Three Tools for Forecasting Federal Elections: Lessons from 2001

Stanford GSB Research Paper No. 1723

24 Pages Posted: 1 Apr 2002

See all articles by Justin Wolfers

Justin Wolfers

University of Michigan at Ann Arbor - Department of Economics; University of Michigan at Ann Arbor - Gerald R. Ford School of Public Policy; The University of Sydney - Discipline of Economics; Brookings Institution - Economic Studies Program; Peter G. Peterson Institute for International Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics; Centre for Economic Policy Research (CEPR); CESifo (Center for Economic Studies and Ifo Institute); Kiel Institute for the World Economy

Andrew Leigh

Australian House of Representatives Parliament House; Centre for Applied Macroeconomic Analysis, ANU; IZA

Date Written: November 2001

Abstract

How best to predict Australian federal election results? This article analyses three forecasting tools - opinion polls, economic models, and betting odds. Historically, we find that opinion polls taken close to the election are quite accurate, while economic models provide better medium-run forecasts. The 2001 election largely follows this pattern, although the economic models provided more accurate projections than recorded through the 1990s. Against these, we compare betting odds, analyzing a rich data source from one of Australia's largest bookmakers, Centrebet. The betting market not only correctly forecast the election outcome, but also provided very precise estimates of outcomes in a host of individual electorates. Betting fluctuations provide an intriguing quantitative record of the shifting fortunes of the campaign. We conclude that - particularly in marginal seats - the press may have better served its readers by reporting betting odds than by conducting polls.

Keywords: Australian elections, polling, gambling, election forecasting

JEL Classification: D7, C5, E6

Suggested Citation

Wolfers, Justin and Leigh, Andrew, Three Tools for Forecasting Federal Elections: Lessons from 2001 (November 2001). Stanford GSB Research Paper No. 1723, Available at SSRN: https://ssrn.com/abstract=296234 or http://dx.doi.org/10.2139/ssrn.296234

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