Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-29T07:20:04.006Z Has data issue: false hasContentIssue false

Forecasting Bloc Support in German Federal Elections: A Political-History Model

Published online by Cambridge University Press:  09 September 2021

Stephen Quinlan
Affiliation:
GESIS—Leibniz Institute for the Social Sciences, Mannheim, Germany
Christian Schnaudt
Affiliation:
University of Mannheim, Germany
Michael S. Lewis-Beck
Affiliation:
University of Iowa, USA

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

Abramowitz, Alan. 2008. “Forecasting the 2008 Presidential Election with the Time-for-Change Model.” PS: Political Science & Politics 41 (4): 691–95.Google Scholar
Arzheimer, Kai. 2016. “ Wahlverhalten in Ost-West-Perspektive .” In Wahlen und Wähler, ed. Schoen, Harald and Wessels, Bernhard, 7189. Wiesbaden: Springer. https://doi.org/10.1007/978-3-658-11206-6_4.Google Scholar
Campbell, Angus, Converse, Phillip, Miller, Warren, and Stokes, Donald. 1960. The American Voter. New York: John Wiley & Sons.Google Scholar
Cuzan, Alfred. 2015. “Five Laws of Politics.” PS: Political Science & Politics 48:415–19.Google Scholar
Dalton, Russell J. 2014. “Interpreting Partisan Dealignment in Germany.” German Politics 23 (1–2): 134–44.CrossRefGoogle Scholar
Dalton, Russell J., and Wattenberg, Martin. 2000. Parties Without Partisans: Political Change in Advanced Industrial Democracies. Oxford: Oxford University Press.Google Scholar
Dalton, Russell J., and Weldon, Steven. 2010. “Political Culture in a United Germany.” German Politics 19 (1): 923.CrossRefGoogle Scholar
Gallagher, Michael, Laver, Michael, and Mair, Peter. 2011. Representative Government in Modern Europe: Institutions, Parties and Governments. Fifth Edition. New York: McGraw Hill.Google Scholar
Graefe, Andreas. 2019. “Accuracy of German Federal Election Forecasts, 2013 & 2017.” International Journal of Forecasting 35 (3): 868–77.CrossRefGoogle Scholar
Jérôme, Bruno, Jérôme-Speziari, Veronique, and Lewis-Beck, Michael S.. 1998. “Prévisions politico—économiques et élections législatives allemandes de septembre 1998.Le Figaro économie, July 10.Google Scholar
Jérôme, Bruno, Jérôme-Speziari, Veronique, 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. https://doi.org/10.1017/S1049096513000814.Google Scholar
Jérôme, Bruno, Jérôme-Speziari, Veronique, and Lewis-Beck, Michael S.. 2017. “The Grand Coalition Reappointed but Angela Merkel on Borrowed Time.” PS: Political Science & Politics 50 (3): 683.Google Scholar
Jérôme, Bruno, Jérôme-Speziari, Veronique, Mongrain, Phillip, and Nadeau, Richard. 2021. “State-Level Forecasts for the 2020 US Presidential Election: Tough Victory Ahead for Biden.” PS: Political Science and Politics 54 (1): 193.Google Scholar
Keilis-Borok, V. I., and Lichtman, Alan. 1981. “Pattern Recognition Applied to Presidential Elections in the United States, 1890–1980: The Role of Integral Social, Economic, and Political Traits.” Proceedings of the National Academy of Sciences of the United States of America 78:7230–34.Google Scholar
Levy, Jack S. 2008. “Case Studies: Types, Designs, and Logics of Inference.” Conflict Management and Peace Science 25 (1): 118.CrossRefGoogle Scholar
Lewis-Beck, Michael S. 2005. “Election Forecasting: Principles and Practice.” British Journal of Politics and International Relations 7 (2): 145–64.CrossRefGoogle Scholar
Mongrain, Phillip. 2021. “10 Downing Street: Who’s Next? Seemingly Unrelated Regressions to Forecast UK Election Results.” Journal of Elections, Public Opinion, and Parties 31 (1): 2232.CrossRefGoogle Scholar
Norpoth, Helmut. 1991. “The Popularity of the Thatcher Government: A Matter of War and Economy.” In Economics and Politics: The Calculus of Support, ed. Norpoth, Helmut, Lafay, Jean-Dominique, and Lewis-Beck, Michael S., 141–60. Ann Arbor: University of Michigan Press.Google Scholar
Norpoth, Helmut, and Gschwend, Thomas. 2003. “Against All Odds? The Red–Green Victory.” German Politics and Society 21 (1): 1534.CrossRefGoogle Scholar
Norpoth, Helmut, and Gschwend, Thomas. 2010. “The Chancellor Model: Forecasting German Elections.” International Journal of Forecasting 26:4253.CrossRefGoogle Scholar
Norpoth, Helmut, and Gschwend, Thomas. 2017. “Chancellor Model Predicts a Change of the Guards.” PS: Political Science & Politics 50 (3): 686–88.Google Scholar
Pierson, Paul. 2000. “Increasing Returns, Path Dependence, and the Study of Politics.” American Political Science Review 94 (2): 251–67.CrossRefGoogle Scholar
Quinlan, Stephen, Schnaudt, Christian, and Lewis-Beck, Michael S.. 2021. “Replication Data for Forecasting Bloc Support in German Federal Elections: A Political History Model.” Harvard Dataverse. DOI:10.7910/DVN/CZLJS6.CrossRefGoogle Scholar
Ratcliffe, Susan. 2016. The Oxford Essential Quotations Dictionary. Fourth Edition. Oxford, UK: Oxford University Press. www.oxfordreference.com/view/10.1093/acref/9780191826719.001.0001/q-oro-ed4-00010959. Accessed June 7, 2021.CrossRefGoogle Scholar
Stoetzer, Lukas F., Neunhoeffer, Marcel, Gschwend, Thomas, and Sternberg, Sebastian. 2019. “Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals.” Political Analysis 27 (2): 255–62.CrossRefGoogle Scholar
wahlrecht.de. 2021. “Kantar (Emnid).” www.wahlrecht.de/umfragen/emnid.htm. Accessed June 5, 2021.Google Scholar
Zellner, Arnold. 1962. “An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias.” Journal of American Statistical Association 57 (298): 348–68.CrossRefGoogle Scholar
Supplementary material: Link

Quinlan et al. Dataset

Link
Supplementary material: PDF

Quinlan et al. supplementary material

Appendices

Download Quinlan et al. supplementary material(PDF)
PDF 347.7 KB