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Econometrics of scoring auctions

Author

Listed:
  • Jean-Jacques Laffont

    (UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse, USC - University of Southern California)

  • 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)

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.

Suggested Citation

  • Jean-Jacques Laffont & Isabelle Perrigne & Michel Simioni & Quang Vuong, 2020. "Econometrics of scoring auctions," Post-Print hal-02536354, HAL.
    • Handle: RePEc:hal:journl:hal-02536354
    DOI: 10.1108/S0731-905320200000041010
    as

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