Unité mixte de recherche 7235

Longevity, pollution and growth

Natacha Raffin, Thomas Seegmuller

[en]We analyze the interplay between longevity, pollution and growth. We develop an OLG model where longevity, pollution and growth are endogenous. The authorities may provide two types of public services, public health and environmental maintenance, that participate to increase agents’ life expectancy and to sustain growth in the long term. We show that global dynamics might be featured by a high growth rate equilibrium, associated with longer life expectancy and a environmental poverty trap. We examine changes in public policies: increasing public intervention on health or environmental maintenance display opposite effects on global dynamics, i.e. on the size of the trap and on the level of the stable balanced growth path. On the contrary, each type of public policy induces a negative leverage on the long run rate of growth.[/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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