FIN 704 Econometric Theory and Applications
Course Catalog Description
Introduction
This course serves as a bridge between an introduction to the field of econometrics and the literature for professionals in the fields of business and social sciences, focusing on applied econometrics and theoretical background. The topics presented in the course provide a rigorous grounding in key aspects of the field of econometrics that allows the student to move from these topics to practice in one or more specialized economics or business areas. At the same time, the student will gain an appreciation of the common foundation of the topics presented.
Prerequisites: School of Business PhD students or MGT700 Econometrics. Note: the course strongly emphasizes on econometric theory and advanced empirical research applications.
| Campus | Fall | Spring | Summer |
|---|---|---|---|
| On Campus | X | X | |
| Web Campus | X | X |
Instructors
| Professor | Office | |
|---|---|---|
|
Victor Xi Luo
|
victor.luo@stevens.edu | Babbio Center 620 |
More Information
Course Outcomes
By the end of this course, the students will be able to:
- Understand the fundamental concepts of econometrics from a theoretical perspective.
- Apply econometric models to solve major research problems in economics, finance, and the main business areas.
- Recognize the value and also the limits of econometrics to solve business problems.
Course Resources
Textbook
- W.H. Greene, Econometric Analysis, 7th Edition, Pearson, 2012. (Required).
- Peter Kennedy, A Guide to Econometrics, 6th Edition, 2008. (Recommended)
- John H. Cochrane, Asset Pricing, Revised Edition, 2005. (Recommended)
- Additional Reading Materials posted
Grading
Grading Policies
| Weights | ||
| 1 | Problem Sets | 35% |
| 2 | In Class Quizzes | 24% |
| 3 | Exams | 41% |
Lecture Outline
| Topic | Quiz | |
|---|---|---|
| Week 1 | Classical Econometrics (1/3) | No |
| Classical Econometrics (2/3) | Client Communication | Yes |
| Week 3 | Classical Econometrics (3/3) | No |
| Week 4 | Panel Data Models and Applications (1/2) | Yes |
| Week 5 | Panel Data Models and Applications (2/2) | No |
| Week 6 | Endogeneity Issues, Instrument Variables | Yes |
| Week 7 | MLE and GMM (1/2) | No |
| Week 8 | MLE and GMM (2/2) | Yes |
| Week 9 | Identification | No |
| Week 10 | Non-linear, Semi-, Non-parametric Models | Yes |
| Week 11 | Discrete Choice models | No |
| Week 12 | Limited Dependent Variables | Yes |
| Week 13 | Time Series and Macro/Finance Applications | Yes |
| Week 14 | State Space Models (Bayesian) | Yes |
| Week 15 | Final Exam TBD | No |