@article{ErfortStoetzerGschwendetal., author = {Erfort, Cornelius and Stoetzer, Lukas F. and Gschwend, Thomas and Koch, Elias and Munzert, Simon and Rajski, Hannah}, title = {The Zweitstimme Forecast for the German Federal Election 2025: Coalition Majorities and Vacant Districts}, series = {PS: Political Science \& Politics}, journal = {PS: Political Science \& Politics}, publisher = {Cambridge University Press (CUP)}, issn = {1049-0965}, doi = {10.1017/S1049096525000150}, pages = {1 -- 12}, language = {en} } @article{StoetzerErfortRajskietal., author = {Stoetzer, Lukas F. and Erfort, Cornelius and Rajski, Hannah and Gschwend, Thomas and Munzert, Simon and Koch, Elias}, title = {An election forecasting model for subnational elections}, series = {Electoral Studies}, volume = {95}, journal = {Electoral Studies}, publisher = {Elsevier BV}, doi = {10.1016/j.electstud.2025.102939}, 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.}, language = {en} }