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Are Uncertainties across the World Convergent?

Author

Listed:
  • Christina Christou

    (School of Economics and Management, Open University of Cyprus, 2252, Latsia, Cyprus)

  • Giray Gozgor

    (Istanbul Medeniyet University, Istanbul, Turkey)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Chi-Keung (Marco) Lau

    (Huddersfield Business School, University of Huddersfield, Huddersfield, HD1 3DH, United Kingdom)

Abstract
We analyse the convergence of a news-based measure of uncertainty across 143 countries (spanning 99 percent of world GDP) over the quarterly period of 1996:01 to 2018:03. We apply a panel data-based unit root test, which controls for both nonlinearity and cross-sectional dependence, to the ratio of the uncertainty of individual countries relative to that of global uncertainty. We find overwhelming evidence of stationarity in 141 of the cross-sectional units, leading to a rejection of the null of a unit root for the entire panel. Our results provide strong evidence of convergence and hence, the spillover of uncertainty spillover across the economies of the world. Given this, policymakers need to be alert all the time to counteract the negative impact on the domestic economy in the wake of uncertainty increases around the world.

Suggested Citation

  • Christina Christou & Giray Gozgor & Rangan Gupta & Chi-Keung (Marco) Lau, 2019. "Are Uncertainties across the World Convergent?," Working Papers 201907, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201907
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    Citations

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    Cited by:

    1. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2021. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(1), pages 188-215, March.
    2. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Uncertainty and Forecastability of Regional Output Growth in the United Kingdom: Evidence from Machine Learning," Working Papers 202111, University of Pretoria, Department of Economics.
    3. Gupta, Rangan & Lau, Chi-Keung (Marco) & Sheng, Xin, 2020. "Graph theory-based network analysis of regional uncertainties of the US Economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    4. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2022. "Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1049-1064, September.
    5. Bonga, Wellington Garikai, 2019. "Measuring Macroeconomic Uncertainty in Zimbabwe," MPRA Paper 94759, University Library of Munich, Germany.
    6. Rangan Gupta & Christian Pierdzioch, 2021. "Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers," Energies, MDPI, vol. 14(14), pages 1-15, July.
    7. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2021. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(1), pages 188-215, March.

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    More about this item

    Keywords

    uncertainty; economic policy; convergence; nonlinear panel data unit root test;
    All these keywords.

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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