Identifying Sources of Survey Error in 2012 Presidential Election Polls: A Dynamic Factor Analytic Approach ∗ Jee-Kwang Park Assistant Professor Nazarbayev University jee.park.wws@gmail.com Adam G. Hughes PhD Candidate University of Virginia ahughes@virginia.edu April 3, 2014 Abstract Although election polls provide important information to voters, they are often biased and unreliable. Existing measures of poll accuracy fail to assess accuracy in the weeks prior to the election and fail to detect systematic manipulation by polling firms. Using data from the 2012 U.S. presidential election, we propose a new econometric method (dynamic factor analysis) for estimating true electoral opinion in the months before an election. Our estimate improves upon simple averages, smoothing estimates, and Bayesian models of true support by distinguishing between the kinds of survey errors in each poll. We provide empirical validation of the total survey error framework; we estimate that non-sampling error accounts for the majority of survey error in 2012’s national presidential polls. By comparing individual poll results with our estimate, we create a measure of accuracy over time and rank eleven major polling firms. We show which polling organizations succeeded throughout the campaign and identify which polling practices were most effective. The results of our analysis suggest that internet polls outperformed telephone polls and that larger sample sizes are correlated with inaccuracy. ∗ Prepared for presentation at the Annual Meeting of the Midwest Political Science Association, April 3-6, 2014, Chicago, Illinois. 1