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Measuring Knightian uncertainty

Author

Listed:
  • Andreas Dibiasi

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

Abstract

Knightian uncertainty represents a situation in which it is no longer possible to form expectations about future events. We propose a method to directly measure Knightian uncertainty. Our approach relies on firm-level data and measures the share of firms that do not formalize expectations about their future demand. We construct the Knightian Uncertainty Indicator for Switzerland and show that the indicator is able to identify times of high uncertainty. We evaluate the indicator by comparing it to established uncertainty measures. We find that a one standard deviation innovation of the Knightian Uncertainty Indicator leads to a negative and persistent reduction of investment.

Suggested Citation

  • Andreas Dibiasi, 2021. "Measuring Knightian uncertainty," Post-Print hal-03391638, HAL.
    • Handle: RePEc:hal:journl:hal-03391638
    DOI: 10.1007/s00181-021-02106-3
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    Citations

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    Cited by:

    1. Petar Soric & Oscar Claveria, 2021. ""Employment uncertainty a year after the irruption of the covid-19 pandemic"," IREA Working Papers 202112, University of Barcelona, Research Institute of Applied Economics, revised May 2021.
    2. Pooja Thakur-Wernz & Helena Barnard & Marianne Matthee, 2024. "Knightian uncertain violence and the challenge of FDI-assisted development: policy recommendations where civilian lives are at risk," Journal of International Business Policy, Palgrave Macmillan, vol. 7(3), pages 356-390, September.
    3. Oscar Claveria, 2020. "Business and consumer uncertainty in the face of the pandemic: A sector analysis in European countries," Papers 2012.02091, arXiv.org.
    4. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    5. Shamugia, Egnate, 2025. "Rule of law and economic performance: A meta-regression analysis," European Journal of Political Economy, Elsevier, vol. 87(C).
    6. Beckmann, Joscha & Kerkemeier, Marco & Kruse-Becher, Robinson, 2025. "Regime-specific exchange rate predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 176(C).
    7. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    8. Eduard Ary Binsar Naibaho & Farah Margaretha Leon & Bahtiar Usman, 2025. "The Effect of Conservatism, Slack, Managerial Ability, and Uncertainty on Company Financial Performance," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 15(1), pages 1-3.
    9. Claveria, Oscar, 2022. "Global economic uncertainty and suicide: Worldwide evidence," Social Science & Medicine, Elsevier, vol. 305(C).
    10. Qingyuan Li & Edward L. Maydew & Richard H. Willis & Li Xu, 2022. "Corporate tax behavior and political uncertainty: Evidence from national elections around the world," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(9-10), pages 1605-1641, October.
    11. Oscar Claveria, 2021. "Disagreement on expectations: firms versus consumers," SN Business & Economics, Springer, vol. 1(12), pages 1-23, December.

    More about this item

    Keywords

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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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