Course Description
This course will cover a wide variety of econometric tools to conduct empirical economic analysis. Topics include ordinary least squares, generalized least squares, instrumental variables, discrete responses and panel data, etc. All methods will be illustrated using R or Eviews. Students are supposed to be familiar with basic concepts in matrix algebra and probability theory to be enrolled in this course.
Course Materials
Text:
Jeffery M. Wooldridge, 2008, Introductory Econometrics: A Modern Approach, (4e), Cengage Learning
Academic Integrity
Dishonesty includes cheating on a test, falsifying data, misrepresenting the work of others as your own (plagiarism, or improper citation of sources), and helping another student cheat or plagiarize. At the very least, an academic honesty infraction will result in the filing of a violation report and a grade of zero on that particular assignment; serious or repeated infractions of the Academic Honesty policy will result in failure of the course.
Course Requirements
Practical Projects: 30%
Midterm Exam: 30%
Final Exam: 40%
There will be approximately two practical projects during the semester. In each of them, students are required to carry out an independent project using a given dataset and econometric models. A written report, which must contain the empirical results and detailed explanations, is due for each project. Late reports will not be accepted, and will result in grades of zero.
Write up your report individually and acknowledge those people and other sources that help you. If you directly copied from someone’s work, your project will receive a 0 grade.
Attendance, while not mandatory, is greatly encouraged. Although anyone who has missed lots of classes and is doing poorly in the course should not expect much sympathy from me. If you do miss a class, it is your responsibility to make up the material and make sure you are prepared for the exams.
Both midterm and final exams will be closed book/notes. Make-up exams will only be allowed if the absence is excused, such as illness, religious observance, or compelling reasons beyond the student's control. I must be notified in advance of the absence, or as soon as possible after the illness or emergency.
Tentative Course Outline
This course outline is preliminary; updates will be made through the term as needed.
Chapter 1: Review of probability theory
Chapter 2: Introduction to econometrics
Chapter 3: The simple regression model
Chapter 4: Ordinary least squares I: Estimation
Chapter 5: Ordinary least squares II: Inference
Chapter 6: Model specification
Midterm
Chapter 7: Dummy variables
Chapter 8: Generalized least squares I: Heteroskedasticity
Chapter 9: Generalized least squares II: Autocorrelation
Chapter 10: Instrumental variables
Chapter 11: Discrete responses
Chapter 12: Panel data model
Final
