Fall 2022 - ECON 837 G100
Econometrics I (4)
Class Number: 3648
Delivery Method: In Person
Develops a foundation for econometric theory and applied econometrics. Topics may include an introduction to measure and probability theory, integration and mathematical expectations, stochastic limit theory, asymptotic theory, mathematical statistics, multiple linear regression, and an introduction to GMM and maximum likelihood estimation.
COURSE-LEVEL EDUCATIONAL GOALS:
This course is an introduction to probability theory and statistical inference designed for first year economics Ph.D. students. Students are expected to have taken calculus, linear algebra and some introductory probability and statistics.
Topics: Probability Theory; Measure Theory; Identification; Statistical Inference.
- Assignments 20%
- Midterm 35%
- Final Exam 45%
- Hogg, Craig and McKean, 2018, "Introduction to Mathematical Statistics," 8th edition, Pearson.
- Casella and Berger, 2002, “Statistical Inference”, Second Edition, Duxbury.
- Cameron and Trivedi, 2005, “Microeconometrics: Methods and Applications”, Cambridge University Press.
- Li, Q., & Racine, J. S. 2007, “Nonparametric econometrics: theory and practice”, Princeton University Press.
REQUIRED READING NOTES:
Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html