Algorithmic Pricing and Market Coordination – Toward a Notion of ‘Collusive Risk’

IF 1.4 4区社会学 Q1 LAW

Law Probability & Risk Pub Date : 2020-05-20 DOI:10.2139/ssrn.3914922

Juliane K. Mendelsohn

引用次数: 0

Abstract

Over the past couple of years, many competition and antitrust scholars have feared the dawn of ‘algorithmic collusion’. Some have thus suggested expanding the notions of ‘collusion’ and ‘agreement’ in order to capture such coordination. Rather than using an expansive reading of ‘collusion’, the author of this article suggests an approach that works with the core and original intent of Article 101(1) TFEU: the fostering of independent conduct and prevention of market coordination. It finds this to be doctrinally undisputed and also consistent with longstanding competition policy debates, as well as an egalitarian notion of price that lays the foundation of the free market economy. On this basis, and considering given uncertainties, an operational notion of ‘collusive risk’ is put forward.

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算法定价与市场协调——走向“合谋风险”的概念

在过去的几年里，许多竞争和反垄断学者担心“算法勾结”的到来。因此，一些人建议扩大“勾结”和“协议”的概念，以捕捉这种协调。这篇文章的作者并没有对“共谋”一词进行宽泛的解读，而是提出了一种符合TFEU第101(1)条核心和初衷的方法:促进独立行为和防止市场协调。它发现，这在理论上是无可争议的，而且与长期以来的竞争政策辩论以及为自由市场经济奠定基础的平等主义价格观念是一致的。在此基础上，考虑到给定的不确定性，提出了“共谋风险”的操作概念。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Law Probability & Risk MATHEMATICSSTATISTICS & PROBABILITY&-STATISTICS & PROBABILITY

CiteScore

2.10

自引率

28.60%

发文量

期刊介绍： Law, Probability & Risk is a fully refereed journal which publishes papers dealing with topics on the interface of law and probabilistic reasoning. These are interpreted broadly to include aspects relevant to the interpretation of scientific evidence, the assessment of uncertainty and the assessment of risk. The readership includes academic lawyers, mathematicians, statisticians and social scientists with interests in quantitative reasoning. The primary objective of the journal is to cover issues in law, which have a scientific element, with an emphasis on statistical and probabilistic issues and the assessment of risk. Examples of topics which may be covered include communications law, computers and the law, environmental law, law and medicine, regulatory law for science and technology, identification problems (such as DNA but including other materials), sampling issues (drugs, computer pornography, fraud), offender profiling, credit scoring, risk assessment, the role of statistics and probability in drafting legislation, the assessment of competing theories of evidence (possibly with a view to forming an optimal combination of them). In addition, a whole new area is emerging in the application of computers to medicine and other safety-critical areas. New legislation is required to define the responsibility of computer experts who develop software for tackling these safety-critical problems.