An election forecasting model for subnational elections


Stoetzer, Lukas F. ; Erfort, Cornelius ; Rajski, Hannah ; Gschwend, Thomas ; Munzert, Simon ; Koch, Elias


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DOI: https://doi.org/10.1016/j.electstud.2025.102939
URL: https://www.sciencedirect.com/science/article/pii/...
Additional URL: https://www.researchgate.net/publication/392296272...
URN: urn:nbn:de:bsz:180-madoc-699445
Document Type: Article
Year of publication: 2025
The title of a journal, publication series: Electoral Studies
Volume: 95
Issue number: Article 102939
Page range: 1-10
Place of publication: Amsterdam [u.a.]
Publishing house: Elsevier Science
ISSN: 0261-3794 , 1873-6890
Publication language: English
Institution: Außerfakultäre Einrichtungen > Mannheim Centre for European Social Research - Research Department B
Pre-existing license: Creative Commons Attribution 4.0 International (CC BY 4.0)
Subject: 320 Political science
Keywords (English): election forecasting , subnational elections , German state elections
Abstract: While election forecasts predominantly focus on national contests, many democratic elections take place at the subnational level. Subnational elections pose unique challenges for traditional fundamentals forecasting models due to less available polling data and idiosyncratic subnational politics. In this article, we present and evaluate the performance of Bayesian forecasting models for German state elections from 1990 to 2024. Our forecasts demonstrate high accuracy at lead times of two days, two weeks, and two months, and offer valuable ex-ante predictions for three state elections held in September 2024. These findings underscore the potential for applying election forecasting models effectively to subnational elections.




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