About the Department
Since its founding in 1925, the students and faculty of the Kenneth C. Griffin Department of Economics (including numerous Nobel laureates) have advanced the world’s understanding of society by extending economic analysis to new spheres of social life, spearheading the study of ideas ranging from economic growth to human capital. Over the decades, numerous new ideas in the field of economics emerged from the University of Chicago, including the economic theory of socialism, the economics of the household, the rationality of peasants in poor countries, the economics of education and other acquired skills (human capital), the economics of information, and the monetary approach to international finance. The unifying thread? The conviction that economics is a powerful tool for understanding society.
Graduate study in the Kenneth C. Griffin Department of Economics is intensely mathematical. Prospective students who declare Economics as their primary field must have prior exposure to real analysis, econometrics, and advanced coursework in multivariable calculus, linear algebra, probability, and statistics. A solid foundation in micro and macroeconomics is strongly preferred.
Students admitted for MAPSS-Econ will receive a separate letter of admission. Only those persons are eligible to work with a member of the Economics faculty on the MA thesis.
Students should complete the doctoral math camp the Department offers in late August/early September.
At the beginning of the academic year, students will be assigned to an Assistant Instructional Professor, who will serve as their advisor for course selection and registration purposes. Students are expected to take MA level coursework in the Economics Department or other departments on campus. The Department has created a dedicated set of MA level courses that are designed with the needs of MA students in mind.
Students who believe they qualify for doctoral level coursework are welcome to request an evaluation of their prior background. If their prior training is deemed to be adequate, they can register for doctoral level coursework in the department. Those students approved for doctoral level coursework may continue to take these courses as long as they earn a B or better.
Students will be supported in their course selections, choice of faculty advisor, and MA thesis by Victor Lima, Senior Instructional Professor in Economics, by Min Sok Lee, Assistant Senior Instructional Professor in Economics, and other Assistant Instructional Professors in the department with expertise across the different fields within economics.
The Kenneth C. Griffin Department of Economics has recently established a March 15th deadline for current MAPSS-Econ students to apply for the PhD program. This allows students to submit application materials that include their performance in the first two quarters of the MAPSS year. If admitted to the PhD program, students continue their training during the subsequent academic year.
Students who find graduate work in the Department beyond their mathematical reach may find more accessible alternatives in the Harris School of Public Policy, in the Booth School of Business, in Political Science, and occasionally in Sociology, Law, or History.
International students are eligible for three years of work authorization in the U.S. after they graduate, since MAPSS-Econ is a STEM-approved program.
We’d be thrilled to discuss the program with you. You can find answers to our frequently asked questions or you can reach us at the address below:
ECMA 30770. Decision and Strategy. ECON 20700 or 30770 may be used as an economics elective, but only one may be used toward degree requirements. This course provides a formal introduction to game theory with applications in economics. We will study models of how individuals make decisions, and how those decisions are shaped by strategic concerns and uncertainty about the world. The topics will include the theory of individual choice, games of complete and incomplete information, and equilibrium concepts such as Nash equilibrium. The applications will include oligopoly, auctions, and bargaining. The course is appropriate for advanced undergraduates who are interested in a rigorous mathematical approach to understanding human behavior.
ECMA 30800. Theory of Auctions. In part, this course covers the analysis of the standard auction formats (i.e., Dutch, English, sealed-bid) and describes conditions under which they are revenue maximizing. We introduce both independent private-value models and interdependent-value models with affiliated signals. Multi-unit auctions are also analyzed with an emphasis on Vickrey's auction and its extension to the interdependent-value setting.
ECMA 31000. Introduction to Empirical Analysis. This course introduces students to the key tools of econometric analysis: Probability theory, including probability spaces, random variables, distributions and conditional expectation; Asymptotic theory, including convergence in probability, convergence in distribution, continuous mapping theorems, laws of large numbers, central limit theorems and the delta method; Estimation and inference, including finite sample and asymptotic statistical properties of estimators, confidence intervals and hypothesis testing; Applications to linear models, including properties of ordinary least squares, maximum likelihood and instrumental variables estimators; Non-linear models. Assignments will include both theoretical questions and problems involving data. Necessary tools from linear algebra and statistics will be reviewed as needed.
ECMA 31130. Topics in Microeconometrics. This course focuses on micro-econometric methods that have applications to a wide range of economic questions. We study identification, estimation, and inference in both parametric and non-parametric models and consider aspects such as consistency, bias and variance of estimators. We discuss how repeated measurements can help with problems related to unobserved heterogeneity and measurement error, and how they can be applied to panel and network data. Topics include duration models, regressions with a large number of covariates, non-parametric regressions, and dynamic discrete choice models. Applications include labor questions such as labor supply, wage inequality decompositions and matching between workers and firms. Students will be expected to solve programming assignment in R.
