Causal Inference/Estimating Treatment Effects Using Stata


This workshop provides an introduction to methods for estimating causal effects, also known as treatment effects, from observational data and how to perform them using Stata. All sessions are a mixture of lecture and hands-on practice using Stata. Both example data and simulation techniques will be used to build intuition for the covered methods.

This course assumes familiarity with the linear regression model and with the maximum-likelihood estimator of the probit model as explained in Wooldridge (2013). Some the material covered is discussed in Wooldridge (2010, Chapter 21), but the course also covers methods pulled from biostatistics and other areas.

Calculus, linear algebra, basic probability theory, and basic mathematical statistics are used through out the course. Mathematical derivations and Monte Carlo simulations techniques are also used through out the course. This course goes beyond interpreting Stata output, although this topic is also covered.

This course provides an introduction to modern methods of causal inference. You must be willing and able to understand mathematics and computational methods to participate in this course.

Fee: Members = $1500; Non-members = $2800

Tags: causal inference, Stata, treatment effects

Course Sections