IDEAS home Printed from https://ideas.repec.org/p/zbw/ifwedp/201925.html
   My bibliography  Save this paper

Beyond quantified ignorance: Rebuilding rationality without the bias bias

Author

Listed:
  • Brighton, Henry

Abstract

If we reassess the rationality question under the assumption that the uncertainty of the natural world is largely unquantifiable, where do we end up? In this article the author argues that we arrive at a statistical, normative, and cognitive theory of ecological rationality. The main casualty of this rebuilding process is optimality. Once we view optimality as a formal implication of quantified uncertainty rather than an ecologically meaningful objective, the rationality question shifts from being axiomatic/probabilistic in nature to being algorithmic/ predictive in nature. These distinct views on rationalitymirror fundamental and longstanding divisions in statistics.

Suggested Citation

  • Brighton, Henry, 2019. "Beyond quantified ignorance: Rebuilding rationality without the bias bias," Economics Discussion Papers 2019-25, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwedp:201925
    as

    Download full text from publisher

    File URL: http://www.economics-ejournal.org/economics/discussionpapers/2019-25
    Download Restriction: no

    File URL: https://www.econstor.eu/bitstream/10419/194877/1/1662970803.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    cognitive science; rationality; ecological rationality; bounded rationality; bias bias; bias/variance dilemma; Bayesianism; machine learning; pattern recognition; decision making under uncertainty; unquantifiable uncertainty;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection

    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:zbw:ifwedp:201925. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwkiede.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.