Abstract
Elite support for modifying electoral institutions and policies generally depends on whether a proposed change is expected to improve their party’s electoral prospects. Prior studies suggest that the average citizen evaluates potential reforms in a similar manner, but they fail to directly demonstrate that individuals actually consider their partisan self-interest when forming policy preferences. I address this limitation through two survey experiments that manipulate the specific group for whom reforms make voting more or less difficult. The results provide strong causal evidence that individuals update their attitudes as expected in response to that information. Members of both parties consistently express greater support for changes when framed as advancing their party’s electoral prospects than when characterized as benefiting their opponents. The findings have important implications for the constraints faced by political actors in gaming the electoral system in their favor and for understanding the role of self-interest in shaping policy attitudes.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Replication materials can be found in the Harvard Dataverse at https://doi.org/10.7910/DVN/LAYMOS.
Admittedly, the latter proposal may slow down the legislative process or generate an electorate less sympathetic to the president’s agenda. That the average citizen can rationalize the institutional change in this way, however, is simply assumed.
Other questions that demonstrate this relationship follow a similar design, framing the same outcome in terms of generic (not partisan) risks and losses.
Since 2000, 13 states have required photo ID to vote, 14 have adopted early voting procedures, and 8 have enacted EDR (though in some states these reforms have yet to be implemented or have been overturned by state legislatures or the courts). These policies are currently in place in 9, 37, and 11 states, respectively.
Voter ID laws disproportionately burden groups that tend to be Democratic supporters (e.g., African Americans, Latinos, and young people) and possess identification at lower rates than the general public (Barreto et al. 2007, 2009; Hood and Bullock 2008). Easier ballot access procedures, which are often perceived to benefit Democrats, have been used at higher rates by some party supporters in recent contests and may increase their participation (e.g., Alvarez et al. 2012; Hanmer 2009; Herron and Smith 2014).
This finding is limited to Democrats. Although seemingly consistent with the story of partisan self-interest, their prime describes those affected vaguely and does not mention any characteristics that could suggest they are co-partisans (though the prompt could prime pre-existing knowledge that voter ID laws disproportionately affect Democratic supporters).
MTurk is a web-based platform that permits the recruitment of subjects to perform tasks (in this case, take a survey). The use of this service to conduct social science research has expanded steadily in recent years, with a number of studies documenting the advantages (and limitations) of doing so (e.g., Berinksy et al. 2012; Buhrmester et al. 2011). MTurk samples are not nationally representative, but they are more representative and diverse than the student and convenience samples typically employed in political science experiments (Berinksy et al. 2012). Consistent with this expectation, the experiment’s sample is more Democratic and educated, younger, and consists of fewer females than the general population. Sample characteristics are reported in Supplemental Appendix 1.
A completed survey is defined as the respondent passing both screener questions and making it to the end of the survey (though not necessarily answering every question). Supplemental Appendix 2 reports a CONSORT diagram tracing the number of started surveys to the number of completed surveys. See Supplemental Appendix 3 for the survey instrument.
Senior citizens have become more reliable Republican voters over the past 15 years (see e.g., Tyson and Maniam 2016), though knowledge of this relationship would attenuate the effect of this treatment condition (as subjects aware of the partisan leanings of elderly voters would not update their attitudes as expected). As with minorities, senior citizens are less likely to have acceptable ID than the general public and may be more likely to use early voting methods (Alvarez et al. 2012; Barreto et al. 2007, 2009; Hood and Bullock 2008).
See Supplemental Appendix 4 for balance tests across treatments for each question.
Results are essentially the same when I treat the dependent variable as ordered (see Supplemental Appendix 6).
In the analyses below, these counts decrease to 660 and 238 due to item nonresponse on the reform questions or covariates.
Variable coding is detailed in Supplemental Appendix 7.
Supplemental Appendix 8 presents response marginals for Democrats and Republicans across the three items.
Supplemental Appendix 1 reports sample characteristics.
As in experiment 1, treatments were randomly assigned for each of the election reform questions, with these items spaced throughout the 10 minute survey (and their order randomized) to guard against concerns that a vignette might prime considerations for the subsequently assigned election reform.
YouGov draws a random sample from a comprehensive consumer list, then uses a matching algorithm to identify the panelist who is the closest match (on an extensive set of demographics) to each individual in that random sample. Those panelists are invited to take the survey, with the firm interviewing a larger number of subjects than the desired sample size to ensure coverage based on anticipated response rates. YouGov then reduces (or matches down) that initial pool of responses to generate the final sample designed to look like the randomly drawn consumer list sample. I use the larger dataset generated before the matching down process.
