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Forecasting Federal Elections: New Data From 2010–2019 and a Discussion of Alternative and Emerging Methods
Author(s) -
GreenopRoberts Hamish
Publication year - 2022
Publication title -
australian economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 29
eISSN - 1467-8462
pISSN - 0004-9018
DOI - 10.1111/1467-8462.12450
Subject(s) - federal election , odds , voting , economics , econometrics , honeymoon , financial economics , macroeconomics , political science , computer science , finance , logistic regression , politics , commission , machine learning , law
Abstract I produce and compare election forecasts for the period 2010–19. The dominant methods of polls, odds and economic models have mixed success, each predicting three out of four federal elections. Consistent with prior research, polls then prediction markets are found to produce the most volatile forecasts, while economic models produce the least. Prediction markets are found to efficiently price available information. Economic models performed well at the 2019 election, however, they were limited by outdated dummy variables for ‘honeymoon effects’. I conclude by discussing some alternative and emerging forecasting methods, including demographic explanations of voting and online sentiment analysis.