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Uncovering the Effect of Forest Certification on the Dynamic Evolution of the Global Log Trade Network: A Stochastic Actor-Oriented Model Approach

Author

Listed:
  • Yingying Zhou

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Baodong Cheng

    (School of Economics and Management, Beijing Forestry University, Beijing 100083, China)

  • Jianbin Chen

    (School of Business, Beijing Union University, Beijing 100025, China)

Abstract

Clarifying the dynamic evolution characteristics and driving mechanism of the global log trade network (GLTN) can provide references for the trade decision-making of various countries. Based on the stochastic actor-oriented model, this paper analyzed the GLTN’s dynamic evolution from 2010 to 2019 and paid more attention to the effect of forest certification on the dynamic evolution of the GLTN. Results indicate that from 2010 to 2019, many changes have occurred in the network. The change rate in the 2010–2015 period is faster than that in the 2015–2019 period. Countries tend to form reciprocity, three-cycles, and transitive trade ties over time. A country with more certified forest area tends to form new log export ties with the other countries. The trade imbalance ratio (TII) has a significant negative mediating effect on the evolutionary relationships between the certified forest area and the log trade network dynamic. Net exporters of log tend to avoid establishing export ties with countries with more certified forest areas over time. Countries with similar cultural backgrounds are easier to establish log trade ties with, while countries with farther geographical distances tend to avoid establishing trade ties over time. A free trade agreement (FTA) has a significant positive impact on the formation of log trade ties among nations. Our findings shed new light on the dynamic evolution mechanism of the global log trade network and offer implications for future trade and forest conservation policy design.

Suggested Citation

  • Yingying Zhou & Baodong Cheng & Jianbin Chen, 2022. "Uncovering the Effect of Forest Certification on the Dynamic Evolution of the Global Log Trade Network: A Stochastic Actor-Oriented Model Approach," Sustainability, MDPI, vol. 14(14), pages 1-13, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8229-:d:856570
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    References listed on IDEAS

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    1. Shore, Jesse C., 2016. "Market formation as transitive closure: The evolving pattern of trade in music," Network Science, Cambridge University Press, vol. 4(2), pages 164-187, June.
    2. Giorgio Fagiolo, 2010. "The international-trade network: gravity equations and topological properties," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 5(1), pages 1-25, June.
    3. Felbermayr, Gabriel J. & Toubal, Farid, 2010. "Cultural proximity and trade," European Economic Review, Elsevier, vol. 54(2), pages 279-293, February.
    4. Masahisa Fujita & Paul Krugman & Anthony J. Venables, 2001. "The Spatial Economy: Cities, Regions, and International Trade," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262561476, April.
    5. Long, Ting & Pan, Huanxue & Dong, Chao & Qin, Tao & Ma, Ping, 2019. "Exploring the competitive evolution of global wood forest product trade based on complex network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1224-1232.
    6. Newsom, Deanna & Bahn, Volker & Cashore, Benjamin, 2006. "Does forest certification matter? An analysis of operation-level changes required during the SmartWood certification process in the United States," Forest Policy and Economics, Elsevier, vol. 9(3), pages 197-208, December.
    7. Scott L. Baier & Jeffrey H. Bergstrand & Erika Vidal, 2007. "Free Trade Agreements In the Americas: Are the Trade Effects Larger than Anticipated?," The World Economy, Wiley Blackwell, vol. 30(9), pages 1347-1377, September.
    8. Yingying Zhou & Yunpei Hong & Baodong Cheng & Lichun Xiong, 2021. "The Spatial Correlation and Driving Mechanism of Wood-Based Products Trade Network in RCEP Countries," Sustainability, MDPI, vol. 13(18), pages 1-17, September.
    9. Luca De Benedictis & Lucia Tajoli, 2011. "The World Trade Network," The World Economy, Wiley Blackwell, vol. 34(8), pages 1417-1454, August.
    10. Pierre-Alexandre Balland & Mathijs De Vaan & Ron Boschma, 2013. "The dynamics of interfirm networks along the industry life cycle: The case of the global video game industry, 1987--2007," Journal of Economic Geography, Oxford University Press, vol. 13(5), pages 741-765, September.
    11. Hubert Paluš & Ján Parobek & Rastislav Šulek & Ján Lichý & Jaroslav Šálka, 2018. "Understanding Sustainable Forest Management Certification in Slovakia: Forest Owners’ Perception of Expectations, Benefits and Problems," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    12. Garlaschelli, Diego & Loffredo, Maria I., 2005. "Structure and evolution of the world trade network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 138-144.
    13. Nasrullah, Muhammad & Chang, Liu & Khan, Khalid & Rizwanullah, Muhammad & Zulfiqar, Farah & Ishfaq, Muhammad, 2020. "Determinants of forest product group trade by gravity model approach: A case study of China," Forest Policy and Economics, Elsevier, vol. 113(C).
    14. D. Garlaschelli & M. I. Loffredo, 2005. "Structure and Evolution of the World Trade Network," Papers physics/0502066, arXiv.org, revised May 2005.
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