Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 社會科學院
  3. 政治學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79666
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor張佑宗(Yu-tzung Chang)
dc.contributor.authorYU-HANG SIen
dc.contributor.author司宇航zh_TW
dc.date.accessioned2022-11-23T09:06:53Z-
dc.date.available2021-09-11
dc.date.available2022-11-23T09:06:53Z-
dc.date.copyright2021-09-11
dc.date.issued2021
dc.date.submitted2021-09-03
dc.identifier.citation壹、 中文部分 石之瑜. (2005). 消失的中間選民:2004年總統大選對空間理論的修正. 問題與研究, 44(4), 1-24. doi:10.30390/isc.200508_44(4).0001 朱雲漢. (2012). 2009 年至 2012 年「選舉與民主化調查」三年期研究規劃 (3/3): 2012 年總統與立法委員選舉面訪案. 計畫編號: NSC 100-2420. 徐火炎. (1991). 政黨認同與投票抉擇: 臺灣地區選民的政黨印象, 偏好與黨派投票行為之分析. 徐火炎. (2005). 認知動員、文化動員與台灣2004年總統大選的選民投票行為-選舉動員類型的初步探討. 臺灣民主季刊, 2(4), 31-66. 盛杏湲. (2002). 統獨議題與台灣選民的投票行為: 一九九○ 年代的分析. 選舉研究, 9(1), 41-80. 盛杏湲. (2008). 政黨的國會領導與凝聚力-2000 年政黨輪替前後的觀察. 臺灣民主季刊, 5(4), 1-46. 陳陸輝. (2006). 政治信任的政治後果―以 2004 年立法委員選舉為例. 臺灣民主季刊, 3(2), 39-61. 陳陸輝. (2018). 情緒政治與 2016 年總統選舉. 選舉研究, 25(2), 31-53. 游清鑫. (2008). 2005 年至 2008 年「選舉與民主化調查」四年期研究規劃 (IV): 2008年總統選舉面訪計畫案. 計畫編號: NSC96-2420-H004-017. 黃秀端. (2004a). 2002 年至 2004 年「選舉與民主化調查」三年期研究規劃 (III): 民國九十三年總統大選民調案. 計畫編號: NSC92-2420-H031-004. 黃秀端. (2004b). 政黨輪替前後的立法院內投票結盟. 選舉研究, 11(1), 1-32. 黃紀. (2016). 2012年至2016年「選舉與民主化調查」四年期研究規劃(4/4):2016年總統與立法委員選舉面訪案. 計畫編號: MOST 101-2420-H004-034-MY4. 黃紀. (2020). 2016年至2020年「選舉與民主化調查」四年期研究規劃(4/4):2020年總統與立法委員選舉面訪案. 計畫編號: MOST 105-2420-H-004-015-SS4. 楊舒喻. (2020). 立法院提案網絡之政黨合作結盟初探: 重大社會事件是否加劇政黨極化?. 臺灣大學公共事務研究所學位論文, 1-136. 蕭怡靖. (2014). 從政黨情感溫度計解析台灣民眾的政治極化. 選舉研究, 21(2), 1-42. 蕭怡靖. (2019). 台灣民衆的黨性極化及其對民主態度的影響. 台灣政治學刊, 23(2), 41-85. 蕭怡靖, 林聰吉. (2013). 台灣政治極化之初探: 測量與分析. 台北: 五南. 貳、 西文部分 黃紀. (2018). Testing Partisan Effects on Economic Perceptions: A Panel Design Approach. 選舉研究, 25(2), 89-115. Abramowitz, A. I., Saunders, K. L. (2008). Is Polarization a Myth? The Journal of Politics, 70(2), 542-555. doi:10.1017/s0022381608080493 Abramowitz, A. I., Stone, W. J. (2006). The Bush effect: Polarization, turnout, and activism in the 2004 presidential election. Presidential Studies Quarterly, 36(2), 141-154. Acar, E. F., Craiu, R. V., Yao, F. (2011). Dependence Calibration in Conditional Copulas: A Nonparametric Approach. Biometrics, 67(2), 445-453. doi:https://doi.org/10.1111/j.1541-0420.2010.01472.x Ane, T., Kharoubi, C. (2003). Dependence structure and risk measure. The journal of business, 76(3), 411-438. Bafumi, J., Shapiro, R. Y. (2009). A New Partisan Voter. The Journal of Politics, 71(1), 1-24. doi:10.1017/s0022381608090014 Baldassarri, D., Gelman, A. (2008). Partisans without Constraint: Political Polarization and Trends in American Public Opinion. American Journal of Sociology, 114(2), 408-446. doi:10.1086/590649 Bouyé, E., Salmon, M. (2009). Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets. The European Journal of Finance, 15(7-8), 721-750. Braun, M. T., Oswald, F. L. (2011). Exploratory regression analysis: A tool for selecting models and determining predictor importance. Behavior research methods, 43(2), 331-339. Caillault, C., Guégan, D. (2005). Empirical estimation of tail dependence using copulas: application to Asian markets. Quantitative Finance, 5(5), 489-501. doi:10.1080/14697680500147853 Carmines, E. G., Ensley, M. J., Wagner, M. W. (2012). Who Fits the Left-Right Divide? Partisan Polarization in the American Electorate. American Behavioral Scientist, 56(12), 1631-1653. doi:10.1177/0002764212463353 Chiba, D., Martin, L. W., Stevenson, R. T. (2017). A Copula Approach to the Problem of Selection Bias in Models of Government Survival. Political Analysis, 23(1), 42-58. doi:10.1093/pan/mpu013 Clayton, D. G. (1978). A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika, 65(1), 141-151. doi:10.1093/biomet/65.1.141 Davison, A., Snell, E. (1991). Residuals and diagnostics. Statistical Theory and Mod. Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., . . . Leitão, P. J. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27-46. Druckman, J. N., Peterson, E., Slothuus, R. (2013). How Elite Partisan Polarization Affects Public Opinion Formation. American Political Science Review, 107(1), 57-79. doi:10.1017/s0003055412000500 Fang, Y., Madsen, L., Liu, L. (2014). Comparison of Two Methods to Check Copula Fitting. International Journal of Applied Mathematics, 44(1). Fiorina, M. P., Abrams, S. J. (2008). Political Polarization in the American Public. Annual Review of Political Science, 11(1), 563-588. doi:10.1146/annurev.polisci.11.053106.153836 Genest, C., Nešlehová, J. G., Rémillard, B. (2017). Asymptotic behavior of the empirical multilinear copula process under broad conditions. Journal of Multivariate Analysis, 159, 82-110. doi:https://doi.org/10.1016/j.jmva.2017.04.002 Genius, M., Strazzera, E. (2008). Applying the copula approach to sample selection modelling. Applied Economics, 40(11), 1443-1455. Goda, K. (2010). Statistical modeling of joint probability distribution using copula: Application to peak and permanent displacement seismic demands. Structural Safety, 32(2), 112-123. doi:https://doi.org/10.1016/j.strusafe.2009.09.003 Grömping, U. (2015). Variable importance in regression models. Wiley interdisciplinary reviews: Computational statistics, 7(2), 137-152. Gumbel, E. J. (1960). Distributions des valeurs extremes en plusiers dimensions. Publ. Inst. Statist. Univ. Paris, 9, 171-173. Retrieved from https://ci.nii.ac.jp/naid/10011938344/en/ Hall, P., Racine, J., Li, Q. (2004). Cross-validation and the estimation of conditional probability densities. Journal of the American Statistical Association, 99(468), 1015-1026. Hao, L., Naiman, D. Q., Naiman, D. Q. (2007). Quantile regression: Sage. Hetherington, M. J. (2001). Resurgent Mass Partisanship: The Role of Elite Polarization. The American Political Science Review, 95(3), 619-631. Retrieved from http://www.jstor.org/stable/3118237 Hsiao, Y.-c., Yu, E. C.-h. (2020). Polarization Perception and Support for Democracy: The Case of Taiwan. Journal of Asian and African Studies, 55(8), 1143-1162. doi:10.1177/0021909620911150 Iyengar, S., Sood, G., Lelkes, Y. (2012). Affect, not ideologya social identity perspective on polarization. Public opinion quarterly, 76(3), 405-431. Jacobson, G. C. (2012). The Electoral Origins of Polarized Politics. American Behavioral Scientist, 56(12), 1612-1630. doi:10.1177/0002764212463352 Jacoby, W. G. (2009). Ideology and vote choice in the 2004 election. Electoral Studies, 28(4), 584-594. doi:10.1016/j.electstud.2009.05.021 