Agric. Econ. - Czech, 2023, 69(9):343-357 | DOI: 10.17221/124/2023-AGRICECON

Factors influencing the global agricultural trade: A network analysisOriginal Paper

Tingting Zhang1, Ju Yang2
1 School of Economics and Management, West Anhui University, Lu’an, China
2 School of Economics and Management, Huazhong Agricultural University, Wuhan, China

In this study, a global agricultural trade network was constructed, and its topological characteristics from 1991 to 2021 were analysed. The influences of nine variables were empirically tested, including factor endowments and economic, geographical, and institutional factors. The research results show that the scale of trade networks is constantly expanding, and trade relations are becoming increasingly concentrated. Further, global agricultural trade patterns are gradually being reshaped. However, European economies and the United States still dominate the power of network control, with a clear ‘core-edge’ hierarchy. Among the factors influencing the global agricultural trade network, differences in arable land areas, agricultural product prices, geographical distances, and financial institutions have proven important. However, their influence varies. Compared to the differences in the endowments of other factors, the comparative advantage of agricultural trade in various nodes worldwide comes more from the arable land areas. The greater the difference in agricultural prices, the closer are the trade ties between nodes. Differences in geographical distance have proven conducive to establishing agricultural trade relations. Finally, the greater the difference in financial systems, the greater the likelihood that agricultural trade links will occur.

Keywords: agricultural products; Quadratic Assignment Procedure method; social networks

