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Global Maize Trade and Food Security: Implications from a Social Network Model

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  • Felicia Wu
  • Hasan Guclu

Abstract

In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.N. Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, whereas Japan and the Republic of Korea are the largest maize importers. In particular, the star‐shaped cluster of the network that represents U.S. maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which U.S. maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide.

Suggested Citation

  • Felicia Wu & Hasan Guclu, 2013. "Global Maize Trade and Food Security: Implications from a Social Network Model," Risk Analysis, John Wiley & Sons, vol. 33(12), pages 2168-2178, December.
    • Handle: RePEc:wly:riskan:v:33:y:2013:i:12:p:2168-2178
    DOI: 10.1111/risa.12064
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    Cited by:

    1. Olaf Erenstein & Moti Jaleta & Kai Sonder & Khondoker Mottaleb & B.M. Prasanna, 2022. "Global maize production, consumption and trade: trends and R&D implications," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(5), pages 1295-1319, October.
    2. Muhammad Irfan Ahmad & Adnan Noor Shah & Jianqiang Sun & Youhong Song, 2020. "Comparative Study on Leaf Gas Exchange, Growth, Grain Yield, and Water Use Efficiency under Irrigation Regimes for Two Maize Hybrids," Agriculture, MDPI, vol. 10(9), pages 1-16, August.
    3. Ponsawan Khamphasan & Khomsorn Lomthaisong & Bhornchai Harakotr & Marvin Paul Scott & Kamol Lertrat & Bhalang Suriharn, 2020. "Combining Ability and Heterosis for Agronomic Traits, Husk and Cob Pigment Concentration of Maize," Agriculture, MDPI, vol. 10(11), pages 1-19, October.
    4. Dong, Chao & Yin, Qiuju & Lane, Kevin J. & Yan, Zhijun & Shi, Tianyu & Liu, Yan & Bell, Michelle L., 2018. "Competition and transmission evolution of global food trade: A case study of wheat," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 998-1008.
    5. Enrico Biffis & Erik Chavez, 2017. "Satellite Data and Machine Learning for Weather Risk Management and Food Security," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1508-1521, August.

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