NDLI: Measuring the performance of large-scale combinatorial auctions: a structural estimation approach

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Measuring the performance of large-scale combinatorial auctions: a structural estimation approach

Content Provider	ACM Digital Library
Author	Olivares, Marcelo Weintraub, Gabriel Kim, Sang Won
Abstract	The main advantage of a procurement combinatorial auction (CA) is that it allows suppliers to express cost synergies through package bids. However, bidders can also strategically take advantage of this flexibility, by discounting package bids and "inflating'" bid prices for single-items, even in the absence of cost synergies; the latter behavior can hurt the performance of the auction. It is an empirical question whether allowing package bids and running a CA improves performance in a given setting. In this paper, we develop a structural estimation approach for large-scale first-price CAs to estimate the firms' cost structure using bidding data, and we use these estimates to evaluate the performance of the auction. To overcome the computational difficulties arising from the large number of bids observed in large-scale CAs, we propose a novel simplified model of bidders' behavior based on pricing package characteristics. This simplified model uses markup restrictions that are parsimonious yet sufficiently flexible to capture strategic markup adjustments that can reduce the performance of CAs. We apply our method to the Chilean school meals auction, in which the government procures half a billion dollars' worth of meal services every year and bidders submit thousands of package bids. Our estimates suggest that bidders' cost synergies are economically significant in this application, and the current CA mechanism achieves high allocative efficiency and a reasonable procurement cost. We believe this is the first paper in the literature that empirically shows that a CA performs well in practice.
Starting Page	587
Ending Page	588
Page Count	2
File Format	PDF
ISBN	9781450319621
DOI	10.1145/2482540.2482597
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-06-16
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Combinatorial auctions Procurement Public sector applications Empirical Structural estimation Auction design
Content Type	Text
Resource Type	Article

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