Optimal search, learning and implementation
AbstractWe 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 agentsʼ 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 (1974) , of finding optimal stopping policies for search that are characterized by a reservation price property.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Theory.
Volume (Year): 147 (2012)
Issue (Month): 3 ()
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Web page: http://www.elsevier.com/locate/inca/622869
Dynamic mechanism design; Learning; Optimal stopping;
Other versions of this item:
- 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, and Information
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