Private information, price discrimination, and collusion

Florian Peiseler, Alexander Rasch and Shiva Shekhar

No 295, DICE Discussion Papers from Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE)

Abstract: We analyze firms' ability to sustain collusion in a setting in which horizontally differentiated firms can price-discriminate based on private information regarding consumers' preferences. In particular, firms receive private signals which can be noisy (e.g., big data predictions). We find that there is a non-monotone relationship between signal quality and sustainability of collusion. Starting from a low level, an increase in signal precision first facilitates collusion. However, there is a turning point from which on any further increase renders collusion less sustainable. Our analysis provides important insights for competition policy. In particular, a ban on price discrimination can help to prevent collusive behavior as long as signals are sufficiently noisy.

Keywords: Big Data; Collusion; Loyalty; Private Information; Third-Degree Price Discrimination (search for similar items in EconPapers)
JEL-codes: D43 L13 L41 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-bec, nep-big, nep-com, nep-gth, nep-ind and nep-mic
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:dicedp:295

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