Hostname: page-component-7b7567c8c-kwt9d Total loading time: 0 Render date: 2026-11-15T08:42:01.873Z Has data issue: false hasContentIssue false
  • English
  • Français

Closeness Counts: Increasing Precision and Reducing Errors in Mass Election Predictions

Published online by Cambridge University Press:  04 January 2017

Kai Quek and
Michael W. Sances
Kai Quek
Affiliation:
Department of Politics and Public Administration, University of Hong Kong, e-mail: quek@hku.hk
Michael W. Sances*
Affiliation:
Department of Political Science, University of Memphis
*
e-mail: msances@memphis.edu (corresponding author)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

Mass election predictions are increasingly used by election forecasters and public opinion scholars. While they are potentially powerful tools for answering a variety of social science questions, existing measures are limited in that they ask about victors rather than voteshares. We show that asking survey respondents to predict voteshares is a viable and superior alternative to asking them to predict winners. After showing respondents can make sensible quantitative predictions, we demonstrate how traditional qualitative forecasts lead to mistaken inferences. In particular, qualitative predictions vastly overstate the degree of partisan bias in election forecasts, and lead to wrong conclusions regarding how political knowledge exacerbates this bias. We also show how election predictions can aid in the use of elections as natural experiments, using the effect of the 2012 election on partisan economic perceptions as an example. Our results have implications for multiple constituencies, from methodologists and pollsters to political scientists and interdisciplinary scholars of collective intelligence.

Information

Type
Articles
Information
Political Analysis , Volume 23 , Issue 4 , Autumn 2015, pp. 518 - 533
Copyright
Copyright © The Author 2015. Published by Oxford University Press on behalf of the Society for Political Methodology 

Footnotes

Authors' note: We thank Eitan Hersh, Krista Loose, Michele Margolis, and Jim Snyder for comments. We also thank the MIT Political Experiments Research Lab for support. Sances thanks the Center for the Study of Democratic Institutions at Vanderbilt University for institutional support. This research received IRB approval from the Committee on the Use of Humans as Experimental Subjects at the Massachusetts Institute of Technology (protocol #1203004950). Replication data for this article may be found in Sances and Quek (2015). Supplementary Materials for this article are available on the Political Analysis Web site.

