Improving Election Prediction Internationally

Journal Article
Publication date: 
Ryan Kennedy
Stefan Wojcik
David Lazer
Improving Election Prediction Internationally

This study reports the results of a multiyear program to predict direct executive elections

in a variety of countries from globally pooled data.We developed prediction models by

means of an election data set covering 86 countries and more than 500 elections, and a

separate data set with extensive polling data from 146 election rounds.We also participated

in two live forecasting experiments. Our models correctly predicted 80 to 90% of elections

in out-of-sample tests. The results suggest that global elections can be successfully

modeled and that they are likely to become more predictable as more information becomes

available in future elections. The results provide strong evidence for the impact of political

institutions and incumbent advantage. They also provide evidence to support contentions

about the importance of international linkage and aid. Direct evidence for economic

indicators as predictors of election outcomes is relatively weak. The results suggest that,

with some adjustments, global polling is a robust predictor of election outcomes, even

in developing states. Implications of these findings after the latest U.S. presidential election

are discussed.


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