Type of Credit: Required
Credit(s)
Number of Students
此課程不加簽。
This course is application driven. We will introduce basic econometric methods to details, but only limited amount of derivation will be included. During the course of the semester, you will also build up your SAS skills toward portfolio construction and data processing skills.
能力項目說明
This course will introduce basic econometric methods which are used to analyze data in finance and other social sciences. The purpose of this course is to equip students with ability to understand empirical analyses presented to them and to conduct empirical research of their own.
| 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 |
|---|---|---|
Week 1 Introduction
Week 2 Simple Regression Model
Week 3 Simple Regression Model; Multiple Regression Analysis: Estimation
Week 4 Multiple Regression Analysis: Estimation
Week 5 Multiple Regression Analysis: Inference
Week 6 Qualitative Information
Week 7 Heteroskedasticity
Week 8 Panel Data Models
Week 9 Limited Dependent Variable Models
Week 10 Midterm Exam
Week 11 Regression with Time Series Data
Week 12 Further Time Series Issues
Week 13 Serial Correlation and Heteroskedasticity in OLS
Week 14 Serial Correlation and Heteroskedasticity in OLS
Week 15 IV and 2SLS
Week 16 IV and 2SLS
Week 17 More data collection, cleaning, and manipulation issues
Week 18 Final Exam
Homework 40%: reproduce parts of three to four papers and present them in class
Midterm Exam 30%: paper and pencil exam
Final Exam 30%: paper and pencil exam
Please hand in your homework in PDF format on Moodle.
Textbook:
Wooldridge (2020) Introductory Econometrics: A Modern Approach, the 7th edition
Reference:
Brooks (2008) Introductory Econometrics for Finance, 2nd Edition.
Boehmer, Broussard and Kallunki (2002) Using SAS in Financial Research
Please see the course page on Moodle.