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The role of the world’s major steel markets in price spillover networks: an analysis based on complex network motifs

Author

Listed:
  • Yanxin Liu

    (China University of Geosciences
    Ministry of Land and Resources)

  • Huajiao Li

    (China University of Geosciences
    Ministry of Land and Resources)

  • Jianhe Guan

    (China University of Geosciences)

  • Xueyong Liu

    (China University of Geosciences
    Ministry of Land and Resources)

  • Yajie Qi

    (China University of Geosciences
    Ministry of Land and Resources)

Abstract

In recent years, the international steel market has shown increasingly strong cross-regional correlation. To better understand the price trends of various markets, it is necessary to identify their inherent price spillovers. This paper combines a generalized autoregressive conditional heteroskedasticity Baba–Engle–Kraft–Kroner (GARCH-BEKK) model and complex network motifs to explore the price fluctuations among international steel markets. The study selects steel markets in 12 countries and regions and uses daily data on import and export prices from January 2009 to September 2017 to analyze eight steel products. The results show that spillovers are associated with geographical location, market development, product type and status. Spillovers mostly occur between buyer’s markets; additionally, the Asian market, especially the East Asian market, is in most cases the recipient of spillover, whereas the European Union (EU) market is in most cases the sender of spillover effects. Developed markets have clear spillover effects on emerging markets, sheet steel products have clear spillover effects on profile steel products, and the prices of midstream and downstream products in the industrial chain are the most influenced. This paper examines international steel market relationships from the perspective of price transmission, and the results can help manage and prevent large-scale economic risks.

