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Bundling against Learning

Author

Listed:
  • Agathe Pernoud
  • Frank Yang

Abstract

A monopolist sells multiple goods to an uninformed buyer. The buyer chooses to learn any one-dimensional linear signal of their values for the goods, anticipating the seller's mechanism. The seller designs an optimal mechanism, anticipating the buyer's learning choice. In a generalized Gaussian environment, we show that every equilibrium has vertical learning where the buyer's posterior means are comonotonic, and every equilibrium is outcome-equivalent to nested bundling where the seller offers a menu of nested bundles. In equilibrium, the buyer learns more about a higher-tier good, resulting in a higher posterior variance on the log scale.

Suggested Citation

  • Agathe Pernoud & Frank Yang, 2025. "Bundling against Learning," Papers 2509.16396, arXiv.org.
    • Handle: RePEc:arx:papers:2509.16396
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    References listed on IDEAS

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    1. Hart, Sergiu & Nisan, Noam, 2019. "Selling multiple correlated goods: Revenue maximization and menu-size complexity," Journal of Economic Theory, Elsevier, vol. 183(C), pages 991-1029.
    2. Soheil Ghili, 2023. "A Characterization for Optimal Bundling of Products with Nonadditive Values," American Economic Review: Insights, American Economic Association, vol. 5(3), pages 311-326, September.
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