ECMA 31340. Big Data Tools in Economics. The goal of the class is to learn how to apply microeconomic concepts to large and complex datasets. We will first revisit notions such as identification, inference and latent heterogeneity in classical contexts. We will then study potential concerns in the presence of a large number of parameters in order to understand over-fitting. Throughout the class, emphasis will be put on project-driven computational exercises involving large datasets. We will learn how to efficiently process and visualize such data using state of the art tools in python. Topics will include fitting models using Tensor-Flow and neural nets, creating event studies using pandas, solving large-scale SVDs, etc.
ECMA 33240. Quantitative Analysis of Macroeconomic Policy. This course focuses on application and covers three commonly used models in macroeconomics, including structural VAR, DSGE models and state space and regime switching models. Various research tools developed to implement these models, such as how to identify structural shocks and analyze their dynamic effects, and how to conduct counter-factual policy simulations, will be discussed and implemented.
ECMA 33330. Introduction to Dynamic Economic Modeling. This course provides an introduction to dynamic economic models, with applications to macroeconomics, labor economics, financial economics, and other subfields of economics. The core methodology will be consistent over time, but the applications will vary from year to year. The course will analyze decentralized equilibrium and social planner's problems in dynamic environments. It will focus on developing techniques for analyzing such models graphically, analytically, and computationally. Students should be familiar with constrained optimization (e.g. Lagrangians), linear algebra, and difference equations, as well as microeconomics, macroeconomics, and econometrics at an intermediate level.
ECON 30100. Price Theory. Theory of consumer choice, including household production, indirect utility, and hedonic indices. Models of the firm. Analysis of factor demand and product supply under competitive and monopolistic conditions. Static and dynamic cost curves, including learning by doing and temporary changes. Uncertainty applied to consumer and producer choices. Property rights and the effects of laws. Investment in human and physical capital.
ECON 30501. Topics in Theoretical Economics. Some of the topics covered in this course are: Nash equilibrium existence in discontinuous games, existence of monotone pure strategy equilibria in Bayesian games, defining sequential equilibrium in infinite extensive form games, efficient auction design, correlated information and mechanism design.
ECON 31000. Empirical Analysis-1. This course introduces students to the key tools of econometric analysis: basic asymptotic theory, including convergence in probability, convergence in distribution, laws of large numbers, continuous mapping theorems, central limit theorems, and the delta method; conditional expectation; applications to linear regression, instrumental variables, maximum likelihood, and extremum estimators.
ECON 33000. The Theory of Income. This course formulates and analyzes aggregate general equilibrium models to study classical questions in macroeconomics. The course starts with the formulation and analysis of competitive equilibrium in the general equilibrium models, including the 1st and 2nd welfare theorem. The first applications of this model are: social security (using an OLEG model), optimal risk sharing, and asset pricing (using a one period model with uncertainty). Most of the remaining applications focus on dynamic models without uncertainty. To do so we study tools to characterize optimal solutions of control problems: Hamiltonian, calculus of variations and dynamic programming. The main application of these tools is the neoclassical growth model in many variations: determinants of steady state and balanced growth path, endogenous growth, effect of variable labor supply, TFP changes and of investment specific technical progress, habit formation, the q-model of investment, taxation of capital and labor, optimal taxation a la Ramsey, among others.
ECON 33603. Macroeconomics and Financial Frictions. This course investigates the interrelationship between financial markets and macroeconomics, presenting some recent developments in that literature. We start from a log-linearized perspective on asset pricing and macroeconomic dynamics. We extend these tools to long-run risk and Epstein-Zin preferences. We discuss higher moments and large disasters. Next, we turn to models of systemic risk as well as DSGE models incorporating a financial sector and house price booms and busts. Finally, we turn to sovereign debt crises. We will learn about tools to analyze stochastic dynamic general equilibrium models, such as Dynare.
ECON 34901. Social Interactions and Inequality. This course will focus on the theory, econometrics, and empirical analysis of social influences on economic behavior, termed social interactions. As such, the course will include topics ranging from social networks to social capital to discrimination. We will examine the effects of social interactions on individual and aggregate behaviors as well as the implications of social interactions for the formation of social structure. Particular attention will be given to the translation of theoretical models into econometric analogs and to the identification questions that arise when attempting to construct empirical evidence on social interactions. Applications of social interactions will focus on contexts in which their presence can help explain observed levels of socioeconomic inequality.