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Pandora's Auctions: Dynamic Matching with Unknown Preferences

Author

Listed:
  • Daniel Fershtman
  • Alessandro Pavan

Abstract

Matching theory typically assumes that agents know their values for possible partners and confines attention to settings in which matching is either static, or driven by population dynamics. In many environments of interest, instead, dynamics originate in the agents learning their preferences through interactions with other agents. In this short paper, we illustrate how platforms can use appropriately designed auctions to account for the joint value of experimentation and cross-subsidization in dynamic matching markets. The model is a stylized version of the general one in Fershtman and Pavan (2016).

Suggested Citation

  • Daniel Fershtman & Alessandro Pavan, 2017. "Pandora's Auctions: Dynamic Matching with Unknown Preferences," American Economic Review, American Economic Association, vol. 107(5), pages 186-190, May.
  • Handle: RePEc:aea:aecrev:v:107:y:2017:i:5:p:186-90
    Note: DOI: 10.1257/aer.p20171043
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    Citations

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    Cited by:

    1. Bruno Jullien & Alessandro Pavan & Marc Rysman, 2021. "Two-sided markets, pricing, and network effects," Post-Print hal-03828345, HAL.
    2. Daniel Fershtman & Alessandro Pavan, 2022. "Matching auctions," RAND Journal of Economics, RAND Corporation, vol. 53(1), pages 32-62, March.

    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions

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