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選舉研究 TSSCI

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篇名 2009年臺灣縣市長選舉預測分析
卷期 18:1
並列篇名 Analysis on the Prediction Results of the 2009 Magistrate and Mayoral Election in Taiwan
作者 童振源周子全林繼文林馨怡
頁次 63-94
關鍵字 預測市場民意調查準確度縣市長選舉Prediction marketsOpinion pollsAccuracyMagistrate and mayoral electionTSSCI
出刊日期 201105

中文摘要

本文摘要民意調查是預測選舉結果最常見的方法之一。但近年來預測市場逐漸成為另一種常見的預測機制,並有許多文獻比較預測市場與民意調查的準確度。本論文根據未來事件交易所的交易資料和本研究彙整的民調資料,分析預測市場對台灣2009 年縣市長選舉預測結果,並對比預測市場和民調機構對於此次選舉的預測。本研究發現:對當選人預測合約,預測市場的加權平均價格對當選比率在統計上有顯著正向影響,並且在統計上相當程度可表示為候選人當選之機率。再者,根據正確率、精準率、命中率、假警報率與貴氏比率差等五項指標,預測市場對當選人預測的能力均高於民調機構。對得票率的預測,預測市場的預測能力在選前20 天以後便高過民調機構,而且預測市場的預測準確度會隨著合約到期日的接近而逐漸增加。不過,本研究也認為民意調查的優點在於可以協助研究者進行變項的相關分析,所以可和預測市場同時運用,相互增強。

英文摘要

AbstractOpinion poll has been the most widely used way to conduct election prediction. However, recently prediction market has become another widely applied prediction mechanism, attracting the literature to compare the accuracy of the two prediction methods. According to trading data of the Exchange of Future Events and opinion polls collected by this study, this paper analyzes the prediction results of the 2009 magistrate and mayoral election in Taiwan, and compares the prediction accuracies on this election between prediction markets and poll institutions. What this paper finds are: for prediction contracts on election winners, the weighted average prices of prediction markets are positive and statistically significant on the ratio of winning elections and can be regarded as the candidates’ probability of winning elections. In addition, based upon five indicators of correctness rate, precision rate, hit rate, false alarm rate and Kuipers score, predictive power of prediction markets on election winners is obviously higher than that of poll institutions. For prediction on vote shares, predictive power of prediction markets is higher than that of poll institutions within 20 days before the election, and prediction accuracy of prediction markets is getting higher along with approaching the expiration of the contracts. Nevertheless, we also agree that opinion survey can help researchers conduct covariance analysis, which can be used together with prediction market to reinforce the findings of each other.

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