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Embracing Uncertainty During the Crisis

Author

Listed:
  • Maria Alina CarataÈ™

    („Ovidius†University of Constanta)

  • Elena Cerasela Spătariu

    („Ovidius†University of Constanta)

  • Raluca Andreea Trandafir

    („Ovidius†University of Constanta)

Abstract

The purpose of this paper is to emphasize the impact of uncertainty over the economic environment in the current crisis installed within the COVID-19 pandemic that is unprecedented because there has never been a phenomenon of such magnitude, a global crisis, with a profound, extensive and more complex impact than any other event that decision-makers have considered so far. The current pandemic caused an uncertainty shock globally, which rose into recession. There is uncertainty about the consequences of the crisis and impact on global health, how the world will live and work, how relations between the largest states will be influenced, how the roles of states in trade relations will change, considering the responses to the crisis.

Suggested Citation

  • Maria Alina CarataÈ™ & Elena Cerasela Spătariu & Raluca Andreea Trandafir, 2020. "Embracing Uncertainty During the Crisis," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 38-43, August.
    • Handle: RePEc:ovi:oviste:v:xx:y:2020:i:1:p:38-43
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    References listed on IDEAS

    as
    1. Johanna Etner & Meglena Jeleva & Jean‐Marc Tallon, 2012. "Decision Theory Under Ambiguity," Journal of Economic Surveys, Wiley Blackwell, vol. 26(2), pages 234-270, April.
    2. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    3. World Bank, 2020. "Global Economic Prospects, January 2020," World Bank Publications - Books, The World Bank Group, number 33044.
    4. Mamdouh Abdelmoula M.Abdelsalam & Hany Abdel-Latif, 2020. "An optimal early warning system for currency crises under model uncertainty," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 20(3), pages 99-107.
    5. Cukierman, Alex & Meltzer, Allan H, 1986. "A Theory of Ambiguity, Credibility, and Inflation under Discretion and Asymmetric Information," Econometrica, Econometric Society, vol. 54(5), pages 1099-1128, September.
    6. Johanna Etner & Meglena Jeleva & Jean-Marc Tallon, 2009. "Decision theory under uncertainty," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00429573, HAL.
    7. Brown, Ross & Rocha, Augusto, 2020. "Entrepreneurial uncertainty during the Covid-19 crisis: Mapping the temporal dynamics of entrepreneurial finance," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
    8. World Bank, 2020. "Global Economic Prospects, June 2020," World Bank Publications - Books, The World Bank Group, number 33748.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    economic uncertainty; economic analysis; pandemic; recession;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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