Teacher(s)
Language
English
Main themes
The purpose of the course is to equip students with the necessary tools to conduct solid theoretical, quantitative and empirical research in the field of international trade. The theoretical part of the class covers the main models commonly used by practitioners and researchers in international trade. An in-depth study of the different building blocks will bring students to the frontier of modeling in international trade. The empirical component of the course will examine the most recent evidence on the socio-economic and political impacts of increasing trade integration and globalization. Empirical topics will include the effects of China’s entry into the global market, the consequences of trade on political polarization, violent conflict, and various forms of inequality.
Learning outcomes
At the end of this learning unit, the student is able to : | ||||
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Content
The course aims to provide students with a comprehensive understanding of recent trade theories and to address some of the most salient empirical questions in international trade. At the end of this course, students should have a good understanding of some of the main questions related to international trade, such as: (i) why do nations/firms trade and what do they trade? (ii) how to quantify the welfare gains from trade? (ii) who benefits and who loses from trade? Under which conditions? A good understanding of these questions is essential to reflect on the contemporary debates linked to globalization and protectionism.
Teaching methods
The course consists of interactive lectures.
Evaluation methods
Oral examination at the end of the course.
Note: Students are discouraged from using generative artificial intelligence (AI) systems in this course. However, if AI systems are used during assessments or class activities, they must adhere to the rules outlined in the faculty memorandum on this subject, which is available on the faculty’s intranet site: Note sur l’utilisation responsable des IA — Juillet 2024.
Note: Students are discouraged from using generative artificial intelligence (AI) systems in this course. However, if AI systems are used during assessments or class activities, they must adhere to the rules outlined in the faculty memorandum on this subject, which is available on the faculty’s intranet site: Note sur l’utilisation responsable des IA — Juillet 2024.
Other information
Students should have a solid background in microeconomics, mathematics, and econometrics.
Bibliography
We will discuss a number of recent academic papers. The list will be announced at the beginning of the semester.
Teaching materials
- Detailed Lecture notes and/or slides.
Faculty or entity