ECON 7910

Econometrics I

Dr. Philip Shaw

Dealy Hall, East 522

Phone: 718-817-4048

Email: pshaw5@fordham.edu

Office Hours: Monday 2:00pm-3:30pm & Thursday 2:00pm-3:30pm on Zoom.

This class will begin with an exploration of the properties required to obtain causality in econometrics.  We will focus largely on the theoretical properties of conditional expectations operators and basic asymptotic theory applied to ordinary least squares (OLS), two-stage least squares (2SLS), and nonlinear methods such as discrete response models.    

The grading for the class breaks down as follows:

Midterm (40%)

Final Exam (40%)

Problem Sets (20%)

Textbooks:

Wooldridge, J., 2010. Econometric Analysis of Cross Section and Panel Data, MIT Press, Edition 2.

Course Outline:

I. Introduction

1. Causal Relationships and Ceteris Paribus Analysis

2. Conditional Expectations and Related Concepts in Econometrics

3. Basic Asymptotic Theory

II. Linear Models

4. Single-Equation Linear Model and Ordinary Least Squares Estimation

5. Instrumental Variables Estimation of Single-Equation Linear Models

6. Additional Single-Equation Topics

7. System Estimation of Instrumental Variables and Simultaneous Equations Models

III. Nonlinear Models and Related Topics

8. Binary Response Models

Where to get R: http://cran.wustl.edu/

Simple Commands in R

R-code Posted Below

R-Code for Moreira's CLR and IV Estimation

R-Code for Robust Standard Errors

Problem Sets:

PS1 PS2

Data Sets and Descriptions:

DOWNLOAD ENTIRE DATA SET BELOW:

Data Files in CSV Format

INDIVIDUAL DATA SETS:

MAURO1995

Additional Readings Posted Below

Instrumental Variables Estimation Additional Readings

Staiger, Douglas and Stock, James H., 1997. "Instrumental Variables Regression with Weak Instruments"., Econometrica, Vol. 65 (3), 557-586. Download Here!

Moreira, Marcelo., 2003. "A Conditional Likelihood Ratio Test for Structural Models"., Econometrica, Vol. 71 (4), 1027-1048. Download Here!

Lewbel, Arthur., 2012. "Using Heteroscedasticity to Indentify and Estimate Mismeasured and Endogenous Regressor Models"., Journal of Business & Economic Statistics, Vol. 30 (1), 67-80. Download Here!