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Bayesian Vector Autoregression Forecasts of Chinese Steel Consumption

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  • Paul Crompton
  • Yanrui Wu

Abstract

China consumed 116 million tonnes of steel in 2000, making it the largest consumer of steel in the world. China differs fundamentally from other countries at similar levels of economic development in that the secondary sector, the traditional consumer of steel products, already accounts for a significant proportion of domestic production. This suggests that little of any future growth in China's steel consumption will result from further rises in the 'steel intensity' of domestic production. Rather, growth in GDP will be the driving force behind future growth in steel consumption. This paper uses a macroeconomic Bayesian vector autoregression model to forecast steel consumption in China to 2010. This technique uses historical correlations among the variables in a system of equations and Bayesian priors on the estimated parameters, to introduce more flexibility into the forecasting process and align the models closer in nature to structural commodity market models. The forecasts suggest that steel consumption in China will rise from 116 million tonnes in 2000 to around 182 million tonnes in 2010.

Suggested Citation

  • Paul Crompton & Yanrui Wu, 2003. "Bayesian Vector Autoregression Forecasts of Chinese Steel Consumption," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 1(2), pages 205-219.
    • Handle: RePEc:taf:jocebs:v:1:y:2003:i:2:p:205-219
    DOI: 10.1080/1476528032000066703E
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    References listed on IDEAS

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    1. Crompton, Paul, 2000. "Future trends in Japanese steel consumption," Resources Policy, Elsevier, vol. 26(2), pages 103-114, June.
    2. Chen, Dongling & Clements, Kenneth W. & Roberts, E. John & Weber, E. Juerg, 1991. "Forecasting steel demand in China," Resources Policy, Elsevier, vol. 17(3), pages 196-210, September.
    3. Crompton, Paul, 1999. "Forecasting steel consumption in South-East Asia," Resources Policy, Elsevier, vol. 25(2), pages 111-123, June.
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    Cited by:

    1. Wu, Yanrui, 2012. "Energy intensity and its determinants in China's regional economies," Energy Policy, Elsevier, vol. 41(C), pages 703-711.
    2. Liu, Yaobin & Xie, Yichun, 2013. "Asymmetric adjustment of the dynamic relationship between energy intensity and urbanization in China," Energy Economics, Elsevier, vol. 36(C), pages 43-54.
    3. Torbat, Sheida & Khashei, Mehdi & Bijari, Mehdi, 2018. "A hybrid probabilistic fuzzy ARIMA model for consumption forecasting in commodity markets," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 22-31.
    4. Chen, Wenying & Yin, Xiang & Ma, Ding, 2014. "A bottom-up analysis of China’s iron and steel industrial energy consumption and CO2 emissions," Applied Energy, Elsevier, vol. 136(C), pages 1174-1183.
    5. Yin, Xiang & Chen, Wenying, 2013. "Trends and development of steel demand in China: A bottom–up analysis," Resources Policy, Elsevier, vol. 38(4), pages 407-415.

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