Detecting Algorithmic Collusion: Insights from Moment Screening Methods

Authors : Yalçıner Yalçın, Selcen Öztürk

Pages : 1066-1084

Doi:10.25295/fsecon.1477143

View : 86 | Download : 83

Publication Date : 2024-09-27

Article Type : Research Paper

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 : Algoritmik Anlaşma, Davranışsal Tarama, Kartel Tespiti, Dinamik Fiyatlama, Makine Öğrenmesi, Online Pazar