Work

Replication Data for: The Zweitstimme Model: A Dynamic Forecast of the 2021 German Federal Election

Year: 2021

Type: dataset

Abstract: We present the Zweitstimme Model to forecast the outcome of the 2021 German federal election. The dynamic Bayesian forecasting model combines data from published pre-election public opinion polls with information from fundamentals-based forecasting models. The model takes care of the multiparty nature of the setting and generates probability statements about other quantities of interest, such as the majority for coalitions in parliament, and the expected overall size of parliament. As a central expectation, 100 days before the election, our model predicts a strengthening in Green party support (17% [12%; 23%]) and new majorities for coalition governments (67% chance for a majority of a CDU/CSU-Green coalition). The model further expects the Bundestag to grow in size to around 814 seats.

Source: Harvard Dataverse

DOI: 10.7910/dvn/edtknw

Authors: Neunhoeffer, Marcel, Gschwend, Thomas, Müller, Klara, Munzert, Simon, Stoetzer, Lukas F.

Institutions: Ludwig-Maximilians-Universität München, University of Mannheim, Hertie School, Humboldt-Universität zu Berlin

Language: English

Topic: Electoral Systems and Political Participation

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W4398333376

Cites:

Cited by: 1

Related to: 10