Antitrust & Competition Policy Blog

Editor: D. Daniel Sokol
University of Florida
Levin College of Law

Friday, July 12, 2019

Reduced Demand Uncertainty and the Sustainability of Collusion: How AI Could Affect Competition

Jason O'Connor (Pitt) and Nathan Wilson (FTC) have a new paper on Reduced Demand Uncertainty and the Sustainability of Collusion: How AI Could Affect Competition. Highly recommended

Abstract: We consider how technologies that eliminate sources of demand uncertainty change the character and prevalence of coordinated conduct. Our results show that mechanisms that reduce firms' uncertainty about the true level of demand have ambiguous welfare implications for consumers and firms alike. An exogenous increase in firms' ability to predict demand may make collusion possible where it was previously unsustainable. However, it also may make collusion impracticable where it had heretofore been possible. The underlying intuition for this ambiguity is that greater clarity about the true state of demand raises the payoffs both to colluding and to cheating. The net effect will depend on a given market's location in a multidimensional parameter space. Our findings on the ambiguous welfare implications of AI in market intelligence applications contribute to the emerging literature on how algorithms and other forms of artificial intelligence may affect competition.

https://lawprofessors.typepad.com/antitrustprof_blog/2019/07/reduced-demand-uncertainty-and-the-sustainability-of-collusion-how-ai-could-affect-competition.html

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