Quantitative Economics - 1st year of master's degree

Program Objectives

The first year of the program provides a solid foundation in the fundamentals of theoretical and applied economics. Covering a variety of topics in macroeconomics, microeconomics, and industrial organization, the focus will be on modeling economic decisions and interactions among economic actors. You will explore applications to relevant economic policy issues, such as health policy, poverty and development, and climate change. Courses in data management, macroeconometrics, and microconometrics will help you become familiar with data treatment and analysis. Empirical data applications will enhance your coding skills using common software tools in economics, such as R, MATLAB, and Stata.

Program objectives:

  • Master fundamental concepts in economics (macroeconomics, microeconomics, game theory, industrial organization, etc.).
  • Learn to model and solve complex economic problems, apply them to various issues (such as health, education, development, trade, … ), and critically assess economic policy design.
  • Learn to process and analyze data to conduct professional and sound data analyses.
  • Acquire knowledge of groundbreaking research in economics and explore decision-making processes among public and private stakeholders.
  • Convey economic, statistical, and/or econometric findings to diverse audiences, both orally and in writing.
Types of education
Executive Education
Initial training
Language(s)
English
ECTS Credits
60 credits
Internship
12 weeks
Capacity
30
Type of Diploma
Diploma from a major institution conferring the Master's degree
Academic Year
2025/2026


Contacts

  • Olivia Bertelli

    Associate professor

    Director of the 1st year program of the Master's Degree in Quantitative Economics

  • Alexandra Reverchon

    Training assistant

     Send an email


The challenges of the ecological and social transition in the Master's degree programs

Several courses and tools are offered to students in the Master’s program, regardless of their specialization