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Private information, price discrimination, and collusion

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  • Peiseler, Florian
  • Rasch, Alexander
  • Shekhar, Shiva

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.

Suggested Citation

  • Peiseler, Florian & Rasch, Alexander & Shekhar, Shiva, 2018. "Private information, price discrimination, and collusion," DICE Discussion Papers 295, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  • Handle: RePEc:zbw:dicedp:295
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    References listed on IDEAS

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    More about this item

    Keywords

    Big Data; Collusion; Loyalty; Private Information; Third-Degree Price Discrimination;
    All these keywords.

    JEL classification:

    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L41 - Industrial Organization - - Antitrust Issues and Policies - - - Monopolization; Horizontal Anticompetitive Practices

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