Imperfect information, algorithmic price discrimination, and collusion

Florian Peiseler*, Alexander Rasch, Shiva Shekhar

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

We analyze the ability of firms to sustain collusion in a setting in which horizontally differentiated firms can price discriminate based on private information. Firms receive private, noisy signals regarding customers' preferences. We find that there is a non-monotonic relationship between signal quality and the sustainability of collusion. Starting from a low level, an increase in signal precision first facilitates collusion. There is, however, a threshold beyond which any further increase renders collusion less sustainable. Our analysis provides important insights for competition policy, particularly in light of firms' growing reliance on increasingly sophisticated computer algorithms to analyze consumer data and to make pricing decisions. In contrast to previous findings, our results reveal that a ban on price discrimination can help to prevent collusive behavior as long as signals are sufficiently noisy.
Original languageEnglish
Pages (from-to)516-549
JournalScandinavian Journal of Economics
Volume124
Issue number2
DOIs
Publication statusPublished - Apr 2022
Externally publishedYes

Keywords

  • Algorithm
  • big data
  • collusion
  • private information
  • signal
  • third-degree price discrimination
  • COMPETITION

Fingerprint

Dive into the research topics of 'Imperfect information, algorithmic price discrimination, and collusion'. Together they form a unique fingerprint.

Cite this