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How communication makes the difference between a cartel and tacit collusion : a machine learning approach

Andres, Maximilian; Bruttel, Lisa Verena; Friedrichsen, Jana - 2022

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free … cartel formation and indirect attempts to collude tacitly. We document that firms are less likely to communicate explicitly … sanctions on communication reinforces the direct cartel-deterring effect of sanctions as collusion is more difficult to reach …

Persistent link: https://www.econbiz.de/10013164725

Communicating cartel intentions

Andres, Maximilian; Bruttel, Lisa Verena - 2024

explicit about how the cartel plans to behave. …

Persistent link: https://www.econbiz.de/10014543450

How communication makes the difference between a cartel and tacit collusion : a machine learning approach

Andres, Maximilian; Bruttel, Lisa Verena; Friedrichsen, Jana - 2022

Persistent link: https://www.econbiz.de/10013418834

Autonomous algorithmic collusion : economic research and policy implications

Assad, Stephanie; Calvano, Emilio; Calzolari, Giacomo; … - In: Oxford review of economic policy 37 (2021) 3, pp. 459-478

Persistent link: https://www.econbiz.de/10012655281

Reduced demand uncertainty and the sustainability of collusion : How AI could affect competition

O'Connor, Jason; Wilson, Nathan E. - In: Information economics and policy : IEP 54 (2021), pp. 1-22

Persistent link: https://www.econbiz.de/10012655874

Algorithmic and human collusion

Werner, Tobias - 2021

As self-learning pricing algorithms become popular, there are growing concerns among academics and regulators that algorithms could learn to collude tacitly on non-competitive prices and thereby harm competition. I study popular reinforcement learning algorithms and show that they develop...

Persistent link: https://www.econbiz.de/10012661268

Machine learning, market manipulation and collusion on capital markets : Why the “Black Box” matters

Azzutti, Alessio; Ringe, Wolf-Georg; Stiehl, Hans Siegfried - 2021

This paper offers a novel perspective on the implications of increasingly autonomous and “black box” algorithms, within the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and particularly its subfield of machine learning (ML) methods...

Persistent link: https://www.econbiz.de/10012587161

Reduced demand uncertainty and the sustainability of collusion : how AI could affect competition

O'Connor, Jason; Wilson, Nathan - 2019

Persistent link: https://www.econbiz.de/10012059942

Artificial intelligence, algorithmic pricing and collusion

Calvano, Emilio; Calzolari, Giacomo; Denicolò, Vincenzo; … - 2018

Persistent link: https://www.econbiz.de/10012113031

Autonomous algorithmic collusion: economic research and policy implications

Assad, Stephanie; Calvano, Emilio; Calzolari, Giacomo; … - 2021

Persistent link: https://www.econbiz.de/10012542205