Non-Bayesian optimal search and dynamic implementation

被引：0
|
作者：
Gershkov, Alex [1 ,2 ]
Moldovanu, Benny [3 ]
机构：
[1] Hebrew Univ Jerusalem, Dept Econ, IL-91905 Jerusalem, Israel
[2] Univ Surrey, Sch Econ, Guildford GU2 5XH, Surrey, England
[3] Univ Bonn, Dept Econ, Bonn, Germany
来源：
ECONOMICS LETTERS | 2013年 / 118卷 / 01期
基金：
欧洲研究理事会;
关键词：
Dynamic mechanism design; Optimal stopping; Learning;
D O I：
10.1016/j.econlet.2012.09.026
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We show that a non-Bayesian learning procedure leads to very permissive implementation results concerning the efficient allocation of resources in a dynamic environment where impatient, privately informed agents arrive over time, and where the designer gradually learns about the distribution of agents' values. This contrasts the rather restrictive results that have been obtained for Bayesian learning in the same environment, and highlights the role of the learning procedure in dynamic mechanism design problems. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：121 / 125
页数：5
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