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Assad, Stephanie, Calvano, Emilio
, Calzolari, Giacomo, Clark, Robert, Denicolo, Vincenzo, Ershov, Daniel, Johnson, Justin Pappas, Pastorello, Sergio, Rhodes, Andrew, XU, Lei and Wildenbeest, Matthijs
(2021)
Autonomous algorithmic collusion: economic research and policy implications.
TSE Working Paper, n. 21-1210, Toulouse
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Abstract
Markets are being populated with new generations of pricing algorithms, powered with Artificial Intelligence, that hve the ability to autonomously learn to operate. This ability can be both a source of efficiency and cause of concern for the risk that algorithms autonomously and tacitly learn to collude. In this paper we explore recent developments in the economic literature and discuss implications for policy.
| Item Type: | Monograph (Working Paper) |
|---|---|
| Language: | English |
| Date: | March 2021 |
| Place of Publication: | Toulouse |
| Uncontrolled Keywords: | Algorithmic Pricing, Antitrust, Competition Policy, Artificial Intelligence, Collusion, Platforms. |
| JEL Classification: | D42 - Monopoly D82 - Asymmetric and Private Information L42 - Vertical Restraints; Resale Price Maintenance; Quantity Discounts |
| Subjects: | B- ECONOMIE ET FINANCE |
| Divisions: | TSE-R (Toulouse) |
| Institution: | Université Toulouse 1 Capitole |
| Site: | UT1 |
| Date Deposited: | 27 May 2021 14:05 |
| Last Modified: | 05 Jan 2024 09:52 |
| OAI Identifier: | oai:tse-fr.eu:125584 |
| URI: | https://publications.ut-capitole.fr/id/eprint/43525 |
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