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Econometrics of Scoring Auctions

Jean-Jacques Laffont ^a

Isabelle Perrigne ^b

Michel Simioni ^c

Quang Vuong ^d

^aToulouse School of Economics; University of Southern California

^bRice University, USA

^cINRAE, France

^dNew York University, USA

Essays in Honor of Cheng Hsiao

ISBN: 978-1-78973-958-9, eISBN: 978-1-78973-957-2

Publication date: 15 April 2020

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

Acknowledgements

Acknowledgments

This chapter partly draws from Laffont, Oustry, Simioni, and Vuong (1997) of which preliminary versions were presented at the 1994 SITE Meeting at Stanford University, the 1994 European Meeting of the Econometric Society in Maastricht, the 1994 CEPR/WZB Workshop in Berlin, the 1995 Journées de Microéconomie Appliquée in Clermont-Ferrand, and seminars at Northwestern University, New York University, and ENSAE. We thank the Editor and a referee for useful comments that led to the current version.

Citation

Laffont, J.-J., Perrigne, I., Simioni, M. and Vuong, Q. (2020), "Econometrics of Scoring Auctions", Li, T., Pesaran, M.H. and Terrell, D. (Ed.) Essays in Honor of Cheng Hsiao (Advances in Econometrics, Vol. 41), Emerald Publishing Limited, Leeds, pp. 287-322. https://doi.org/10.1108/S0731-905320200000041010

Publisher

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Emerald Publishing Limited