Can Exchanges of Anonymized Disaggregated Data Facilitate Collusion?

Abstract The exchange of information among competitors poses inherent risks to competition. Antitrust guidelines tend to view exchanges of aggregated data, where competitors' identity is kept anonymous, as less likely to facilitate collusion. However, the impact of data aggregation and anonymization on collusion remains relatively underexplored in the economic literature. This paper examines whether exchanging disaggregated data increases the risk of collusion compared with aggregated data exchanges, under the assumption that firms lack full control over production decisions and are subject to random production shocks. Our analysis reveals that exchanging disaggregated data reduces the discount rate necessary for collusion, relative to aggregated data exchanges. Furthermore, data anonymization may not effectively prevent collusion when firms exchange disaggregated data for monitoring purposes. These findings underscore the importance of antitrust guidelines favoring aggregated data exchanges and highlight the limited role of data anonymization in preventing collusion.

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Publication Details

Journal
Journal of Competition Law & Economics
Published
2025-08-25
DOI
https://doi.org/10.1093/joclec/nhaf024
Primary Topic
Stochastic processes and statistical mechanics
Type
article
Field-Weighted Citation Impact
0.00
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article

Can Exchanges of Anonymized Disaggregated Data Facilitate Collusion?

Albert Metz, Rosa M. Abrantes-Metz, Ben Wagner, Pedro Erdei-Gonzaga
Journal of Competition Law & Economics
Stochastic processes and statistical mechanics
article

Can Exchanges of Anonymized Disaggregated Data Facilitate Collusion?

Albert Metz, Rosa M. Abrantes-Metz, Ben Wagner, Pedro Erdei-Gonzaga
article en

Abstract

Abstract The exchange of information among competitors poses inherent risks to competition. Antitrust guidelines tend to view exchanges of aggregated data, where competitors' identity is kept anonymous, as less likely to facilitate collusion. However, the impact of data aggregation and anonymization on collusion remains relatively underexplored in the economic literature. This paper examines whether exchanging disaggregated data increases the risk of collusion compared with aggregated data exchanges, under the assumption that firms lack full control over production decisions and are subject to random production shocks. Our analysis reveals that exchanging disaggregated data reduces the discount rate necessary for collusion, relative to aggregated data exchanges. Furthermore, data anonymization may not effectively prevent collusion when firms exchange disaggregated data for monitoring purposes. These findings underscore the importance of antitrust guidelines favoring aggregated data exchanges and highlight the limited role of data anonymization in preventing collusion.

Journal of Competition Law & Economics
Openalex Percentile: Top 72%
Stochastic processes and statistical mechanics
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Can Exchanges of Anonymized Disaggregated Data Facilitate Collusion? — Albert Metz, Rosa M. Abrantes-Metz, et al. · Journal of Competition Law & Economics (2025) | TGRS Research Map | TGRS