Fall 2020 - ECON 837 G100

Econometrics I (4)

Class Number: 2216

Delivery Method: In Person

Overview

  • Course Times + Location:

    Tu 12:30 PM – 3:20 PM
    REMOTE LEARNING, Burnaby

  • Prerequisites:

    ECON 835 or equivalent.

Description

CALENDAR DESCRIPTION:

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 DETAILS:

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.

Grading

  • Assignments 20%
  • Midterm exam 35%
  • Final exam 45%

Materials

REQUIRED READING:

None.

RECOMMENDED READING:

  1. Hogg, Craig and McKean, 2018, "Introduction to Mathematical Statistics," 8th edition, Pearson.
  2. Casella and Berger, 2002, “Statistical Inference”, Second Edition, Cengage Learning. (ebook)
  3. Cameron and Trivedi, 2005, “Microeconometrics: Methods and Applications”, Cambridge University Press.
  4. Li, Q., & Racine, J. S. 2007, “Nonparametric econometrics: theory and practice”, Princeton University Press.

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.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site 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

TEACHING AT SFU IN FALL 2020

Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).