Course Description: This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Topics include statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of government policies and programs.
Course Objectives/ Student Learning Outcomes: Upon completion of this course, students will:
1. Be able to explain the assumptions of the simple and multiple linear regression models,
2. Be able to understand and apply proper econometric models to answer economic questions,
3. Be able to test theories about the true model using formal hypothesis tests,
4. Learn how to communicate the results of econometric analysis in a clear way,
5. Learn how to use statistical software to apply all of these statistical techniques to analyze the relationship between real-world economic variables

Microeconomics (CMEF 302) recommended, but not required.
- Understanding of Demand and Supply curve will be more than enough.

High-school level knowledge on Calculus, Linear Algebra, and probability

10 homework assignments 50%
2 Exams 40%
Attendance 10%

1. Introductory Econometrics: A Modern Approach. Jeffery M. Wooldridge. Cengage Learning
2. I will also provide more references when needed.

Topics to be Covered:
1. Fundamentals of Probability
2. Review of R Software to conduct econometric analysis
3. Simple Regression
4. Multiple Regression
5. Heteroskedasticity
6. Instrumental Variables
7. Simultaneous Equations Models
8. Time Series
9. Panel Data

Grading and Evaluation Procedures:
10 homework assignments 50%
2 Exams 40%
Attendance 10%

Major Teaching Methods: Lecture and Hands-on Practices
Special Instructional Platforms/Materials: None
Notice: No deadline extensions on homework assignment will be given unless prior approval to reschedule has been given by the instructor.