Picking the winner(s): Forecasting elections in multiparty systems

From the 1970s onwards, a wide range of forecasting techniques have been developed in the literature on electoral forecasting. However, these models have primarily been applied in two-party, presidential democracies, with the US being by far the most popular country to investigate. The question thus arises whether the same techniques that have proved successful in this context can also be applied to the more complex, multiparty democracies in northern Europe. This paper seeks to answer this question and in the process makes two main contributions. Firstly, the popular dynamic linear model (Jackman, 2005) is tried and tested in Germany and Sweden where it is shown that reasonable forecasts can be made despite the complexity of the systems and the emergence of new parties. A novelty is then introduced when cyclical changes in party support are modelled through a seasonal component. This extension of the dynamic linear model helps to significantly lower the error in early forecasts and is thus something that could be useful in future applications of the model.