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Asymmetric information in bilateral trade and in markets: An inversion result

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  • Lauermann, Stephan

Abstract

I consider bilateral trade between a seller and a buyer with private valuations. The seller makes a take-it-or-leave-it price offer. If the seller observes the buyerʼs valuation (symmetric information), bilateral trade is trivially efficient. If the seller cannot observe the valuation (asymmetric information), bilateral trade is inefficient. This bilateral trading game is embedded into a large matching market. In the steady-state equilibrium of the market game, the relation between the informational regime and efficiency is inverted: With small frictions efficiency obtains if information is asymmetric. If information is symmetric, however, the trading outcome can be very inefficient—even if frictions vanish.

Suggested Citation

  • Lauermann, Stephan, 2012. "Asymmetric information in bilateral trade and in markets: An inversion result," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1969-1997.
    • Handle: RePEc:eee:jetheo:v:147:y:2012:i:5:p:1969-1997
    DOI: 10.1016/j.jet.2012.05.021
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    References listed on IDEAS

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    1. Mark Satterthwaite & Artyom Shneyerov, 2007. "Dynamic Matching, Two-Sided Incomplete Information, and Participation Costs: Existence and Convergence to Perfect Competition," Econometrica, Econometric Society, vol. 75(1), pages 155-200, January.
    2. Leonardo Felli & Kevin Roberts, 2016. "Does Competition Solve the Hold-up Problem?," Economica, London School of Economics and Political Science, vol. 83(329), pages 172-200, 01.
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    Cited by:

    1. 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.
    2. Distefano, Rosaria, 2022. "The social cost of playing by the rules in the credit market," MPRA Paper 115326, University Library of Munich, Germany.
    3. Arnold Polanski & Fernando Vega-Redondo, 2013. "Markets, Bargaining, and Networks with Heterogeneous Agents," University of East Anglia Applied and Financial Economics Working Paper Series 038, School of Economics, University of East Anglia, Norwich, UK..
    4. Yujing Xu, 2022. "Unobservable investments, trade efficiency and search frictions," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(2), pages 764-799, May.
    5. Eeva Mauring, 2020. "Informational Cycles in Search Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 12(4), pages 170-192, November.
    6. Stephan Lauermann, 2013. "Dynamic Matching and Bargaining Games: A General Approach," American Economic Review, American Economic Association, vol. 103(2), pages 663-689, April.
    7. Eeva Mauring, 2020. "Informational Cycles in Search Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 12(4), pages 170-192, November.
    8. Petrikaite, Vaiva & Hämäläinen, Saara, 2018. "Mobility with private information and privacy suppression," CEPR Discussion Papers 12860, C.E.P.R. Discussion Papers.
    9. Dilmé, Francesc, 2023. "Bargaining in small dynamic markets," Journal of Economic Theory, Elsevier, vol. 207(C).
    10. Shneyerov, Artyom & Wong, Adam Chi Leung, 2011. "The role of private information in dynamic matching and bargaining: Can it be good for efficiency?," Economics Letters, Elsevier, vol. 112(1), pages 128-131, July.
    11. Yujing Xu, 2022. "Unobservable investments, trade efficiency and search frictions," Post-Print hal-03848827, HAL.
    12. Shneyerov, Artyom & Wong, Adam C.L., 2020. "Price discovery in a matching and bargaining market with aggregate uncertainty," Games and Economic Behavior, Elsevier, vol. 124(C), pages 183-206.
    13. 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

    Keywords

    Dynamic matching and bargaining games; Decentralized markets; Consumer privacy; Search frictions; Asymmetric information;
    All these keywords.

    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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