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Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis

Author

Listed:
  • Danilo Leiva-Leon

    (Banco de España)

  • Gabriel Pérez-Quirós

    (European Central Bank and CEPR)

  • Eyno Rots

    (Magyar Nemzeti Bank (Central Bank of Hungary))

Abstract

We propose an empirical framework to measure the degree of weakness of the global economy in real‐time. It relies on non‐linear factor models designed to infer recessionary episodes of heterogeneous deepness, and fitted to the largest advanced economies (U.S., Euro Area, Japan, U.K., Canada and Australia) and emerging markets (China, India, Russia, Brazil, Mexico and South Africa). Based on such inferences, we construct a Global Weakness Index that has three main features. First, it can be updated as soon as new regional data is released, as we show by measuring the economic effects of coronavirus. Second, it provides a consistent narrative of the main regional contributors of world economy’s weakness. Third, it allows to perform robust risk assessments based on the probability that the level of global weakness would exceed a certain threshold of interest in every period of time. With information up to March 2nd 2020, we show that the Global Weakness Index already sharply increased at a speed at least comparable to the experienced in the 2008 crisis.

Suggested Citation

  • Danilo Leiva-Leon & Gabriel Pérez-Quirós & Eyno Rots, 2020. "Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis," MNB Working Papers 2020/4, Magyar Nemzeti Bank (Central Bank of Hungary).
  • Handle: RePEc:mnb:wpaper:2020/4
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    Cited by:

    1. Phurichai Rungcharoenkitkul, 2021. "Macroeconomic effects of COVID‐19: A mid‐term review," Pacific Economic Review, Wiley Blackwell, vol. 26(4), pages 439-458, October.
    2. Massimiliano Ferraresi, 2022. "The regional (re)allocation of migrants during the Great Lockdown in Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 39(2), pages 403-426, July.
    3. Marina Diakonova & Luis Molina & Hannes Mueller & Javier J. Pérez & Cristopher Rauh, 2022. "The information content of conflict, social unrest and policy uncertainty measures for macroeconomic forecasting," Working Papers 2232, Banco de España.
    4. Salisu, Afees A. & Gupta, Rangan & Bouri, Elie, 2023. "Testing the forecasting power of global economic conditions for the volatility of international REITs using a GARCH-MIDAS approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 303-314.
    5. Pérez Quirós, Gabriel, 2020. "Global Weakness Index – reading the economy’s vital signs during the COVID-19 crisis," Research Bulletin, European Central Bank, vol. 72.
    6. Donato Masciandaro, 2020. "Covid-19 Helicopter Money, Monetary Policy And Central Bank Independence: Economics And Politics," BAFFI CAREFIN Working Papers 20137, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    7. Funke, Michael & Tsang, Andrew, 2020. "The People’s bank of China’s response to the coronavirus pandemic: A quantitative assessment," Economic Modelling, Elsevier, vol. 93(C), pages 465-473.
    8. Balsalobre-Lorente, Daniel & Driha, Oana M. & Bekun, Festus & Sinha, Avik & Fatai Adedoyin, Festus, 2020. "Consequences of COVID-19 on the social isolation of the Chinese economy: accounting for the role of reduction in carbon emissions," MPRA Paper 102894, University Library of Munich, Germany, revised 2020.
    9. Donato Masciandaro, 2020. "Ecb Helicopter Money: Economic And Political Economy Arithmetics," BAFFI CAREFIN Working Papers 20138, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    10. Hervé Le Bihan & Danilo Leiva-León & Matías Pacce, 2023. "Underlying inflation and asymetric risks," Working Papers 2319, Banco de España.
    11. Piotr Skórka & Beata Grzywacz & Dawid Moroń & Magdalena Lenda, 2020. "The macroecology of the COVID-19 pandemic in the Anthropocene," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-17, July.
    12. Miguel A. Mascarúa Lara, 2024. "Heterogeneous recessions and expansions in Mexican regions and sectors," Working Papers 2024-13, Banco de México.
    13. Mary Oluwatoyin Agboola & Festus Victor Bekun & Daniel Balsalobre-Lorente, 2021. "Implications of Social Isolation in Combating COVID-19 Outbreak in Kingdom of Saudi Arabia: Its Consequences on the Carbon Emissions Reduction," Sustainability, MDPI, vol. 13(16), pages 1-16, August.
    14. repec:zbw:bofitp:2020_012 is not listed on IDEAS
    15. Boriss Siliverstovs, 2021. "Gauging the Effect of Influential Observations on Measures of Relative Forecast Accuracy in a Post-COVID-19 Era: Application to Nowcasting Euro Area GDP Growth," Working Papers 2021/01, Latvijas Banka.
    16. Sułkowski Łukasz, 2020. "Covid-19 Pandemic; Recession, Virtual Revolution Leading to De-globalization?," Journal of Intercultural Management, Sciendo, vol. 12(1), pages 1-11, March.
    17. Romain Aumond & Julien Royer, 2024. "Improving the robustness of Markov-switching dynamic factor models with time-varying volatility," Working Papers 2024-04, Center for Research in Economics and Statistics.

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    More about this item

    Keywords

    International; Business Cycles; Factor Model; Nonlinear;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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