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    Title: 因果推論與效應評估:區段識別法及其於「選制效應」之應用
    Other Titles: Causal Inference and Treatment Effect Evaluation: Partial Identification Approach and Its Application to Electoral System Effect
    Authors: 黃紀
    Huang, Chi
    Contributors: 政大政治系
    Keywords: 因果推論;內因性問題;區段識別;混合選制;污染效應
    Causal inference;Endogeneity problem;Partial identification;Mixed-member electoral systems;Contamination effect
    Date: 2010-11
    Issue Date: 2013-06-21 10:34:01 (UTC+8)
    Abstract: 社會科學中涉及效應評估的問題,都無法迴避因果推論。以觀察研究進行因果推論之所以棘手,癥結在於比較研究的組別,往往取決於因和果之間的內部因素,也就是所謂「內因性」(endogeneity),造成平均因果效應的識別問題。一般分析因果效應的參數模型 (parametricmodels),雖有考慮內因問題,但多建立在很特定的函數形式及變數分佈等假定之上。如果研究的主題及資料的確符合這些假定,自可充分運用;但社會科學研究也常常會碰到與假定不符的情況,此時 Manski 的無母數局部識別法 (nonparametric partial identification) 最為適合,因為這個方法從無假定出發,逐步帶入不同強度的假定,檢視其對於參數區段的影響,將假定與推論之間的關係完全透明化,避免為了達到「定點識別」而強加或暗藏與實際不符的假定,導致過當的推論。本文從「反事實因果模型」(counterfactual model of causality) 的角度,以最基礎的邏輯與機率論,探討 Manski 的區段識別法,及各種學理假定與「平均因果效應」之上下限的關係,並以 2008 年立委選舉台聯提名區域立委對其政黨票得票率之影響為例,將區段識別法應用於分析混合選制中所謂之「污染效應」(contamination effect)。
    Relation: 選舉研究, 17(2), 103-134
    Data Type: article
    Appears in Collections:[Department of Political Science] Periodical Articles

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