Author: Richard SteppePublisher:
ISBN:
Category :
Languages : en
Pages : 136
Book Description
Algorithmic Pricing and Tacit Collusion
Author: Richard SteppeAlgorithmic Tacit Collusion
Author: Valeria CaforioPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
In light of the ongoing debate on algorithmic collusion, this paper intends to answer the following question: should algorithmic tacit collusion be prohibited under EU competition law? By algorithmic tacit collusion it is meant the capability of algorithmic pricing agents to unilaterally engage into tacitly collusive strategies without human intervention (we also call it 'machine-to-machine cooperation' or 'algorithmic interdependent pricing'). Essentially, this practice raises the very same issues as the well-known oligopoly problem. Therefore, to make it prohibited one could envisage the traditional proposed solution of disentangling the categories of article 101 TFEU from the notions of an 'act of reciprocal communication between firms' or 'meeting of minds'. The paper sets out to discuss this option and its implications. It argues that, from a competition law standpoint, although algorithmic tacit collusion remains undesirable, the notions of agreement and concerted practices should not be changed to encompass it. Rather, it embraces a regulatory perspective referred to as 'algorithms by design' which relies on introducing a legal obligation for firms to program algorithms in such a way as to prevent them from setting oligopolistic prices. In particular, while exploring this regulatory proposal, the paper discusses the peculiar case of algorithms that, though designed not to violate antitrust law, end up charging collusive prices. In this regard, the paper develops a second proposal: it introduces the idea of 'outcome visibility' to nail firms to their responsibility. This concept implies the idea that even if firms are not aware that their pricing algorithms are implementing a collusive strategy, they cannot ignore their visible market outcome.
Algorithmic Pricing & Collusion; The Limits of Antitrust Enforcement
Author: Sumit BhadauriaPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
The combination of big data, large storage capacity and computational power has strengthened the emergence of algorithms in making myriads of business decision. It allows business to gain a competitive advantage by making automatic and optimize decision making. In particular, the use of pricing algorithms allows business to match the demand and supply equilibrium by monitoring & setting dynamic pricing. It benefits consumer alike to see and act on fast changing prices. However, on the downside, the widespread use of algorithm in an industry has the effect of altering the structural characteristic of market such as price transparency, high speed trading which increases the likelihood of collusion. The ability of pricing algorithm to solve the cartel incentive problem by quickly detecting and punishing the deviant further strengthen the enforcement of price fixing agreement. In addition, the use of more advance forms of algorithm such as self-learning algorithm allows business to achieve a tacitly collusive outcome in limited market characteristic even without communication between humans. This raises the fundamental challenge for anti-cartel enforcement as the current law in most jurisdictions is ill-equipped to deal with algorithmic facilitated tacit collusion. The legality of tacit collusion is questionable primarily because the pricing algorithm has the ability to alter the market characteristics where the tacitly collusive outcome is difficult to achieve; thus widening the scope of the so-called 'oligopoly problem'. This paper studies the usages of pricing algorithms by business in online markets. In particular, the paper identify the conditions under which the algorithm prices causes the harm to consumers. It seeks to analyze how algorithms might facilitate or even causes the collusive outcome without human interventions. Further, it looks at the legal challenges faced by the competition authorities around the globe to deal with the algorithmic let collusion and examine the various approaches suggested to counter act it.
Algorithms, Collusion and Competition Law
Author: Steven Van UytselPublisher: Edward Elgar Publishing
ISBN: 1802203044
Category : Law
Languages : en
Pages : 281
Book Description
What is algorithmic collusion? This evaluative book provides an insight into tackling this important question for competition law, with contrasting critical perspectives, including theoretical, empirical, and doctrinal – the latter frequently from a comparative perspective. Bringing together scholarly discussion on algorithmic collusion, the book questions whether competition law is adeptly equipped to deal with its various facets.
