GTAP Resources: Resource Display
| GTAP Resource #7719 |
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"Risky Global Agricultural Supply Chains: Evidence from Firm-to-Firm Trade " Authors: Ai, Jianwei, Bernhard Dalheimer and Wendong Zhang Abstract Risks are inherent and increasingly recognized in global agricultural value chains; however, their effects and firm-level responses are poorly understood. Using novel global firm-to-firm trade data, we show that agricultural markets are highly concentrated and have sparse network structures, with buyers typically relying on a limited set of suppliers, and prices are shaped by the two-sided market power of both importers and exporters. We find that U.S. import prices are lower when importers account for a larger share of purchases, and that price volatility is reduced when firms diversify their foreign suppliers, for example, in response to the Ukraine-Russia war. Motivated by these findings, we develop the first structural model of international sourcing under matching frictions and risk aversion applied to agricultural markets and global agricultural value chains. In this model, agri-food firms adjust along three margins: absorbing shocks, renegotiating with existing suppliers, or diversifying by switching to new suppliers. The relative importance of these adjustment strategies depends on the relative Ricardian comparative advantage, risk aversion, and matching friction correlation across countries. Our simulated supply chain disruption counterfactual exercises show that policies promoting import-source diversification and reducing matching frictions enable importers to access new suppliers and help stabilize agricultural prices, especially with a more competitive upstream market structure. |
| Resource Details () | GTAP Keywords | ||||||||||||||||
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- Non-competitive markets - New quantitative trade models - Supply chains - Econometric methods - North America |
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Public Access No documents have been attached. Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 4/30/2026 12:56:16 PM
