Hostname: page-component-77c89778f8-vsgnj Total loading time: 0 Render date: 2024-07-17T05:58:46.807Z Has data issue: false hasContentIssue false

A Länder-Based Forecast of the 2021 German Bundestag Election

Published online by Cambridge University Press:  09 September 2021

Mark A. Kayser
Affiliation:
Hertie School, Berlin
Arndt Leininger
Affiliation:
Chemnitz University of Technology
Anastasiia Vlasenko
Affiliation:
Florida State University

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Forecasting the 2021 German Elections
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Caramani, Daniele, and Kollman, Ken. 2017. “Symposium on ‘The Nationalization of Electoral Politics: Frontiers of Research.’Electoral Studies 47:5154.10.1016/j.electstud.2017.02.001CrossRefGoogle Scholar
Duch, Raymond, Przepiorka, Wojtek, and Stevenson, Randolph. 2015. “Responsibility Attribution for Collective Decision Makers.” American Journal of Political Science 59 (2): 372–89.CrossRefGoogle Scholar
Enns, Peter K., and Lagodny, Julius. 2021. “Forecasting the 2020 Electoral College Winner: The State Presidential Approval/State Economy Model.” PS: Political Science & Politics 54 (1): 8185.Google Scholar
Erikson, Robert S., and Wlezien, Christopher. 2014. “Forecasting US Presidential Elections Using Economic and Noneconomic Fundamentals.” PS: Political Science & Politics 47 (2): 313–16.Google Scholar
Graefe, Andreas. 2015. “German Election Forecasting: Comparing and Combining Methods for 2013.” German Politics 24 (2): 195204.CrossRefGoogle Scholar
Jastramskis, Maẑvydas. 2012. “Election Forecasting in Lithuania: The Case of Municipal Elections.” International Journal of Forecasting 28 (4): 822–29.CrossRefGoogle Scholar
Jennings, Will, and Wlezien, Christopher. 2016. “The Timeline of Elections: A Comparative Perspective.” American Journal of Political Science 60 (1): 219–33.CrossRefGoogle Scholar
Jérôme, Bruno, and Jérôme-Speziari, Véronique. 2012. “Forecasting the 2012 US Presidential Election: Lessons from a State-by-State Political Economy Model.” PS: Political Science & Politics 45 (4): 663–68.Google Scholar
Jérôme, Bruno, Jérôme-Speziari, Véronique, and Lewis-Beck, Michael S.. 2013. “A Political-Economy Forecast for the 2013 German Elections: Who to Rule with Angela Merkel?PS: Political Science & Politics 46 (3): 479–80.Google Scholar
Kayser, Mark A., and Leininger, Arndt. 2015. “Vintage Errors: Do Real-Time Economic Data Improve Election Forecasts?Research & Politics 2 (3). https://doi.org/10.11772053168015589624.CrossRefGoogle Scholar
Kayser, Mark A., and Leininger, Arndt. 2016. “A Predictive Test of Voters’ Economic Benchmarking: The 2013 German Bundestag Election.” German Politics 25 (1): 106–30.CrossRefGoogle Scholar
Kayser, Mark A., and Leininger, Arndt. 2017. “A Länder-Based Forecast of the 2017 German Bundestag Election.” PS: Political Science & Politics 50 (3): 689–92.Google Scholar
Kayser, Mark A., Leininger, Arndt, and Vlasenko, Anastasiia. 2021. “Replication Data for: A Länder-Based Forecast of the 2021 German Bundestag Election.” https://doi.org/10.7910/DVN/KCMSB0.CrossRefGoogle Scholar
Klarner, Carl E. 2012. “State-Level Forecasts of the 2012 Federal and Gubernatorial Elections.” PS: Political Science & Politics 45 (4): 655–62.Google Scholar
Küntzler, Theresa. 2017. “Using Data Combination of Fundamental Variable-Based Forecasts and Poll-Based Forecasts to Predict the 2013 German Election.” German Politics 27 (1): 2543.CrossRefGoogle Scholar
Norpoth, Helmut, and Gschwend, Thomas. 2010. “The Chancellor Model: Forecasting German Elections.” International Journal of Forecasting 26 (1): 4253.CrossRefGoogle Scholar
Stoetzer, Lukas F., Neunhoeffer, Marcel, Gschwend, Thomas, Munzert, Simon, and Sternberg, Sebastian. 2019. “Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals.” Political Analysis 27 (2): 255–62.10.1017/pan.2018.49CrossRefGoogle Scholar
Thesen, Gunnar, Mortensen, Peter B., and Green-Pedersen, Christoffer. 2020. “Cost of Ruling as a Game of Tones: The Accumulation of Bad News and Incumbents’ Vote.” European Journal of Political Research 59:555–77. DOI:10.1111/1475-6765.12367.CrossRefGoogle Scholar
Toros, Emre. 2012. “Forecasting Turkish Local Elections.” International Journal of Forecasting 28 (4): 813–21.CrossRefGoogle Scholar
Turgeon, Mathieu, and Rennó, Lucio. 2012. “Forecasting Brazilian Presidential Elections: Solving the N Problem.” International Journal of Forecasting 28 (4): 804–12.CrossRefGoogle Scholar
Supplementary material: Link

Kayser et al. Dataset

Link