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Nowcasting global economic growth: A factor-augmented mixed-frequency approach

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  • L. Ferrara
  • C. Marsilli

Abstract

Facing several economic and financial uncertainties, assessing accurately global economic conditions is a great challenge for economists. The International Monetary Fund proposes within its periodic World Economic Outlook report a measure of the global GDP annual growth, that is often considered as the benchmark nowcast by macroeconomists. In this paper, we put forward an alternative approach to provide monthly nowcasts of the annual global growth rate. Our approach builds on a Factor-Augmented MIxed DAta Sampling (FA-MIDAS) model that enables (i) to account for a large monthly database including various countries and sectors of the global economy and (ii) to nowcast a low-frequency macroeconomic variable using higher-frequency information. Pseudo real-time results show that this approach provides reliable and timely nowcasts of the world GDP annual growth on a monthly basis.

Suggested Citation

  • L. Ferrara & C. Marsilli, 2014. "Nowcasting global economic growth: A factor-augmented mixed-frequency approach," Working papers 515, Banque de France.
    • Handle: RePEc:bfr:banfra:515
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    References listed on IDEAS

    as
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Guest Contribution: “Nowcasting Global GDP Growth”
      by Menzie Chinn in Econbrowser on 2015-03-12 09:56:18

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    Cited by:

    1. Laurent Ferrara & Anna Simoni, 2023. "When are Google Data Useful to Nowcast GDP? An Approach via Preselection and Shrinkage," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1188-1202, October.
    2. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(54), pages 5802-5816.
    3. Katja Heinisch & Axel Lindner, 2019. "For how long do IMF forecasts of world economic growth stay up-to-date?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(3), pages 255-260, February.
    4. Knut Are Aastveit & Tuva Marie Fastbø & Eleonora Granziera & Kenneth Sæterhagen Paulsen & Kjersti Næss Torstensen, 2020. "Nowcasting Norwegian household consumption with debit card transaction data," Working Paper 2020/17, Norges Bank.
    5. Luke Hartigan & Tom Rosewall, 2024. "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," Working Papers 2024-15, University of Sydney, School of Economics.
    6. Camacho, Maximo & Martinez-Martin, Jaime, 2015. "Monitoring the world business cycle," Economic Modelling, Elsevier, vol. 51(C), pages 617-625.
    7. Baumeister, Christiane & Guérin, Pierre, 2021. "A comparison of monthly global indicators for forecasting growth," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1276-1295.
    8. C. Marsilli, 2014. "Variable Selection in Predictive MIDAS Models," Working papers 520, Banque de France.
    9. Mahmut Gunay, 2018. "Nowcasting Annual Turkish GDP Growth with MIDAS," CBT Research Notes in Economics 1810, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    10. Michael Zhemkov, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, CEPII research center, issue 168, pages 10-24.
    11. Martin Enilov, 2024. "The predictive power of commodity prices for future economic growth: Evaluating the role of economic development," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3040-3062, July.
    12. M. Ayhan Kose & Naotaka Sugawara & Marco E. Terrones, 2020. "Global Recessions," Working Papers 162, Peruvian Economic Association.
    13. Ferrara , L. & Marsilli, C., 2016. "Nowcasting global economic growth," Rue de la Banque, Banque de France, issue 23, April..
    14. Nicolas Chatelais & Menzie Chinn & Arthur Stalla-Bourdillon, 2022. "Macroeconomic Forecasting Using Filtered Signals from a Stock Market Cross Section," Working papers 903, Banque de France.
    15. Francesco Ravazzolo & Joaquin Vespignani, 2020. "World steel production: A new monthly indicator of global real economic activity," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(2), pages 743-766, May.
    16. Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
    17. Denisa Georgiana Banulescu & Ferrara Laurent & Marsilli Clément, 2019. "Prévoir la volatilité d’un actif financier à l’aide d’un modèle à mélange de fréquences," Working Papers hal-03563168, HAL.
    18. Chatelais, Nicolas & Stalla-Bourdillon, Arthur & Chinn, Menzie D., 2023. "Forecasting real activity using cross-sectoral stock market information," Journal of International Money and Finance, Elsevier, vol. 131(C).
    19. Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    20. Jack Fosten & Shaoni Nandi, 2023. "Nowcasting from cross‐sectionally dependent panels," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 898-919, September.
    21. Luciano Campos & Danilo Leiva-León & Steven Zapata- Álvarez, 2022. "Latin American Falls, Rebounds and Tail Risks," Borradores de Economia 1201, Banco de la Republica de Colombia.
    22. Baumann, Ursel & Gomez-Salvador, Ramon & Seitz, Franz, 2019. "Detecting turning points in global economic activity," Working Paper Series 2310, European Central Bank.

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    More about this item

    Keywords

    Global growth; Nowcasting; Factor-Augmented MIDAS.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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