FIN 704 Econometric Theory and Applications

Course Catalog Description


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


Professor Email Office
Victor Xi Luo Babbio Center 620

More Information

Course Outcomes

By the end of this course, the students will be able to:

  1. Understand the fundamental concepts of econometrics from a theoretical perspective.
  2. Apply econometric models to solve major research problems in economics, finance, and the main business areas.
  3. Recognize the value and also the limits of econometrics to solve business problems.

Course Resources


  • 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 Policies

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