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2020 | OriginalPaper | Chapter

Forecasting

Author : Arndt Leininger

Published in: Handbuch Methoden der Politikwissenschaft

Publisher: Springer Fachmedien Wiesbaden

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Zusammenfassung

Prognosen stellen in der Politikwissenschaft ein zwar noch kleines, aber stetig wachsendes Forschungsfeld dar, welches in verschiedenen Teilbereichen der Disziplin Anwendung findet. Gemeint sind hiermit statistische Modelle, mit denen explizit politikwissenschaftlich relevante Phänomene vor ihrem Eintreten vorhergesagt werden. Dabei folgen sie den wissenschaftlichen Leitlinien der intersubjektiven Nachvollziehbarkeit und Reproduzierbarkeit. Dieser Beitrag führt ein in die Grundlagen politikwissenschaftlicher Prognosen. Den Schwerpunkt der Darstellung bilden Wahlprognosen, insbesondere strukturelle Modelle, welche beispielhaft anhand eines kanonischen Wahlprognosemodells erläutert werden. Daneben werden synthetische Modelle, Aggregationsmodelle, „Wisdom of the crowd“-Ansätze und Prognosemärkte diskutiert.

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Footnotes
1
Aufgrund der besseren Lesbarkeit wird in diesem Beitrag der Einfachheit halber nur die weibliche Form verwendet. Die männliche Form ist selbstverständlich immer mit eingeschlossen.
 
2
Andere Versionen dieses Modells enthalten statt dieser Variablen eine Dummy-Variable, die anzeigt, ob die amtierende Präsidentin bereits zwei Amtszeiten im Amt war.
 
3
Für eine Erläuterung des Jury Theorems siehe Nurmi (2002).
 
4
Die Odds einer Wette auf das Eintreten eines Ereignisses E entsprechen der Wahrscheinlichkeit, dass das Ergebnis nicht eintritt relativ zur Wahrscheinlichkeit, dass es eintritt:\( \frac{1-p(E)}{p(E)} \). Hieraus ergibt sich auch der Auszahlungsbetrag.
 
5
Für eine genauere Erläuterung der Funktionsweise von Prognosemärkten und einigen Beispielen siehe Wolfers und Zitzewitz (2004), sowie Berg et al. (2008).
 
6
Während bayesianische Verfahren und Ansätze aus dem Machine Learning in ersten Anwendungen vielversprechende Ergebnisse liefern, hat was das Potenzial von Daten aus dem Internet, insbesondere Social Media, angeht bereits Ernüchterung eingesetzt (Huberty 2015).
 
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Metadata
Title
Forecasting
Author
Arndt Leininger
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-658-16936-7_36