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Forecasting Federal Elections: New Data From 2010–2019 and a Discussion of Alternative and Emerging Methods

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  • Hamish Greenop‐Roberts

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 Economic models performed well at the 2019 election, however, they were limited by outdated dummy variables for ‘honeymoon effects’.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.

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  • Hamish Greenop‐Roberts, 2022. "Forecasting Federal Elections: New Data From 2010–2019 and a Discussion of Alternative and Emerging Methods," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 55(1), pages 25-39, March.
    • Handle: RePEc:bla:ausecr:v:55:y:2022:i:1:p:25-39
    DOI: 10.1111/1467-8462.12450
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    1. David Paton & Donald S. Siegel & Leighton Vaughan Williams, 2010. "Gambling, Prediction Markets and Public Policy," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 878-883, April.
    2. Erik Snowberg & Justin Wolfers & Eric Zitzewitz, 2007. "Partisan Impacts on the Economy: Evidence from Prediction Markets and Close Elections," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(2), pages 807-829.
    3. M. Galesic & W. Bruine de Bruin & M. Dumas & A. Kapteyn & J. E. Darling & E. Meijer, 2018. "Asking about social circles improves election predictions," Nature Human Behaviour, Nature, vol. 2(3), pages 187-193, March.
    4. David Paton & Donald S. Siegel & Leighton Vaughan Williams, 2010. "Symposium - Gambling, Prediction Markets and Public Policy," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 878-883, April.
    5. Nikolaos Stoupos & Apostolos Kiohos, 2021. "BREXIT referendum’s impact on the financial markets in the UK," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(1), pages 1-19, February.
    6. Lisa Cameron & Mark Crosby, 2000. "It's the Economy Stupid: Macroeconomics and Federal Elections in Australia," The Economic Record, The Economic Society of Australia, vol. 76(235), pages 354-364, December.
    7. Andrew Leigh & Justin Wolfers, 2006. "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets," The Economic Record, The Economic Society of Australia, vol. 82(258), pages 325-340, September.
    8. Fair, Ray C, 1978. "The Effect of Economic Events on Votes for President," The Review of Economics and Statistics, MIT Press, vol. 60(2), pages 159-173, May.
    9. Robert W. Hahn & Paul Tetlock, 2006. "Information Markets: A New Way of Making Decisions," Books, American Enterprise Institute, number 51409, September.
    10. Lee A. Smales & Henk Berkman, 2016. "The role of political uncertainty in Australian financial markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(2), pages 545-575, June.
    11. Will Jennings & Christopher Wlezien, 2018. "Election polling errors across time and space," Nature Human Behaviour, Nature, vol. 2(4), pages 276-283, April.
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