Simon Fraser University
Engaging the World

Course Outlines

Fall 2021 - ECON 832 G100

Computational Methods in Economics (4)

Class Number: 3216

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 8 – Dec 7, 2021: Wed, 11:30 a.m.–2:20 p.m.
    Burnaby

  • Prerequisites:

    ECON 802, 807 or 808, or with the approval of the instructor.

Description

CALENDAR DESCRIPTION:

The first part of the course will focus on dynamic optimization problems, with an emphasis on dynamic programming. Applications may include growth, business cycles, monetary and fiscal policy, and optimal contracts. The second part of the course will focus on models of learning and bounded rationality. Genetic and stochastic approximation algorithms will be studied. Applications may include the stability of rational expectations equilibria, the evolution of institutions and social conventions, and models of robust control and Knightian uncertainty.

COURSE DETAILS:

This class will focus on a number of topics in the area of computational economics. These will include studying learning, adaptation and agent-based economics in a variety of micro and macroeconomic environments. These include, among others, models of growth, exchange rate behavior, monetary policy, financial markets, game theoretic environments, auctions, voluntary contribution mechanisms. We will also study how we can test the predictions of these models through the analysis of real world data as well as through experiments with human subjects. Computational methods that we will use include evolu- tionary algorithms, q-learning, neural networks, deep learning, and other machine learning algorithms.

There will be a list of readings for the class which can be accessed through SFU library’s electronic journals collection and working papers that are available on line.

Reading List: not exhaustive

  1. Bounded rationality and adaptive behavior
  1. Economics as an experimental science
  1. Adaptation in Cournot model
  1. Social Individual Learning
  1. Evolution of cooperation
  1. Strategic thinking and heterogeneity
  1. Principal-agent problems, credit markets, growth and development
  1. Heterogenous agent models in finance: asset pricing, exchange rates
  1. Bubbles, crashes, bank runs, currency crises
  1. Money and monetary
  1. Mechanism design: provision of public goods, call markets, auctions, principal- agent models

Grading

  • Midterm exam 35%
  • Class assignments and presentations 25%
  • Class discussion 10%
  • Term paper 30%

Materials

RECOMMENDED READING:

Handbook of Computational Economics, Agent-Based Computational Economics, Volume 2, eds. L. Tesfatsion and K. Judd, North-Holland, 2006.

Applied Computational Economics and Finance, M. Miranda, and P.L. Fackler, The MIT Press, 2002.


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 2021

Teaching at SFU in fall 2021 will involve primarily in-person instruction, with approximately 70 to 80 per cent of classes in person/on campus, with safety plans in place.  Whether your course will be in-person or through remote methods 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 fall 2021 term.