M.S. Degree

Economics M.S. course descriptions

Semester 1

Econ-M 500 Mathematics for Economists
P: Calculus
Introduction to concepts and methods of constrained and unconstrained optimization theory applied in modern economics. Theory and application of Lagrange multipliers, comparative statics analysis, value functions and envelope theorems. Elements of dynamic programming and other methods of economic dynamics.

Econ-M 501 Microeconomic Theory I
P: Calculus
The course develops the methodology and language of price theory. Partial equilibrium analysis of consumer theory, producer theory, and economics of uncertainty. Emphasis on comparative statics and the duality theory. Topics include welfare analysis, the theory of price indices, quality of goods, revealed preferences, the theory of derived demand, expected utility theory, attitudes toward risk, and various measures of riskiness.

Econ- M 504 Econometrics I
P: Calculus
Emphasis is on the probability and statistical theory underpinning the classical linear regressionmodel used in economic applications. Special topics include finite and asymptotic properties ofpoint and interval estimation, hypothesis testing and model building. Several software packages such as Stata or R are used in computer lab applications.

Semester 2

Econ-M 511 Microeconomic Theory II
P: Calculus
General equilibrium theory; welfare economics; microeconomics of capital theory; monopoly, oligopoly and game theory, product differentiation, monopolistic competition. Price discrimination. Economics of Information including adverse selection, moral hazard and principal agent models.

Econ-M 502 Macroeconomics
P: Calculus
General equilibrium modelling of economic growth, business cycle fluctuations, evolution of income and wealth inequality and technological progress. Analysis of monetary and fiscal policy and its effects on aggregate economic outcomes.

Econ-M 514 Econometrics II
P: Calculus
Emphasis is on the matrix formulation and computer estimation methods for single and multiple equation models using economic and business data. Attention is given to the assumptions required for testing sets of coefficients and model structures. Special topics include heteroscedasticity, multicollinearity, errors in variables, simultaneity, time-series analysis, limited dependent variables, sample selection, and alternatives to least squares estimation.

Semester 3 (Track 1: Game Theory)

Econ-M 516 Game Theory
P: Calculus
Rigorous analysis of strategic interaction. Focus on non-cooperative games in normal and extensive form. Static and repeated games. The role of information in strategic interaction. Topics include mechanism design, auction theory and one and two sided matching.

Econ-M 518 Econometrics: Big Data
P: E370, E371 or equivalent
The course consists of discussion of how to import, clean and visualize data on the computer, an introduction to popular tools from machine learning and an overview on recent advances on combining machine learning methods with economic models to conduct causal inference. Use of software package R to analyze large models and large economic data sets.

Semester 3 (Track 2: Financial Markets)

Econ-M 513 Financial Economics
P: Micro theory I
The class covers theory and empirical evidence relevant to understanding the functioning of modern financial-asset markets. Topics include: present value, analysis of risk and return, asset pricing, modern portfolio theory, equilibrium in asset markets, arbitrage pricing theory, the capital asset pricing model, the efficient markets hypothesis, price bubbles and crashes, futures markets, derivative securities and option pricing models.

Econ-M 524 Financial Econometrics
P: Econometrics I & II
The course covers the econometrics toolboxes that are useful to analyze financial market data, in particular, time series data. The goal is to understand and implement state-of-the-art econometric methods with the data at hand, providing answers to empirical questions. While the course intends to put more emphasis on implementation, and less on rigorous theory, learning some heuristics behind the theory is important part of the course. Topics include stationary time series analysis, persistency, predictive regression, model selection, factor models, and advanced topics.

Econ-M 517 Computational Economics
P: Calculus
The course will begin with a solid introduction to programming in Matlab. The topics to be covered include first of all: calculation of value functions in discrete and in continuous time, solving Hamilton-Jacobi-Bellman equations, diffusions, Ito’s Lemma, solving for asset prices implied by theoretical models. The second set of topics to be covered include computing best responses and Nash equilibria.