IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y2018i131p45-58.html
   My bibliography  Save this article

Nonparametric Estimation for Regulation Models

Author

Listed:
  • Andreea Enache
  • Jean-Pierre Florens

Abstract

This paper presents a nonparametric structural analysis of a class of contract models à la Baron, Myerson, et al. (1982). Our analysis is based on a well-posed inverse problem linking the quantile function of the observations and the functional parameter of interest. The resolution of this problem gives the identification properties of the model and leads to an estimation procedure. We provide implementation and asymptotic properties of this type of L-estimator. We extend our analysis by introducing an instrumental variable estimator of the cost function.

Suggested Citation

  • Andreea Enache & Jean-Pierre Florens, 2018. "Nonparametric Estimation for Regulation Models," Annals of Economics and Statistics, GENES, issue 131, pages 45-58.
  • Handle: RePEc:adr:anecst:y:2018:i:131:p:45-58
    DOI: 10.15609/annaeconstat2009.131.0045
    as

    Download full text from publisher

    File URL: https://www.jstor.org/stable/10.15609/annaeconstat2009.131.0045
    Download Restriction: no

    File URL: https://libkey.io/10.15609/annaeconstat2009.131.0045?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Enache, Andreea & Florens, Jean-Pierre, 2020. "Quantile Analysis of "Hazard-Rate" Game Models," TSE Working Papers 20-1117, Toulouse School of Economics (TSE).
    2. Enache, Andreea & Florens, Jean-Pierre & Sbai, Erwann, 2023. "A functional estimation approach to the first-price auction models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1564-1588.
    3. Andreea Enache & Jean-Pierre Florens, 2020. "Identification and Estimation in a Third-Price Auction Model," Post-Print hal-02929530, HAL.
    4. Enache, Andreea & Florens, Jean-Pierre, 2019. "Identification and Estimation in a Third-Price Auction Model," TSE Working Papers 19-989, Toulouse School of Economics (TSE).

    More about this item

    Keywords

    L-functionals; Regulation Models; Principal-Agent Model; Adverse Selection; Nonparametric Statistics; Structural Econometrics.;
    All these keywords.

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • D86 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Economics of Contract Law
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:adr:anecst:y:2018:i:131:p:45-58. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Secretariat General or Laurent Linnemer (email available below). General contact details of provider: https://edirc.repec.org/data/ensaefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.