References

Ansolabehere, Stephen, Meredith, Marc, and Snowberg, Erik. 2013. Asking about numbers: Why and how. Political Analysis 21:48–69.CrossRefGoogle Scholar
Barber, Michael J., Mann, Christopher B., Quin Monson, J., and Patterson, Kelly D. 2014. Online polls and registration-based sampling: A new method for pre-election polling. Political Analysis 22:321–35.CrossRefGoogle Scholar
Bartels, Larry M. 2002. Beyond the running tally: Partisan bias in political perceptions. Political Behavior 24:117–50.Google Scholar
Bullock, John G., Gerber, Alan S., Hill, Seth J., and Huber, Gregory A. 2015. Partisan bias in factual beliefs about politics. Quarterly Journal of Political Science, forthcoming.Google Scholar
Campbell, Angus, Converse, Philip E., Miller, Warren E., and Stokes, Donald E. 1960. The American Voter. New York: John Wiley and Sons.Google Scholar
Campbell, James E. 2012. Forecasting the 2012 American national elections. PS: Political Science & Politics 45:610–3.Google Scholar
Caughey, Devin, and Sekhon, Jasjeet S. 2011. Elections and the regression discontinuity design: Lessons from close US House races, 1942–2008. Political Analysis 19:385–408.Google Scholar
Daniller, Andrew M., Silver, Laura, and Coren Moehler, Devra. 2013. Calling it wrong: Partisan media effects on electoral expectations and institutional trust. Paper presented at the 2013 American Political Science Association Annual Meeting. http://ssrn.com/abstract=2301154 (accessed September 17, 2015).Google Scholar
Eggers, Andrew C., Fowler, Anthony, Hainmueller, Jens, Hall, Andrew B., and Snyder, James M. 2015. On the validity of the regression discontinuity design for estimating electoral effects: New evidence from over 40,000 close races. American Journal of Political Science 59:259–74.Google Scholar
Erikson, Robert S., and Wlezien, Christopher. 2008. Are political markets really superior to polls as election predictors? Public Opinion Quarterly 72:190–215.CrossRefGoogle Scholar
Erikson, Robert S., and Wlezien, Christopher. 2012. Markets vs. polls as election predictors: An historical assessment. Electoral Studies 31:532–9.Google Scholar
Finkel, Steven E. 1985. Reciprocal effects of participation and political efficacy: A panel analysis. American Journal of Political Science 29:891–913.Google Scholar
Gerber, Alan S., and Huber, Gregory A. 2009. Partisanship and economic behavior: Do partisan differences in economic forecasts predict real economic behavior? American Political Science Review 103:407–26.CrossRefGoogle Scholar
Gerber, Alan S., and Huber, Gregory A. 2010. Partisanship, political control, and economic assessments. American Journal of Political Science 54:153–73.Google Scholar
Gilens, Martin. 2001. Political ignorance and collective policy preferences. American Political Science Review 95:379–95.Google Scholar
Ginsberg, Benjamin, and Weissberg, Robert. 1978. Elections and the mobilization of popular support. American Journal of Political Science 22:31–55.Google Scholar
Graefe, Andreas. 2014. Accuracy of vote expectation surveys in forecasting elections. Public Opinion Quarterly 78:204–32.Google Scholar
Herron, Michael C. 2000. Estimating the economic impact of political party competition in the 1992 British election. American Journal of Political Science 44:326–37.Google Scholar
Kam, Cindy D. 2012. Risk attitudes and political participation. American Journal of Political Science 56:817–36.Google Scholar
Keele, Luke. 2005. The authorities really do matter: Party control and trust in government. Journal of Politics 67:873–86.Google Scholar
Keith, Bruce E., Magleby, David B., Nelson, Candice J., Orr, Elizabeth, and Westlye, Mark C. 1992. The myth of the independent voter. Berkeley, CA: University of California Press.CrossRefGoogle Scholar
Knight, Brian. 2006. Are policy platforms capitalized into equity prices? Evidence from the Bush/Gore 2000 presidential election. Journal of Public Economics 90:751–73.Google Scholar
Krosnick, Jon A. 1991. Response strategies for coping with the cognitive demands of attitude measures in surveys. Applied Cognitive Psychology 5:213–36.Google Scholar
Lewis-Beck, Michael S., and Rice, Tom W. 1992. Forecasting elections. Washington, D.C.: CQ Press.Google Scholar
Lewis-Beck, Michael S., and Tien, Charles. 1999. Voters as forecasters: A micromodel of election prediction. International Journal of Forecasting 15:175–84.Google Scholar
Malhotra, Neil, Margalit, Yotam, and Mo, Cecilia. 2013. Economic explanations for opposition to immigration: Distinguishing between prevalence and conditional impact. American Journal of Political Science 57:391–410.CrossRefGoogle Scholar
Margolis, Michele M. 2015. Don't lose control: How partisanship and the political landscape shape religious behaviors. Working paper, Department of Political Science, University of Pennsylvania.Google Scholar
Matsubayashi, Tetsuya. 2013. Do politicians shape public opinion? British Journal of Political Science 43:451–78.Google Scholar
Miller, Michael K., Wang, Guanchun, Kulkarni, Sanjeev R., Vincent Poor, H., and Osherson, Daniel N. 2012. Citizen forecasts of the 2008 US presidential election. Politics & Policy 40:1019–52.Google Scholar
Moehler, Devra C. 2009. Critical citizens and submissive subjects: Election losers and winners in Africa. British Journal of Political Science 39:345–66.Google Scholar
Murr, Andreas Erwin. 2011. Wisdom of crowds? A decentralised election forecasting model that uses citizens’ local expectations. Electoral Studies 30:771–83.CrossRefGoogle Scholar
Page, Benjamin I., and Shapiro, Robert Y. 1992. The rational public: Fifty years of trends in Americans’ policy preferences. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Prior, Markus. 2007. Is partisan bias in perception of objective conditions real? Paper presented at the Annual Conference of the Midwest Political Science Association in Chicago, Illinois.Google Scholar
Rothschild, David M. 2009. Forecasting elections comparing prediction markets, polls, and their biases. Public Opinion Quarterly 73:895–916.Google Scholar
Rothschild, David M., and Wolfers, Justin. 2013. Forecasting elections: Voter intentions versus expectations. Working Paper, Department of Economics, University of Michigan. http://users.nber.org/∼jwolfers/Papers/VoterExpectations.pdf (accessed September 17, 2015).Google Scholar
Sances, Michael, and Quek, Kai. 2015. Replication data for: Closeness counts: Increasing precision and reducing errors in mass election predictions, V1 [Version]. http://dx.doi.org/10.7910/DVN/INGQYA (accessed July 20, 2015).CrossRefGoogle Scholar
Sances, Michael, and Stewart, Charles. 2015. Partisanship and confidence in the vote count: Evidence from U.S. National Elections since 2000. Working paper, Department of Political Science, Vanderbilt University.Google Scholar
Snowberg, Erik, Wolfers, Justin, and Zitzewitz, Eric. 2007a. Partisan impacts on the economy: Evidence from prediction markets and close elections. Quarterly Journal of Economics 122:807–29.Google Scholar
Snowberg, Erik, Wolfers, Justin, and Zitzewitz, Eric. 2007b. Party influence in Congress and the economy. Quarterly Journal of Political Science 2:277–86.Google Scholar
Taber, Charles S., and Lodge, Milton. 2006. Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science 50:755–69.Google Scholar
Thibodeau, Paul, Peebles, Matthew M., Grodner, Daniel J., and Durgin, Frank H. 2015. The wished-for always wins until the winner was inevitable all along: Motivated reasoning and belief bias regulate emotion during elections. Political Psychology, 36:431–48.Google Scholar
Wolfers, Justin, and Zitzewitz, Eric. 2004. Prediction markets. Journal of Economic Perspectives 18:107–26.Google Scholar
Supplementary material: PDF

Quek and Sances supplementary material

Appendix

Download Quek and Sances supplementary material(PDF)
PDF 176.8 KB