Ph.D. and MSQ in Quantitative Economics
The Ph.D. Program is designed to ensure that students acquire a thorough knowledge of economic theory, the structure of modern economies, as well as econometric and computational methods before beginning their own research under faculty supervision.
In the first year students attend core courses in microeconomics, macroeconomics, econometrics, and mathematical methods. At the end of that year they must pass qualifying examinations in microeconomics, macroeconomics, and econometrics. In the second year students complete field courses in two to three fields of their election and begin to work on their own research with the support of a faculty advisor, whose main role is to help them to make the transition from coursework to research and to identify suitable dissertation topics. By the end of their third year students must have completed their first research paper. The dissertation is completed in the fourth year of the program. It must be a major piece of research and its chapters must have the potential for publication in an international scientific journal.
First-year students in the MSQ Program in Quantitative Economics enroll in the same set of courses as their peers from the Ph.D. Program in Economics. Those who complete their first year of studies with strong success are eligible and strongly encouraged to join the Ph.D. Program in Economics from their second year of studies onwards. The MSQ Program in Quantitative Economics is completed with a Master thesis written in the final months of the second year of studies.Students who decide to take part in both programs may earn both an MSQ and a Ph.D. degree in a total of four years.
Pre-Semester: Mathematics, Statistics and Econometrics
First Semester: Advanced Econometrics 1 (8 CP), Advanced Macroeconomics 1 (8 CP), Advanced Microeconomics 1 (8 CP), Mathematical Methods (8 CP)
Second Semester: Advanced Econometrics 2 (8 CP), Advanced Macroeconomics 2 (8 CP), Advanced Microeconomics 2 (8 CP), Programming Languages (4 CP)
First Semester: Field Courses, Workshop Attendance
Second Semester: Field Courses, Seminar, Workshop Attendance
Development and International Economics (including Cross-Country Studies, Development Microeconomics, Economic Growth, International Trade)
Econometrics (including Bayesian Econometrics, Dynamic Panel Models, Econometrics of Duration and Transition Data, Long Memory in Time-Series, Non-Parametric Econometrics)
Finance (including Asset Pricing, Corporate Finance Theory, Empirical Banking, Household Finance, Option Pricing, Taxes and Finance)
Macroeconomics (including Consumption and Saving, Economic Growth, Family Macroeconomics, Household Finance, Monetary Theory and Policy, Monetary and Fiscal Policy, Numerical Methods in Macroeconomics)
Marketing (including Bayesian Modelling for Marketing, Customer Management and Social Media, Pricing and Online-Advertising, Structural Models and Competition)
Microeconomics and Management (including Behavioral Auction Theory, Behavioral Economics, Decision Making under Risk and Ambiguity, Economics of Taxation, Empirical Labor Economics, Empirics of Contracts, Experimental Economics, General Equilibrium Theory: History, Incentives in Organizations, Intergenerational Economics, Modeling Group Behavior Using Game Theory, Taxes and Finance)
Historical and Normative Foundations of Economics (including History of Economic Thought, Normative Foundations)
|Independent Studies Course (Teaching Skills)|
|Third-Year Research Paper|
|Job Market Course|
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 following list summarizes typical first-year course contents but the details of the offerings may differ from year to year, depending on the faculty member teaching the course in question. For more details on these courses in any given year as well as the field courses, please 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 Econometrics 1: fundamentals of linear regression (OLS, SUR, 2SLS, 3SLS, GMM, QML), cross-section regression models with limited dependent variables, static panel data models.
Advanced Macroeconomics 1: dynamic optimization in models with representative and with heterogeneous agents, consumption, investment, saving and financial markets.
Advanced Microeconomics 1: theory of the household, theory of the firm, decisions under uncertainty, market equilibrium, static and dynamic games under alternative information structures.
Mathematical Methods: probability theory, measure theory, stochastic processes, topology, difference and differential equations, dynamic optimization, numerical methods.
Advanced Econometrics 2: integration and cointegration, single and multiple equation time-series models (ARMA, ARDL, VAR, VECM), spectral analysis, conditional heteroskedasticity.
Advanced Macroeconomics 2: structure of DSGE models, monopolistic competition and pricing, strategic complementarities, optimal monetary and fiscal policy, learning.
Advanced Microeconomics: 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.