A non-parametric estimator for setting reservation prices in procurement auctions

Electronic auction markets collect large amounts of auction field data. This enables a structural estimation of the bid distributions and the possibility to derive optimal reservation prices. In this paper we propose a new approach to setting reservation prices. In contrast to traditional auction th...

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Bibliographic Details
Published in:Information technology and management 2006-09, Vol.7 (3), p.157-169
Main Authors: Bichler, Martin, Kalagnanam, Jayant R
Format: Article
Language:English
Subjects:
Auctions
Bids
Commodities
Costs
Electronic commerce
Electronic procurement
Estimating techniques
Informatics
Mathematical models
Opportunity costs
Prices
Probability
Profits
Studies
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Summary:Electronic auction markets collect large amounts of auction field data. This enables a structural estimation of the bid distributions and the possibility to derive optimal reservation prices. In this paper we propose a new approach to setting reservation prices. In contrast to traditional auction theory we use the buyer's risk statement for getting a winning bid as a key criterion to set an optimal reservation price. The reservation price for a given probability can then be derived from the distribution function of the observed drop-out bids. In order to get an accurate model of this function, we propose a nonparametric technique based on kernel distribution function estimators and the use of order statistics. We improve our estimator by additional information, which can be observed about bidders and qualitative differences of goods in past auctions rounds (e.g. different delivery times). This makes the technique applicable to RFQs and multi-attribute auctions, with qualitatively differentiated offers. [PUBLICATION ABSTRACT]
ISSN:1385-951X
1573-7667
DOI:10.1007/s10799-006-9180-5