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Forecasting Election Results in the Czech Republic
 Doskočilová, Kateřina ; Havránek, Tomáš (advisor) ; Čech, František (referee)
Forecasting Election Results in the Czech Republic Kateřina Doskočilová In this thesis, a forecasting model for the 2017 legislative election in the Czech Republic is built. As the Czech Republic has a multi-party system, the outcomes of the model are the expected vote shares for each party. There are two types of forecasts calculated. Firstly, a poll-based forecast using a dynamic linear model and Kalman filter to weigh the information in the polls. Secondly, the prices on betting markets are translated into probabilistic forecasts for the expected vote shares. This is a novel approach as prediction markets were previously used to forecasts only the probabilities of winning an election. Finally, the two types of forecasts are combined into one and weighed by their variance. Comparing the forecasts, we conclude that the betting market is able to predict the exact vote shares the most accurately right before the election.
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