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Welcome to the undergraduate Economics website for prospective and current students. On these pages, you will find information about our programs and courses, as well as other useful resources and links. Read more...

Why economics?

Wondering why to choose an economics program? We asked some of our students.

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In the News

Special Topics Courses: Fall 2022 & Winter 2023

Scheduling information is available on the Arts & Science Timetable.

ECO351H1F/S LEC0101 - Special Topics in Economics: Principles of Fair Decisions

How can we combine the well-being of individuals into a concept of societal well-being? What does it mean to balance conflicting interests fairly? We explore these and related ethical questions from the perspective of economic theory. By featuring the axiomatic approach as a central tool, we seek to develop fairness principles that are applicable across diverse situations. Possible topics include: Arrow's impossibility theorem, the Nash bargaining problem, foundations of utilitarianism and egalitarianism, fair division, measurement of inequality, intergenerational equity, and population ethics.

Prerequisites, in addition to those listed in the calendar: ECO200Y1(63%)/ECO204Y1(63%)/ECO206Y1

ECO352H1S LEC0101 - Special Topics in Economics: Macroeconomics and Psychology

The course will introduce some basic concepts from psychology (and sociology), that are relevant for economics. In the second half of the course we will apply the concepts to macroeconomic problems. I do not expect you to be familiar with psychology, but do expect you to have understanding of micro- and macroeconomics. By the end of the course the goal is that you have gained more appreciation for psychology and what it can add to economic thinking.

ECO353H1F/S LEC0101- Special Topics in Economics with Data Analytics: Sports Economics

This applied economics course used both theoretical and empirical analysis to explore aspects of the economics of sports and sports leagues. We start by considering the business of professional sports—how teams and leagues make money—and then delve into further topics including competitive-balance policies, athlete labour markets, and the relationship between professional leagues and their amateur counterparts (e.g., US university sports). Representative data assignments include exploring team profitability and athlete value.

ECO421H1F LEC0101 - Special Topics in Economics: Topics in Experimental Economics

Experimental Economics is a relatively new and very exciting field in Economics. While most data used in Economics is observational, experimentalists use controlled environments to study various economic issues: from individual decision making, to interaction in games and markets, to assets markets and even macroeconomic issues. This is a “hands-on” course. I will introduce you to a few topics I have been working on recently, and we will read a few related papers in class, with your active participation! Then we will discuss the experimental design in class, run the experiments together, and then you will get access to the real data, and in your papers, you will analyze it and draw conclusions. The two topics I hope to be able to cover this year involve rationality in games and a decision theoretic project. It would be helpful if you took a course in game theory to understand the former project, and have a good understanding of probability for the latter.

ECO421H1F LEC0201 - Special Topics in Economics: Competition Policy

The primary objective of this course is to provide a systematic analysis of economic issues in competition policy. This will include analysis of economic theory of antitrust as well as applications in policy documents and cases.

ECO480H1S LEC0101 -Special Topics in Economics with Data Analytics: Machine learning and data mining

Many important economic questions remain unanswered, partly because the data necessary to address them is encoded into high-dimensional data structures such as text or images. Applied economists have become increasingly interested in using machine learning models to transform these data into simpler representations, which can be used as inputs for subsequent economic analysis. After introducing statistical learning, this course provides a comprehensive understanding of some of the most capable supervised learning models including random forest, gradient boosted trees, or neural network architectures to make sense of these complex forms of data and perform original economic analysis. From a strong base in theory and mathematical formalisation, focus is kept on intuition and effective implementation using Python.

Prerequisites, in addition to those listed in the calendar: ECO375H1(60%)/ECO374H1(70%)/ECO220Y1(80%)/ECO227Y1(80%); CSC108H1/CSC148H1/ECO225H1/GGR272H1

ECO481H1F/S LEC0101 - Special Topics in Economics with Data Analytics: Macroeconomic Finance (with machine learning applications)

This course is an introductory course to different concepts and techniques related to Machine Learning, focusing mainly on Macro-finance applications. In the first part of the course, we will review supervised and unsupervised learning methods. In the second part, we will discuss various macro-finance concepts, where the use of Machine Learning is more and more common. Therefore, the course's objective is to provide students with the basics of machine learning for them to be able to solve certain economic problems using these techniques and be prepared for more advanced machine learning courses.

Special Topics Courses: Summer 2022

Scheduling information is available on the Arts & Science Timetable

ECO421H1F L5101 - Special Topics in Financial Risk Management

This course is intended to drill down into details of some important and urgent issues concerning contemporary financial industry. The topics may include: Economic Capital and Stress Testing, Business Performance Measurement, Emerging Capital Markets and Risks, Innovative and Exotic Derivatives in capital Markets and Risks; Asset securitization and Risks; Hedge Funds and Risks. Please note the topics chosen for each term are subject to changes. The instructor will use the real world problems for research projects and case studies required by the course. This would encourage the students to take initiatives in researching, formulating and resolving the issues, reasoning through to obtain buy-in from a panel consisting of industrial practitioners. This is a new course and designed to best equip the participants with the most current knowledge and in-depth understanding in the risk management when entering the mainstream financial institutions.

Prerequisite: EO358H1/RSM332H1

Note: For Financial Economics Specialist students, this course may be used to fulfill the 3rd year or higher 1.0 FCE course list. Contact department for details.

2021–21 Undergraduate Awards for Academic Excellence

On December 2, we were thrilled to fete our award winners.

Course Match

We are offering pre-enrolment for some 400-level ECO courses for Fall-Winter 2022-23, for fourth-year students who have not yet fulfilled the 400-level Economics program requirement.   The purpose of this pre-enrolment process is to ensure that students who require one or two 400-level courses for program completion are better able to enrol in a course.   If you qualify for Course Match, you will receive an email from the Undergraduate Office in early June.  For more information, see Economics: Course Match.

Focus in Data Analytics: Major or Specialist

Starting 2020–2021, students will be able to add the Focus in Data Analytics to the Economics Major or Specialist program. The focus ensures that students gain proficiency in applied empirical economics. It provides students with hands-on exposure to the tools empirical economists use to build and analyze datasets - programming languages such as Python, and software programs to manage, statistically analyze, and visualize data such as Excel, GIS, Stata and R. The focus will also direct students to empirical economics courses that apply these tools in a wide variety of contexts. Please see the Focus in Data Analytics (Major) or Focus in Data Analytics (Specialist) typical pathway handout for highlights and refer to the Calendar for details.