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Cluster :  Public Policy

Session Information  : Sunday Oct 14, 16:30 - 18:00

Title:  United States Presidential Election Forecasting: Who Will Win the White House in 2012?
Chair: Sheldon Jacobson,Professor, University of Illinois, 201 N. Goodwin Avenue (MC258), Urbana IL 61801, United States of America,

Abstract Details

Title: The Keys to the White House: Forecast for 2012
 Presenting Author: Allan Lichtman,Distinguished Professor, Department of History, American University, Washington DC 20817, United States of America,
Abstract: This paper will present the Keys to the White House and provide a forecast for the 2012 presidential election. The Keys to the White House are a historically-based prediction system that retrospectively account for the popular-vote winners of every American presidential election from 1860 to 1980 and prospectively forecast well ahead of time the popular-vote winners of every presidential election from 1984 through 2012.
Title: Modeling a Presidential Prediction Market
 Presenting Author: Keith Chen,Yale School of Management, New Haven CT, United States of America,
 Co-Author: Edward Kaplan,William N and Marie A Beach Professor of Management Sciences, Yale School of Management, 135 Prospect Street, New Haven CT 06520, United States of America,
Abstract: Using data from past Intrade US presidential prediction markets, we examined three alternative models for security prices, focusing on consistency with electoral college rules. We show that a simple diffusion model provides a good description of the overall distribution of electoral college votes, while an even simpler ranking model provides excellent predictions of the probability of winning the presidency. We derive implications for predicting the 2012 US presidential election.
Title: The 2012 United States Presidential Election: And the Winner is…
 Presenting Author: Sheldon Jacobson,Professor, University of Illinois, 201 N. Goodwin Avenue (MC258), Urbana IL 61801, United States of America,
 Co-Author: Steve Rigdon,St. Louis University, Dept of Math and Stats, St. Louis MO, United States of America,
 Jason Sauppe,University of Illinois, Dept of CS, Urbana IL, United States of America,
 Edward Sewell,Southern Illinois University-Edwardsville, Dept of Math and Stats, Edwardsville IL 62026, United States of America,
Abstract: Predict the number of electoral college votes for each candidatein the United States Presidential election can be a difficult task. This presentation discusses a Bayesian approach incorporating undecided voter effects into the analysis. A web site has been created for people to follow the resulting forecasts.