Econometrics of scoring auctions

Jean-Jacques Laffont, Isabelle Perrigne, Michel Simioni () and Quang Vuong
Additional contact information
Isabelle Perrigne: Rice University [Houston]
Michel Simioni: UMR MOISA - Marchés, Organisations, Institutions et Stratégies d'Acteurs - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Quang Vuong: NYU - New York University [New York] - NYU - NYU System

Post-Print from HAL

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
References: Add references at CitEc
Citations:

Published in Li, T.; Pesaran, M.; Terrel, D. Essays in honor of Cheng Hsiao, 41, Emerald Publishing Limited, 2020, Advances in Econometrics, 978-1-78973-958-9. ⟨10.1108/S0731-905320200000041010⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Chapter: Econometrics of Scoring Auctions (2020)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02536354

DOI: 10.1108/S0731-905320200000041010

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().