• Resources Science
  • Vol. 42, Issue 8, 1580 (2020)
Meirui ZHONG1、2 and Wanting SONG1、2、*
Author Affiliations
  • 1School of Business, Central South University, Changsha 410083, China
  • 2Institute of Metal Resources Strategy, Central South University, Changsha 410083, China
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    DOI: 10.18402/resci.2020.08.12 Cite this Article
    Meirui ZHONG, Wanting SONG. Impact of strategic metal price shocks on industrial output:Time-varying analysis based on the TVP-FAVAR model[J]. Resources Science, 2020, 42(8): 1580 Copy Citation Text show less

    Abstract

    Based on the perspective of industrial security, this study used monthly data from August 2006 to December 2018 to incorporate factors that directly or indirectly affect the price fluctuations of strategic metals into a unified framework of analysis, and constructed a time varying parameter factor augmented vector autoregressive (TVP-FAVAR) model to conduct a comprehensive analysis of the dynamic impacts of supply shocks, economic demand shocks, strategic metal-specific demand shocks, and financial speculative shocks on the strategic metal industry’s output. The results show that the impacts of strategic metal price shocks on the strategic metal industry are time-varying. At different temporal scales and at different points in time, the effects are heterogeneous. Among the four types of shocks, supply shocks affect most in the output of strategic metal ore mining and dressing industry. The output of the strategic metal smelting and rolling processing industry is mainly affected by economic demand shocks; fluctuations in the price of strategic metals have a significant inhibitory effect on China’s strategic metal industry output, especially that of the strategic metal ore mining and dressing industry, which has severely affected the security of the strategic metal industry, and is particularly significant in the context of the current Sino-US trade war.
    Meirui ZHONG, Wanting SONG. Impact of strategic metal price shocks on industrial output:Time-varying analysis based on the TVP-FAVAR model[J]. Resources Science, 2020, 42(8): 1580
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