Thin-Slice Forecasts of Gubernatorial Elections
We showed 10-second, silent video clips of unfamiliar gubernatorial debates to a group of experimental participants and asked them to predict the election outcomes. The participants' predictions explain more than 20 percent of the variation in the actual two-party vote share across the 58 elections in our study, and their importance survives a range of controls, including state fixed effects. In a horse race of alternative forecasting models, participants' visual forecasts significantly outperform economic variables in predicting vote shares, and are comparable in predictive power to a measure of incumbency status. Adding policy information to the video clips by turning on the sound tends, if anything, to worsen participants' accuracy, suggesting that naïveté may be an asset in some forecasting tasks.
We are deeply indebted to the Taubman Center for State and Local Government and to KNP Communications for financial support. We thank Alberto Alesina, Nalini Ambady, Chris Chabris, James Choi, Stefano DellaVigna, Ray Fair, Luis Garicano, Matt Gentzkow, Ed Glaeser, David Laibson, Steve Levitt, Ulrike Malmendier, Hal Movius, Kevin M. Murphy, Emily Oster, Jane Risen, Emmanuel Saez, Bruce Sacerdote, Andrei Shleifer, Matt Weinzerl, Rick Wilson, and seminar participants at the University of Chicago, Harvard University, the Stanford Institute for Theoretical Economics, and the University of Michigan for helpful comments. Benjamin thanks the Program on Negotiation at Harvard Law School; the Harvard University Economics Department; the Chiles Foundation; the Federal Reserve Bank of Boston; the Institute for Quantitative Social Science; Harvard's Center for Justice, Welfare, and Economics; the National Institute of Aging, through Grant Number T32-AG00186 to the National Bureau of Economic Research; the Institute for Humane Studies; and the National Science Foundation for financial support. We are very grateful to Sujie Chang, Jonathan Hall, Ethan Lieber, Dina Mishra, Marina Niessner, Krishna Rao, and David Sokoler for outstanding research assistance, Robert Jacobs for excellent programming, and John Neffinger for generous assistance with the second and third rounds of the study. The views expressed herein are those of the author(s) and do not necessarily reflect the views of the National Bureau of Economic Research.
- Students who saw silent videos picked the right candidate 58 percent of the time, whereas those viewers who heard full sound or muddled...
Daniel J Benjamin & Jesse M Shapiro, 2009. "Thin-Slice Forecasts of Gubernatorial Elections," The Review of Economics and Statistics, MIT Press, vol. 91(3), pages 523-536, 02. citation courtesy of