Virtual Competition
Author: Ariel EzrachiPublisher: Harvard University Press
ISBN: 0674545478
Category : Business & Economics
Languages : en
Pages : 365
Book Description
“A fascinating book about how platform internet companies (Amazon, Facebook, and so on) are changing the norms of economic competition.” —Fast Company Shoppers with a bargain-hunting impulse and internet access can find a universe of products at their fingertips. But is there a dark side to internet commerce? This thought-provoking exposé invites us to explore how sophisticated algorithms and data-crunching are changing the nature of market competition, and not always for the better. Introducing into the policy lexicon terms such as algorithmic collusion, behavioral discrimination, and super-platforms, Ariel Ezrachi and Maurice E. Stucke explore the resulting impact on competition, our democratic ideals, our wallets, and our well-being. “We owe the authors our deep gratitude for anticipating and explaining the consequences of living in a world in which black boxes collude and leave no trails behind. They make it clear that in a world of big data and algorithmic pricing, consumers are outgunned and antitrust laws are outdated, especially in the United States.” —Science “A convincing argument that there can be a darker side to the growth of digital commerce. The replacement of the invisible hand of competition by the digitized hand of internet commerce can give rise to anticompetitive behavior that the competition authorities are ill equipped to deal with.” —Burton G. Malkiel, Wall Street Journal “A convincing case for the need to rethink competition law to cope with algorithmic capitalism’s potential for malfeasance.” —John Naughton, The Observer
What Do We Know About Algorithmic Tacit Collusion?
Author: Ai DengPublisher:
ISBN:
Category :
Languages : en
Pages : 17
Book Description
The past few years have seen many legal scholars and antitrust agencies expressing interest in and concerns with algorithmic collusion. In this paper, I survey and draw lessons from the literature on Artificial Intelligence and on the economics of algorithmic tacit collusion. I show that a good understanding of this literature is a crucial first step to better understand the antitrust risks of algorithmic pricing and devise antitrust policies to combat such risks.
Product Rankings, AI Pricing Algorithms, and Collusion
Author: Liying QiuPublisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
Reinforcement learning (RL) based pricing algorithms have been shown to tacitly collude to set supra-competitive prices in oligopoly models of repeated price competition. We investigate the impact of ranking systems, a common feature of online marketplaces, on algorithmic collusion in prices. We study experimentally the behavior of algorithms powered by Artificial Intelligence (deep Q-learning) in a workhorse duopoly model of repeated price competition in the presence of product rankings. Through extensive experiments, we find that the introduction of the ranking system significantly mitigates the tacit collusion that stems from RL based pricing. The ranking system increases the incentives for the RL agents to deviate from a collusive price which in turn requires more complicated punishment strategies to prevent deviation and sustain collusive prices. These punishment strategies are harder to learn for RL algorithms in non stationary environments and the high collusive prices are not sustained as a result. The ranking system's mitigation effect is moderated by the horizontal differentiation between the products offered by the firms and the stickiness of product ranks. In particular, when products are more horizontally differentiated from each other and when past sales have a larger influence on product ranks (sticky ranking), the prices charged by the two firms are higher and the ranking system's mitigation effect is weaker. However, in both cases, prices in the presence of ranking are lower than that in the absence of ranking. Our analysis sheds light on the impact of ranking systems on consumer welfare and on design of ranking systems to prevent algorithmic pricing collusion.
Big Data and Competition Policy
Author: Maurice E. StuckePublisher:
ISBN: 9780191092190
Category : LAW
Languages : en
Pages :
Book Description
The first text to provide understanding of the important new issue of Big Data and how it relates to competition laws and policy, both in the EU and US.
Research Handbook on the Law of Artificial Intelligence
Author: Woodrow BarfieldPublisher: Edward Elgar Publishing
ISBN: 1786439050
Category : Computers
Languages : en
Pages : 736
Book Description
The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.
Repeated Games and Reputations
Author: George J. MailathPublisher: Oxford University Press
ISBN: 0198041217
Category : Business & Economics
Languages : en
Pages : 664
Book Description
Personalized and continuing relationships play a central role in any society. Economists have built upon the theories of repeated games and reputations to make important advances in understanding such relationships. Repeated Games and Reputations begins with a careful development of the fundamental concepts in these theories, including the notions of a repeated game, strategy, and equilibrium. Mailath and Samuelson then present the classic folk theorem and reputation results for games of perfect and imperfect public monitoring, with the benefit of the modern analytical tools of decomposability and self-generation. They also present more recent developments, including results beyond folk theorems and recent work in games of private monitoring and alternative approaches to reputations. Repeated Games and Reputations synthesizes and unifies the vast body of work in this area, bringing the reader to the research frontier. Detailed arguments and proofs are given throughout, interwoven with examples, discussions of how the theory is to be used in the study of relationships, and economic applications. The book will be useful to those doing basic research in the theory of repeated games and reputations as well as those using these tools in more applied research.