Econometrics I


Math Notes

Course Description

This is an econometrics course for first-year PhD students and advanced undergraduates who are interested in doing quantitative research in the social sciences. The aim of the course is to teach you to use popular applied econometric methods while developing your theoretical understanding of those methods. Topics include least squares, asymptotic theory, hypothesis testing, instrumental variables, difference-in-differences, regression discontinuity, treatment effects, panel data, maximum likelihood, discrete choice models, machine learning, and model selection.

Problem Sets

Group Project Guidelines

Problem Set 1 (updated 9/16) Due 9/20

Problem Set 2 Due 10/4

Problem Set 3 Due 10/25

Problem Set 4 Due 11/15


1 - Introduction

2 - Math and Statistics Review

3 - Linear Regression

4 - Inference

5 - Extended Example: The Wage Equation

6 - Endogeneity and Internal Validity

7 - Experiments and Quasi-Experiments

8 - Instrumental Variables and GMM

9 - Panel Data

10 - Nonparametric Estimation with Kernels

11 - Maximum Likelihood


I thank Bill Greene, Chris Conlon, and Sharon Traiberman for sharing course materials that I have borrowed heavily from.