Suggested Citation

  • Yanxin Liu & Huajiao Li & Jianhe Guan & Xueyong Liu & Yajie Qi, 2019. "The role of the world’s major steel markets in price spillover networks: an analysis based on complex network motifs," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 697-720, December.
    • Handle: RePEc:spr:jeicoo:v:14:y:2019:i:4:d:10.1007_s11403-019-00261-6
    DOI: 10.1007/s11403-019-00261-6
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    as
    1. Julian Maluck & Reik V Donner, 2015. "A Network of Networks Perspective on Global Trade," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-24, July.
    2. Sebastien Bradley & Estelle Dauchy & Makoto Hasegawa, 2018. "Investor valuations of Japan’s adoption of a territorial tax regime: quantifying the direct and competitive effects of international tax reform," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 25(3), pages 581-630, June.
    3. Gao, Xiangyun & Fang, Wei & An, Feng & Wang, Yue, 2017. "Detecting method for crude oil price fluctuation mechanism under different periodic time series," Applied Energy, Elsevier, vol. 192(C), pages 201-212.
    4. Sevrin Waights, 2019. "The preservation of historic districts—is it worth it?," Journal of Economic Geography, Oxford University Press, vol. 19(2), pages 433-464.
    5. Muhammad Z. Mumtaz & Zachary A. Smith, 2017. "Estimation of the spillover effect between patents and innovation using the GARCH–BEKK model," Pacific Economic Review, Wiley Blackwell, vol. 22(5), pages 772-791, December.
    6. Jingze Jiang & T. Randall Fortenbery, 2019. "El Niño and La Niña induced volatility spillover effects in the U.S. soybean and water equity markets," Applied Economics, Taylor & Francis Journals, vol. 51(11), pages 1133-1150, March.
    7. Daniel Fricke & Thomas Lux, 2015. "The effects of a financial transaction tax in an artificial financial market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(1), pages 119-150, April.
    8. Truong, Thuy D. & Adamowicz, Wiktor L. (Vic) & Boxall, Peter C., 2015. "Modeling non-compensatory preferences in environmental valuation," Resource and Energy Economics, Elsevier, vol. 39(C), pages 89-107.
    9. Itzhack, Royi & Mogilevski, Yelena & Louzoun, Yoram, 2007. "An optimal algorithm for counting network motifs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 482-490.
    10. Yudong Wang & Zhiyuan Pan & Chongfeng Wu, 2018. "Volatility spillover from the US to international stock markets: A heterogeneous volatility spillover GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 385-400, April.
    11. Chandra, Piyush, 2016. "Impact of temporary trade barriers: Evidence from China," China Economic Review, Elsevier, vol. 38(C), pages 24-48.
    12. Theodore Tsekeris, 2017. "Network analysis of inter-sectoral relationships and key sectors in the Greek economy," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 413-435, July.
    13. Dariusz Wójcik & Eric Knight & Vladimír Pažitka, 2018. "What turns cities into international financial centres? Analysis of cross-border investment banking 2000–2014," Journal of Economic Geography, Oxford University Press, vol. 18(1), pages 1-33.
    14. Chevallier, Julien & Le Pen, Yannick & Sévi, Benoît, 2011. "Options introduction and volatility in the EU ETS," Resource and Energy Economics, Elsevier, vol. 33(4), pages 855-880.
    15. Peri, Massimo & Baldi, Lucia, 2013. "The effect of biofuel policies on feedstock market: Empirical evidence for rapeseed oil prices in EU," Resource and Energy Economics, Elsevier, vol. 35(1), pages 18-37.
    16. Milstein, Irena & Tishler, Asher, 2015. "Can price volatility enhance market power? The case of renewable technologies in competitive electricity markets," Resource and Energy Economics, Elsevier, vol. 41(C), pages 70-90.
    17. Chia-Hsuan Yeh & Chun-Yi Yang, 2013. "Do price limits hurt the market?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 125-153, April.
    18. Orlando Gomes, 2017. "Heterogeneous wage setting and endogenous macro volatility," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 27-57, April.
    19. Aki-Hiro Sato & Takaki Hayashi & Janusz Hołyst, 2012. "Comprehensive analysis of market conditions in the foreign exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 167-179, October.
    20. Lee, Keun & Ki, Jee-hoon, 2017. "Rise of latecomers and catch-up cycles in the world steel industry," Research Policy, Elsevier, vol. 46(2), pages 365-375.
    21. Yaxian Lu & Longguang Yang & Lihong Liu, 2019. "Volatility Spillovers between Crude Oil and Agricultural Commodity Markets since the Financial Crisis," Sustainability, MDPI, vol. 11(2), pages 1-12, January.
    22. repec:dau:papers:123456789/6793 is not listed on IDEAS
    23. Hou, Wenyu & Liu, Huifang & Wang, Hui & Wu, Fengyang, 2018. "Structure and patterns of the international rare earths trade: A complex network analysis," Resources Policy, Elsevier, vol. 55(C), pages 133-142.
    24. Takaaki Ohnishi & Hideki Takayasu & Misako Takayasu, 2010. "Network motifs in an inter-firm network," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(2), pages 171-180, December.
    25. Oliver Hein & Michael Schwind & Markus Spiwoks, 2008. "Frankfurt Artificial Stock Market: a microscopic stock market model with heterogeneous interacting agents in small-world communication networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(1), pages 59-71, June.
    26. Aghabozorgi, Farshad & Khayyambashi, Mohammad Reza, 2018. "A new similarity measure for link prediction based on local structures in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 12-23.
    27. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    28. Luisa Gagliardi & Sara Lemos, 2016. "Evidence on immigrants’ assimilation into recipient labour markets using UK longitudinal data between 1981 and 2006," Journal of Economic Geography, Oxford University Press, vol. 16(3), pages 547-583.
    29. Bateman, Ian J. & Brouwer, Roy, 2006. "Consistency and construction in stated WTP for health risk reductions: A novel scope-sensitivity test," Resource and Energy Economics, Elsevier, vol. 28(3), pages 199-214, August.
    30. Emawtee Bissoondoyal-Bheenick & Robert Brooks & Wei Chi & Hung Xuan Do, 2018. "Volatility spillover between the US, Chinese and Australian stock markets," Australian Journal of Management, Australian School of Business, vol. 43(2), pages 263-285, May.
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    3. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).

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    More about this item

    Keywords

    Price volatility; Spillover network; Steel market; Global trade;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • F02 - International Economics - - General - - - International Economic Order and Integration
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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