Ph.D. and MSQ in Quantitative Marketing



Pre-Semester: Mathematics, Statistics and Econometrics

First Semester: Advanced Marketing 1 (8 CP), Advanced Econometrics 1 (8 CP), Advanced Microeconomics 1 (8 CP), Mathematical Methods (8 CP)

Second Semester: Advanced Marketing 2 (8 CP), Advanced Econometrics 2 (8 CP), Advanced Microeconomics 2 (8 CP), Programming Languages (4 CP)

Qualifying Examinations

First Semester: Field Courses, Workshop Attendance

Second Semester: Field Courses, Seminar, Workshop Attendance 

Fields Offered:

Marketing (including Customer Value Management, Digital Marketing, Bayesian Modelling for Marketing, experimental studies of consumer behaviour)

Econometrics (for a list of courses see the Econometrics section )

Microeconomics and Management (for a list of courses see the Microeconomics and Management section)

Finance (for a list of courses see the Finance section)

Development and International Economics (for a list of courses see the Development and International Economics section)

Historical and Normative Foundations of Economics (including History of Economic Thought, Normative Foundations.

Workshop Attendance
Independent Studies Course (Teaching Skills)
Third-Year Research Paper
Workshop Attendance
Job Market Course
Thesis Defense

During either the third or fourth year in the program, students may spend one or two semesters abroad for a research stay at an internationally top ranked Ph.D. program. Such stays are facilitated by the faculty advisor.

First Year Courses

The details of the course offerings will differ somewhat from year to year, depending on the faculty member teaching the course in question. The following list summarizes typical first-year course contents. For more details on these courses in any given year as well as the field courses, it is best to consult the course syllabi typically retrievable on individual faculty members’ websites.

Mathematics and Statistics: real analysis, multivariable calculus, linear algebra, linear difference equation systems, introduction to MATLAB, static optimization, statistics, introduction to STATA, linear regression with STATA.
Advanced Marketing 1: customer value management (customer equity, customer-based firm valuation, customer acquisition, retention and cross-selling), digital marketing multivariable testing, experiments. 
Advanced Econometrics 1: fundamentals of linear Regression (OLS, SUR, 2SLS, 3SLS, GMM, QML), cross-section regression models with limited dependent variables, statistic panel data models.
Advanced Microeconomics 1: theory of the household, theory of the firm, decisions under uncertainty, market equilibrium, static and dynamic games under alternative Information structures.
Advanced Mathematical Methods: propability theory, measure theory, stochastic processes, topology, differance and differantial equations, dynamic optimization, numerical methods.
Advanced Marketing 2: frameworks for judgement and decision making, heuristics and biases, context-dependent preferences, emotions and decision making, attention and decision making, process tracing.
Advanced Econometrics 2: integration and cointegration, single and multiple equation time-series models (ARMA, ARDL, VAR, VECM), spectral analysis, conditional heteroskedasticity.
Advanced Microeconomics 2: contract theory (moral hazard, adverse selection, mechanism design, incomplete contracts), general equilibrium theory, welfare economics, externalities.
Programming Languages: major methods of programming (such as Python, R, and C) applied to research, specifically data analysis, in economics and business.