Knowledge of causal effects is of great importance to decision makers in a wide variety of settings. In many cases, however, these causal effects are not known to the decision makers and need to be estimated from data. This fundamental problem has been known and studied for many years in many disciplines. In the past thirty years, however, the amount of empirical as well as methodological research in this area has increased dramatically, and so has its scope. It has become more interdisciplinary, and the focus has been more specifically on methods for credibly estimating causal effects in a wide range of both experimental and observational settings. This work has greatly impacted empirical work in the social and biomedical sciences. In this article, I review some of this work and discuss open questions.

中文翻译：

---

社会科学中的因果推理


了解因果效应对于各种环境中的决策者来说非常重要。然而，在许多情况下，决策者不知道这些因果效应，需要根据数据进行估计。这个基本问题在许多学科中已经被认识和研究了很多年。然而，在过去的 30 年里，该领域的实证和方法论研究的数量急剧增加，其范围也急剧增加。它变得更加跨学科，重点更具体地放在在各种实验和观察环境中可信地估计因果效应的方法上。这项工作极大地影响了社会和生物医学科学的实证工作。在本文中，我将回顾其中一些工作并讨论开放性问题。