Type of Credit: Required
Credit(s)
Number of Students
This first-year economics course delves into econometric principles and methods. It begins with Matrix Algebra as a fundamental tool for handling economic data, followed by Least Squares and Normal Regression to establish the basis for regression analysis. The course then explores Heteroskedasticity, Time Series Analysis, and Vector Autoregression.
Additionally, the syllabus aims to cover advanced topics like Panel Data Models, Maximum Likelihood Estimation, and Quantile Regression, depending on time availability. The course emphasizes real-world applications to prepare students for practical research and encourages active engagement with the material for success.
能力項目說明
CourseOutlines:
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
|---|---|---|
1. Matrix Algebra
2. Least Squares Regression
3. Normal Regression
4. Heteroskedasticity
5. Time Series and Vector Autoregression
6. Panel Data Models
7. Maximum Likelihood Estimation
8. Quantile Regression
Throughout the semester, students will be tasked with a series of homework assignments, undergo three examinations, and complete one culminating term project.
The grading structure for the course is as follows:
1. Three exams: 75%
2. Homework assignments: 10%
3. Term project: 15%