Replication data for: The Zweitstimme Model: A dynamic forecast of the 2021 German federal election
| Item Type: | Dataset |
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| Title: | Replication data for: The Zweitstimme Model: A dynamic forecast of the 2021 German federal election |
| Date: | 2021 |
| Creator: |
Neunhoeffer, Marcel  ORCID: 0000-0002-9137-5785 ; Gschwend, Thomas ORCID: 0000-0002-8656-9622 ; Müller, Klara ORCID: 0000-0001-9314-4094 ; Munzert, Simon ; Stoetzer, Lukas ORCID: 0000-0003-2486-7496
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| Divisions: | Außerfakultäre Einrichtungen > MZES School of Social Sciences > Politische Wissenschaft, Quantitative Sozialwissenschaftliche Methoden (Gschwend 2007-) |
| DDC Classification: |
320 Political science |
|---|---|
| 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. (English) |
| External Identifier for Data: | https://doi.org/10.7910/DVN/EDTKNW |
| URL: | https://madata.bib.uni-mannheim.de/684/ |
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| Access (Controlled): | Only Metadata |
| License (Controlled): | Creative Commons: CC0 | Universal 1.0 (recommended) |
| Related Publication(s) in MADOC: | Gschwend, Thomas und Müller, Klara und Munzert, Simon und Neunhoeffer, Marcel und Stoetzer, Lukas F. (2022), The Zweitstimme model: A dynamic forecast of the 2021 German federal election |
Full text not available from this repository.
| Date Deposited: | 08 Apr 2026 16:46 |
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| Last Modified: | 08 Apr 2026 16:46 |
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