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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

In this paper we propose a new indicator of monthly global real economic activity, named world steel production. We use world steel production, OECD industrial production index and Kilian’s rea index to forecast world real GDP, and key commodity prices. We find that world steel production generates large statistically significant gains in forecasting world real GDP and oil prices, relative to an autoregressive benchmark. A forecast combination of the three indices produces statistically significant gains in forecasting world real GDP, oil, natural gas, gold and fertilizer prices, relative to an autoregressive benchmark.

Suggested Citation

  • Francesco Ravazzolo & Joaquin Vespignani, 2017. "World steel production: A new monthly indicator of global real economic activity," CAMA Working Papers 2017-42, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2017-42
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    Cited by:

    1. Afees A. Salisu & Philip C. Omoke & Abdulsalam Abidemi Sikiru, 2023. "Geopolitical risk and global financial cycle: Some forecasting experiments," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 3-16, January.
    2. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    3. 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.
    4. Olayeni, Olaolu Richard & Tiwari, Aviral Kumar & Wohar, Mark E., 2020. "Global economic activity, crude oil price and production, stock market behaviour and the Nigeria-US exchange rate," Energy Economics, Elsevier, vol. 92(C).
    5. Arabinda Basistha & Richard Startz, 2023. "Measuring Persistent Global Economic Factors with Output, Commodity Price, and Commodity Currency Data," Working Papers 23-05, Department of Economics, West Virginia University.
    6. Stolbov, Mikhail & Shchepeleva, Maria, 2022. "Modeling global real economic activity: Evidence from variable selection across quantiles," The Journal of Economic Asymmetries, Elsevier, vol. 25(C).
    7. Pérez-Quirós, Gabriel & Diaz, Elena, 2020. "Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic," CEPR Discussion Papers 15451, C.E.P.R. Discussion Papers.
    8. Funashima, Yoshito, 2020. "Global economic activity indexes revisited," Economics Letters, Elsevier, vol. 193(C).
    9. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2022. "Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 134-157, January.
    10. Stavros Degiannakis, George Filis, and Vipin Arora, 2018. "Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    11. Diaz, Elena Maria & Perez-Quiros, Gabriel, 2021. "GEA tracker: A daily indicator of global economic activity," Journal of International Money and Finance, Elsevier, vol. 115(C).
    12. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020. "Forecasting Oil Volatility Using a GARCH-MIDAS Approach: The Role of Global Economic Conditions," Working Papers 202051, University of Pretoria, Department of Economics.
    13. Wen, Xiaoqian & Xie, Yuxin & Pantelous, Athanasios A., 2022. "Extreme price co-movement of commodity futures and industrial production growth: An empirical evaluation," Energy Economics, Elsevier, vol. 108(C).
    14. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
    15. Nonejad, Nima, 2021. "The price of crude oil and (conditional) out-of-sample predictability of world industrial production," Journal of Commodity Markets, Elsevier, vol. 23(C).
    16. Jiménez-Rodríguez, Rebeca, 2022. "Oil shocks and global economy," Energy Economics, Elsevier, vol. 115(C).
    17. 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).
    18. Nguyen, BH & Zhang, Bo, 2022. "Forecasting oil Prices: can large BVARs help?," Working Papers 2022-04, University of Tasmania, Tasmanian School of Business and Economics.

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    More about this item

    Keywords

    Global real economic activity; World steel production; Forecasting;
    All these keywords.

    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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