About
NYU’s Master of Science in Quantitative Economics is a cutting-edge program for students with research-oriented ambitions in economics, such as a demanding doctoral program, or employment in technology, finance and research in both the private or public sectors. Drawing on the combined resources of the Economics Departments of the Faculty of Arts and Science and NYU’s Stern School, the MSc in Quantitative Economics is streamlined and sequenced to get you where you need to go with maximal stimulation, speed and efficiency. Our ten month program starts with the fundamentals of microeconomics, macroeconomics and econometrics, supplemented by the mathematical and data science tools needed for investigating and applying each of those fields. Then game theory, applied microeconomics, finance and open economy considerations are introduced. The final two modules include a “capstone experience” in which students choose one of two paths toward original research (see the FAQ). If you are ultimately headed for a top doctoral program in economics, the timing of our program was designed for you. Starting in July and ending in June, it offers a wealth of challenging material while moving you toward beginning the PhD in one academic year. This MSc in Quantitative Economics is taught in intensive six-week modules. It allows you to interact with over 20 leading faculty members through coursework alone. By the time you are looking for recommendation letters at the end of November, you will have completed eight courses with eight instructors who can write the kind of informative letters that doctoral admissions committees (and prospective employers) take seriously. NYU’s MSc in Quantitative Economics is a superb program in an exciting university, in one of the world’s greatest cities. If you feel driven to do research, or seek out a demanding career that will use your analytical skills, consider applying to the MSc in Quantitative Economics at NYU.
Courses
- ECON-GA 4011 Math Methods I
- ECON-GA 4021 Data & Computation
- ECON-GA 4031 Microeconomics I
- ECON-GA 4041 Macroeconomics I
- ECON-GA 4012 Math Methods II
- ECON-GA 4071 Econometrics I
- ECON-GA 4032 Microeconomics II
- ECON-GA 4042 Macroeconomics II
Term 3: Fall
- ECON-GA 4051 Game Theory I
- ECON-GA 4061 Applied Micro I
- ECON-GA 4072 Econometrics II
- ECON-GA 4043 Macroeconomics III
Term 4: Winter
- ECON-GA 4052 Game Theory II
- ECON-GA 4062 Applied Micro II
- ECON-GA 4022 Data & Computation II
- ECON-GA 4044 Macroeconomics IV
Term 5: Spring
- ECON-GA 4081 Industrial Organization I*
- ECON-GA 4091 Computational Dynamics*
- ECON-GA 4073 Econometrics III*
- ECON-GA 4121 Research Practicum I
Term 6: Spring
- ECON-GA 4082 Industrial Organization II*
- ECON-GA 4111 Financial Economics*
- ECON-GA 4101 International Economics*
- ECON-GA 4122 Research Practicum II
Course Descriptions
Term 1: Summer
ECON-GA 4011. Mathematical Methods for Economics I.
The course begins with a quick review of basic methods of optimization theory, including necessary and sufficient conditions for optimality, the method of Lagrange multipliers and the Kuhn-Tucker conditions. These methods are required in the microeconomics and macroeconomics courses in the program. The course then develops the tools of real analysis and study conver- gent sequences, compact sets, continuous and differentiable functions, the Heine-Borel Theorem and the Weierstrass Theorem. Several applications are presented, including one-dimensional discrete dynamic systems and price adjustment models, and existence of optimal solutions in economic problems, The course then goes on to study convex and concave functions, derive the basic results for unconstrained optimization, and provide some applications to risk theory. Finally, the course investigates the basic properties of convex sets and cones, prove Caratheodory’s Theorem (on convex closures), and deduces some important results (such as Radon’s Lemma and Helly’s Intersection Theorem).
ECON-GA 4021. Data and Computation I.
This course is a hands-on approach to the study of open-source computational and data management tools now available online. Workhorses will be Python and affiliated programs for efficient calculations and numpy and pandas for data managment. These tools are presented in ways designed to open doors for doing applied quantitative economics at the graduate level. The aim is to help students become literate in the open source ecology for doing machine learning with economic data and models at the graduate level. It is assumed that students are comfortable with linear algebra, multivariable calculus, and probability and statistics.
ECON-GA 4031. Microeconomics I.
This course studies how market outcomes are determined by the decision-making of individual consumers and firms in the economy. The focus for most of the course will be on the decisions of each side of the market separately, taking as given a set of prices which fix terms of trade. On the consumption side of the market, rigorous models of consumer preferences will be used to microfound demand curves and describe notions of complementarity and substitutability between different goods. On the production side, descriptions of production technologies coupled with an assumption of profit-maximization by firms will be used to generate supply curves. Finally, demand and supply will be brought together to determine market allocations in conditions of perfect competition, monopolistic competition, and monopoly, with particular emphasis on the welfare implications of each environment.
ECON-GA 4041. Macroeconomics I.
The first course in the macro sequence introduces the technical foundation for the study of macroeconomic models, introducing the theory and applications of dynamic programming. The first part of the course develops the technical tools on dynamic programing, including Bellman equations and the principle of optimality. On the second part, these tools are applied to the workhorse model of macroeconomics, the one sector growth model, covering its deterministic and stochastic versions. As another application of application of dynamic programming, the canonical labor search model is studied.
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Term 2: Fall
ECON-GA 4012. Mathematical Methods for Economics II.
The second course goes deeper into convex analysis and optimization theory, and derives a number of core results such as the characterization of convex and quasiconvex functions, separating hyperpane theorems, Krein-Milman Theorem, the Kuhn-Tucker Theorem, and the Envelope Theorem. Optimization is required in the analysis of almost every economic model. Many economic applications are presented here, including some basic results in demand theory, Birkhoff’s Theorem on bistochastic matrices and its consequences for measurement of income inequality, linear regression analysis, duality in linear programming, and job- matching models.
ECON-GA 4071. Econometrics I.
This course introduces the core tools used for conducting empirical research in economics. The course will focus primarily on estimation and inference using linear regression and instrumental variables methods. Theory of estimation and inference will be developed rigorously. In addition, the course will cover important topics for empirical research, such as causal inference, random experiments, selection bias, and control variables. Practical issues will also be discussed, such as standard errors for dependent, heterogeneous, or clustered data, specification tests, and measurement error. Methods will be illustrated using numerous empirical applications across diverse fields of economics.
ECON-GA 4032. Microeconomics II.
This course introduces the study of general equilibrium theory in economics. The approach adopted in the course aims at introducing the theory as the canonical theoretical structure for the study of market economies. Competitive equilibria are therefore studied as the main micro-foundation for macroeconomics and finance. The series of fundamental theorems which constitute the classic theory of general equilibrium, concerning existence, characterization, and welfare properties of competitive equilibria in frictionless economies, are introduced in their rigor, abstraction, and elegance. But the course will complement the classic theory with the modern analysis of financial market equilibria in dynamic economies with different kind of frictions, exposing students to fundamental conceptual notions like complete and incomplete markets, constrained inefficiency, moral hazard, adverse selection, bubbles. Topics will be enriched with applications of the concepts and results.
ECON-GA 4041. Macroeconomics II.
This course studies competitive macro models and its applications to growth and fiscal policies. The complete markets model is studied with rigor, showing its equivalence with the sequential environment, its recursive repre- sentation and the welfare theorems. We discuss the implementation of fiscal policies, focusing on its normative recommendations. The overlapping generation model is intro- duced, with emphasis on its dynamic properties and the role of money and fiscal policy when agents have finite and overlapping lives.
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