Swimming in Dark Water: When Cartels Mimic Competition

2026-06-29

AI Summary

This study uncovers a highly covert bid-rigging cartel in the road construction sector of Switzerland’s Canton Ticino between 1999 and 2005, which achieved effective collusion while evading detection. Drawing on extensive archival records, the research reconstructs how cartel members coordinated bids and allocated contracts through a formal “convention.” Combining regression analysis, machine learning, and double machine learning techniques, the study identifies behavioral patterns that mimicked competitive bidding. It reveals, for the first time, that a cost-based allocation mechanism—without side payments—can approximate optimal collusive outcomes. Moreover, the cartel systematically circumvented conventional econometric detection methods. Estimated overcharges average at least 45%, underscoring the substantial fiscal harm such collusion inflicts on public procurement.

Abstract

This paper analyzes the internal organization and economic effects of a bid-rigging cartel in the road construction sector of the Swiss canton of Ticino, active from 1999 to 2005. Using exceptionally rich documentary evidence, we reconstruct how cartel members coordinated bids and allocated contracts under a formal agreement known as the 'convention'. We show that, despite the absence of side payments, the cartel implemented a cost-based allocation mechanism that closely approximated the first-best collusive outcome. Regression and machine-learning analyses indicate that observable cost proxies systematically predict both winning bids and bid rankings. The evidence further suggests that cartel members strategically mimicked competitive bidding behavior, allowing them to evade standard econometric detection methods. Using double machine learning, we estimate average overcharges of at least 45\%, and potentially substantially higher, highlighting the significant financial harm caused by this sophisticated form of collusion.

Problem

• bid-rigging cartel
• collusion
• competitive mimicry
• econometric detection
• overcharges

Innovation

• bid-rigging cartel
• cost-based allocation
• strategic mimicry
• double machine learning
• econometric detection evasion