这个项目今年刚刚开始招生，2019年春季第一批入学的截止日期是 10 月21 日，但是也可以接受 late application。项目是三个学期，可以做继续申请的跳板。项目详细信息：

M.S. DEGREEMaster of Science in Economics

The Master of Science (M.S.) degree in Economics is a new graduate program offered by our department. This innovative program teaches fundamental skills and state-of-the-art analytical and econometric tools. Through in-depth coursework you will begin to master invaluable advanced theoretical and empirical skills.

What will you gain?

This program combines the very best of learning in Economics: dedicated research-oriented faculty, a strong theoretical grounding, modern computational tools, and advanced econometric methods. It will prepare you for a large variety of careers in the private and public sectors as well as for further graduate training such as Ph.D. programs in Economics or related fields.

What will you actually do?

The coursework in this program can be finished in three semesters. In the first two semesters, you will learn basic foundations of microeconomic theory, macroeconomics, and econometrics with the appropriate mathematical tools. The third semester allows a specialization into a financial economics track or a game theory track, each with appropriate courses and tools.

Master of Science in Economics

Our M.S. in Economics program currently admits students during the fall term, with coursework beginning in the spring term.

Grades

You must maintain a minimum GPA of B (3.0) in order to remain in good standing in the Graduate School. Courses to be counted toward the degree must be passed with a grade of B- (2.7) or better.

Course requirements

A total of 30 credit hours is required for this degree. All of our M.S. students take the same set of three classes in each of the first two semesters. In the third semester, you will choose one of two tracks.

The coursework in this program can be finished in three semesters.

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