IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202062.html
   My bibliography  Save this paper

Time-Varying Impact of Pandemics on Global Output Growth

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Xin Sheng

    (Lord Ashcroft International Business School, Anglia Ruskin University, Chelmsford, CM1 1SQ, United Kingdom)

  • Mehmet Balcilar

    (Department of Economics, Eastern Mediterranean University, Famagusta, via Mersin 10, Northern Cyprus, Turkey)

  • Qiang Ji

    (Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

This paper analyses the dynamic impact of uncertainty due to global pandemics (SARS, H5N1, H1N1, MERS, Ebola, and COVID-19) on global output growth for the quarterly period of 1996:Q1 to 2020:Q1, using a time-varying parameter structural vector autoregressive (TVP-SVAR) model. Besides the index based on the discussion about pandemics which appear in Economist Intelligence Unit (EIU) country reports, our model contains the growth rate of the United States (US), advanced economies excluding the US, and emerging market countries. We find that the negative effect of the coronavirus on the growth rate of output is unprecedented, with the emerging markets being the worst hit. We also find that since 2016, the comovement among the growth rates has increased significantly. Our results imply that policymakers would need to undertake massive expansionary policies, but it is also important to pursue well-coordinated policy decisions across the economic blocs.

Suggested Citation

  • Rangan Gupta & Xin Sheng & Mehmet Balcilar & Qiang Ji, 2020. "Time-Varying Impact of Pandemics on Global Output Growth," Working Papers 202062, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202062
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Elie Bouri & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2020. "Infectious Diseases, Market Uncertainty and Oil Market Volatility," Energies, MDPI, vol. 13(16), pages 1-8, August.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Maliszewska,Maryla & Mattoo,Aaditya & Van Der Mensbrugghe,Dominique, 2020. "The Potential Impact of COVID-19 on GDP and Trade : A Preliminary Assessment," Policy Research Working Paper Series 9211, The World Bank.
    4. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    5. 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.
    6. Afees A. Salisu & Rangan Gupta & Riza Demirer, 2022. "A Note On Uncertainty Due To Infectious Diseases And Output Growth Of The United States: A Mixed-Frequency Forecasting Experiment," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-9, June.
    7. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 98(1), pages 85-106.
    8. Grossman, Valerie & Mack, Adrienne & Martínez-García, Enrique, 2014. "A New Database of Global Economic Indicators," Journal of Economic and Social Measurement, IOS Press, issue 3, pages 163-197.
    9. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost & Marco C. Sammon & Tasaneeya Viratyosin, 2020. "The Unprecedented Stock Market Impact of COVID-19," NBER Working Papers 26945, National Bureau of Economic Research, Inc.
    10. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    11. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    12. Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
    13. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    14. repec:zbw:bofrdp:2020_011 is not listed on IDEAS
    15. Caggiano, Giovanni & Castelnuovo, Efrem & Kima, Richard, 2020. "The global effects of Covid-19-induced uncertainty," Economics Letters, Elsevier, vol. 194(C).
    16. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    17. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    18. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    19. Vasilios Plakandaras & Juncal Cunado & Rangan Gupta & Mark E. Wohar, 2017. "Do leading indicators forecast U.S. recessions? A nonlinear re†evaluation using historical data," International Finance, Wiley Blackwell, vol. 20(3), pages 289-316, December.
    20. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Yongan & Wang, Jianqiong & Chen, Zhonglu & Liang, Chao, 2021. "Economic policy uncertainty and stock market returns: New evidence," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. 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).
    3. Plakandaras, Vasilios & Gupta, Rangan & Balcilar, Mehmet & Ji, Qiang, 2022. "Evolving United States stock market volatility: The role of conventional and unconventional monetary policies," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    4. Ruipeng Liu & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
    5. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    6. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2020. "Uncertainty due to Infectious Diseases and Forecastability of the Realized Variance of US REITs: A Note," Working Papers 202099, University of Pretoria, Department of Economics.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Gupta, Rangan & Subramaniam, Sowmya & Bouri, Elie & Ji, Qiang, 2021. "Infectious disease-related uncertainty and the safe-haven characteristic of US treasury securities," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 289-298.
    3. Zhang, Yulian & Hamori, Shigeyuki, 2021. "Do news sentiment and the economic uncertainty caused by public health events impact macroeconomic indicators? Evidence from a TVP-VAR decomposition approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 145-162.
    4. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    5. 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.
    6. Mehmet Balcilar & Zeynel Abidin Ozdemir & Huseyin Ozdemir & Gurcan Aygun & Mark E. Wohar, 2022. "Effectiveness of monetary policy under the high and low economic uncertainty states: evidence from the major Asian economies," Empirical Economics, Springer, vol. 63(4), pages 1741-1769, October.
    7. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    8. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2021. "Volatility spillovers during market supply shocks: The case of negative oil prices," Resources Policy, Elsevier, vol. 74(C).
    9. 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).
    10. Pagnottoni, Paolo & Spelta, Alessandro & Pecora, Nicolò & Flori, Andrea & Pammolli, Fabio, 2021. "Financial earthquakes: SARS-CoV-2 news shock propagation in stock and sovereign bond markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    11. Li, Yanshuang & Shi, Yujie & Shi, Yongdong & Yi, Shangkun & Zhang, Weiping, 2023. "COVID-19 vaccinations and risk spillovers: Evidence from Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    12. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    13. Nong, Huifu, 2021. "Have cross-category spillovers of economic policy uncertainty changed during the US–China trade war?," Journal of Asian Economics, Elsevier, vol. 74(C).
    14. Faheem Aslam & Paulo Ferreira & Khurrum Shahzad Mughal & Beenish Bashir, 2021. "Intraday Volatility Spillovers among European Financial Markets during COVID-19," IJFS, MDPI, vol. 9(1), pages 1-19, January.
    15. Nasir, Muhammad Ali & Le, Thi Ngoc Lan & Ghabri, Yosra & Huynh, Luu Duc Toan, 2023. "Sovereign bonds and flight to safety: Implications of the COVID-19 crisis for sovereign debt markets in the G-7 and E-7 economies," International Review of Financial Analysis, Elsevier, vol. 86(C).
    16. Cheng, Tingting & Liu, Junli & Yao, Wenying & Zhao, Albert Bo, 2022. "The impact of COVID-19 pandemic on the volatility connectedness network of global stock market," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    17. Vladimir Balash & Alexey Faizliev & Sergei Sidorov & Elena Chistopolskaya, 2021. "Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets," Mathematics, MDPI, vol. 9(19), pages 1-31, October.
    18. Costa, Antonio & Matos, Paulo & da Silva, Cristiano, 2022. "Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics," Finance Research Letters, Elsevier, vol. 45(C).
    19. Abakah, Emmanuel Joel Aikins & Caporale, Guglielmo Maria & Gil-Alana, Luis Alberiko, 2021. "Economic policy uncertainty: Persistence and cross-country linkages," Research in International Business and Finance, Elsevier, vol. 58(C).
    20. Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).

    More about this item

    Keywords

    Pandemics-related uncertainty; output growth; TVP-SVAR;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pre:wpaper:202062. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.