 Detecting Algorithmic Collusion: Insights from Moment Screening MethodsYalçıner Yalã‡in and Selcen ÖZTÃœRK Fiscaoeconomia, 2024, issue 3 Abstract: The development of global, automated, and dynamic manufacturing processes is having a growing impact on industries. Virtual machines commonly function behind the scenes, supporting a variety of operations. Algorithms are the essential intelligence of these virtual machines, greatly increasing efficiency and effectiveness within marketplaces. Algorithms have the ability to promote competition and increase efficiency, eventually improving market competitiveness. However, algorithmic collusion can be maintained using “dynamic pricing†techniques, which are typically associated with automated pricing. Algorithmic collusion leads to increases in prices and/or decreases in the quality of products and services. The main objective and the function of competition authorities is to fight against those formations. In this regard, cartel screening is an important first step toward detecting collusive activity. In this paper, we used several moment screens to capture the effects of algorithmic pricing. Our findings suggest that algorithmic pricing exhibits non-collusive behavior within the particular industry and time frame examined in our analysis. Keywords: Algorithmic Collusion; Behavioral Screens; Cartel Detection; Dynamic Pricing; Machine Learning; Online Marketplace (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:fis:journl:240306 Access Statistics for this article More articles in Fiscaoeconomia from Tubitak Ulakbim JournalPark (Dergipark) |
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