Journal of Electoral Studies

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Home Issues Backissues Volume 31, No.1 Change in Voting Behaviour: Applying an Election Forecasting Model of Probability Distributions to Modify the Accuracy of Poll Outcomes

Change in Voting Behaviour: Applying an Election Forecasting Model of Probability Distributions to Modify the Accuracy of Poll Outcomes

Shun-Chuan Chang and Wen-Jong Juang
2008 / 11
Volume 15, No.2

pp.91-117
10.6612/tjes.2008.15.02.91-117
Paper

Abstract

Due to undervotes, misvotes, or switchvotes bias, many polling data users felt frustrated in using the past polling outcome to forecast the new election. It is commonplace for voters to note an early frontrunner in polls will be doomed to fall in the real election outcome. A beta-binominal distribution is suggested to model the accuracy of early poll outcome which strategically influences the polling data users such as political parties, candidates, and mass media in implementing the election campaign. We demonstrate the advantages of probabilistic distribution and Bayesian reasoning, and how to estimate the parameters from past data, in modifying the accuracy of prior poll outcomes. In comparison with the traditional frequency approach, beta-binominal mixture distribution imposes a statistical-adjusting framework with ability to proportionate a coherent mechanism that synthesizes the performances of prior votes. The empirical data sets include the 2004 US presidential election in Atlas Web and TVBS polls in 2006 Kaohsiung mayor election and 2008 presidential election in Taiwan. This paper describes the general fitting of beta-binomial distribution on both datasets and discusses fruitful avenues for future research.

Keywords

Public Polling

Voting Behavior

Election Forecasting

Mixture Distribution

Bayesian Statistics