IDEAS home Printed from https://ideas.repec.org/a/taf/jecmet/v22y2015i3p391-409.html
   My bibliography  Save this article

Expertise and institutional design in economic committees

Author

Listed:
  • Carlo Martini

Abstract

In this paper, I consider the problem of selecting and justifying a lost of principles of expertise as part of a methodology of expert judgment in economics. I argue that a methodology of expertise, trying to list and justify a number of principles of expertise, is in need of a theoretical background against which to select, evaluate, and weight each of the principles. I explain by means of case studies why problems arise for lack of such background, using the Bank of England's Monetary Policy Committee and the Council of Economic Advisors as examples. I then make a proposal for a categorization in 'types of committees' and 'types of expertise,' and use it to evaluate some of the principles of expertise that have been previously suggested in the philosophical and economic literatures.

Suggested Citation

  • Carlo Martini, 2015. "Expertise and institutional design in economic committees," Journal of Economic Methodology, Taylor & Francis Journals, vol. 22(3), pages 391-409, September.
    • Handle: RePEc:taf:jecmet:v:22:y:2015:i:3:p:391-409
    DOI: 10.1080/1350178X.2015.1071509
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/1350178X.2015.1071509
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/1350178X.2015.1071509?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Julie Jebeile & Vincent Lam & Mason Majszak & Tim Räz, 2023. "Machine learning and the quest for objectivity in climate model parameterization," Climatic Change, Springer, vol. 176(8), pages 1-19, August.

    More about this item

    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:taf:jecmet:v:22:y:2015:i:3:p:391-409. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RJEC20 .

    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.