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Contributions to causal inference for political science.

机译:对政治学因果推理的贡献。

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摘要

This thesis presents five independent essays that advance causal inference in political science. It is divided into a methodological and an empirical part.;The methodological part presents a suite of statistical techniques, called synthetic inference methods, that allows researchers to construct control groups that more accurately resemble the treated units than is possible by commonly used methods of covariate adjustment. Synthetic inference is based on the idea of using weighted averages of control units to create so-called synthetic comparison units or comparison groups that resemble either a single treated unit or a group of treated units in all relevant characteristics that may confound a comparison. The thesis develops two variants of synthetic inference for empirical settings that are typically encountered in political science: comparative case studies (essay 1, with Alberto Abadie and Alexis Diamond) and cross-sectional studies (essay 2). Both methodological essays demonstrate the methods in real world applications and provide companion software for implementation.;The empirical part of the thesis presents three original empirical studies that contribute answers to previously unanswered causal questions about (a) the financial rewards to serving in Parliament (essay 3, with Andy Eggers), (b) the impact of foreign free media on the stability of authoritarian regimes (essay 4, with Holger Kern), and (c) the impact of economic concerns on public attitudes toward immigration (essay 5). The empirical essays advance the debates in these substantive fields by combining newly collected data and a design-based approach to causal inference. Design-based inference provides an effective strategy to identify valid control groups in settings where statistical control is insufficient since units potentially differ on more characteristics than can be measured and controlled for in a statistical model.
机译:这篇论文提出了五篇独立的论文,它们促进了政治科学中的因果推理。它分为方法论部分和经验部分。方法论部分提供了一套统计技术,称为合成推理方法,该方法使研究人员能够构建比通常的协变量方法更准确地类似于治疗单位的对照组。调整。合成推断基于以下思想:使用控制单元的加权平均值来创建所谓的合成比较单元或比较组,这些比较组在可能混淆比较的所有相关特征中类似于单个已处理单元或一组已处理单元。本文针对政治学中通常遇到的经验背景提出了两种综合推论:比较案例研究(论文1,Alberto Abadie和Alexis Diamond)和横断面研究(论文2)。两种方法论论文均论证了实际应用中的方法并提供了用于实施的辅助软件。;论文的实证部分提出了三项原始实证研究,这些研究为先前未解决的因果关系问题提供了答案,这些因果关系是: 3,与安迪·艾格斯(Andy Eggers)合作,(b)外国自由媒体对威权政权稳定的影响(文章4,与霍尔格·科恩(Holger Kern)合作),以及(c)经济问题对公众对移民态度的影响(文章5)。通过结合新收集的数据和基于设计的因果推论方法,实证论文推动了这些实质性领域的争论。基于设计的推理提供了一种有效的策略,可以在统计控制不充分的环境中识别有效的控制组,这是因为单位的潜在差异可能超过统计模型中可以测量和控制的特征。

著录项

  • 作者

    Hainmueller, Jens.;

  • 作者单位

    Harvard University.;

  • 授予单位 Harvard University.;
  • 学科 Statistics.;Political Science General.;Mass Communications.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 263 p.
  • 总页数 263
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 统计学;政治理论;传播理论;
  • 关键词

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