Econometrics I

Class Notes

Professor W. Greene
Department of Economics
Office: MEC 7-90, Ph. 998-0876
Home page:

Abstract: This is an intermediate level, Ph.D. course in Applied Econometrics. Topics to be studied include specification, estimation, and inference in the context of models that include then extend beyond the standard linear multiple regression framework. After a review of the linear model, we will develop the asymptotic distribution theory necessary for analysis of generalized linear and nonlinear models. We will then turn to instrumental variables, maximum likelihood, generalized method of moments (GMM), and two step estimation methods. Inference techniques used in the linear regression framework such as t and F tests will be extended to include Wald, Lagrange multiplier and likelihood ratio and tests for nonnested hypotheses such as the Hausman specification test. Specific modelling frameworks will include the linear regression model and extensions to models for panel data, multiple equation models, and models for discrete choice.

Notes: The following list points to the class discussion notes for Econometrics I. These are Power Point (.pptx) files and pdf documents (.pdf).

1. Introduction: Paradigm of Econometrics (pptx) (pdf)

2. The Linear Regression Model: Regression and Projection (pptx) (pdf)

3. Linear Least Squares, Regression Fit, Transformations (pptx) (pdf)

4. Frisch-Waugh Theorem, Least Squares, Partial Regression and Partial Correlation (pptx) (pdf)

5. Regression Fit, Restricted Least Squares (pptx) (pdf)

6. Functional Form, Difference in Differences, Regression Discontinuity (pptx) (pdf)

7. Finite Sample Properties of Least Squares, Multicollinearity (pptx) (pdf)

8. Asymptotic Distributions, Delta Method, Partial Effects (pptx) (pdf)

9. Asymptotic Distribution Theory for Linear Regression, Wald Tests, Robust Inference (pptx) (pdf)
Asymptotic Distribution Theory for Linear Regression, Wald Tests, Robust Inference Partial Effects
(Additional notes on asymptotic distribution theory)

10. Interval Estimation, Prediction, Quantile Regression (pptx) (pdf)

11. Hypothesis Tests: Structural Break, Specification, Non-nested Models (pptx) (pdf)

12. Endogeneity, Instrumental Variables, Two Stage Least Squares, Treatment Effects (pptx) (pdf)
(Notes on IV - John Snow Cholera Study)

13. Instrumental Variables and Treatment Effects (pptx) (pdf)

14. The Generalized Regression Model (pptx) (pdf)

15. Panel Data Modeling (pptx) (pdf)

16. Linear Models for Panel Data, Applications (pptx) (pdf)

17. Two Step Estimation and Sample Selection Models (pptx) (pdf)

18. Nonlinear Regression (pptx) (pdf)

19. Maximum Likelihood Estimation, Binary Choice (pptx) (pdf)

20. MLE, Count Data, Stochastic Frontier (pptx) (pdf)

21. Generalized Method of Moments - GMM and Minimum Distance Estimation (pptx) (pdf)

22. Time Series Data (pptx) (pdf)

23. Monte Carlo Methods: Simulation Based Estimation (pptx) (pdf)

24. Monte Carlo Methods: Bayesian Analysis (pptx) (pdf)