IDEAS home Printed from https://ideas.repec.org/p/ecl/stabus/3020.html
   My bibliography  Save this paper

Chameleons: The Misuse of Theoretical Models in Finance and Economics

Author

Listed:
  • Pfleiderer, Paul

    (Stanford University)

Abstract

In this essay I discuss how theoretical models in finance and economics are used in ways that make them “chameleons†and how chameleons devalue the intellectual currency and muddy policy debates. A model becomes a chameleon when it is built on assumptions with dubious connections to the real world but nevertheless has conclusions that are uncritically (or not critically enough) applied to understanding our economy. I discuss how chameleons are created and nurtured by the mistaken notion that one should not judge a model by its assumptions, by the unfounded argument that models should have equal standing until definitive empirical tests are conducted, and by misplaced appeals to “as-if†arguments, mathematical elegance, subtlety, references to assumptions being “standard in the literature,†and the need for tractability.

Suggested Citation

  • Pfleiderer, Paul, 2018. "Chameleons: The Misuse of Theoretical Models in Finance and Economics," Research Papers 3020, Stanford University, Graduate School of Business.
  • Handle: RePEc:ecl:stabus:3020
    as

    Download full text from publisher

    File URL: https://www.gsb.stanford.edu/gsb-cmis/gsb-cmis-download-auth/359071
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Yew-Kwang Ng, 2016. "Are Unrealistic Assumptions/Simplifications Acceptable? Some Methodological Issues in Economics," Pacific Economic Review, Wiley Blackwell, vol. 21(2), pages 180-201, May.
    2. Jacky Mallett, 2015. "Threadneedle: An Experimental Tool for the Simulation and Analysis of Fractional Reserve Banking Systems," Papers 1502.06163, arXiv.org.
    3. Falkinger, Josef, 2016. "The order of knowledge and robust action: How to deal with economic uncertainty?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-30.
    4. Leonardo Ivarola, 2021. "Economic Models, Realism And Similarity," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2021-63, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    5. Weidong Tian & Junya Jiang & Weidong Tian, 2017. "Model Uncertainty Effect on Asset Prices," International Review of Finance, International Review of Finance Ltd., vol. 17(2), pages 205-233, June.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ecl:stabus:3020. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/gsstaus.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.