An additional 600 cases were purchased for the module on which these questions appeared to augment the standard 1000 observations provided by YouGov.
Theoretically, moving from the unmatched data to the matched data can induce imbalances across treatments on observable and unobservable subject characteristics, as treatment assignment is not used to match the initial dataset down to its reduced form. This is also a concern when survey weights are used with the matched dataset, as those weights are not estimated with regard to treatment assignment. In Supplemental Appendix 9, I show that I achieve better balance using the unmatched data than the matched data (either unweighted or weighted). Using multinomial logit to predict treatment assignment based on covariates, the chi-squared test for all covariates predicting assignment is significant at p < 0.1 for the voter ID and EDR questions using the matched dataset (both weighted and unweighted). This signals that the covariate distributions across treatments are imbalanced for these two questions.
Item nonresponse reduces these partisan counts to 1028 and 790, respectively (see the corresponding CONSORT diagram in Supplemental Appendix 2).
Across both samples, analyses reveal no consistent pattern that levels of political interest or exposure to the reforms (in the form of living in a state with the reform in question) condition the observed treatment effects.
References
Alvarez, R. M., Hall, T. E., Levin, I., & Stewart, C., III. (2011). Voter opinions about election reform: Do they support making voting more convenient? Election Law Journal,10(2), 73–87.
Alvarez, R. M., Levin, I., & Sinclair, J. A. (2012). Making voting easier: Convenience voting in the 2008 presidential election. Political Research Quarterly,65(2), 248–262.
Anderson, C. J., Blais, A., Bowler, S., Donovan, T., & Listhaug, O. (2005). Losers’ consent. Oxford: Oxford University Press.
Banducci, S. A., & Karp, J. A. (1999). Perceptions of fairness and support for proportional representation. Political Behavior,21(3), 217–238.
Barreto, M. A., Nuño, S. A., & Sanchez, G. R. (2007). Voter ID requirements and the disenfranchisements of Latino, Black and Asian voters. In Paper presented at the American Political Science Association Annual Conference, Chicago, IL.
Barreto, M. A., Nuño, S. A., & Sanchez, G. R. (2009). The disproportionate impact of voter-ID requirements on the electorate—New evidence from Indiana. Political Science and Politics,42(1), 111–116.
Bawn, K., Cohen, M., Karol, D., Masket, S., Noel, H., & Zaller, J. (2012). A theory of political parties: Groups, policy demands and nominations in American politics. Perspectives on Politics, 10(3), 571–597.
Bentele, K. G., & O’Brien, E. E. (2013). Jim Crow 2.0? Why states consider and adopt restrictive voter access policies. Perspectives on Politics,11(4), 1088–1116.
Berinksy, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk. Political Analysis,20(3), 351–368.
Biggers, D. R., & Hanmer, M. J. (2015). Who makes voting convenient? Explaining the adoption of early and no-excuse absentee voting in the American states. State Politics & Policy Quarterly,15(2), 192–210.
Biggers, D. R., & Hanmer, M. J. (2017). Understanding the adoption of voter identification laws in the American states. American Politics Research,45(4), 560–588.
Boix, C. (1999). Setting the rules of the game: The choice of electoral systems in advanced democracies. American Political Science Review,93(3), 609–624.
Bowler, S., & Donovan, T. (2007). Reasoning about institutional change: Winners, losers, and support for electoral reforms. British Journal of Political Science,37(3), 455–476.
Bowler, S., & Donovan, T. (2013). The limits of electoral reform. Oxford: Oxford University Press.
Bowler, S., Donovan, T., & Karp, J. A. (2002). Why might institutions change? Elite support for direct democracy in three nations. Political Research Quarterly,55(4), 731–754.
Bowler, S., Donovan, T., & Karp, J. A. (2006). Why politicians like electoral institutions: Self-interest, values, or ideology? Journal of Politics,68(2), 434–446.
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6(1), 3–5.
Campbell, A., Converse, P. E., Miller, W. E., & Stokes, D. E. (1960). The American voter. New York: Wiley.
Delli Carpini, M. X., & Keeter, S. (1996). What Americans know about politics and why it matters. New Haven, CT: Yale University Press.
Fougere, J., Ansolabehere, S., & Persily, N. (2010). Partisanship, public opinion, and redistricting. Election Law Journal,9(4), 325–347.
