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Market demand dynamic induced mechanism in China's steel industry

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  • Sun, Wei
  • Dong, Kaiqiang
  • Zhao, Tianyu

Abstract

Using the example of iron and steel industry, this paper aims to reveal the market demand effect and the mechanism on investment and capacity allocation. Based on building the theoretical model containing demand dynamic gap with the quarterly data of iron and steel industry since 2004, time-varying parameter model is used to empirically test the asymmetric adjustment mechanism of the productivity allocation under demand inducing and the effect of policies. The results show that obvious asymmetric features in the formulating and withdrawing phases of iron and steel productivity caused by inducing demand dynamics and its asymmetric periodic motion; self-correction mechanism of productivity under the situation of frequent switching between supply and demand is limited. Once the deviation from the equilibrium level of production capacity exceeds its own threshold adjustment mechanism, it is unable to restore equilibrium through market regulation, and leads to the extraordinary "trial and error" cost; further takes the correlation mechanism among industries as the breakthrough point to do more empirical tests of the effects of downstream industry dynamic demand on the steel industry capacity. It also indicates that the development of the real estate industry when Chinese economic environment is good directly introduces the steel industry capacity allocation, Grasping accurately the above rules is the premise of achieving market’s decisive role in the resource allocating process while giving full play to government function.

Suggested Citation

  • Sun, Wei & Dong, Kaiqiang & Zhao, Tianyu, 2017. "Market demand dynamic induced mechanism in China's steel industry," Resources Policy, Elsevier, vol. 51(C), pages 13-21.
    • Handle: RePEc:eee:jrpoli:v:51:y:2017:i:c:p:13-21
    DOI: 10.1016/j.resourpol.2016.10.011
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    References listed on IDEAS

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    Cited by:

    1. Guo, Sui & Li, Huajiao & An, Haizhong & Sun, Qingru & Hao, Xiaoqing & Liu, Yanxin, 2019. "Steel product prices transmission activities in the midstream industrial chain and global markets," Resources Policy, Elsevier, vol. 60(C), pages 56-71.
    2. Dong, Kaiqiang & Sun, Wei, 2022. "Would the market mechanism cause the formation of overcapacity?: Evidence from Chinese listed firms of manufacturing industry," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 97-113.
    3. Lin, Boqiang & Xu, Bin, 2018. "Growth of industrial CO2 emissions in Shanghai city: Evidence from a dynamic vector autoregression analysis," Energy, Elsevier, vol. 151(C), pages 167-177.
    4. Mehmanpazir, Farhad & Khalili-Damghani, Kaveh & Hafezalkotob, Ashkan, 2022. "Dynamic strategic planning: A hybrid approach based on logarithmic regression, system dynamics, Game Theory and Fuzzy Inference System (Case study Steel Industry)," Resources Policy, Elsevier, vol. 77(C).
    5. Mehmanpazir, Farhad & Khalili-Damghani, Kaveh & Hafezalkotob, Ashkan, 2019. "Modeling steel supply and demand functions using logarithmic multiple regression analysis (case study: Steel industry in Iran)," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    6. Ren, Xiaohang & Qin, Jianing & Jin, Chenglu & Yan, Cheng, 2022. "Global oil price uncertainty and excessive corporate debt in China," Energy Economics, Elsevier, vol. 115(C).
    7. Liu, Jian & An, Rui & Xiao, Rongge & Yang, Yongwei & Wang, Gaoshang & Wang, Qian, 2017. "Implications from substance flow analysis, supply chain and supplier’ risk evaluation in iron and steel industry in Mainland China," Resources Policy, Elsevier, vol. 51(C), pages 272-282.
    8. Sun, Wei & Geng, Danqing & Dong, Kaiqiang, 2021. "State of demand and excessive indebtedness: Evidence from Chinese listed manufacturing firms," Finance Research Letters, Elsevier, vol. 42(C).

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