| Abstract: | 本計畫的首要目標是找出台灣社會中各個層次的民意，包含國家認同以及地方政策議題。民主政治應該奠基在一定的共識之上，包括國家認同、民主價值等等。然而過去的研究過於重視國家認同，未觸及公共政策。這項研究將回答台灣民眾究竟有那些共識或歧異，而我們又要如何從歧異或共識解釋政策決定以及選舉結果。本計畫是利用貝式定理以及相關軟體分析各個縣市的投票支持對象及政治心理。過去以本次的總統選舉為研究對象，雖然成效良好，但是估計過程中使用的是2000年的總統選舉結果。而且在實務上，在一個全國性選舉中估計各個縣市的支持度並不切實際，因為全部票數最後還是要統合計算。而這個三年期計畫將進行兩次全國性問卷調查，用第一次問卷調查的資料協助第二次問卷調查的資料分析，目標是深入探討民意、政策、選舉行為之間的關聯。除此之外，我們將收集縣市長的預算資料，以及立委候選人在選舉公報上刊登的政見，檢視他們回應民意的程度，找些一些民意與施政互動的模式。。在多層次分析模型的模擬協助下，全國性的調查將可以充份運用到地方政治，以解決許多地方政治的研究問題，分析民眾如何回應各種建設及預算分配，而地方精英又如何回應民眾的要求。以同樣模式，可以研究立法院代表選區偏好的程度為何。由於有各縣市的民調資料，該模型可以深入探討各縣市以及未來的立委選區的政治態度，以穿透長期以來較少研究的地方政治行為領域。整體而言，本計畫的貢獻在於找出台灣社會的全國性及地方性的共識/歧異、測量民意被反映到政治的程度、用小樣本預策小選區的投票結果。
For every democracy, consensus on basic values is critical to its stability. In Taiwan, however, people appear to have differing ideas about self-identification as Taiwanese, Chinese, or both. Consequently, the cross-Strait relations are a controversial issue because people have no agreement about whether Taiwan is part of China. It is also found that national identity strongly influences partisan choice. Therefore, it is important to keep track of national identity and its related issues. Beyond national identity, searching for consensus on socioeconomic issues has been an important task. It is widely believed that cross-cut social cleavages benefit democracy because the mass public has diversified opinions. Therefore, it is necessary to examine public opinions and drew possible consensus on the sub-national level, such as county or election districts. We aim to develop a multilevel Bayesian model that combines both polling and census data, thereby we can evaluate sub-level public opinions, such as county and township. The previous project that predicts the 2004 presidential results is extended to the legislative election in 2007, which will use single-member district. Our Bayesian analysis can simulate enough samples from each of the two-wave national polling data included in this project, predicting public opinions of every county and legislative district. After estimating the influence of each parameter, we use poststratification technique to predict behavior of sub-levels, such as party vote share of each county. The Ministry of Interior collected census data in 2000, which allows us to calculate the proportion of every category, such as gender, age, and education. Moreover, we can fit varying models with different dependent variables, such as multi-nomial logistic regression model.We also manage to collect the budgets of local governments and calculate the association between the budget and public opinions. In doing so, we can show the degree to which the local governments are responsive to public opinions. Additionally, we will code candidates』 issue positions printed on the election bulletin. With the simulated public opinion data, we can examine the extent to which the point of view of candidates is congruent public opinion. This project will contributes to finding public opinions at the local level, measuring representation, and predicting voting shares of the small districts. |
