Forecasting Election Results: A Bayesian Frequentist Comparison
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