Humanities Quarterly 9.Google Scholar
Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., and Fowler, J. H.. 2012. “A 61-million-person experiment in social influence and political mobilization,” Nature 489: 295298.CrossRefGoogle ScholarPubMed
DeSilver, D. 2014.“Voter turnout always drops off for midterm elections, but why?” Pew Research Center: Fact Tank.Google Scholar
DeSilver, D. 2017. “U.S. trails most developed countries in voter turnout,” Pew Research Center: Fact Tank.Google Scholar
Gerber, A. S. and Green, D. P.. 2017. “Field Experiments on Voter Mobilization: An Overview of a Burgeoning Literature,” In Handbook of Economic Field Experiments, eds. Banerjee, A. V. and Duflo, E., vol. 1 of Handbook of Field Experiments, North-Holland, 395438.CrossRefGoogle Scholar
Gerber, A. S., Green, D. P., and Larimer, C. W.. 2008. “Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment,” American Political Science Review 102: 3348.CrossRefGoogle Scholar
Green, D. P. and Gerber, A. S.. 2015. Get Out the Vote: How to Increase Voter Turnout. Washington, DC: Brookings Institution Press.Google Scholar
Handan-Nader, C., Ho, D. E., Morantz, A., and Rutter, T. A.. 2020. “Replication Data for: The Effectiveness of a Neighbor-to-Neighbor Get-Out-the-Vote Program: Evidence from the 2017 Virginia State Elections,” doi: 10.7910/DVN/QPRZD4.CrossRefGoogle Scholar
Imai, K. and Khanna, K.. 2016. “Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records,” Political Analysis 24: 263272.CrossRefGoogle Scholar
Imbens, G. W. and Rubin, D. B.. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Klofstad, C. A. 2009. “Civic Talk and Civic Participation: The Moderating Effect of Individual Predispositions,” American Politics Research 37: 856878.CrossRefGoogle Scholar
Klofstad, C. A. 2010. “The Lasting Effect of Civic Talk on Civic Participation: Evidence from a Panel Study,” Social Forces 88: 23532375.CrossRefGoogle Scholar
Klofstad, C. A. 2015. “Exposure to Political Discussion in College is Associated With Higher Rates of Political Participation Over Time,” Political Communication 32: 292309.CrossRefGoogle Scholar
Kolmogorov, V. 2009. “Blossom V: a new implementation of a minimum cost perfect matching algorithm,” Mathematical Programming Computation 1: 4367.CrossRefGoogle Scholar
Kuhn, H. W. 1955. “The Hungarian method for the assignment problem,” Naval Research Logistics Quarterly 2: 8397.CrossRefGoogle Scholar
Lake, R. L. D. and Huckfeldt, R.. 1998. “Social Capital, Social Networks, and Political Participation,” Political Psychology 19: 567584.CrossRefGoogle Scholar
McClurg, S. D. 2003. “Social Networks and Political Participation: The Role of Social Interaction in Explaining Political Participation,” Political Research Quarterly 56: 449464.CrossRefGoogle Scholar
Nickerson, D. W. 2008. “Is Voting Contagious? Evidence from Two Field Experiments,” The American Political Science Review 102: 4957.CrossRefGoogle Scholar
Rubin, D. B. 1980. “Discussion of “Randomization Analysis of Experimental Data in the Fisher Randomization Test” by Basu,” Journal of the American Statistical Association 75: 591593.Google Scholar
Schneider, G. S., Vozzella, L., and Nirappil, F.. 2017. “In the final sprint to Election Day, a historic push to turn out voters in Va.” Washington Post.Google Scholar
Schwartzman, P. 2017. “Why a historically conservative county in Virginia is making national Republicans nervous,” Washington Post.Google Scholar
Sinclair, B., McConnell, M., and Michelson, M. R.. 2013. “Local Canvassing: The Efficacy of Grassroots Voter Mobilization,” Political Communication 30: 4257.CrossRefGoogle Scholar
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