Causal Inference Commands Overview in Stata

This guide provides an overview of the estimation commands in Stata that are specifically designed for causal inference. It details the various commands available, including teffects, stteffects, telasso, cate, lateffects, and others, along with the types of data and assumptions required for their application. The document outlines the statistics that can be estimated, such as average treatment effects (ATE), average treatment effects on the treated (ATET), and potential-outcome means (POM). Each command's requirements regarding outcome and treatment types are specified, including whether models for the outcome, treatment, or both must be defined. Additionally, the guide discusses the difference-in-differences commands and their application in estimating treatment effects from longitudinal data. The document serves as a comprehensive resource for researchers looking to apply causal inference methods using Stata commands.