**Course Description:**

This course is a fundamental course in econometric theory. The course will open with regression models and their properties. Along the way, we will cover hypothesis testing, confidence intervals and bootstrap theory. We will also cover nonlinear regressions, generalized least squares, method of moments and instrumental variables estimation.The course will close with a look at discrete models, multivariate models, nonparametric regressions, and unit roots and cointegration. The primary aim of the course is to provide students with a sound understanding of econometric theory and prepare them for research positions in the field. Once you complete this course, your skill set will not only be of use in economics and finance, but in virtually any field which requires the use of regression analysis.

**Course Literature:**

**Required Textbook:****Suggested Textbook:****Course Notes:**

- Davidson and MacKinnon (2004)
- Bruce Hansen’s Econometrics Notes (2014)

Although you are responsible only for what is covered in class, you are encouraged to obtain at least the required text if for no other reason than to have access to additional practice problems.

**Course Software:**

Homework assignments may require the use of statistical software. The typical software of choice at this level is R, Matlab, STATA, or any other comparable software package. If you are not familiar with a programming language, you are strongly encouraged to begin learning as soon as possible. The T.A. will also be available to help you in this regard should you require assistance.

**Course Outline:**

- Linear Regressions
- Hypothesis Testing and Confidence Intervals
- Bootstrapping
- Nonlinear Regression
- Generalized Least Squares

- Instrumental Variables Estimation
- Generalized Method of Moments
- Discrete and Nonparametric Models
- Multivariate Models
- Unit Roots and Cointegration

**Grading:**

**Assignments:****Midterm:****Final Exam:**

- 30%
- 30%
- 40%

**Course Syllabus**

- Syllabus: