MGT-494 / 6 credits
We address societal grand challenges (inequality, climate change ...) using quantitative tools for analyzing market-oriented economies. We aim at designing incentive-compatible policy interventions and actions. Students will use data management/vizualisation/analysis technics.
Session 1: Economics for Action: An Introduction
Session 2: Prosperity: Facts and Proximate Drivers
Session 3: Fundamental Drivers of Development
Session 4: Basics of market economies
Session 5: Market power, pricing and pass-through
Session 6: Strategic behavior and game theory
Session 7: Incentives and Cognitive Bias
Session 8: Introduction to environmental economics
Session 9: Climate change economics
Session 10: Inequalities and Discrimination
Session 11: A Global World
Session 12: Governance and Public Policies
Sessions 13/14: Students'presentations
By the end of the course, the student must be able to:
- Develop an economic argument based on logic and data
- Model complex socio-economic issues (such as inequality, climate change)
- Structure critical thinking
- Use a work methodology appropriate to the task.
- Write a scientific or technical report.
- Make an oral presentation.
- Communicate effectively, being understood, including across different languages and cultures.
The course will be based on active participation of students. We will cover the important theoretical and empirical tools in class, using active teaching methods such as group work and online voting, and students will have to apply this knowledge and develop their own solutions in teams using specific datasets during the seminars. They will work in mixed team (engineers and managers) to design an original answer to the questions and present it to the rest of the class. Such active learning techniques accelerate learning and improve the depth of understanding. They will also focus on skills that are particularly valuable in professional life (such as team working and evaluating each others work). Class attendance is thus fundamental and active student participation is strongly encouraged.
Our idea is to flip the usual learning model: students acquire the basic knowledge before coming to class and time spent in class is devoted to the most complex issues and solving problems in teams.
Expected student activities
The course is divided into lectures and training sessions. Lectures are devoted to the exposition of the big challenges; training sessions are devoted to the acquisition of the quantitative tools and skills (formal models, computational skills, data manipulation and exploration).
Students will have to read textbook chapters, research papers and watch short videos ahead of meetings. This work can be done individually or in small groups.
Weekly assignment (60% of the final grade): You will be required to write a one-page essay ahead of each of the classes based on mandatory readings. This note or essay needs to be written in plain English, using full sentence, and containing a maximum of 600 words. Please submit your essay no later than 2hours before the beginning of the lecture. We will grade 3 of your essays along the semester (picked randomly). In computing the final grade, we will disregard the lowest of the three marks and double the best.
Presentation of a term paper (40% of the final grade): You will have to present one extension of a research paper (from a reading list we will circulate in week 2) during one of the last 2 classes. This extension is made in a group of 4 students, composed at the beginning of the year. By week 4, you should have chosen a paper to replicate and extend. Replication means that you re-produce the main tables of results. Extension means you add to the paper in some way for example by combining the original data with new data, exploiting variation within the existing data that were not utilized, adding robustness checks or constructing new hypothesis tests. If the code is available for the empirical papers, your mark will be heavily weighted towards the extension. You will be required to present your paper and its extension in the last 2 classes. Presentations should last 45-60 minutes (depending on the number of participants) and usual seminar rules apply.
Virtual desktop infrastructure (VDI)
In the programs
- Semester: Fall
- Exam form: During the semester (winter session)
- Subject examined: Economics for challenging times
- Lecture: 3 Hour(s) per week x 14 weeks
- Exercises: 1 Hour(s) per week x 14 weeks