An Empirical Investigation of the Emergence of Money: Contrasting Temporal Difference and Opportunity Cost Reinforcement Learning

Germain Lefebvre, Aurélien Nioche, Sacha Bourgeois-Gironde and Stefano Palminteri

MPRA Paper from University Library of Munich, Germany

Abstract: Money is a fundamental and ubiquitous institution in modern economies. However, the question of its emergence remains a central one for economists. The monetary search-theoretic approach studies the conditions under which commodity money emerges as a solution to override frictions inherent to inter-individual exchanges in a decentralized economy. Although among these conditions, agents' rationality is classically essential and a prerequisite to any theoretical monetary equilibrium, human subjects often fail to adopt optimal strategies in tasks implementing a search-theoretic paradigm when these strategies are speculative, i.e., involve the use of a costly medium of exchange to increase the probability of subsequent and successful trades. In the present work, we hypothesize that implementing such speculative behaviors relies on reinforcement learning instead of lifetime utility calculations, as supposed by classical economic theory. To test this hypothesis, we operationalized the Kiyotaki and Wright paradigm of money emergence in a multi-step exchange task and fitted behavioral data regarding human subjects performing this task with two reinforcement learning models. Each of them implements a distinct cognitive hypothesis regarding the weight of future or counterfactual rewards in current decisions. We found that both models outperformed theoretical predictions about subjects' behaviors regarding the implementation of speculative strategies and that the latter relies on the degree of the opportunity costs consideration in the learning process. Speculating about the marketability advantage of money thus seems to depend on mental simulations of counterfactual events that agents are performing in exchange situations.

Keywords: Money; Speculative Behaviours; Reinforcement Learning (search for similar items in EconPapers)
JEL-codes: C91 D83 E03 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-cbe, nep-exp, nep-mon and nep-pay
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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