Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth

Beitrag in einer Fachzeitschrift


Details zur Publikation

Autorinnen und Autoren: Burger M, Lorz A, Wolfram MT
Zeitschrift: Kinetic and Related Models
Verlag: American Institute of Mathematical Sciences
Jahr der Veröffentlichung: 2017
Band: 10
Seitenbereich: 117-140
ISSN: 1937-5093


Abstract

In this paper we study balanced growth path solutions of a Boltzmann mean field game model proposed by Lucas and Moll [15] to model knowledge growth in an economy. Agents can either increase their knowledge level by exchanging ideas in learning events or by producing goods with the knowledge they already have. The existence of balanced growth path solutions implies exponential growth of the overall production in time. We prove existence of balanced growth path solutions if the initial distribution of individuals with respect to their knowledge level satisfies a Pareto-tail condition. Furthermore we give first insights into the existence of such solutions if in addition to production and knowledge exchange the knowledge level evolves by geometric Brownian motion.


Einrichtungen weiterer Autorinnen und Autoren

King Abdullah University of Science and Technology (KAUST) / جامعة الملك عبد الله للعلوم و التقنية
University of Warwick
Westfälische Wilhelms-Universität (WWU) Münster


Zitierweisen

APA:
Burger, M., Lorz, A., & Wolfram, M.-T. (2017). Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth. Kinetic and Related Models, 10, 117-140. https://dx.doi.org/10.3934/krm.2017005

MLA:
Burger, Martin, Alexander Lorz, and Marie-Therese Wolfram. "Balanced growth path solutions of a Boltzmann mean field game model for knowledge growth." Kinetic and Related Models 10 (2017): 117-140.

BibTeX: 

Zuletzt aktualisiert 2018-03-12 um 14:53