Fall 2012 Course Descriptions
Course descriptions, Fall 2012
MINI 1 -
47-718, Accounting & Information Economics I, Prof. Jonathan Glover
47-723, Seminar in Finance III, Prof. Chester Spatt
47-746, Advanced Data Analysis, Prof. Peter Boatwright
The course is 1) designed to cover a broad set of empirical methods that have been employed in research in marketing, 2) to facilitate discussion on said methods in order to help students understand the methods, 3) to give students experience in using empirical methods.
47-774, Analytical Performance Modeling I, Prof. Mor Harchol-Balter
47-780, Math for Economists, Prof. Chris Sleet
This course covers the mathematical prerequisites for the graduate sequence in microeconomics, econometrics, and macroeconomics. Topics include linear algebra, constrained optimization, comparative statics, correspondences and fixed point theorems, dynamic programming, and topology. Real Analysis is strongly recommended as a co-requisite.
47-800, Microeconomics I, Prof. Isa Hafalir
This course is an introduction to microeconomic theory and concerns the behavior of individual consumers and firms in competitive settings. The specific topics to be covered are preference and choice, optimization theory, consumer theory, producer theory and choice under uncertainty. The course is intended to teach students the foundations of formal economic analysis in these areas. Emphasis is on precise statements and proofs of some basic propositions in economics.
The treatment of the topics will be fairly mathematical and presumes knowledge of linear algebra, optimization, multivariate calculus and some real analysis. At the end of the course, students should be able to (i) understand theories and concepts in consumer and producer theory, (ii) develop analytical and problem solving skills regarding the analysis of the topics covered, and (iii) be ready to apply these skills in Microeconomics II, General Equilibrium.
47-811, Econometrics I, Prof. Yaroslav Kryukov
This course is an introduction to the basic questions, tools and techniques used in empirical social science research. Students will learn to calculate and perform correct inference on parameter estimates.
The course focuses on the multivariate linear model. Topics include:
consistency and asymptotic normality of the parameter estimates, sampling distributions, hypothesis testing parameter restrictions and specification tests. Students will learn the impact of departures from traditional assumptions in the linear model (e.g. correlated errors, heteroscedastic errors, correlation between the regressors and the errors) and how to address these situations.
Students are expected to be familiar with multivariate calculus, linear algebra, and basic probability and statistics.
Students will write MATLAB programs on problem sets.
47-817, Game Theory & Applications, Prof. Christoph Mueller
This course is a PhD level introductory course in game theory and concerns economic situations in which rational decision-makers interact. The course is intended to teach students the tools necessary to use game theoretic models in a wide variety of applications. At the end of the course, studens should be able to (i) understand solution concepts in games in strategic or extensive form, and (ii) develop analytical and problem-solving skills regarding the analysis of games.
47-834, Linear Programming, Prof. Fatma Kilinc-Karzan
Linear programming lies at the basis of modern optimization theory. This course focuses primarily on linear programming theory and algorithms, leaving beyond the scope of its practical applications. The main topics to be covered include modeling examples and expressive power of linear programs, polyhedral sets and their geometry, theory of systems of linear inequalities and duality, classical linear optimization algorithms (simplex and network simplex), and decomposition approaches for large-scale optimization. If time permits polynomial time solvability of linear programs, extensions to conic optimization problems, conic duality, and an introduction to interior point methods are topics of interest in the given order.
47-835, Graph Theory, Prof. R. Ravi
This is a graduate-level course on introductory graph theory. The objective of the course is to introduce basic concepts in graph theory and develop problem-solving ability and mathematical maturity in this area. The topics covered include Basic Terminology,Trees, Connectivity, Eulerian and Hamiltonian graphs, Vertex and Edge colorings, Planarity, and an introduction to Matchings, Independent Sets and Covers in graphs.
47-890, Seminar in Organizational Behavior (micro), Prof. Rosalind Chow
This course takes the most “micro” level of analysis in organizational research, focusing on dynamics of social cognition, interpersonal interactions, and behavior in small groups. The goal of the course is to expose students to some of the fundamental theories in organizational research and to develop critical skills in order to conduct and evaluate organizationally relevant research at a social psychological level of analysis.
47-952, Seminar in Information Systems, Prof. Tridas Mukhopadhyay
47-981, American English Speech I, Prof. Natalie Baker Shirer
MINI 2 -
47-719, Accounting & Information Economics II, Prof. Pierre Jinghong Liang
47-724, Seminar in Finance IV, Prof. Antje Berndt
47-755, Multivariate Data Analysis, Prof. Alan Montgomery
Researchers frequently collect measurements on several variables simultaneously. Multivariate data analysis is focused on the analysis of these simultaneous measurements. It generalizes the ideas of univariate data analysis to create analyses that are more powerful both in a statistical as well as a practical sense. This power comes with the added costs of multivariate notation and computing effort. Since statistical software can readily handle the complex statistical calculations that are necessary, the goal for this course is provide students with the supporting knowledge to interpret these results, select appropriate techniques, and evaluate the strengths and weaknesses of these approaches. The course covers the following topics: multivariate normal distribution, general linear model, multivariate regression, MANOVA, principal components and factor analysis. Additional topics such as multinomial choice models, cluster analysis, and multidimensional scaling may be covered if time permits. This course is specifically designed for graduate students who intend to do empirical research.
