The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
An Evaluation of the 2016 Election Polls in the United States
Abstract
The 2016 presidential election was a jarring event for polling in the United States. Preelection polls fueled high-profile predictions that Hillary Clinton’s likelihood of winning the presidency was about 90 percent, with estimates ranging from 71 to over 99 percent. When Donald Trump was declared the winner of the presidency, there was a widespread perception that the polls failed. But did the polls fail? And if so, why? Those are among the central questions addressed by an American Association for Public Opinion Research (AAPOR) ad hoc committee. This paper presents the committee’s analysis of the performance of preelection polls in 2016, how that performance compares to polling in prior elections, and the extent to which performance varied by poll design. In addition, the committee examined several theories as to why many polls, particularly in the Upper Midwest, underestimated support for Trump. The explanations for which the most evidence exists are a late swing in vote preference toward Trump and a pervasive failure to adjust for overrepresentation of college graduates (who favored Clinton). In addition, there is clear evidence that voter turnout changed from 2012 to 2016 in ways that favored Trump, though there is only mixed evidence that misspecified likely voter models were a major cause of the systematic polling error. Finally, there is little evidence that socially desirable (Shy Trump) responding was an important contributor to poll error.
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Citations
Cites
The spiral of silence a theory of public opinion
Noelle-Neumann, E. (1974) · Journal of Communication · doi:10.1111/j.1460-2466.1974.tb00367.x · Cited by 2,352
The Impact of Nonresponse Rates on Nonresponse Bias: A Meta-Analysis
Groves, R. M., & Peytcheva, E. (2008) · Public Opinion Quarterly · doi:10.1093/poq/nfn011 · Cited by 1,441
National Surveys Via Rdd Telephone Interviewing Versus the Internet
Chang, L., & Krosnick, J. A. (2009) · Public Opinion Quarterly · doi:10.1093/poq/nfp075 · Cited by 956
Gauging the Impact of Growing Nonresponse on Estimates from a National RDD Telephone Survey
Keeter, S., Kennedy, C., Dimock, M. A., Best, J., & Craighill, P. (2006) · Public Opinion Quarterly · doi:10.1093/poq/nfl035 · Cited by 902
Self-citationComputing Response Metrics for Online Panels
Callegaro, M., & DiSogra, C. (2008) · Public Opinion Quarterly · doi:10.1093/poq/nfn065 · Cited by 516
Voter Turnout and the National Election Studies
Burden, B. C. (2000) · Political Analysis · doi:10.1093/oxfordjournals.pan.a029823 · Cited by 235
White Reactions to Black Candidates: When Does Race Matter?
Citrin, J., GREEN, D. P., & Sears, D. O. (1990) · Public Opinion Quarterly · doi:10.1086/269185 · Cited by 222
Link, M., Battaglia, M. P., Frankel, M. R., Osborn, L., & Mokdad, A. H. (2008) · Public Opinion Quarterly · doi:10.1093/poq/nfn003 · Cited by 207
Race-of-Interviewer Effects in a Preelection Poll: Virginia 1989
Finkel, S. E., Guterbock, T. M., & Borg, M. J. (1991) · Public Opinion Quarterly · doi:10.1086/269264 · Cited by 161
The Timeline of Presidential Elections
Erikson, R. S., & Wlezien, C. B. (2012) · University of Chicago Press eBooks · doi:10.7208/chicago/9780226922164.001.0001 · Cited by 156
Self-citation
Research works printed but not linked: 26
- American Association for Public Opinion Research (AAPOR), 2016, Standard Definitions Final Dispositions of Case Codes and Outcome Rates for Surveys
- Barnes, 2016, “Reality Check: Should We Give Up on Election Polling?”
- Blake, 2016, “How America Decided, at the Last Moment, to Elect Donald Trump.”
- Byers, 2016, “How Politicians, Pollsters and Media Missed Trump’s Groundswell.”
- Cassino, 2016, “How Today’s Political Polling Works.”
- Cillizza, 2016, “Winners and Losers from the 2016 Election.”
- Cohn, 2014, “Two Polls That Highlight the Challenges of Polling.”
- Cohn, 2016, “There Are More White Voters Than People Think. That’s Good News for Trump.”
- Collins, 2016, “Poll: Clinton, Trump Most Unfavorable Candidates Ever.”
- Crespi, 1988, Sources of Accuracy and Error in Pre-Election Polling
- Easley, 2016, “Pollsters Suffer Huge Embarrassment.”
- Enten, 2012, “The Other 2012 Election Contest: Which Pollster and Polling Method Will Win?”
- Enten, 2016, “Shy’ Voters Probably Aren’t Why the Polls Missed Trump.”
- File, 2017, “Voting in America: A Look at the 2016 Presidential Election.”
- Jackson, 2016, “Here’s Why HuffPost Is Dropping Polls That Rely Only on Landlines.”
- Jacobs, 2016, “Trump Says He Expected to Lose Election Because of Poll Results.”
- Katz, 2016, “Who Will Be President?”
- Merkle, 2002, Nonresponse in Exit Polls: A Comprehensive Analysis, 243
- Pew Research Center, 2012, “Assessing the Representativeness of Public Opinion Surveys.”
- Shepard, 2016, “How Could the Polling Be So Wrong?”
- Silver, 2016, “Pollsters Probably Didn’t Talk to Enough White Voters Without College Degrees.”
- Silver, 2017, “Why Early Voting Was Overhyped.”
- Silver, 2017, “The Real Story of 2016: What Reporters—and Lots of Data Geeks, Too—Missed about the Election, and What They’re Still Getting Wrong.”
- Smith, Andrew . 2016. “UNH 2016 Election Polls.” Paper presented at the New England AAPOR Chapter Election Postmortem.
- Trende, 2016, “It Wasn’t the Polls That Missed, It Was the Pundits.”
- Yourish, 2016, “Clinton and Trump Have Terrible Approval Ratings. Does It Matter?”
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Metadata
- Authors
- Kennedy, C., Blumenthal, M., Clement, S., Clinton, J. D., Durand, C., Franklin, C., McGeeney, K., Miringoff, L., Olson, K., Rivers, D., Saad, L., Witt, G. E., & Wlezien, C.
- Affiliations
- Pew Research Center (US)
- Marquette University (US)
- Corresponding author
- Kennedy, Courtney
- ORCID
- Venue
- Public Opinion Quarterly
- Publisher
- Oxford University Press (OUP)
- Published
- 2018
- Volume
- 82
- Issue
- 1
- Pages
- 1-33
- ISSN
- 0033-362X (ISSN-L)
- 1537-5331
- OpenAlex
- W2793769061
- Cited by
- 200
- References
- 26
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 25 · 2023: 28 · 2022: 26 · 2021: 27 · 2020: 36 · 2019: 12 · 2018: 16
- FWCI
- 89.09
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Public Opinion Quarterly (publishedVersion)
- Lincoln (University of Nebraska) (submittedVersion)
- Topics
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
- Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
- Keywords
- 2016 US presidential election, election polls, polling accuracy, Hillary Clinton, Donald Trump, Upper Midwest, voter turnout, social desirability bias, polling error
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