A Path Integral Approach to Business Cycle Models with Large Number of Agents

Pierre Gosselin, Aïleen Lotz and Marc Wambst

MPRA Paper from University Library of Munich, Germany

Abstract: This paper presents an analytical treatment of economic systems with an arbitrary number of agents that keeps track of the systems' interactions and agents' complexity. This formalism does not seek to aggregate agents. It rather replaces the standard optimization approach by a probabilistic description of both the entire system and agents' behaviors. This is done in two distinct steps. A first step considers an interacting system involving an arbitrary number of agents, where each agent's utility function is subject to unpredictable shocks. In such a setting, individual optimization problems need not be resolved. Each agent is described by a time-dependent probability distribution centered around his utility optimum. The entire system of agents is thus defined by a composite probability depending on time, agents' interactions and forward-looking behaviors. This dynamic system is described by a path integral formalism in an abstract space - the space of the agents' actions - and is very similar to a statistical physics or quantum mechanics system. We show that this description, applied to the space of agents' actions, reduces to the usual optimization results in simple cases. Compared to a standard optimization, such a description markedly eases the treatment of systems with small number of agents. It becomes however useless for a large number of agents. In a second step therefore, we show that for a large number of agents, the previous description is equivalent to a more compact description in terms of field theory. This yields an analytical though approximate treatment of the system. This field theory does not model the aggregation of a microeconomic system in the usual sense. It rather describes an environment of a large number of interacting agents. From this description, various phases or equilibria may be retrieved, along with individual agents' behaviors and their interactions with the environment. For illustrative purposes, this paper studies a Business Cycle model with a large number of agents.

Keywords: path integrals; statistical field theory; business cycle; budget constraint; multi-agent model; interacting agents. (search for similar items in EconPapers)
JEL-codes: C02 C60 E00 E1 (search for similar items in EconPapers)
Date: 2018-10
New Economics Papers: this item is included in nep-hme, nep-mac and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: A path integral approach to business cycle models with large number of agents (2020)
Working Paper: A Path Integral Approach to Business Cycle Models with Large Number of Agents (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:89488

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