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Cream Skimming and Information Design in Matching Markets

Author

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  • Gleb Romanyuk
  • Alex Smolin

Abstract

Short-lived buyers arrive to a platform over time and randomly match with sellers. The sellers stay at the platform and decide whether to accept incoming requests. The platform designs what buyer information the sellers observe before deciding to form a match. We show full information disclosure leads to a market failure because of excessive rejections by the sellers. If sellers are homogeneous, then coarse information policies are able to restore efficiency. If sellers are heterogeneous, then simple censorship policies are often constrained efficient as shown by a method of calculus of variations.

Suggested Citation

  • Gleb Romanyuk & Alex Smolin, 2019. "Cream Skimming and Information Design in Matching Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 11(2), pages 250-276, May.
    • Handle: RePEc:aea:aejmic:v:11:y:2019:i:2:p:250-76
    Note: DOI: 10.1257/mic.20170154
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    Citations

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    Cited by:

    1. Bar Light & Ramesh Johari & Gabriel Weintraub, 2019. "Quality Selection in Two-Sided Markets: A Constrained Price Discrimination Approach," Papers 1912.02251, arXiv.org, revised Aug 2023.
    2. Hopenhayn, Hugo & Saeedi, Maryam, 2023. "Optimal information disclosure and market outcomes," Theoretical Economics, Econometric Society, vol. 18(4), November.
    3. Sergei Kovbasyuk & Giancarlo Spagnolo, 2016. "Memory and Markets," EIEF Working Papers Series 1606, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2017.
    4. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
    5. Piolatto, A. & Schuett, Florian, 2022. "Information vs Competition : How Platform Design Affects Profits and Surplus," Discussion Paper 2022-002, Tilburg University, Tilburg Law and Economic Center.
    6. Hemant K. Bhargava & Olivier Rubel & Elizabeth J. Altman & Ramnik Arora & Jörn Boehnke & Kaitlin Daniels & Timothy Derdenger & Bryan Kirschner & Darin LaFramboise & Pantelis Loupos & Geoffrey Parker &, 2020. "Platform data strategy," Marketing Letters, Springer, vol. 31(4), pages 323-334, December.
    7. Wang, Hai & Yang, Hai, 2019. "Ridesourcing systems: A framework and review," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 122-155.
    8. Foster, Joshua, 2022. "How rating mechanisms shape user search, quality inference and engagement in online platforms: Experimental evidence," Journal of Business Research, Elsevier, vol. 142(C), pages 791-807.
    9. Jinzhao Du & Ying Lei, 2022. "Information design of matching platforms when user preferences are bidimensional," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3320-3336, August.
    10. Michael Choi & Guillaume Rocheteau, 2024. "Information acquisition and price discrimination in dynamic, decentralized markets," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 53, pages 1-46, July.

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    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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