PhD in Business Economics

Through rigorous economic analysis, we advance solutions to most pressing questions faced by firms and policy-makers.

PhD in Business Economics Course Requirements

The PhD in Business Economics curriculum establishes a strong foundation in economic analysis, with a focus on impacts on firms and policymakers.

The Business Economics Curriculum

The PhD in Business Economics attracts students with curiosity about markets and organizations and the drive to build, test, and apply economic models with data. If that sounds like you, download the Business Economics Curriculum sheet by clicking the link below.

Business Economics Curriculum Sheet

The program cultivates collaboration with faculty and prepares students to publish in top journals, positioning graduates for successful academic careers in both business schools and economics departments.

The following is a typical course schedule:

Year 1-2:
  • Four field courses
  • Three electives, including at least one Questrom course

Neoclassical general equilibrium theory. Topics covered include consumption, production, existence of competitive equilibrium, fundamental welfare theorems, externalities, and uncertainty.

Introduction to topics and tools in macroeconomics. Dynamic programming and rational expectations; neoclassical growth and real business cycle models; investment and financial markets; analysis of frictional labor markets.

Noncooperative game theory. Economics of information: adverse selection, signaling, principal agent problem, moral hazard and introduction to mechanism design.

Effects of taxation and government spending; monetary non-neutrality and nominal rigidities; optimal fiscal and monetary policy.

The first half of the course covers introductory real analysis, including metric spaces, correspondences, fixed point theorems, and convex analysis. The second half covers basic skills for programming and computation for economists, including basic programming, software engineering, and numerical methods.

Intermediate level probability and statistics course intended as preparation for econometrics and economic theory. Topics typically covered include random variables, moments, sampling, point and interval estimation, hypothesis testing, and asymptotic theory in the context of univariate and multivariate models.

Advanced treatment of econometric theory: projections, OLS, asymptotic theory, instrumental variables, GLS, heteroskedasticity and autocorrelation robust standard errors, multivariate systems, non-linear models, maximum likelihood, misspecified models, hypothesis testing, introduction to time series, unit root and cointegration, simultaneous equations, GMM.

Advanced course in econometrics with an emphasis on applications to cross-section, panel, and time series data. Typically covers generalized method of moments and/or likelihood-based estimation in the context of limited dependent variable models, linear panel models, rational expectation models, structural vector autoregressions, and treatment effects.

Total Credits: 64

Years 3-5

After the completion of all coursework and a comprehensive exam, students advance to candidacy. At this time, the focus shifts to dissertation research. Students will form a committee, develop a research proposal, and ultimately defend their work. During this time, students will also develop teaching skills and independently teach at least one class.