Spring 2022 - ECON 838 G100

Econometrics II (4)

Class Number: 3842

Delivery Method: In Person

Overview

  • Course Times + Location:

    Fr 2:30 PM – 5:20 PM
    WMC 3611, Burnaby

  • Prerequisites:

    ECON 837.

Description

CALENDAR DESCRIPTION:

Develops the core tools of theoretical and applied econometrics including time series, cross sectional, and panel data methods. Topics may include limited dependent variable models, GMM, instrumental variables, ARMA models, unit roots and cointegration, fixed and random effects, incidental parameters, testing, program evaluation, nonlinear regression, semi- and nonparametric methods.

COURSE DETAILS:

Develops the core tools of theoretical and applied econometrics including limited dependent variable models, program evaluation, nonparametric and
semiparametric estimation, panel data methods and big data/machine learning methods.

Topics: Covered topics will include:
1. Limited dependent variable models (probit, logit, tobit and selection models)
2. Program evaluation (RCT, natural experiments, matching, instrumental variable
models, regression discontinuity design, and control function methods)
3. Generalized method of moment
4. Nonparametric and semiparametric estimation (kernel density estimator,
conditional mean function estimator, maximum score estimator and more)
5. Panel data methods (static and dynamic panel models)
6. Big data/machine learning (LASSO, regression trees and random forest)

Grading

  • Midterm 40%
  • Final Exam 60%

Materials

REQUIRED READING:

Li and Racine, 2017, “Nonparametric Econometrics” 

Angrist and Pischke, 2009, “Mostly Harmless Econometrics”

RECOMMENDED READING:

James, Witten, Hastie and Tibshirani, 2017, “An Introduction to Statistical Learning”

Wooldridge, 2010, “Econometric Analysis of Cross Section and Panel Data, Second Edition”

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 SPRING 2022

Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware 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.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.