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.Expected final online publication date for the Annual Review of Statistics and Its Application, Volume 11 is March 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译：

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社会科学中的因果推理

了解因果效应对于各种环境下的决策者都非常重要。然而，在许多情况下，决策者并不知道这些因果效应，需要根据数据进行估计。这个基本问题已经在许多学科中被了解和研究了很多年。然而，在过去的三十年里，这一领域的实证研究和方法论研究的数量急剧增加，其范围也随之扩大。它已经变得更加跨学科，并且重点更具体地集中在在广泛的实验和观察环境中可靠地估计因果效应的方法。这项工作极大地影响了社会科学和生物医学领域的实证工作。在本文中，我回顾了其中的一些工作并讨论了一些悬而未决的问题。《统计及其应用年度回顾》第 11 卷的预计最终在线发布日期是 2024 年 3 月。请参阅 http://www.annualreviews.org/page/修订后的估计的期刊/出版物。