The chancellor model: forecasting German elections

Journal article | Zeitschriftenartikel

"Our forecast model for German Bundestag elections relies on three predictors: (1) the popularity of the incumbent chancellor (hence the christening of it as the 'Chancellor Model'); (2) the long-term partisan balance in the German electorate; and (3) the cost of ruling, as captured by the tenure of the government in office. The model forecasts the vote share of the governing parties (typically two, such as Social Democrats and Greens, or Christian Democrats and Free Democrats), except for instances of a grand coalition. The coefficients of the predictors are estimated based on elections since 1949, the beginning of the Federal Republic. The out-of-sample forecasts of the model deviate from the actual results by just over one percentage point, on average. The first real-time test of the model came in 2002. The forecast issued three months before Election Day picked the incumbent vote share to the decimal (47.1% for the SPD-Greens coalition); for the 2005 election, called a year early, our forecast three weeks before Election Day was just three-tenths of a percentage off the mark. For the upcoming election, we offer separate forecasts, conditional at this moment, for each of the two parties in the grand coalition." (authors abstract)

Angaben zum Objekt

• Umfang: Seite(n): 42–53
• Sprache: Englisch
• Anmerkungen: Status: Veröffentlichungsversion

Verweise und Beziehungen

• Erschienen in: International Journal of Forecasting, 26(1)

Klassifikation und Themen

• Thema: Politikwissenschaft ; politische Willensbildung, politische Soziologie, politische Kultur ; Bundesrepublik Deutschland ; Popularität ; Prognosemodell ; Prognose ; Wahlverhalten ; Wahlergebnis ; Bundestagswahl ; Bundeskanzler ; Wahl

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Norpoth, Helmut ; Gschwend, Thomas
• Ereignis: Veröffentlichung
• (wo): Niederlande
• (wann): 2010

Weitere Informationen

• DOI: https://doi.org/10.1016/j.ijforecast.2009.02.008
• URN: urn:nbn:de:0168-ssoar-257809
• Rechteinformation: GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
• Letzte Aktualisierung: 21.06.2024, 16:27 MESZ