I teach two eight-week courses in the first-year econometrics core sequence of the economics Ph.D. program at Clemson University. The courses introduce graduate-level linear regression and empirical design for causal inference. Both courses provide empirical applications and version control and statistical-software training.

In the Spring of 2022, I am hosting Econ 899-02, a reading group for Econ Ph.D. students. We are studying advanced tools for causal inference and policy evaluation. The reading group has four modules: difference in differences, synthetic cohort, instrumental variables, and dynamic panel models.

At Clemson, I have also taught a course on the economics of education for undergraduate and M.A. students and a Ph.D. course on microeconometrics for labor economics.

Econ 900-02: Econometrics I (first-year Econ Ph.D. sequence)—Ph.D. Course

This course provides a primer on graduate-level regression analysis. The course covers mathematical, statistical, mechanical, and computational intrinsic details of linear regression. The course offers several empirical applications. It provides version control and statistical-software training.

Econ 900-03: Econometrics II (first-year Econ Ph.D. sequence)—Ph.D. Course

This course provides an introduction to empirical design for causal inference. Building on the material of Econ-900-02, it discusses methods for policy evaluation and identification of causal effects. The course offers several empirical applications. It provides version control and statistical-software training.

Econ 899-02: Econometrics II (Econ Ph.D.)—Ph.D. Reading Group

This reading group studies advanced tools for causal inference and policy evaluation. The four modules study generalizations of standard uses of difference-in-difference, instrumental variables, synthetic cohort, and dynamic panels models. Examples of the topics covered include difference in differences with variation in the timing of treatment, identification of marginal treatment effects using instrumental variables, dynamic synthetic controls, and moment estimators in panel settings.

Econ 816: Microeconometrics for Labor Economics—Ph.D. Course

Econ 411/611: Economics of Education—Undergraduate and M.A. Course