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.

ACKNOWLEDGEMENTS

I am grateful for the comments and support of Peter Selb and Susumu Shikano. I also thank the two anonymous reviewers for their detailed reviews.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author.

ABOUT THE AUTHOR

Theresa Küntzler has an MSc in Communication Science and an MA in Politics and Public Administration. She is working as doctoral student at the University of Konstanz. Her research interests include election forecasting and voting advice applications.

Notes

1 Published on 12 July 2013, 2 Aug. 2013, 16 Aug. 2013 and 23 Aug. 2013.

2 The ‘Sunday question’ (German national elections are held on Sundays): ‘Assuming the elections were next Sunday which party would you vote for?’