The role of polls for election forecasting in German state elections

German state elections are in focus of this work due to the decreasing importance of the "catch all parties" and rise of the AfD in 2013. As small parties like the AfD first reached the 5% threshold in state parliaments (e.g. in the Saxony state election 2014), state elections can be used as barometer elections for the national ones. Further, state elections fill the gap between the 4-year national election cycle and provide additional information for the national election. The aim of this thesis is to forecast state elections based on polling data from different institutes. Despite occurring errors in polls like measurement or sampling errors - which are also discussed in this work - forecasting is made with aggregate models depending on short term polling data. Irregular polling data have to be customized to generate daily data to apply parametric regression based models. To forecast single vote shares in multi-party elections, the range of methods varies from basic methods like averaging over nonparametric regression based methods to dynamic linear models.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Passau

Year

2018

Author dc:creator

• Huber, Sandra

Contributors dc:contributor

• Haupt, Harry
• Oberreuter, Heinrich

• forecasting
• election
• polls
• Umfragen

Statement dc:rights

• Standardbedingung laut Einverständniserklärung

Repository record source_url

https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/555

OAI identifier oai:identifier

oai:kobv.de-opus4-uni-passau:555