Unité mixte de recherche 7235

The determinants of international mobility of students

Michel Beine, Romain Noël, Lionel Ragot

[en]This paper analyzes the determinants of the choice of location of international students. Building on the documented trends in international migration of students, we develop a small theoretical model allowing to identify the various factors associated to the attraction of migrants as well as the costs of moving abroad. Using new data capturing the number of students from a large set of origin countries studying in a set of 13 OECD countries, we assess the importance of the various factors identified in the theory. We find support for a significant network effect in the migration of students, a result so far undocumented in the literature. We also find a significant role for cost factors such as housing prices and for attractiveness variables such as the reported quality of universities. In contrast, we do not find an important role for registration fees.[/en]


mardi 17 mai 2022

Rencontres économiques

9h30 à 11h30

Comment se débarrasser des énergies fossiles et développer les énergies renouvelables dans un monde en crise ?

jeudi 19 mai 2022


Christophe Blot

Are all central bank asset purchases the same?

lundi 23 mai 2022

Law, Institutions and Economics in Nanterre (LIEN)

Clara Jean (Grenoble Ecole de Management)

The Value of Your Data: Privacy and Personal Data Exchange Networks

mardi 24 mai 2022

Recherche et Economie et Socioéconomie Politique, des Institutions et des Régulations (RESPIR)

Alice Sindzingre (CEPN) et Fabrice Tricou

De 13h30 à 15h30

Six forms of hierarchy for a theoretical analysis of capitalism

lundi 30 mai 2022

Law, Institutions and Economics in Nanterre (LIEN)

Antoine Dubus (ETH Zurich)

Salle G110

Data Driven Mergers and Acquisitions with Information Synergies

mardi 31 mai 2022

Series of Webinars on Economics of Environment, Energy and Transport (SWEEET)

Juan Pablo Montero (PUC)


jeudi 9 juin 2022


Rémi Generoso


jeudi 9 juin 2022

Groupe de travail « Intelligence artificielle »

Hugo Le Picard (IFRI)

Salle G614B

Le deep learning au service de l’analyse des énergies renouvelables en Afrique

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