Joe, H. (1997). Multivariate Models and Multivariate Dependence Concepts: Taylor Francis. Joe, H., Kurowicka, D. (2011). Dependence modeling: vine copula handbook: World Scientific. Jordanger, L. A., Tjøstheim, D. (2014). Model selection of copulas: AIC versus a cross validation copula information criterion. Statistics Probability Letters, 92, 249-255. Körösényi, A. (2013). Political polarization and its consequences on democratic accountability. Corvinus Journal of Sociology and Social Policy, 4(2). doi:http://dx.doi.org/10.14267/cjssp.2013.02.01 Keele, L., Stevenson, R. T., Elwert, F. (2020). The causal interpretation of estimated associations in regression models. Political Science Research and Methods, 8(1), 1-13. Lau, R. R., Redlawsk, D. P. (1997). Voting Correctly. The American Political Science Review, 91(3), 585-598. doi:10.2307/2952076 Layman, G. C., Carsey, T. M., Horowitz, J. M. (2006). Party polarization in American politics: Characteristics, causes, and consequences. Annu. Rev. Polit. Sci., 9, 83-110. Lee, L.-F. (1983). Generalized Econometric Models with Selectivity. Econometrica, 51(2). doi:10.2307/1912003 Levendusky, M. S. (2010). Clearer cues, more consistent voters: A benefit of elite polarization. Political Behavior, 32(1), 111-131. doi:10.1007/s11109-009-9094-0 Lu, X. (2020). Discrete Choice Data with Unobserved Heterogeneity: A Conditional Binary Quantile Model. Political Analysis, 28(2), 147-167. doi:10.1017/pan.2019.29 Mason, L. (2012). The Rise of Uncivil Agreement. American Behavioral Scientist, 57(1), 140-159. doi:10.1177/0002764212463363 Mason, L. (2015). “I Disrespectfully Agree”: The Differential Effects of Partisan Sorting on Social and Issue Polarization. American Journal of Political Science, 59(1), 128-145. doi:https://doi.org/10.1111/ajps.12089 McCoy, J., Rahman, T., Somer, M. (2018). Polarization and the Global Crisis of Democracy: Common Patterns, Dynamics, and Pernicious Consequences for Democratic Polities. American Behavioral Scientist, 62(1), 16-42. doi:10.1177/0002764218759576 Nagler, T. (2018). A generic approach to nonparametric function estimation with mixed data. Statistics Probability Letters, 137, 326-330. doi:https://doi.org/10.1016/j.spl.2018.02.040 Niemi, R. G., Weisberg, H. F., Kimball, D. C. (2011). Controversies in voting behavior / edited by Richard G. Niemij, Herbert F. Weisberg, David C. Kimball (5th ed. ed.). Washington, D.C: CQ Press. Nikoloulopoulos, A. K. (2013). On the estimation of normal copula discrete regression models using the continuous extension and simulated likelihood. Journal of Statistical Planning and Inference, 143(11), 1923-1937. doi:https://doi.org/10.1016/j.jspi.2013.06.015 Pierce, D. R., Lau, R. R. (2019). Polarization and correct voting in U.S. presidential elections. Electoral Studies, 60, 102048. doi:https://doi.org/10.1016/j.electstud.2019.102048 Poole, K. T., Rosenthal, H. (1984). The Polarization of American Politics. The Journal of Politics, 46(4), 1061-1079. doi:10.2307/2131242 Poole, K. T., Rosenthal, H. (2000). Congress: A Political-economic History of Roll Call Voting: Oxford University Press. Robison, J., Mullinix, K. J. (2016). Elite Polarization and Public Opinion: How Polarization Is