Curriculum

Our 10-month track is designed to be completed mid-July through mid-May. Students are required to take ten 3-credit courses for a total of 30 credit hours. Courses are offered in a 2-4-4 format, with two courses in the summer semester, four courses in the fall semester, and four courses in the spring semester. No thesis is required. See below for detailed information about course offerings.

Our 18-month and 24-month tracks also begin in mid-July but are completed later. For the July 2023 entering cohort, these programs would end in December 2024 and May 2025, respectively. The degree requirements, including completion of the core courses and 30 graded credit hours, are identical in all three degree tracks. A thesis option is not required (or offered) in any of the degree tracks. A longer degree option can be a good fit for many students, including those looking to: complete the degree at a slower pace; work part-time or pursue an internship while completing the degree, build a stronger profile for PhD applications or private-sector jobs, and/or take additional Economics courses.

The following chart provides a side-by-side comparison of the three program tracks. *M.A. program staff will work closely with individual students on course selection and the progress to degree.

Semester 10-month 18-month 24-month
Summer Math for Economists
Probability & Statistics
Optional: Real Analysis		 Math for Economists
Probability & Statistics
Optional: Real Analysis		 Math for Economists
Probability & Statistics
Optional: Real Analysis
Fall Microeconomics
Econometrics
Macroeconomics
1 elective		 Microeconomics
Econometrics
Macroeconomics or 1 elective		 Microeconomics
Econometrics
Macroeconomics or 1 elective
Spring 3-4 electives 2-3 electives
Optional: Internship		 1-3 electives
Optional: Internship
Fall Macroeconomics (if not yet taken)
2-3 electives
Optional: Internship		 Macroeconomics (if not yet taken)
1-3 electives
Optional: Internship
Spring 1-3 electives
Optional: Internship

*Please note that to satisfy U.S. student visa requirements, international students must enroll on a full-time basis (9 credit hours/3 classes) in fall and spring semesters. The only exception to this U.S. immigration policy is in the final semester of study (the semester of graduation) when international students are permitted to enroll on a part-time basis.

Rigor

The MA program is highly ranked nationally. The technical level of the MA program has been targeted to be in between the level of intermediate undergraduate courses and first-year doctoral courses. (For example, the Micreconomics course (ECO 394K) will be more advanced than our undergraduate Intermediate Economics (ECO 420K) and less advanced than our doctoral Microeconomics I (ECO 387L.1).) The MA courses have been specially designed for this program and are completely distinct from our PhD courses.

Some sample course syllabi are provided below.

Comparable Programs

The MA curriculum will fully prepare students who wish to apply to economics PhD programs. The curriculum is similar in rigor to the Master’s programs offered at other top departments (Boston University, Duke University, New York University, Columbia University). Please note that the technical level of this program is more advanced than most “Applied Economics” master’s programs. For a list of other terminal master’s programs in the United States, please visit the American Economic Association website.

Courses

Additional details on the MA courses are provided below. Five core courses are offered in the summer and fall semesters combined. Elective courses will be offered in both the fall and spring semesters. In addition to brief course descriptions, we have provided sample textbooks for some of the courses; while these textbooks will not necessarily be adopted by faculty teaching these courses, they do provide a good sense of the level at which the courses will be taught.

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 2023
  • 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 2023
  • 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 2023
  • 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 2023
  • 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 2023
  • 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 2023
  • 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 2023