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Influencing factors analysis of China’s iron import price: Based on quantile regression model

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  • Chen, Wenhui
  • Lei, Yalin
  • Jiang, Yong

Abstract

When encountering high import prices and price volatility, China does not have the power to affect prices, although China has ranked first in iron ore imports since 2003. The existing literature usually investigates the impact factors of iron ore prices using the averaging method. It is difficult to depict the detailed impact of various factors on prices accurately. To provide sounder basis for the Chinese government to enact policy, this paper develops a quantile regression model with the lagged variables to measure factors that affect the import prices of iron ore in China under high, medium and low price levels. The analysis uses monthly data through January 2003 to March 2015. The results indicate that the effect intensity of the factors on the prices are various under different quantiles. As prices rise, the degree of positive influence of previous period of crude steel production on iron ore prices is gradually decreasing; conversely, the strength of previous period of import volume’s negative effect on prices is falling. Furthermore, it verifies that China has no voice in the international iron ore market. In low quantile, the strength of effect of prior period iron ore volume on prices is higher than that of China’s production of iron ore on import prices because the grade of China's iron ore resources is low. Therefore, when the iron ore prices are at a low quantile, China should expand the import of iron ore appropriately and reduce the exploitation of low-grade iron ore resources. Additionally, China should optimize crude steel output and actively invest in overseas iron ore exploration and mining to reduce the effect of prices fluctuations by reducing the dependence on imported iron ore. China may also promote the development of an international iron ore futures market and innovate iron ore business models to hedge foreign exchange risks because of the US dollar index has greatest negative effect on the prices.

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  • Chen, Wenhui & Lei, Yalin & Jiang, Yong, 2016. "Influencing factors analysis of China’s iron import price: Based on quantile regression model," Resources Policy, Elsevier, vol. 48(C), pages 68-76.
    • Handle: RePEc:eee:jrpoli:v:48:y:2016:i:c:p:68-76
    DOI: 10.1016/j.resourpol.2016.02.007
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    References listed on IDEAS

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    Cited by:

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    2. Su, Chi-Wei & Wang, Kai-Hua & Chang, Hsu-Ling & Dumitrescu–Peculea, Adelina, 2017. "Do iron ore price bubbles occur?," Resources Policy, Elsevier, vol. 53(C), pages 340-346.
    3. Liu, Yanxin & Li, Huajiao & Guan, Jianhe & Liu, Xueyong & Guan, Qing & Sun, Qingru, 2019. "Influence of different factors on prices of upstream, middle and downstream products in China's whole steel industry chain: Based on Adaptive Neural Fuzzy Inference System," Resources Policy, Elsevier, vol. 60(C), pages 134-142.
    4. Qiangfeng, Li & Weiqiong, Zhong & Gaoshang, Wang & Jinhua, Cheng & Tao, Dai & Bojie, Wen & Liang, Liang & Qindong, Yang, 2018. "Material and value flows of iron in Chinese international trade from 2010 to 2016," Resources Policy, Elsevier, vol. 59(C), pages 139-147.
    5. Yufeng CHEN & Shuo YANG, 2022. "How Does the Reform in Pricing Mechanism Affect the World’s Iron Ore Price: A Time-Varying Parameter SVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 83-103, April.
    6. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(C).
    7. Zhu, Xuehong & Zheng, Weihang & Zhang, Hongwei & Guo, Yaoqi, 2019. "Time-varying international market power for the Chinese iron ore markets," Resources Policy, Elsevier, vol. 64(C).
    8. Liu, Yanxin & Li, Huajiao & Guan, Jianhe & Feng, Sida & Guo, Sui, 2019. "The impact of Chinese steel product prices based on the midstream industry chain," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    9. Wei, Jiangqiao & Ma, Zhe & Wang, Anjian & Li, Pengyuan & Sun, Xiaoyan & Yuan, Xiaojing & Hao, Hongchang & Jia, Hongxiang, 2022. "Multiscale nonlinear Granger causality and time-varying effect analysis of the relationship between iron ore futures and spot prices," Resources Policy, Elsevier, vol. 77(C).

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