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A Note on the COVID-19 Shock and Real GDP in Emerging Economies: A Counterfactual Analysis from the Threshold-Augmented Global Vector Autoregressive Model

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria)

  • Idris A. Adediran

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

In this study, we estimate a multi-country Threshold-Augmented Global Vector Autoregressive (TGVAR) model of Chudik et al., (2020) to analyse the response of real GDP of emerging economies (Brazil, India, China and South Africa) as well as the US (as a reference country) to the COVID-19 shock. The result of the counterfactual analysis beyond the 2019Q4 indicates that the impact of COVID-19 shock on real GDP is pervasive and heterogeneous but more prevalent in the US than the emerging economies. We expect real GDP in the selected emerging economies, but not the US, to revert to pre-COVID levels.

Suggested Citation

  • Afees A. Salisu & Idris A. Adediran & Rangan Gupta, 2021. "A Note on the COVID-19 Shock and Real GDP in Emerging Economies: A Counterfactual Analysis from the Threshold-Augmented Global Vector Autoregressive Model," Working Papers 202149, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202149
    as

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    References listed on IDEAS

    as
    1. Alexander Chudik & M. Hashem Pesaran, 2016. "Theory And Practice Of Gvar Modelling," Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, February.
    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. Chudik, Alexander & Mohaddes, Kamiar & Pesaran, M. Hashem & Raissi, Mehdi & Rebucci, Alessandro, 2021. "A counterfactual economic analysis of Covid-19 using a threshold augmented multi-country model," Journal of International Money and Finance, Elsevier, vol. 119(C).
    4. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    5. repec:zbw:bofrdp:2020_011 is not listed on IDEAS
    6. Salisu, Afees A. & Ebuh, Godday U. & Usman, Nuruddeen, 2020. "Revisiting oil-stock nexus during COVID-19 pandemic: Some preliminary results," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 280-294.
    7. Caggiano, Giovanni & Castelnuovo, Efrem & Kima, Richard, 2020. "The global effects of Covid-19-induced uncertainty," Economics Letters, Elsevier, vol. 194(C).
    8. Chudik, Alexander & Grossman, Valerie & Pesaran, M. Hashem, 2016. "A multi-country approach to forecasting output growth using PMIs," Journal of Econometrics, Elsevier, vol. 192(2), pages 349-365.
    9. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2020. "COVID-19 and The Macroeconomic Effects of Costly Disasters," NBER Working Papers 26987, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Real GDP; COVID-19; threshold-augmented GVAR; emerging economies; US;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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