Download this Paper Open PDF in Browser

Accuracy of Vote Expectation Surveys in Forecasting Elections

Forthcoming, Public Opinion Quarterly

34 Pages Posted: 10 Oct 2012 Last revised: 13 Jan 2014

Andreas Graefe

Ludwig Maximilians University of Munich - Department of Communication Science and Media Research

Date Written: January 13, 2014

Abstract

Simple surveys that ask people who they expect to win are among the most accurate methods for forecasting U.S. presidential elections. The majority of respondents correctly predicted the election winner in 193 (89%) of 217 surveys conducted from 1932 to 2012. Across the last 100 days prior to the seven elections from 1988 to 2012, vote expectation surveys provided more accurate forecasts of election winners and vote shares than four established methods (vote intention polls, prediction markets, econometric models, and expert judgment). Gains in accuracy were particularly large compared to polls. On average, the error of expectation-based vote-share forecasts was 51% lower than the error of polls published the same day. Compared to prediction markets, vote expectation forecasts reduced the error on average by 6%. Vote expectation surveys are inexpensive, easy to conduct, and the results are easy to understand. They provide accurate and stable forecasts and thus make it difficult to frame elections as horse races. Vote expectation surveys should be more strongly utilized in the coverage of election campaigns.

Keywords: combining forecasts, Iowa Electronic Markets, election forecasting, forecast accuracy, econometric models, FiveThirtyEight

JEL Classification: C53, C42

Suggested Citation

Graefe, Andreas, Accuracy of Vote Expectation Surveys in Forecasting Elections (January 13, 2014). Forthcoming, Public Opinion Quarterly. Available at SSRN: https://ssrn.com/abstract=2158733 or http://dx.doi.org/10.2139/ssrn.2158733

Andreas Graefe (Contact Author)

Ludwig Maximilians University of Munich - Department of Communication Science and Media Research ( email )

Geschwister-Scholl-Platz 1
Munich, Bavaria 80539
Germany

HOME PAGE: http://www.andreas-graefe.org

Paper statistics

Downloads
197
Rank
129,161
Abstract Views
1,170