Communicated and Its Effects. Political Communication, 33(2), 261-282. doi:10.1080/10584609.2015.1055526 Rogowski, J. C., Sutherland, J. L. (2015). How Ideology Fuels Affective Polarization. Political Behavior, 38(2), 485-508. doi:10.1007/s11109-015-9323-7 Song, P. X., Li, M., Yuan, Y. (2009). Joint regression analysis of correlated data using Gaussian copulas. Biometrics, 65(1), 60-68. doi:10.1111/j.1541-0420.2008.01058.x Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society: Series B (Methodological), 58(1), 267-288. Wang, A. H. E. (2019). The myth of polarization among Taiwanese voters: The missing middle. Journal of East Asian Studies, 19(3), 275-287. Webster, S. W., Abramowitz, A. I. (2017). The Ideological Foundations of Affective Polarization in the U.S. Electorate. American Politics Research, 45(4), 621-647. doi:10.1177/1532673x17703132 Wichitaksorn, N. (2012). Estimation of bivariate Copula-based seemingly unrelated Tobit models. Available at SSRN 2122388. Zhou, X. (2019). Hierarchical Item Response Models for Analyzing Public Opinion. Political Analysis, 27(4), 481-502. doi:10.1017/pan.2018.63 Zimmer, D. M., Trivedi, P. K. (2006). Copula Modeling: An Introduction for Practitioners. Foundations and Trends® in Econometrics, 1(1), 1-111. doi:10.1561/0800000005 Zou, H. (2006). The adaptive lasso and its oracle properties. Journal of the American Statistical Association, 101(476), 1418-1429.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79666-
dc.description.abstract本文以2004年至2020年間五次台灣選舉作為研究對象,通過測量意識形態在選民投票行為中的的重要性,探討了兩個研究問題:一、台灣選民是否逐漸出現了意識形態極化的現象?二、當選民感受到國民黨和民進黨之間存在顯著的立場差異時,是否影響了選民投票時對於意識形態因素的考量? 考虑到意識形態和投票行為是一種非線性的關係,本文選擇了目前在政治學界被較少使用的Copula函數作為研究方法,用以測量相關性及尾部依賴情況。再通過Probit模型和经过調整後適用於二元類別變數的條件Copula模型,查看精英極化是否對選民極化產生了作用。 研究結果發現,雖然2012年後出現了緩慢的上升趨勢,但整體上意識形態因素的重要性呈現出了「波動性」的變化。其次,選民對於精英極化的感知確實影響了選民的投票決策,認為兩黨之間意識形態立場差距較大的選民更看重意識形態因素,但是其影響程度在不同選舉、不同程度的「精英極化感知」中差別較大。綜合來看,目前沒有充分證據顯示台灣選民出現了意識形態極化的趨勢。zh_TW
dc.description.provenanceMade available in DSpace on 2022-11-23T09:06:53Z (GMT). No. of bitstreams: 1
U0001-3108202121252300.pdf: 1986101 bytes, checksum: 27d4c7a95a7402f9d501bfcf5df1bd1a (MD5)
Previous issue date: 2021
en
dc.description.tableofcontents口試委員會審定書 I 謝 辭 II 中文摘要 III 英文摘要 IV 第一章 緒論 1 第一節 研究動機 1 第二節 文獻回顧 2 第三節 研究設計 9 第四節 章節安排說明 12 第二章 研究方法 15 第一節 研究模型 15 第二節 投票模型設定 21 第三節 蒙特卡羅模擬 24 第四節 資料來源及變數設定 31 第五節 實際數據應用中的模型修正 32 第三章 實證分析 35 第一節 描述性統計 35 第二節 選民意識形態極化分析 41 第三節 精英極化的影響分析 44 第四章 結論 49 第一節 研究主要發現 49 第二節 研究缺失與未來研究方向 49 參考資料 53 附 錄 59
dc.language.isozh-TW
dc.title意識形態、精英極化與選民投票抉擇:以Copula函數分析zh_TW
dc.title"Ideology, Elite Polarization and Voting Choices of Voters: Analysis with Copula Model"en
dc.date.schoolyear109-2
dc.description.degree碩士
dc.contributor.oralexamcommittee俞振華(Hsin-Tsai Liu),張傳賢(Chih-Yang Tseng)
dc.subject.keyword政治極化,意識形態,台灣選舉,尾部依賴,Copula函數,zh_TW
dc.subject.keywordPolitical Polarization,Ideology,Taiwan Elections,Tail Dependence,Copula Function,en
dc.relation.page70
dc.identifier.doi10.6342/NTU202102918
dc.rights.note同意授權(全球公開)
dc.date.accepted2021-09-06
dc.contributor.author-college社會科學院zh_TW
dc.contributor.author-dept政治學研究所zh_TW
顯示於系所單位:政治學系

文件中的檔案:
檔案 大小格式 
U0001-3108202121252300.pdf1.94 MBAdobe PDF檢視/開啟
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved