Winter 2026 course offerings

ECON602- Macroeconomic Theory I: The main purpose of this course is to provide students with the methodological tools that underlie dynamic equilibrium analysis of the macro-economy.

ECON623 - Time Series Econometrics: This course introduces students to methods and practices of analyzing data that exhibit dependence over time. The topics may cover fundamental linear time series models (autoregressive processes, moving average processes and their generalizations), modelling time-varying volatility (the autoregressive conditional heteroskedasticity or ARCH family of models and stochastic volatility models), multivariate time series analysis, non-stationary models, and ongoing topics in modern time series econometric research.

ECON626 - Machine Learning for Economists: This course explores a variety of machine learning methods used to analyze complex economic data and inform policy decisions. The course introduces students to predictive methods and exploratory data analysis for high-dimensional data. These methods, such as decision trees and neural networks, are applied to observational data with an emphasis on the analysis of large and/or complex datasets of interest to social scientists and policy makers

ECON641 - Public Economics: This course studies the economic role of the public sector in a market economy. Topics may include the provision of public goods, externalities and public choice, analysis of the growth in government spending, the design of tax systems, international aspects of taxation, and fiscal federalism.

ECON643 - Health Economics: This course introduces students to the role of economics in health care and health policy. It is meant to be a survey of major topics in health economics and an introduction to the ongoing debate over health care policy. Topics include the economic determinants of health and health policy, the market for medical care, the market for health insurance, and the role of the government in health care, and health care reform.

ECON672 - Financial Economics: Topics covered include: expected utility theory, no-arbitrage pricing, equilibrium-pricing models, derivative-security pricing, asymmetric information, capital structure theory and dividend policy.

ECON 673 - This course focuses on strategic decision-making with uncertainty and its applications to mechanism/market design. We will cover single-agent models with hidden characteristics(screening) and hidden actions (moral hazard), with applications to pricing, risk-sharing, taxation, and incentive contracting. For multi-agent environments, we explore dominant strategy/Bayesian implementation and applications to auction design, matching markets, and AI-driven mechanism design. This advanced treatment blends theoretical rigor with practical insights, equipping students with tools to analyze and design strategic interactions in complex settings.

ECON701 - Micro II: This course builds on the models and the techniques developed in Microeconomic Theory I. Topics may include general-equilibrium analysis, game theory, the economics of information, mechanism design and applications of bargaining theory to the theory of markets.

ECON703 - Advanced Macroeconomics: Problems and Policies: This is a research-oriented course in macroeconomics. Topics may include issues in economic growth and development, economic inequality, fiscal policy, labour market policy, and business cycles.

ECON721 - Econometrics II: The course provides a rigorous treatment of more advanced topics in econometrics. They include system of equations, simultaneous equations, generalized method of moments, empirical likelihood, vector autoregression and dynamic models, time series models and methods, discrete dependent variables, and limited dependent variables.

ECON723 - Applied Macroeconometrics II: This course covers some of the most important concepts, models and methods used in the empirical analysis of macroeconomic problems. In particular the course covers established time series techniques as well as more recent developments such as testing for unit roots, measurement of the persistence of shocks and estimation and hypothesis testing in cointegrated systems. Several dynamic models will be studied using time series analysis methods. Topics covered include basic concepts in time series analysis (modelling volatility and trend), VAR Modes (including structural VAR's), VECM and Cointegration, neural networks and estimation of DSGE models. During the course, students will have the opportunity to explore several case studies using econometric software such as RATS and MATLAB.