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Persistence of economic uncertainty: a comprehensive analysis

Author

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  • Vasilios Plakandaras
  • Rangan Gupta
  • Mark E. Wohar

Abstract

One of the most heavily researched and cited issue in applied economics is the relationship of uncertainty indices with the financial and macroeconomic variables. While the statistical features of financial and macroeconomic variables have been thoroughly examined, virtually nothing has been done to examine uncertainty indices under the statistical perspective. In this paper, we focus on two primary characteristics of uncertainty indices: persistence and chaotic behaviour. In order to evaluate the persistence and the chaotic behaviour we analyse 72 popular uncertainty indices constructed by forecasting models, text mining from news articles and data mining from monetary variables to measure the Hurst and Lyapunov exponents in rolling windows. The examination in rolling windows provides a dynamic evaluation of the specific characteristics revealing significant variations of persistence and chaotic dynamics with time. More specifically, we find that almost all uncertainty indices are persistent, while the chaotic dynamics are detected only sporadically and for certain indices during recessions of economic turbulence. Thus, we suggest that the examination of persistence and chaos should be a prerequisite step before using uncertainty indices in economic policy models.

Suggested Citation

  • Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2019. "Persistence of economic uncertainty: a comprehensive analysis," Applied Economics, Taylor & Francis Journals, vol. 51(41), pages 4477-4498, September.
  • Handle: RePEc:taf:applec:v:51:y:2019:i:41:p:4477-4498
    DOI: 10.1080/00036846.2019.1591607
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    Cited by:

    1. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
    2. OlaOluwa S. Yaya & Nurudeen Abu & Tayo P. Ogundunmade, 2021. "Economic policy uncertainty in G7 countries: evidence of long-range dependence and cointegration," Economic Change and Restructuring, Springer, vol. 54(2), pages 541-556, May.
    3. Sheng, Xin & Gupta, Rangan & Cepni, Oguzhan, 2022. "Persistence of state-level uncertainty of the United States: The role of climate risks," Economics Letters, Elsevier, vol. 215(C).
    4. Christina Christou & Giray Gozgor & Rangan Gupta & Chi keung Marco Lau, 2020. "Are Uncertainties across the World Convergent?," Economics Bulletin, AccessEcon, vol. 40(1), pages 855-862.
    5. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2022. "Commodity and financial markets’ fear before and during COVID-19 pandemic: Persistence and causality analyses," Resources Policy, Elsevier, vol. 76(C).
    6. Solarin, Sakiru Adebola & Gil-Alana, Luis A., 2021. "The persistence of economic policy uncertainty: Evidence of long range dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    7. Gupta, Rangan & Sun, Xiaojin, 2020. "Forecasting economic policy uncertainty of BRIC countries using Bayesian VARs," Economics Letters, Elsevier, vol. 186(C).
    8. Jacobus Nel & Rangan Gupta & Mark E. Wohar & Christian Pierdzioch, 2022. "Climate Risks and Predictability of Commodity Returns and Volatility: Evidence from Over 750 Years of Data," Working Papers 202242, University of Pretoria, Department of Economics.

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    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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