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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

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Type
Forecasting the 2021 German Elections
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the American Political Science Association

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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
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