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Author: Jeanine Miklós-Thal
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
We build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand conditions, it also increases each firm's temptation to deviate to a lower price in time periods of high predicted demand. Overall, our research suggests that, despite concerns expressed by policymakers, better forecasting and algorithms can lead to lower prices and higher consumer surplus.
Author: Jeanine Miklós-Thal
Publisher:
ISBN:
Category :
Languages : en
Pages : 18
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Book Description
We build a game-theoretic model to examine how better demand forecasting due to algorithms, machine learning and artificial intelligence affects the sustainability of collusion in an industry. We find that while better forecasting allows colluding firms to better tailor prices to demand conditions, it also increases each firm's temptation to deviate to a lower price in time periods of high predicted demand. Overall, our research suggests that, despite concerns expressed by policymakers, better forecasting and algorithms can lead to lower prices and higher consumer surplus.
Author: Simon Martin
Publisher:
ISBN: 9783863043810
Category :
Languages : en
Pages :
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Book Description
We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question. Moreover, our analysis reveals a dual role of improving forecasting ability when actions are not observable. Deviations become more tempting, reducing profits, but also uncertainty concerning deviations is increasingly eliminated. This results in a u-shaped relationship between profits and prediction ability. When prediction ability is perfect, the "observable actions" case emerges.
Author: Ariel Ezrachi
Publisher: Harvard University Press
ISBN: 0674545478
Category : Business & Economics
Languages : en
Pages : 365
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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
Author: Thomas Loots
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
"This thesis demonstrates algorithmic collusion in a price oligopoly with multinomial logit demand. Of main interest is the scenario where competing firms independently adopt copies of the same price algorithm. One of the key takeaways is that in this scenario, major challenges to achieving and sustaining supra-competitive outcomes can be overcome by the firms. We show this by constructing competitive price algorithms that have collusive capabilities when at least one of the opponents uses a copy of the same algorithm. Importantly, the firms do not have to activate the algorithm at the same time, do not need to use the same input parameters, and do not need to know that they are using the same algorithm. Moreover, the proposed algorithms do not engage in illicit forms of communication or signaling, and therefore exemplify tacit (lawful) algorithmic collusion . This thesis thus contributes to the ongoing debate on the extent to which collusion by algorithms is possible within the confines of existing antitrust law and jurisprudence, and further contributes to the fields of axiomatic bargaining, dynamic pricing, and demand learning in the presence of competitors."--
Author: Aurelien Portuese
Publisher: Springer Nature
ISBN: 3030858596
Category : Law
Languages : en
Pages : 182
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Book Description
Algorithms are ubiquitous in our daily lives. They affect the way we shop, interact, and make exchanges on the marketplace. In this regard, algorithms can also shape competition on the marketplace. Companies employ algorithms as technologically innovative tools in an effort to edge out competitors. Antitrust agencies have increasingly recognized the competitive benefits, but also competitive risks that algorithms entail. Over the last few years, many algorithm-driven companies in the digital economy have been investigated, prosecuted and fined, mostly for allegedly unfair algorithm design. Legislative proposals aim at regulating the way algorithms shape competition. Consequently, a so-called “algorithmic antitrust” theory and practice have also emerged. This book provides a more innovation-driven perspective on the way antitrust agencies should approach algorithmic antitrust. To date, the analysis of algorithmic antitrust has predominantly been shaped by pessimistic approaches to the risks of algorithms on the competitive environment. With the benefit of the lessons learned over the last few years, this book assesses whether these risks have actually materialized and whether antitrust laws need to be adapted accordingly. Effective algorithmic antitrust requires to adequately assess the pro- and anti-competitive effects of algorithms on the basis of concrete evidence and innovation-related concerns. With a particular emphasis on the European perspective, this book brings together experts and scrutinizes on the implications of algorithmic antitrust for regulation and innovation.
Author: Woodrow Barfield
Publisher: Cambridge University Press
ISBN: 1108663184
Category : Law
Languages : en
Pages : 1327
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Book Description
Algorithms are a fundamental building block of artificial intelligence - and, increasingly, society - but our legal institutions have largely failed to recognize or respond to this reality. The Cambridge Handbook of the Law of Algorithms, which features contributions from US, EU, and Asian legal scholars, discusses the specific challenges algorithms pose not only to current law, but also - as algorithms replace people as decision makers - to the foundations of society itself. The work includes wide coverage of the law as it relates to algorithms, with chapters analyzing how human biases have crept into algorithmic decision-making about who receives housing or credit, the length of sentences for defendants convicted of crimes, and many other decisions that impact constitutionally protected groups. Other issues covered in the work include the impact of algorithms on the law of free speech, intellectual property, and commercial and human rights law.
Author: Marcelo Corrales
Publisher: Springer
ISBN: 9811328749
Category : Law
Languages : en
Pages : 245
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Book Description
Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robots, including sensors, virtual realities, algorithms, bots, drones, self-driving cars, and more sophisticated “human-like” robots are creating new and previously unimagined challenges for regulators. These advances also give rise to new opportunities for legal professionals to make efficiency gains in the delivery of legal services. With the exponential growth of such technologies, radical disruption seems likely to accelerate in the near future. This collection brings together a series of contributions by leading scholars in the newly emerging field of artificial intelligence, robotics, and the law. The aim of the book is to enrich legal debates on the social meaning and impact of this type of technology. The distinctive feature of the contributions presented in this edition is that they address the impact of these technological developments in a number of different fields of law and from the perspective of diverse jurisdictions. Moreover, the authors utilize insights from multiple related disciplines, in particular social theory and philosophy, in order to better understand and address the legal challenges created by AI. Therefore, the book will contribute to interdisciplinary debates on disruptive new AI technologies and the law.
Author: Maurice E. Stucke
Publisher:
ISBN: 9780191092190
Category : LAW
Languages : en
Pages :
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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.
Author: Steven Van Uytsel
Publisher: Edward Elgar Publishing
ISBN: 1802203044
Category : Law
Languages : en
Pages : 281
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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.
Author: Malte Jeschonneck
Publisher:
ISBN: 9783863043698
Category :
Languages : en
Pages :
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Book Description
The increased prevalence of pricing algorithms incited an ongoing debate about new forms of collusion. The concern is that intelligent algorithms may be able to forge collusive schemes without being explicitly instructed to do so. I attempt to examine the ability of reinforcement learning algorithms to maintain collusive prices in a simulated oligopoly of price competition. To my knowledge, this study is the first to use a reinforcement learning system with linear function approximation and eligibility traces in an economic environment. I show that the deployed agents sustain supra-competitive prices, but tend to be exploitable by deviating agents in the short-term. The price level upon convergence crucially hinges on the utilized method to estimate the qualities of actions. These findings are robust to variations of parameters that control the learning process and the environment.
