Econometrics of Scoring Auctions

Jean-Jacques Laffont, Isabelle Perrigne, Michel Simioni and Quang Vuong

A chapter in Essays in Honor of Cheng Hsiao, 2020, vol. 41, pp 287-322 from Emerald Group Publishing Limited

Abstract: This chapter develops a structural framework for the analysis of scoring procurement auctions where bidder’s quality and bid are taken into account. With exogenous quality, the authors characterize the optimal mechanism whether the buyer is private or public and show that the optimal scoring rule need not be linear in the bid. The model primitives include the buyer benefit function, the bidders’ cost inefficiencies distribution and cost function, and potentially the cost of public funds. We show that the model primitives are nonparametrically identified under mild functional assumptions from the buyer’s choice, firms’ bids and qualities. The authors then develop a multistep kernel-based procedure to estimate the model primitives and provide their convergence rates. Our identification and estimation results are general as they apply to other scoring rules including quasi-linear ones.

Keywords: Scoring auctions; procurement; identification; nonparametric estimation; cost efficiency; quality (search for similar items in EconPapers)
Date: 2020
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Working Paper: Econometrics of scoring auctions (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320200000041010

DOI: 10.1108/S0731-905320200000041010

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