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Optimal Search, Learning and Implementation

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  • Alex Gershkov
  • Benny Moldovanu

Abstract

We characterize the incentive compatible, constrained efficient policy ("second-best") in a dynamic matching environment, where impatient, privately informed agents arrive over time, and where the designer gradually learns about the distribution of agents' values. We also derive conditions on the learning process ensuring that the complete-information, dynamically efficient allocation of resources ("first-best") is incentive compatible. Our analysis reveals and exploits close, formal relations between the problem of ensuring implementable allocation rules in our dynamic allocation problems with incomplete information and learning, and between the classical problem, posed by Rothschild [19], of finding optimal stopping policies for search that are characterized by a reservation price property .

Suggested Citation

  • Alex Gershkov & Benny Moldovanu, 2010. "Optimal Search, Learning and Implementation," Discussion Paper Series dp543, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
  • Handle: RePEc:huj:dispap:dp543
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Bergemann, Dirk & Pavan, Alessandro, 2015. "Introduction to Symposium on Dynamic Contracts and Mechanism Design," Journal of Economic Theory, Elsevier, vol. 159(PB), pages 679-701.
    2. Mierendorff, Konrad, 2016. "Optimal dynamic mechanism design with deadlines," Journal of Economic Theory, Elsevier, vol. 161(C), pages 190-222.
    3. Yizhaq Minchuk & Aner Sela, 2018. "Asymmetric sequential search under incomplete information," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(2), pages 315-325, June.
    4. Gershkov, Alex & Moldovanu, Benny, 2013. "Non-Bayesian optimal search and dynamic implementation," Economics Letters, Elsevier, vol. 118(1), pages 121-125.
    5. Kruse, Thomas & Strack, Philipp, 2015. "Optimal stopping with private information," Journal of Economic Theory, Elsevier, vol. 159(PB), pages 702-727.
    6. Babaioff, Moshe & Blumrosen, Liad & Roth, Aaron, 2015. "Auctions with online supply," Games and Economic Behavior, Elsevier, vol. 90(C), pages 227-246.
    7. Hector Chade & Jan Eeckhout & Lones Smith, 2017. "Sorting through Search and Matching Models in Economics," Journal of Economic Literature, American Economic Association, vol. 55(2), pages 493-544, June.
    8. Liu, Heng, 2018. "Efficient dynamic mechanisms in environments with interdependent valuations: the role of contingent transfers," Theoretical Economics, Econometric Society, vol. 13(2), May.
    9. Maarten Janssen & Paul Pichler & Simon Weidenholzer, 2009. "Sequential Search with Incompletely Informed Consumers: Theory and Evidence from Retail Gasoline Markets," Vienna Economics Papers 0914, University of Vienna, Department of Economics.
    10. Alex Gershkov & Benny Moldovanu & Philipp Strack, 2018. "Revenue-Maximizing Mechanisms with Strategic Customers and Unknown, Markovian Demand," Management Science, INFORMS, vol. 64(5), pages 2031-2046, May.

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    More about this item

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D78 - Microeconomics - - Analysis of Collective Decision-Making - - - Positive Analysis of Policy Formulation and Implementation
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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