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Statistical foundations of ecological rationality

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  • 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 rationality mirror fundamental and long-standing divisions in statistics.

Suggested Citation

  • Brighton, Henry, 2020. "Statistical foundations of ecological rationality," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 14, pages 1-32.
    • Handle: RePEc:zbw:ifweej:20202
    DOI: 10.5018/economics-ejournal.ja.2020-2
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    1. Levin, Yuri & McGill, Jeff, 2009. "Introduction to the special issue on revenue management and dynamic pricing," European Journal of Operational Research, Elsevier, vol. 197(3), pages 845-847, September.
    2. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    3. Simon, Herbert A, 1978. "Rationality as Process and as Product of Thought," American Economic Review, American Economic Association, vol. 68(2), pages 1-16, May.
    4. David Aikman & Mirta Galesic & Gerd Gigerenzer & Sujit Kapadia & Konstantinos Katsikopoulos & Amit Kothiyal & Emma Murphy & Tobias Neumann, 2021. "Taking uncertainty seriously: simplicity versus complexity in financial regulation [Uncertainty in macroeconomic policy-making: art or science?]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 30(2), pages 317-345.
    5. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    6. Brighton, Henry & Gigerenzer, Gerd, 2015. "The bias bias," Journal of Business Research, Elsevier, vol. 68(8), pages 1772-1784.
    7. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    8. Gigerenzer, Gerd, 2018. "The Bias Bias in Behavioral Economics," Review of Behavioral Economics, now publishers, vol. 5(3-4), pages 303-336, December.
    9. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    10. Gilboa, Itzhak & Schmeidler, David, 1989. "Maxmin expected utility with non-unique prior," Journal of Mathematical Economics, Elsevier, vol. 18(2), pages 141-153, April.
    11. Machina, Mark J & Schmeidler, David, 1992. "A More Robust Definition of Subjective Probability," Econometrica, Econometric Society, vol. 60(4), pages 745-780, July.
    12. Chater, Nick & Oaksford, Mike & Nakisa, Ramin & Redington, Martin, 2003. "Fast, frugal, and rational: How rational norms explain behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 63-86, January.
    13. Itzhak Gilboa & Andrew Postlewaite & David Schmeidler, 2012. "Rationality of belief or: why savage's axioms are neither necessary nor sufficient for rationality," Post-Print hal-00745599, HAL.
    14. Boland, Lawrence A, 1981. "On the Futility of Criticizing the Neoclassical Maximization Hypothesis," American Economic Review, American Economic Association, vol. 71(5), pages 1031-1036, December.
    15. Larry G. Epstein, 1999. "A Definition of Uncertainty Aversion," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 66(3), pages 579-608.
    16. Aikman, David & Galesic, Mirta & Gigerenzer, Gerd & Kapadia, Sujit & Katsikopoulos, Konstantinos & Kothiyal, Amit & Murphy, Emma & Neumann, Tobias, 2014. "Financial Stability Paper No 28: Taking uncertainty seriously - simplicity versus complexity in financial regulation," Bank of England Financial Stability Papers 28, Bank of England.
    17. David J. Hand & Keming Yu, 2001. "Idiot's Bayes—Not So Stupid After All?," International Statistical Review, International Statistical Institute, vol. 69(3), pages 385-398, December.
    18. David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
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    Cited by:

    1. Riedl, Anna & Vervaeke, John, 2022. "Rationality and Relevance Realization," OSF Preprints vymwu, Center for Open Science.

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    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
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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