ECON 2120 Principles of Econometrics
2025 Fall
Linear predictor as approximation to conditional expectation function. Least-
squares projection as sample counterpart. Splines. Omitted variable bias and panel data. Bayesian inference for parameters defined by moment conditions. Finite sample frequentist inference for the normal linear model. Statistical decision theory and dominating least squares with many predictor variables; applications to estimating fixed effects (teacher effects, place effects) using panel data. Asymptotic inference in the generalized method of moments framework. Likelihood inference using information measures to define best approximations within parametric models. Instrumental variable models and the role of random assignment; applications include models of demand and supply and the evaluation of treatment effects.
Enrollment is limited to PhD students in the Economics Department, Business Economics program, and PEG program. Other students wanting to enroll in the course should contact the instructor.
Recommended Prep: probability at the level of Statistics 110; linear algebra.

ECON 2903 Early-Stage Research and Discussions on Econometrics
2025 Fall/2026 Spring
The goal of the Econometrics Clinic is to offer feedback on econometric questions that students encounter when writing research papers.

ECON 3003 Graduate Student Workshop in Econometrics
2025 Fall/2026 Spring
Participants discuss recent research in econometrics and present their own work in progress. Open to doctoral students in economics.

Seminar in Econometrics
2025 Fall/2026 Spring
Outside speakers and faculty present current research topics in theory and applications of econometrics.