Coursework

Quantitative Marketing Students

During the first two years of the program, quantitative doctoral students take a mix of courses in marketing, economics, and statistics. In addition to four quantitative PhD courses in the marketing department, students receive rigorous theoretical and empirical training through the Microeconomic Theory, Econometrics, and Industrial Organization sequences from the economics department. Elective courses allow students to develop specialized skills to advance their specific research interests.

This rigorous commitment to coursework gives students an opportunity to build their expertise in key approaches and theories and allows students to take advantage of the instruction available via the many excellent Northwestern doctoral programs beyond marketing (for example, economics, statistics, operations research, and computer science). In addition to introducing students to theoretical areas of research, these courses provide students with training in research philosophy and empirical analysis.

Students in their third year and beyond may take additional classes as needed.

Below is an example of a typical course plan for the first two years in the program.

Year 1

Pre-term: Micro and Econometrics boot camps

Fall

Winter

Spring

Quantitative Marketing: Introduction to Theory and Empirical Methods (MKTG 551-0)

Microeconomic Theory (ECON 410-1)

Introduction to Econometrics (ECON 480-1)

[Optional class]

Quantitative Marketing: Statistical Modeling (MKTG 552-0)


Microeconomic Theory (ECON 410-2)

Introduction to Econometrics (ECON 480-2)

 [Optional class]

Quantitative Marketing: Structural Modeling (MKTG 553-0)


Microeconomic Theory (ECON 410-3)

Introduction to Econometrics (ECON 480-3)

[Optional class]

 

Year 2

Fall

Winter

Spring

Topics in Quantitative Marketing

[Elective class]

Industrial Organization (ECON 450-1)

[Optional class]

Industrial Organization (ECON 450-2)

[Elective class]

[Optional class]

[Optional class]

Industrial Organization (ECON 450-3)

[Elective class]

[Optional class]

[Optional class]

Marketing Department Courses: Quantitative

The marketing department offers four doctoral-level quantitative courses each year. Students take four of these courses in their first year and one course in their second year. More senior doctoral students are welcome to enroll.

Three courses serve as the core foundation for the quantitative doctoral curriculum. Students start with an Introduction to Theory and Empirics in the fall quarter, which introduces a range of concepts and methodological techniques. In the winter students take Statistical Modeling to learn fundamental tools involved in Bayesian and statistical analysis. In the spring, students enroll in Structural Modeling and Analytical Modeling, which discuss the empirical and theoretical application of models grounded in economics to problems in marketing, respectively.

The marketing department offers a fourth course with topics that vary each year, and which allows us to flexibly extend the skills taught in our standard three-course offering.

Marketing Department Courses: Behavioral

At Kellogg, we believe that quantitative students who graduate with a doctorate in marketing should have some familiarity with the kind of research done by those who study consumer behavior. Therefore, in addition to taking the quantitative marketing courses described, quantitative students are encouraged, but not required, to take one doctoral seminar offered by the behavioral marketing faculty at some point during their Kellogg graduate studies. Students often do this during their second year.

Additional Doctoral Courses at Northwestern

Beyond the required marketing and economics courses, quantitative doctoral students can take additional courses as they see fit to achieve their academic goals. Within Kellogg, this might include courses offered in Strategy , Operations, Managerial Economics and Decision Making (MEDS), or Management and Organizations (MORS). Beyond Kellogg, students may take courses in economics, statistics, mathematics, computer science , or any other department if the student feels the course will benefit his or her research agenda.

Below are examples of additional doctoral classes that might be relevant:

Kellogg

Structural Estimation in Operations (OPNS 523)
Foundations of Managerial Economics I: Static Decision Models (MECS 460-1)
Foundations of Managerial Economics II: Dynamic Decision Models (MECS 460-2)
Foundations of Managerial Economics III: Game Theory (MECS 460-3)
Contract Theory and Mechanism Design (MECS 465-1)
The Economics of Organizations (MECS 475-0)
Economics of Innovation (MECS 449-1)
Economics, Social Psychology, and their Experiments (MORS 522)

Economics

Applied Econometrics: Time Series (ECON 482)
Applied Econometrics: Cross-Section (ECON 483)

Statistics and Computer science

Nonparametric methods (STAT 352)
Generalized Linear Models (STAT 456-0)
Topics in Statistics - Data Mining (STAT 359)
Multivariate methods (STAT 448)
Machine Learning (EECS 349, 395, 495)
Social Media Mining (EECS 510)

Independent Study

In rare cases, students in their first and second years may sign up for an independent study with a faculty member as one of the four courses. A Director of Graduate Studies (DGS) must approve independent studies and no more than one independent study may be taken in a quarter. Independent studies are approved only to the extent that the proposed course reflects a level of rigor and expectations similar to a typical doctoral seminar, and only to the extent that the work is not explicitly focused on the development of a first-year or second-year paper. Students should work closely with the faculty member to develop a syllabus for the independent study that clearly documents the course’s aims and expectations. Students should take care that registering for an independent study does not preclude them from taking a course that is critical for their doctoral studies.