An information-Theoretic approach to partially identified auction models

被引：0

作者：

Jun, Sung Jae ^{[1
]}

Pinkse, Joris ^{[1
]}

机构：

[1] Penn State Univ, Dept Econ, 619 Kern Bldg, University Pk, PA 16802 USA

来源：

JOURNAL OF ECONOMETRICS | 2024年 / 238卷 / 02期

关键词：

English auctions; partial identification; maximum entropy; inequality constraints; nonparametric inference; INFERENCE;

D O I：

10.1016/j.jeconom.2023.105566

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We consider a situation in which we have data from ascending auctions with symmetric bidders, independent private values, and exogenous entry in which the bidders' value distribution is partially identified. Focusing on the case in which the seller intends to use a second price auction, we discuss how to determine an optimal reserve price. We justify the use of maximum entropy, explore the properties of the estimand, determine the asymptotic properties of our maximum entropy estimator, evaluate its behavior in a simulation study, and demonstrate its use in a modest application. As an extension, we propose a maxmin decision rule with entropy regularization, which includes Aryal and Kim (2013) and the maximum entropy solution as extreme cases.

引用

页数：39

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