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World steel production: A new monthly indicator of global real economic activity

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  • Francesco Ravazzolo
  • Joaquin Vespignani

Abstract

This paper proposes world steel production as an indicator of global real economic activity. World steel production data is published with only a one‐month delay, thereby providing timely information for world real GDP forecasters. We find that world steel production and Lutz Kilian's (2009) index of global real economic activity generate large gains in forecasting world real GDP, relative to an autoregressive benchmark. A forecast combination of world steel production, Kilian's (2009) index of global real economic activity and an index of the industrial production of OECD countries plus six non‐OECD emerging economies produces significant gains in forecasting world real GDP, relative to an autoregressive benchmark Production mondiale d’acier : un nouvel indicateur mensuel de l’activité économique mondiale réelle. Cet article propose d’utiliser la production mondiale d’acier comme indicateur de l’activité économique internationale réelle. Les données relatives à la production mondiale d’acier étant publiées dans un délai d’un mois, les prévisionnistes du PIB mondial réel peuvent ainsi profiter de renseignements en temps opportun. Nos travaux montrent que la production mondiale d’acier, ainsi que l’indice d’activité économique globale réelle développé par Kilian en 2009, permettent de mieux prévoir le PIB mondial par rapport à un modèle de référence autoregressif. Ainsi, la combinaison d’outils tels que la production mondiale d’acier, l’indice d’activité économique globale réelle de Killian ainsi qu’un indice de production des pays de l’OCDE plus six économies émergentes non OCDE permet de mieux estimer le PIB mondial réel comparativement à un modèle de référence autoregressif.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:canjec:v:53:y:2020:i:2:p:743-766
    DOI: 10.1111/caje.12442
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    4. Salisu, Afees A. & Gupta, Rangan & Bouri, Elie & Ji, Qiang, 2020. "The role of global economic conditions in forecasting gold market volatility: Evidence from a GARCH-MIDAS approach," Research in International Business and Finance, Elsevier, vol. 54(C).

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    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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