Hanmer, M. J. (2009). Discount voting. Cambridge: Cambridge University Press.
Herron, M. C., & Smith, D. A. (2014). Race, party, and the consequences of restricting early voting in Florida in the 2012 General Election. Political Research Quarterly,67(3), 646–665.
Hibbing, J. R., & Alford, J. R. (2004). Accepting authoritative decisions: Humans as wary cooperators. American Journal of Political Science,48(1), 62–76.
Hibbing, J. R., & Theiss-Morse, E. (2002). Stealth democracy. Cambridge: Cambridge University Press.
Hicks, W. D., McKee, S. C., Sellers, M. D., & Smith, D. A. (2015). A principle or a strategy? Voter identification laws and partisan competition in the American states. Political Research Quarterly,68(1), 18–33.
Hood, M. V., III, & Bullock, C. S., III. (2008). Worth a thousand words? An analysis of Georgia’s voter identification statute. American Politics Research,36(4), 555–579.
Karol, D. (2009). Party position change in American politics: Coalition management. Cambridge: Cambridge University Press.
Karp, J. A., & Tolbert, C. J. (2010). Support for nationalizing presidential elections. Presidential Studies Quarterly,40(4), 771–793.
Lau, R. R., & Redlawsk, D. P. (2006). How voters decide. Cambridge: Cambridge University Press.
Lind, E. A., & Tyler, T. R. (1988). The social psychology of procedural justice. New York: Plenum Press.
Lupia, A. (1994). Shortcuts versus encyclopedias: Information and voting behavior in California insurance reform elections. American Political Science Review,88(1), 63–76.
Lupia, A., & McCubbins, M. D. (1998). The democratic dilemma. Cambridge: Cambridge University Press.
Mason, L. (2015). “I disrespectfully agree”: The differential effects of partisan sorting on social and issue polarization. American Journal of Political Science,59(1), 128–145.
McGhee, E. (2014). Measuring partisan bias in single-member district electoral systems. Legislative Studies Quarterly,39(1), 55–85.
Rocha, R. R., & Matsubayashi, T. (2014). The politics of race and voter ID laws in the states: The return of Jim Crow? Political Research Quarterly,67(3), 666–679.
Shepsle, K. A. (2001). A comment on institutional change. Journal of Theoretical Politics,13(3), 321–325.
Smith, D. A., Tolbert, C. J., & Keller, A. M. (2010). Electoral and structural losers and support for a national referendum in the US. Electoral Studies,29(3), 509–520.
Stewart, C., III, Ansolabehere, S., & Persily, N. (2016). Revisiting public opinion on voter identification and voter fraud in an era of increasing partisan polarization. Stanford Law Review,68(6), 1455–1489.
Tolbert, C. J., Smith, D. A., & Green, J. C. (2009). Strategic voting and legislative redistricting reform: District and statewide representational winners and losers. Political Research Quarterly,62(1), 92–109.
Tyler, T. R. (2000). Social justice: Outcome and procedure. International Journal of Psychology,35(2), 117–125.
Tyson, A., & Maniam, S. (2016). Behind Trump’s victory: Divisions by race, gender, education. Pew Research Center. Retrieved April 20, 2018 from http://www.pewresearch.org/fact-tank/2016/11/09/behind-trumps-victory-divisions-by-race-gender-education/.
Wenzel, J. P., Bowler, S., & Lanoue, D. J. (2000). Citizen opinion and constitutional choices: The case of the UK. Political Behavior,22(3), 241–265.
Wilson, D. C., & Brewer, P. R. (2013). The foundations of public opinion on voter ID laws: Political predispositions, racial resentment, and information effects. Public Opinion Quarterly,77(4), 962–984.
Zaller, J. R. (1992). The nature and origins of mass opinion. Cambridge: Cambridge University Press.
Acknowledgements
I thank Greg Huber, Shaun Bowler, Craig Burnett, Tom Carsey, Alan Gerber, the two anonymous reviewers, and the editor for their helpful comments and feedback. A previous version of this paper was presented at the 2014 State Politics and Policy Conference. All errors are my own.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Biggers, D.R. Does Partisan Self-interest Dictate Support for Election Reform? Experimental Evidence on the Willingness of Citizens to Alter the Costs of Voting for Electoral Gain. Polit Behav 41, 1025–1046 (2019). https://doi.org/10.1007/s11109-018-9481-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11109-018-9481-5