Forecasting elections with non-representative polls

International Journal of Forecasting

Volumn 31, Issue 3, 2015, Pages 980-991

  Wang, Wei ^a   Rothschild, David ^b   Goel, Sharad ^b   Gelman, Andrew ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

Election forecasting; Multilevel regression and poststratification; Non representative polling

Indexed keywords

EID: 84908441366     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijforecast.2014.06.001     Document Type: Article

References (28)

1. Bates, D., Maechler, M., & Bolker, B. (2013). lme4: Linear mixed-effects models using S4 classes. URL: . R package version 0.999999-2. http://CRAN.R-project.org/package=lme4.
2. Blumenthal, M. (2004). Should pollsters weight by party identification? URL: . http://www.pollster.com/faq/should_pollsters_weight_by_par.php.
3. Campbell J.E. The American campaign: US presidential campaigns and the national vote (Volume 6) 2008, Texas A&M University Press.
4. Cavan Reilly A.G., Katz J.N. Post-stratification without population level information on the post-stratifying variable, with application to political polling. Journal of the American Statistical Association 2001, 96:1-11.
5. Chen M.K., Ingersoll J.E., Kaplan E.H. Modeling a presidential prediction market. Management Science 2008, 54:1381-1394.
6. Erikson R.S., Wlezien C. Are political markets really superior to polls as election predictors?. Public Opinion Quarterly 2008, 72:190-215.
7. Gelman A., Hill J. Data analysis using regression and multilevel/hierarchical models 2007, Cambridge University Press.
8. Gelman A., King G. Why are American presidential election campaign polls so variable when votes are so predictable?. British Journal of Political Science 1993, 23:409-451.
9. Ghitza Y., Gelman A. Deep interactions with MRP: Election turnout and voting patterns among small electoral subgroups. American Journal of Political Science 2013, 57:762-776.
10. Gosnell H.F. How accurate were the polls?. Public Opinion Quarterly 1937, 1:97-105.
11. Hillygus D.S., Shields T.G. The persuadable voter: wedge issues in presidential campaigns 2009, Princeton University Press.
12. Holbrook A., Krosnick J.A., Pfent A. The causes and consequences of response rates in surveys by the news media and government contractor survey research firms 2007, 499-528. Wiley.
13. Jackman S. Pooling the polls over an election campaign. Australian Journal of Political Science 2005, 40:499-517.
14. Kaufmann K.M., Petrocik J.R. The changing politics of American men: understanding the sources of the gender gap. American Journal of Political Science 1999, 43:864-887.
15. Keeter S., Kennedy C., Dimock M., Best J., Craighill P. Gauging the impact of growing nonresponse on estimates from a national RDD telephone survey. Public Opinion Quarterly 2006, 70:759-779.
16. Kohut A., Keeter S., Doherty C., Dimock M., Christian L. Assessing the representativeness of public opinion surveys 2012, Pew Research Center for The People & The Press.
17. Lax J.R., Phillips J.H. How should we estimate public opinion in the states?. American Journal of Political Science 2009, 53:107-121.
18. Little R.J. Post-stratification: a modeler's perspective. Journal of the American Statistical Association 1993, 88:1001-1012.
19. Lock K., Gelman A. Bayesian combination of state polls and election forecasts. Political Analysis 2010, 18:337-348.
20. Park D.K., Gelman A., Bafumi J. Bayesian multilevel estimation with poststratification: state-level estimates from national polls. Political Analysis 2004, 12:375-385.
21. Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Development Core Team, (2012). nlme: Linear and nonlinear mixed effects models. R package version 3.1-104.
22. Rothschild D. Forecasting elections comparing prediction markets, polls, and their biases. Public Opinion Quarterly 2009, 73:895-916.
23. Rothschild, D. (2013). Combining forecasts: accurate, relevant, and timely. Working paper.
24. Squire P. Why the 1936 Literary Digest poll failed. Public Opinion Quarterly 1988, 52:125-133.
25. Steeh C., Kirgis N., Cannon B., DeWitt J. Are they really as bad as they seem? Nonresponse rates at the end of the twentieth century. Journal of Official Statistics 2001, 17:227-248.
26. Tourangeau R., Plewes T.J. Nonresponse in social science surveys: a research agenda 2013, The National Academies Press, URL: http://www.nap.edu/openbook.php?record_id=18293.
27. Wolfers J., Zitzewitz E. Prediction markets 2004, National Bureau of Economic Research.
28. Yeager D.S., Krosnick J.A., Chang L., Javitz H.S., Levendusky M.S., Simpser A., Wang R. Comparing the accuracy of RDD telephone surveys and Internet surveys conducted with probability and non-probability samples. Public Opinion Quarterly 2011, 75:709-747.