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題名 Election Prediction: Using National Survey to Predict District-Level Legislative Yuan Elections
選舉預測:利用全國性調查推估區域立委選情
作者 俞振華
涂志揚
貢獻者 選研中心
關鍵詞 Multilevel regression and post-stratification ; MRP ; Election prediction ; National survey ; Legislative Yuan elections
多層次估計模型與事後分層加權 ; 選舉預測 ; 全國民調 ; 立委選舉 ;
日期 2017-12
上傳時間 14-Aug-2018 17:20:36 (UTC+8)
摘要 This paper uses pre-election national survey data and a method combining the Bayesian multilevel modeling approach with the population information for post-stratification (i.e., multilevel regression and post-stratification: MRP) to predict Legislative Yuan elections in the 73 single-member districts. Specifically, our method is consisted of three steps: first, we construct a multilevel logistic regression model to estimate the vote choice variables for the Kuomintang (KMT) and Democratic Progressive Party (DPP) candidates, respectively, given demographics and districts of residence. Second, we post-stratify on all the variables in the model by using the joint population distribution of the demographic variables within each district. Third, we then combine the above two steps and estimate the mean of support for the KMT and DPP candidates in the district level. Given that each district only has about 55 samples on average, this study shows that MRP method can be regarded as an effective tool for election prediction, as the average absolute measurement error between the estimates and actual vote shares is just about 5 percentage points. In a comparison with the pre-election district-level predictions issued by the prediction market "xFuture", our estimates are almost as good as the results of "xFuture".
關聯 東吳政治學報, Vol.35, No.3, pp.71-120
Soochow Journal of Political Science . 2017, Vol. 35 Issue 3, p71-120. 50p
資料類型 article
dc.contributor 選研中心-
dc.creator (作者) 俞振華zh_TW
dc.creator (作者) 涂志揚zh_TW
dc.date (日期) 2017-12-
dc.date.accessioned 14-Aug-2018 17:20:36 (UTC+8)-
dc.date.available 14-Aug-2018 17:20:36 (UTC+8)-
dc.date.issued (上傳時間) 14-Aug-2018 17:20:36 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/119361-
dc.description.abstract (摘要) This paper uses pre-election national survey data and a method combining the Bayesian multilevel modeling approach with the population information for post-stratification (i.e., multilevel regression and post-stratification: MRP) to predict Legislative Yuan elections in the 73 single-member districts. Specifically, our method is consisted of three steps: first, we construct a multilevel logistic regression model to estimate the vote choice variables for the Kuomintang (KMT) and Democratic Progressive Party (DPP) candidates, respectively, given demographics and districts of residence. Second, we post-stratify on all the variables in the model by using the joint population distribution of the demographic variables within each district. Third, we then combine the above two steps and estimate the mean of support for the KMT and DPP candidates in the district level. Given that each district only has about 55 samples on average, this study shows that MRP method can be regarded as an effective tool for election prediction, as the average absolute measurement error between the estimates and actual vote shares is just about 5 percentage points. In a comparison with the pre-election district-level predictions issued by the prediction market "xFuture", our estimates are almost as good as the results of "xFuture".en_US
dc.format.extent 175 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 東吳政治學報, Vol.35, No.3, pp.71-120-
dc.relation (關聯) Soochow Journal of Political Science . 2017, Vol. 35 Issue 3, p71-120. 50p-
dc.subject (關鍵詞) Multilevel regression and post-stratification ; MRP ; Election prediction ; National survey ; Legislative Yuan electionsen_US
dc.subject (關鍵詞) 多層次估計模型與事後分層加權 ; 選舉預測 ; 全國民調 ; 立委選舉 ;zh_TW
dc.title (題名) Election Prediction: Using National Survey to Predict District-Level Legislative Yuan Electionsen_US
dc.title (題名) 選舉預測:利用全國性調查推估區域立委選情zh_TW
dc.type (資料類型) article-