学习因果推断

因果推断的知识学习

因果推断的理论与技术，在不同学科的努力下，在近20、30年得到了充分发展，虽然有术语和哲学基础上会有一些分歧，但是基本的原则上的共识已然形成，学习因果推断技术，除了专门的文章之外，比如工具变量技术，有大量的理论和实证文章，也形成一些很好的教材。以下作一简要介绍，材料以计量经济、流行病学和计算机科学三个学科视角进行划分。

Econometric视角下的因果推断

Angrist 和Pischke的两本经典著作。Imbens和Rubin的理论性著作。最新Cunningham和Huntington-Klein是最新的集成之作，提供了相应的代码。

• Angrist, Joshua D., and Jörn-Steffen Pischke. Mastering Metrics: The Path from Cause to Effect, 2015.

• Joshua D. Angrist and Jörn-Steffen Pischke, Mostly Harmless Econometrics

• Imbens, Guido W., and Donald B. Rubin. Causal Inference for Statistics, Social, and Bio-medical Sciences: An Introduction. 2015.

• Cunningham, Scott. Causal Inference: The Mixtape

• The Effect: An Introduction to Research Design and Causality

Epistemology视角下的因果推断

• Causal Inference: What If

• Morgan, Stephen L., and Christopher Winship. Counterfactuals and Causal Inference: Methods and Principles for Social Research, 2014.

• VanderWeele, Tyler. Explanation in Causal Inference, 2015.

Computer Science视角下的因果推断

• Pearl, Judea. The Book of Why: The New Science of Cause and Effect. Basic Books. New York, 2018.

• Pearl, Judea. Causality: Models, Reasoning, and Inference, Second Edition. Second Edition, 2009.

• Pearl, Judea, Madelyn Glymour, and Nicholas P. Jewell. Causal Inference in Statistics: A Primer. Wiley, 2016.

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• Program Evaluation for Public Service