Fall 2019 - ECON 837 G100

Econometrics I (4)

Class Number: 1024

Delivery Method: In Person

Overview

  • Course Times + Location:

    Mo 12:30 PM – 2:20 PM
    WMC 3611, Burnaby

    We 12:30 PM – 1:20 PM
    WMC 3611, Burnaby

  • Instructor:

    Xiaoting Sun
  • 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:

  1. Probability: Probability Spaces, Random Variables, Random Vectors, Distributions, Transformations, Special Distributions of the Discrete Type and of the Continuous Type;
  2. Statistics: Sample analogue estimation, maximum likelihood, Hypothesis testing;
  3. Asymptotics: Modes of Convergence, Law of Large Numbers, and Central Limit Theorem;
  4. Identification

Grading

  • Midterm exam 40%
  • Final exam 60%
  • There will be weekly problem sets that are discussed in the lecture.

Materials

REQUIRED READING:

Casella and Berger, 2001, “Statistical Inference”, 2nd Edition, Cengage Learning.

RECOMMENDED READING:

Cameron and Trivedi, 2005,Microeconometrics: Methods and Applications”, Cambridge University Press.

Hogg, Craig and McKean, 2018, "Introduction to Mathematical Statistics," 8th edition, Pearson.

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:

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

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS