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Can probability theory deal with entrepreneurship?

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  • Vlad Tarko

    (George Mason University)

Abstract

The Austrian theory of entrepreneurship emphasizes the importance of epistemic heterogeneity and the unlistability of the set of all possibilities. A similar concern with what has been called “the art of choosing the space of possibilities” is an important part of Bayesian model selection. Both Austrian and Bayesian authors view the common knowledge assumption as an unrealistic and unnecessary restriction. This coincidence of concerns leads to a joint theory of entrepreneurship. Three important benefits result from this merger: (1) the ability to use Itti & Baldi’s Bayesian theory of surprise to empirically measure radical surprise and improve the Betrand competition model as a consequence, (2) dealing with the unlistability problem, and (3) better understanding why the emergence of common knowledge is always the outcome of a social process rather than an inherent consequence of “rationality”.

Suggested Citation

  • Vlad Tarko, 2013. "Can probability theory deal with entrepreneurship?," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 26(3), pages 329-345, September.
    • Handle: RePEc:kap:revaec:v:26:y:2013:i:3:d:10.1007_s11138-012-0193-5
    DOI: 10.1007/s11138-012-0193-5
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    References listed on IDEAS

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    Cited by:

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    More about this item

    Keywords

    Kiznerian entrepreneurship; Bayesian surprise; Unknown unknowns; Radical uncertainty; Bertrand competition;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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