Received: April 10, 2023; Revised: July 20, 2023; Accepted: July 21, 2023; Prepublished online: September 6, 2023; Published: September 22, 2023  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Zhang T, Yang J. Factors influencing the global agricultural trade: A network analysis. Agric. Econ. - Czech. 2023;69(9):343-357. doi: 10.17221/124/2023-AGRICECON.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Abeysinghe T., Forbes K. (2005): Trade linkages and output-multiplier effects: A structural VAR approach with a focus on Asia. Review of International Economics, 13: 356-375. Go to original source...
    2. Anderson J.E., Van Wincoop E. (2003): Gravity with gravitas: A solution to the border puzzle. American Economic Review, 93: 170-192. Go to original source...
    3. Barabási A.L., Albert R. (1999): Emergence of scaling in random networks. Science, 286: 509-512. Go to original source... Go to PubMed...
    4. Blondel V.D., Guillaume J.L., Lambiotte R., Lefebvre E. (2008): Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008: P10008. Go to original source...
    5. CEPII (2021): International geostatistical data. Research and expertise on the world economy. Available at http://www.cepii.fr/CEPII/en/ (accessed Feb 25, 2023).
    6. Cheptea A. (2007): Trade liberalization and institutional reforms. Economics of Transition, 15: 211-255. Go to original source...
    7. Chung M.G., Kapsar K., Frank K.A., Liu J.G. (2020): The spatial and temporal dynamics of global meat trade networks. Scientific Reports, 10: 16657. Go to original source... Go to PubMed...
    8. Clague C., Desser A. (1998): International differences in the agricultural price level: Factor endowments, transportation costs, and the political economy of agricultural protection. Eastern Economic Journal, 24: 281-292.
    9. Dalin C., Konar M., Hanasaki N., Rinaldo A., Rodriguez-Iturbe I. (2012): Evolution of the global virtual water trade network. Proceedings of the National Academy of Sciences of the United States of America, 109: 5989-5994. Go to original source... Go to PubMed...
    10. Dupas M.C., Halloy J., Chatzimpiros P. (2019): Time dynamics and invariant subnetwork structures in the world cereals trade network. PLOS One, 14: e0216318. Go to original source... Go to PubMed...
    11. Ercsey-Ravasz M., Toroczkai Z., Lakner Z., Baranyi J. (2012): Complexity of the international agro-food trade network and its impact on food safety. PLOS One, 7: e37810. Go to original source...
    12. Fagiolo G., Reyes J., Schiavo S. (2009): World-trade web: Topological properties, dynamics, and evolution. Physical Review E, 79: 036115. Go to original source... Go to PubMed...
    13. Fair K.R., Bauch C.T., Anand M. (2017): Dynamics of the global wheat trade network and resilience to shocks. Scientific Reports, 7: 7177. Go to original source... Go to PubMed...
    14. FAO (2021): Global agriculture-related data. Available at https://www.fao.org/faostat/en/#data/ (accessed Feb 21, 2023).
    15. Freeman L.C. (1979): Centrality in social networks conceptual clarification. Social Networks, 1: 215-239. Go to original source...
    16. Garlaschelli D., Loffredo M.I. (2004): Fitness-dependent topological properties of the world trade web. Physical Review Letters, 93: 188701. Go to original source... Go to PubMed...
    17. Gutiérrez-Moya E., Lozano S., Adenso-Díaz B. (2020): Analyzing the structure of the global wheat trade network: An ERGM approach. Agronomy, 10: 1967. Go to original source...
    18. Henderson J.V., Squires T., Storeygard A., Weil D. (2018): The global distribution of economic activity: Nature, history, and the role of trade. The Quarterly Journal of Economics, 133: 357-406. Go to original source... Go to PubMed...
    19. Heritage Foundation (2021): The world's leading think tank for policy impact. Available at https://www.heritage.org/ (accessed Feb 21, 2023).
    20. Jafari Y., Engemann H., Zimmermann A. (2022): The Evolution of the Global Structure of Food and Agricultural Trade: Evidence from Network Analysis. Background Paper for The State of Agricultural Commodity Markets (SOCO). Rome, FAO: 61.
    21. Karagoz K., Saray M.O. (2022): Trade potential of Turkey with Asia-Pacific countries: Evidence from panel gravity model. International Economics Studies, 36: 19-26.
    22. Kohlhagen S.W. (1977): Income distribution and 'representative demand' in international trade flows: An empirical test of Linder's hypothesis. Southern Economic Journal, 44: 167-172. Go to original source...
    23. Linders G.J., de Groot H.L., Rietveld P. (2005a): Institutional Determinants of Bilateral Trade: An Analysis According to Product Type. Tinbergen Institute Discussion Paper 05-023/3. Amsterdam, Tinbergen Institute: 31. Go to original source...
    24. Linders G.J.M., Slangen A., De Groot H.L.F., Beugelsdijk S. (2005b): Cultural and Institutional Determinants of Bilateral Trade Flows. Tinbergen Institute Discussion Paper 05-074/3. Amsterdam, Tinbergen Institute: 28. Go to original source...
    25. Martinez-Zarzoso I. (2003): Gravity model: An application to trade between regional blocs. Atlantic Economic Journal, 31: 174-187. Go to original source...
    26. Martínez-Zarzoso I., Vollmer S. (2016): Bilateral trade flows and income distribution similarity. PLOS One, 11: e0128191. Go to original source... Go to PubMed...
    27. Ohlin B. (1967): Interregional and International Trade. Cambridge, Harvard University Press: 324.
    28. Platte E. (1991): Japan-China trade: Performance and prospects. Hitotsubashi Journal of Economics, 32: 111-126.
    29. Schmutzler A. (1999): The new economic geography. Journal of Economic Surveys, 13: 355-379. Go to original source...
    30. Schweitzer F., Fagiolo G., Sornette D., Vega-Redondo F., Vespignani A., White D.R. (2009): Economic networks: The new challenges. Science, 325: 422-425. Go to original source... Go to PubMed...
    31. Scott J. (2000): Social Networks Analysis: A Handbook. 2nd Ed. London, Sage Publications: 208.
    32. Serrano M.A., Boguna M. (2003): Topology of the world trade web. Physical Review E, 68: 015101. Go to original source... Go to PubMed...
    33. Serrano R., Pinilla V. (2010): Causes of world trade growth in agricultural and food products, 1951-2000: A demand function approach. Applied Economics, 42: 3503-3518. Go to original source...
    34. Simpson W. (2001): QAP: The quadratic assignment procedure. Available at https://www.stata.com/meeting/1nasug/simpson.pdf (accessed Mar 11, 2023)
    35. Staugaitis A.J., Vaznonis B. (2022): Short-term speculation effects on agricultural commodity returns and volatility in the European market prior to and during the pandemic. Agriculture, 12: 623. Go to original source...
    36. Torreggiani S., Mangioni G., Puma M.J., Fagiolo G. (2018): Identifying the community structure of the food-trade international multi-network. Environmental Research Letters, 13: 054026. Go to original source...
    37. UN Comtrade Database (2021): International trade statistics. United Nations Comtrade Database. Available at https://comtrade.un.org/data/ (accessed Feb 15, 2023).
    38. Wilhite A. (2001): Bilateral trade and 'small-world' networks. Computational Economics, 18: 49-64. Go to original source...
    39. World Bank (2021): Global development data. The World Bank. Available at https://data.worldbank.org/ (accessed Feb 15, 2023).

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content