Quotation Wachs, Johannes, Kertesz, Janos. 2019. A network approach to cartel detection in public auction markets. Scientific Reports. 9 (10818)




Competing firms can increase profits by setting prices collectively, imposing significant costs on consumers. Such groups of firms are known as cartels and because this behavior is illegal, their operations are secretive and difficult to detect. Cartels feel a significant internal obstacle: members feel short-run incentives to cheat. Here we present a network-based framework to detect potential cartels in bidding markets based on the idea that the chance a group of firms can overcome this obstacle and sustain cooperation depends on the patterns of its interactions. We create a network of firms based on their co-bidding behavior, detect interacting groups, and measure their cohesion and exclusivity, two group-level features of their collective behavior. Applied to a market for school milk, our method detects a known cartel and calculates that it has high cohesion and exclusivity. In a comprehensive set of nearly 150,000 public contracts awarded by the Republic of Georgia from 2011 to 2016, detected groups with high cohesion and exclusivity are significantly more likely to display traditional markers of cartel behavior. We replicate this relationship between group topology and the emergence of cooperation in a simulation model. Our method presents a scalable, unsupervised method to find groups of firms in bidding markets ideally positioned to form lasting cartels.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Scientific Reports
Citation Index SCI
Language English
Title A network approach to cartel detection in public auction markets
Volume 9
Number 10818
Year 2019
URL http://www.nature.com/articles/s41598-019-47198-1.pdf
DOI http://dx.doi.org/10.1038/s41598-019-47198-1
Open Access Y
Open Access Link http://www.nature.com/articles/s41598-019-47198-1.pdf


Wachs, Johannes (Details)
Kertesz, Janos (CEU, Hungary)
Institute for Data, Process and Knowledge Management (AE Polleres) (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
5370 Industrial economics (Details)
5415 Economic sociology (Details)
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