CHM Seminar: Artificial Intelligence, Algorithmic Recommendations, and Competition – Emilio Calvano

Artificial Intelligence, Algorithmic Recommendations, and Competition

Speaker: Emilio Calvano, Tor Vergata University

We present a methodology for analyzing the impact of algorithmic recommendations on product market competition, addressing concerns that have been raised in both academic and policy circles regarding their potential anti-competitive effects. Our analysis demonstrates that recommender systems (RSs) lead to higher market concentration and prices compared to a scenario where algorithmic recommendations are unavailable and consumers rely solely on individual search. However, RSs also improve the match between products and consumers and reduce the need for expensive search processes. By accounting for both the positive and negative effects, we find that RSs are likely to increase consumer surplus for reasonable parameter values. However, increasing the amount of data available to the algorithms may lead to a reduction in consumer surplus. We also examine the potential for manipulation of recommendations and its impact on competition, finding that such manipulation is more likely to represent an exclusionary abuse than an exploitative one.

Emilio Calvano is an economist with expertise in the field of industrial organization, specifically focusing on digital and media markets. He holds a Ph.D. from the University of Toulouse and currently serves as a Full Professor of Economics at LUISS university in Rome and as Associate Faculty member at the Toulouse School of Economics. His work has been published in top scholarly journals, including the American Economic Review, Science, Management Science, American Economic Journal: Micro, the Economic Journal, and the Journal of Economics and Management Strategy. Emilio Calvano's research interests revolve around the Industrial Organisation of digital and media markets. He explores the dynamics of competition within these sectors and investigates the implications of market structure and firm behavior. He was recently awarded an ERC (European Research Council) Advanced grant in 2023 focusing on studying the impact of Artificial Intelligence-powered algorithms on competition.

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