Lecture 1 - Course Logistics and Introduction to the OLS Model

Lecture 2 - Problem Set #0 Discussion, Gauss-Markov, Functional Forms,
Goodness of Fit, Dummy Variables

Lecture 3 - Problem Set #1 Discussion, Hypothesis Testing on Multiple Variables,
Heteroskedasticity, Mulitcollinearity, Omitted Variable Bias

Lecture 4 - Problem Set #2 Discussion, Heteroskedasticity, Serial Correlation Card & Krueger

Lecture 5 - Serial Correlation, Panel Data, Fixed/Random Effects

Lecture 6 - Problem Set #3 Discussion, Panel Data, Instrumental Variables

Lecture 7 - Mid-term and Introduction to Two-Stage Least Squares

Lecture 8 - Simultaneous Equations and Two-Stage Least Squares;
Angrist & Krueger Discussion

Lecture 9 - Problem Set #4 and Intro to Maximum Likelihood

Lecture 10 - Qualitative Dependent Variables

Lecture 11 - Problem Set #5, Distributed Lags, Granger Causality

Lecture 12 - Piece-wise Linear Regression Factor Analysis

Lecture 13 - Empirical Exercise Discussion and Wrap-up