Graduate Program


I: Reviews theory of calculus, linear algebra, and constrained optimization. Theory and methods of differential equations, calculus of variations, optimal control theory, and dynamic programming applied to economic problems.

II: Methods and applications of optimal control theory to problems of economics. Discusses economic applications of stochastic processes, probability, measure theory, and topology.

I: Decision theory, theory of the firm, and consumer behavior; introduction to general equilibrium theory and welfare economics.

II: Game theory, including extensive form solution concepts, bargaining, and repeated games; information economics, contract theory and mechanism design.

I: Models of national income determination; sectorial inflation; labor markets, production theories, and aggregate supply models; supply and demand for money; foreign trade and balance of payments.

II: Classical and Keynesian macroeconomic thought, modern-day microeconomic theories of money-wage and price determinations, reconstruction of macro theory and heterogeneous agent macroeconomics.

I: Concise introduction to probability theory and to the problem and methods of statistical inference as encountered and applied in econometrics: maximum likelihood theory, method of moments, method of least squares, and hypothesis testing.

II: Econometrics analysis of the general linear model; the estimation of distributed lag models; misspecification analysis; and models involving errors in variables.

Studies experimental methods and reviews the literature in an effort to give the student a working knowledge of experimental techniques. While the areas of application vary, the course is research oriented.

This is a doctoral level workshop in which students, faculty and guest speakers present work that uses experimental methods on economics. Although the focus will be on test of economic methods using laboratory methods, issues in behavioral economics and neuroeconomics will sometimes be covered. Studies that use controlled treatment manipulation within a field setting will also be presented. This course will allow students interested in applied work to be exposed to studies that use experimental methods.

The C.E.S.S. Experimental Seminar invites speakers to present novel work in economics using experimental methods. It should be of interest to students and faculty members interested in applied work in economics and related fields such as psychology, neural science, political science, business administration, finance, and management.

This course introduces students to the field of behavioral economics, which seeks to insert more behavioral realism into economic theory. Typically we try to accomplish this by making nonstandard assumptions about human preferences, but occasionally our approach will be to explore non-standard beliefs or emphasize the limitations of our decision making faculties. We will usually approach a topic by examining evidence of some departure from the assumptions made in the canonical economic model. We then ask how such departures can be formalized theoretically and how the resulting models can be tested empirically.

Neural Science

Team-taught, intensive course. Lectures and readings cover basic biophysics and cellular, molecular, and developmental neuroscience.

Team-taught intensive course. Lectures and readings concentrate on neural regulation of sensory and motor systems.

Team-taught, state-of-the-art teaching laboratory in neural science. The first semester includes histology and cellular and molecular neuroscience. The second semester includes neuroanatomy, sensory neurophysiology, modern neuroanatomical tracer techniques, psychophysics, and computational neuroscience.

Team-taught intensive course. Lectures, readings, and laboratory exercises cover neuroanatomy, cognitive neuroscience, learning, memory, and emotion.

II: Econometrics analysis of the general linear model; the estimation of distributed lag models; misspecification analysis; and models involving errors in variables.

Team-taught intensive course. Lecture, readings, and homework exercises cover basic mathematical techniques for analysis and modeling of neural systems. Homework sets are based on the MATLAB software package.

This seminar will survey the emerging field of neuroeconomics, the interdisciplinary study of the brain’s mechanisms for decision evaluation and choice. We will approach these issues from multiple perspectives, drawing on theoretical, behavioral, and neural data from economics, psychology, and neurobiology. Major topics include: decision under risk and uncertainty; multiplayer interactions and social preferences; the role of learning in evaluating options; and choice mechanisms.


Intensive course in basic mathematical techniques for analysis and modeling of behavioral and neural data, including tools from linear systems and statistics. In 2008, first semester Math Tools is being offered jointly for students from Neural Science and Psychology, as an alternative for the first-semester of the two-semester psychology sequence.

Survey of basic areas in behavioral neuroscience. Areas of primary interest include behavioral and neurobiological analysis of instinctive behavior, conditioning, motivation and emotion, and learning and cognition.

Covers topics in numerical analysis, probability theory, and mathematical statistics essential to developing Monte Carlo models of complex cognitive and neural processes and testing them empirically. Most homework assignments include programming exercises in the MATLAB language.

Exploration of the psychological processes that underlie people’s judgments and decisions. First identifies some general rules that capture the way people make decisions. Then explores how people make decisions in numerous domains, including consumer, social, clinical, managerial, and organizational decision making. Looks at both rational and irrational patterns in the way people select options. Discusses the impact of the media on our choices. Also examines how different ways of presenting options and different decision-making strategies can influence decision outcomes. In general, emphasizes the applied implications of the various perspectives on decision-making.

This course examines decisions from theoretical, behavioral, and neural perspectives. A first goal of the course is to review normative and descriptive theories of decision under risk or uncertainty, decisions based on sampling, temporal discounting, visuo-motor analogues of decision, and decisions in multi-agent interactions. We will also explore learning in the context of decision problems, including reinforcement learning and foraging models. Finally, we will consider how all this work informs and is informed by research in humans and animals about the neural substrates for decisions. We will read both classical papers and very recent work, some chosen to reflect the interests of the participants.

This course covers the major topics and issues in the field of fMRI. With this background, students will be able to design and implement their own fMRI experiments. There are weekly lab projects that will involve acquiring and analyzing fMRI data, and submitted written lab reports. Final grades are based on the lab reports. The lectures provide background information useful in performing the labs, along with additional information for a broader and deeper understanding of fMRI methods.

Stern Business School

Coursework for PhD programs at Stern is specific to each of the eight departments that offer PhD programs, however the interdisciplinary nature of Stern’s doctoral programs means students may complete coursework in other related fields as deemed appropriate by their faculty advisor (e.g., economics, psychology). Additionally, Stern offers a broad range of academic programs (i.e., MA, MS, MBA and executive programs) that can be found here.