Collusion and Artificial Intelligence: A computational experiment with sequential pricing algorithms under stochastic costs

Gonzalo Ballestero
Additional contact information
Gonzalo Ballestero: Department of Economics, Universidad de San Andrés

No 1, Young Researchers Working Papers from Universidad de San Andres, Departamento de Economia

Abstract: Firms increasingly delegate their strategic decisions to algorithms. A potential con- cern is that algorithms may undermine competition by leading to pricing outcomes that are collusive, even without having been designed to do so. This paper investigates whether Q-learning algorithms can learn to collude in a setting with sequential price competition and stochastic marginal costs adapted from Maskin and Tirole (1988). By extending a previous model developed in Klein (2021), I find that sequential Q-learning algorithms leads to supracompetitive profits despite they compete under uncertainty and this finding is robust to various extensions. The algorithms can coordinate on focal price equilibria or an Edgeworth cycle provided that uncertainty is not too large. However, as the market environment becomes more uncertain, price wars emerge as the only possible pricing pattern. Even though sequential Q-learning algorithms gain supracompetitive profits, uncertainty tends to make collusive outcomes more difficult to achieve.

Keywords: Competition; Policy (search for similar items in EconPapers)
Pages: 33
Date: 2021-11, Revised 2022-10
New Economics Papers: this item is included in nep-big, nep-cmp, nep-com, nep-des, nep-exp, nep-mac and nep-reg
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://webacademicos.udesa.edu.ar/pub/econ/ydoc1.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sad:ypaper:1

Access Statistics for this paper

More papers in Young Researchers Working Papers from Universidad de San Andres, Departamento de Economia Contact information at EDIRC.
Bibliographic data for series maintained by Maria Amelia Gibbons ().