Causal Inference in Sociological Research
Causal Inference in Sociological Research
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DOI：
10.1146/annurev.soc.012809.102702
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发表时间：
2010-01-01
期刊：
影响因子：
--
通讯作者：
Gangl, Markus
中科院分区：
文献类型：
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作者：
Gangl, Markus
反事实模型起源于计量经济学和统计学，为澄清社会科学中有效因果推理的要求提供了一个自然的框架。本文介绍了潜在结果模型的基本概念，并讨论了社会科学研究中潜在结果识别的主要方法。然后，它解决的方法，无论是unconfoundedness或在存在不可测量的异质性的治疗效果的统计估计。作为对Winship & Morgan（1999）早期综述的更新，本文总结了最近的文献，其特点是更广泛的感兴趣的被估量，对利用实验和准实验设计的新兴趣，以及治疗效果的半参数和非参数估计，差异估计和工具变量估计领域的重要进展。评论的结论是突出了最近的计量经济学和统计学文献的社会学研究实践的影响。避免因果关系的语言时，因果关系是真实的主题，我们的调查要么使研究无关紧要，或允许它不受纪律的规则，科学推理。.相反，我们应该在适当的地方进行因果推论，但也要为读者提供对推论不确定性的最佳和最诚实的估计。(King等，1994，第76页）
Originating in econometrics and statistics, the counterfactual model provides a natural framework for clarifying the requirements for valid causal inference in the social sciences. This article presents the basic potential outcomes model and discusses the main approaches to identification in social science research. It then addresses approaches to the statistical estimation of treatment effects either under unconfoundedness or in the presence of unmeasured heterogeneity. As an update to Winship & Morgan's (1999) earlier review, the article summarizes the more recent literature that is characterized by a broader range of estimands of interest, a renewed interest in exploiting experimental and quasi-experimental designs, and important progress in the areas of semi- and nonparametric estimation of treatment effects, difference-in-differences estimation, and instrumental variable estimation. The review concludes by highlighting implications of the recent econometric and statistical literature for sociological research practice.Avoiding causal language when causality is the real subject of our investigation either renders the research irrelevant or permits it to be undisciplined by the rules of scientific inference .... Rather we should draw causal inferences where they seem appropriate but also provide the reader with the best and most honest estimate of the uncertainty of that inference. (King et al. 1994, p. 76)