Estimating Causal Effects with Hidden Confounding using Instrumental Variables and Environments
利用工具变量与环境估计存在隐藏混杂的因果效应
Recent works have proposed regression models which are invariant across data collection environments. These estimators often have a causal interpretation under conditions on the environments and type of invariance imposed. One recent example, the Causal Dantzig (CD), is consistent under hidden confounding and represents an alternative to classical instrumental variable estimators such as Two Stage Least Squares (TSLS). In this work we derive the CD as a generalized method of…