Course descriptions, instructors, and syllabi for the most recent academic year are listed below:

Summer Semester (July – August, 6 weeks)

Fall Semester (August – December)

Spring Semester (January – May)

While students take their core courses in the fall semester, the spring semester provides ample opportunity to explore various fields of economics through elective coursework. In addition to traditional economics subfields, we offer three methods courses that aim to develop students’ skills in data science and econometric analysis.

  • ECO 395K Game Theory (elective)
    Short description: Introduction to game theoretic concepts and analyses and their application to study strategic interactions between individuals, firms, and other economic agents.
    Sample textbook: A Course in Game Theory by Martin J. Osborne and Ariel Rubinstein
    Sample syllabus: Spring 2024
  • ECO 394K Industrial Organization (elective)
    Short description: Covers the way markets are configured, how many firms exist, how they relate to each other, and how this interaction affects production, pricing, investment, advertising, and other managerial decisions. This is an advanced course which teaches underlying theory but also introduces students to practical methods commonly used in consulting and antitrust enforcement.
    Sample textbook: The Theory of Industrial Organization, by Jean Tirole and The Antitrust Revolution, by J. Kwoka and L. White
    Sample Syllabus: Spring 2024
  • ECO 394K Labor Economics (elective)
    Short description: Presents major theoretical models for understanding behavior and outcomes in the labor market. Topics include labor supply of individuals; labor demand by firms; wage determination in competitive labor markets and the wage structure; nonwage job attributes and compensating wage differentials; investment in human capital and wage differentials related to education and experience; and labor market discrimination and wage differentials by race and gender.
    Sample textbook: Labor Economics, by George Borjas
    Sample syllabus: Spring 2024
  • ECO 394L Macro and the Labor Market (elective)
    Short description: Focuses on contemporary topics in labor economics from a macroeconomic perspective, including an analysis of the determinants of wages, hours and unemployment both from a theoretical and empirical perspective. Topics include labor supply, the determinants of unemployment and vacancies, the flow approach to the labor market, theoretical models with search frictions, wage inequality, wage bargaining and wage rigidity, the relationship between the labor market and inflation, the decline in the labor share, the dynamics of search behavior over the unemployment spell, and unemployment insurance policy.
    Sample textbook: Equilibrium Unemployment Theory by Christopher A. Pissarides, and others
    Sample syllabus: Spring 2024
  • ECO 394M: Data Mining/Statistical Learning (elective)
    Short description: A machine learning course taught in R, focusing on practical applications rather than theory. Topics include data wrangling, linear regression, classification, resampling methods, regularization, feature selection, nonlinear models, trees and ensembles, latent feature models, principal component analysis, and clustering.
    Sample textbook: Introduction to Statistical Learning by James, Witten, Hastie, and Tibshirani
    Sample syllabus: Spring 2024
  • ECO 394M: Causal Inference (elective)
    Short description: An advanced course in econometrics covering topics related to causal inference and empirical research in economics. The goal is to introduce students to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques (regression discontinuity design, instrumental variables, differences-in-differences) and coding instructions.
    Sample textbook: Causal Inference: The Mixtape by Scott Cunningham
    Sample syllabus: Spring 2024
  • ECO 394M: Time Series Econometrics (elective)
    Short description: An advanced course in econometrics covering current techniques used in time series models with applications in macroeconomics and finance. Topics include distributed lag models, ARMA models, ARCH and GARCH models of volatility, unit roots; forecasting; impulse response functions, local projections, VARs; state-space models, recursive estimation and Kalman filtering. S pecial applications on monetary policy shocks and fiscal shocks.
    Sample textbook: A Guide to Modern Econometrics by M. Verbeek; Elements of Forecasting by F. Diebold, and other textbooks and journal articles
    Sample syllabus: Spring 2024

Internship Course Credit

  • ECO 380D and ECO 180D are available in Summer, Fall, and Spring semesters. See the Internship page for details.