• search hit 7 of 20
Back to Result List

Eine länderbasierte Prognose zur Bundestagswahl 2017

  • When elections are distant, polls are poor predictors. Too few voters are paying attention and too much can change before election day. Structural models can establish baseline expectations but suffer from high uncertainty and underspecification imposed by small samples. We present an early forecast of the 2017 Bundestag election results for individual parties that leverages economic and political data as well as state parliament (Landtag) election results in the German states (Länder) to sidestep these shortcomings. A linear random effects model provides our estimates. Länder elections are dispersed over the calendar and offer the advantage of capturing both actual voter preferences and new political issues. We argue that this approach offers a promising method for early forecasts when polls are not informative.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Document Type:Article
Language:German
Author(s):Mark A. KayserORCiD, Arndt Leininger
Parent Title (German):Politische Vierteljahresschrift
ISSN:0032-3470
Publication year:2017
Publishing Institution:Hertie School
First Page:407
Last Page:417
DOI:https://doi.org/10.5771/0032-3470-2017-3-407
Release Date:2020/05/13
Tag:Elections; Germany; forecasting; parties
Issue:58(3)
Hertie School Research:Publications PhD Researchers
Licence of document (German):Metadaten / metadata
Verstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.