Tepper School of Business

Tues / Thurs, 10:30 am - 12:20 pm

147 Posner

Instructor: Christopher 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.

Mon / Wed, 1:30 pm - 3:20 pm

147 Posner

Instructor: 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.

Tues / Thurs, 1:30 pm - 3:20 pm

147 Posner

Instructor: Prof. Yaroslav Kryukov

This course introduces the basic estimation and inference problems faced in social science research. The material starts with a brief summary of commonly used probability and statistics results. Most of the course will focus 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, heteroskedastic errors, correlation between the regressors and the errors) and how to address these departures. Students are expected to be familiar with multivariate calculus, linear algebra, basic probability and statistics.

Mon / Wed, 3:30 pm - 5:20 pm

147 Posner

Instructor: Prof. Christoph Mueller

This course is a Ph.D. 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, students 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.

Mon / Wed, 1:30 pm - 3:20 pm

147 Posner

Instructor: 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.

Tues / Thurs, 1:30 pm - 3:20 pm

147 Posner

Instructor: Prof. Karam Kang

Tues / Thurs, 1:30 pm - 3:20 pm

147 Posner

Instructor: Prof. Karam Kang

This course presents the basic estimation and inference problems associated with nonlinear models in social science research. The material will focus on maximum likelihood estimation and the generalized method of moments. Topics include: consistency and asymptotic normality of the parameter estimates, sampling distributions, hypothesis testing parameter restrictions and specification tests. In this course, the estimators are defined as the solution to an optimization problem without assuming that it has a closed form. Prerequisite: 47-811.

Mon / Wed, 8:30 am - 10:20 am

147 Posner

Instructor: Prof. Laurence Ales

The goal of this course is to provide students with basic knowledge of information economics and uncertainty in particular, optimal contracts and principal agent models. The economics of information is centered on a fundamental aspect of contractual relationship: the effect on the contractual format when one party has, or will have, an informational advantage over the others. Most interesting cases are when participants have asymmetric information and opposing objectives.