Food and nutrition security under global trade: a relation-driven agent-based global trade model

Area of Science:

• Global Trade and Food Security
• Agent-Based Modeling
• Nutritional Science

Background:

• Traditional trade models often overlook relational factors influencing international trade.
• Food security is a complex issue influenced by socio-economic, geopolitical, and environmental factors.
• A holistic approach is needed to understand the interplay between global trade and nutrition.

Purpose of the Study:

• To develop an empirically grounded, relation-driven agent-based global trade model.
• To investigate the impact of international trade on food and nutrition security, including macro and micronutrients.
• To integrate socio-economic, geopolitical, nutrition, environmental, and agri-food systems for a comprehensive analysis.

Main Methods:

• Development of a relation-driven agent-based global trade model.
• Incorporation of relational factors (trust, familiarity, trade history, conflicts) into trade behavior.
• Linking the trade model with a comprehensive nutrition formula.

Main Results:

• Global trade demonstrably improves food and nutrition security in Africa, Asia, and Latin America.
• International trade leads to healthier, more balanced diets through increased food variety.
• The positive impact of trade on nutrition security, encompassing macro and micronutrients, is universal.

Conclusions:

• The developed model offers valuable insights into the multifaceted role of global trade in enhancing food and nutrition security.
• This research provides a unique integrated framework for addressing global challenges at the intersection of trade, nutrition, and sustainability.
• Findings are particularly relevant in the context of current global events like Brexit, trade wars, and pandemics.