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Granger causality transmission mechanism of steel product prices under multiple scales—The industrial chain perspective

Yajie Qi, Huajiao Li, Yanxin Liu, Sida Feng, Yang Li and Sui Guo

Resources Policy, 2020, vol. 67, issue C

Abstract: The steel industry is a basic industry of the national economy, and its product structure is complicated. Due to price differences, the prices of products of different varieties, specifications and origins affect each other and transmit each other. In addition, the steel industry covers the stages of product selection, smelting and processing. The transmission patterns between product prices at different stages also vary. At the same time, the steel industry has been confirmed to be a typical cyclical industry. Thus, our work mainly explores the transmission relationship between steel product prices under multiple timescales from the perspective of the industrial chain. First, we use discrete wavelet transform to extract the time series of 553 steel products at different timescales. Second, based on the Granger causality test, the transmission relationship between every two products is measured. Third, by constructing multiscale steel product price transmission networks, important steel products with different roles are identified. Finally, based on motif recognition, the main modes of product price transmission between different reaches of the industrial chain are summarized. The results show that as the timescale increases, the transmission between products becomes increasingly frequent and that the transmission patterns become increasingly clear. In general, there is a high probability of occurrence of important steel products in hot rolled coils, structural steel and medium and heavy plates, especially 4.75 mm and 3 mm hot rolled coils produced in Beijing and 4.75 mm hot rolled coils produced in Beijing and Zhengzhou. In addition, the transmission of steel products at different stages has undergone a process of transmission between two stages to transmission among three stages and then to transmission between two stages. In this regard, under 4–8 days, transmission within a stage and transmission among three stages is the most frequent transmission pattern. Our work will help investors and policy makers gain an in-depth understanding of the steel market and mitigate risks in investment and the policy development process.

Keywords: Steel products; Industrial chain; Granger causality; Multiple scales; Network motif (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.resourpol.2020.101674

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