Forecasting Election Results: A Bayesian Frequentist Comparison

Sammanfattning: We present a Bayesian and frequentist comparison when forecasting elections through polls. Our focus is on studying the differences of these approaches in forecasting elections. An evaluation of the fit is performed using the odds ratio. We propose a frequentist methodology for prediction horizons three months ahead while a Bayesian methodology may be slightly more accurate for shorter prediction horizons. The contribution of this paper lies in shedding light on the importance of the prediction horizon when choosing between a Bayesian or frequentist methodology to forecasting election results.