Economic Conditions and Predicting Elections: Insights from Weather Forecasting

Abstract:
Advances in weather forecasting may hold lessons for advancing election forecasting. We spell out leading implications. Election forecasting models should begin with sound electoral theory. The models should be dynamic. Data-gathering should be intensive. Repeated measures should be taken. When independent variables cannot be measured, tracking of the dependent variable may be necessary. Finally, the discrete nature of the dependent variable may require, in the end, a return to more long-distance structural models. The leading example will be forecasting US presidential elections, but other cases will also be examined, including the British and French cases.

Short biography of Guest Speaker:

Michael S. Lewis-Beck is F. Wendell Miller Distinguished Professor of Political Science at the University of Iowa. His interests are comparative elections, election forecasting, political economy, and quantitative methodology. Professor Lewis-Beck has authored or co-authored over 225 articles and books, including Economics and Elections, The American Voter Revisited, French Presidential Elections, Forecasting Elections, The Austrian Voter, and Applied Regression. He has served as Editor of the American Journal of Political Science and of the Sage QASS series (the green monographs) in quantitative methods.

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