47-775, Analytical Performance Modeling II, Prof. Mor Harchol-Balter
47-801, Microeconomics II, Prof. Steve Spear
General Equilibrium analysis focuses on the question of how a market economy allocates resources. This analysis builds on the theories of consumer and producer behavior developed in the study of microeconomics by examining how the interactions of economic agents determine equilibrium in the markets for all goods simultaneously.The starting point for the analysis is the canonical model of general equilibrium known as the Arrow-Debreu model. We will spend much of the course formulating this model, examining its properties, demonstrating existence of equilibrium, and examining properties of the equilibrium prices and allocations. We will then look at extensions of the model, and at drawbacks of the model.Lectures will provide the primary development of the theory. Students may wish to supplement the material from the lectures with material from G. Debreu’s "Theory of Value". While this text is not required for the course, it is considered a classic in economic theory and is worth owning for that reason alone. When appropriate, I will also hand out additional readings. Most of this material is also covered in detail in Part Four of Mas-Colell, Whinston and Green.
47-802, Macroeconomics I, Prof. Chris Sleet
47-812, Econometrics II, Prof. Yaroslav Kryukov
This course is about estimating structural economic models. The basic question is how to use data to estimate the parameters of an economic model. We will want to establish:
1. establish the consistency of the estimators,
2. establish the asymptotic normality of the estimators,
3. the data has been used as efficiently as possible in terms of obtaining the smallest possible variance of the asymptotic distribution, and
4. test hypothesis about the parameters.
We would like to use economic theory to restrict our estimation problem so that we has as much structure as possible implied by theory.
Students should learn how to establish the consistency and asymptotic normality for parameters estimated from nonlinear objective functions. The students should also learn how to calculate the parameter estimates and perform inference.
47-818, Economics of Contracts, Prof. Laurence Ales
This course will cover the basics of contract theory and its application to economic problems. A contract is a set of rules that facilitates interaction among individuals beyond the simplest forms of barter. You have already encountered simple contracts; for example, in the form of spot labor contracts (exchanging leisure for goods) or borrowing and saving agreements (exchanging resources today for resources tomorrow). This course studies more involved contracts. The basic setup will feature the parties involved in the contract having conflicting objectives. In addition contracting will be limited by two types of frictions: we will look at environments where a party in the contract has some valuable, privately observed information; and we will consider environments where at least one party in the contractual relationship cannot credibly commit to it. In the course I will first start by presenting the theory behind the optimal design of contracts in environments with asymmetric information and limited commitment. Then, I will show how these optimally designed contracts can find application in different economic situations. In particular I will show applications with regards to optimal taxation, corporate finance, asset pricing and economic development.
47-836, Networks & Matchings, Prof. Gérard Cornuéjols
47-840, Dynamic Programming, Prof. Soo-Haeng Cho
In this course we will study the theory and applications of stochastic dynamic programming (SDP). The undergraduate level of probability theory is a prerequisite for this course. Prior knowledge of stochastic processes and convex optimization would be helpful but are not required, as we will cover the basic principles in this course. We will first study the theory of SDP including finite-stage models, discounted dynamic programming, and optimal stopping problems, and then study both classical and recent applications of SDP to Operations Management. The specific objectives of the course are: (i) to train you to model and analyze SDP problems, and (ii) to introduce you to various SDP models in Operations Management in order to help you develop your own research interests. We will have a three-hour final exam.
47-881, Seminar in Electricity Market Restructuring I, Prof. Jay Apt
This is a reading and discussion seminar for PhD students. We will read some of the seminal literature in the study of the modern electric power industry. We will begin by reading and discussing portions of Power Loss: The Origins of Deregulation and Restructuring in the American Electric Utility System by Richard F. Hirsh (MIT Press, 2001). After this introduction to both the history and the factors that lead to the modern regulatory and industry structure, we will critically review and discuss important and interesting papers from the contemporary literature that will help develop research directions and sharpen analysis skills.
47-892, Seminar in Organizational Theory (macro), Prof. Brandy Aven
This course introduces central concepts in Organizational Theory. The main objective of this course is to create a forum to discuss and develop an understanding of the different strategies organizational theorists use to explain organizational processes, develop theories, and make these theories as convincing as possible. Topics include: Economic Sociology, Organizational Learning, Institutional Theory, Status & Power, and Social Networks within and among firms.
47-899, Learning Processes in Organizations, Prof. Linda Argote
47-953, Seminar in Information Systems II, Prof. Param Vir Singh
47-982, American English Speech II, Prof. Natalie Baker Shirer
