Using Data Combination of Fundamental Variable-Based Forecasts and Poll-Based Forecasts to Predict the 2013 German Election

Abstract

In this paper I present an election forecasting approach to predict the vote share of the governing coalition in German national elections. The model is composed of two independent prediction components: the first is based on poll data, the second on fundamental variables. Both approaches have their advantages and disadvantages when used in isolation. The basic idea is to use both and find a better informed overall forecast. The predictions are combined using a shrinkage estimator, where the predictions are weighted by their respective prediction uncertainty. The uncertainty of the poll prediction is modelled time-dependent. The result is a dynamic model allowing for predictions longer before the elections highly relying on fundamental variables. With the elections coming closer predictions rely more and more on the polling data.