AI-Generated Production Networks: Measuring and Understanding Global Trade Dynamics
by Fetzer, Lambert, Feld, Garg (2024)
In our recent paper, we introduce the AI-generated Production Network (AIPNET)—a groundbreaking approach that maps out the complex web of global production processes using advanced generative AI technology. AIPNET captures the relationships between over 5,000 product categories, revealing how goods are interconnected through input-output relationships in production.
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Understanding Global Trade Patterns
By analyzing AIPNET, we’ve uncovered significant shifts in global trade patterns over the past decade. One of the most notable trends is the marked increase in the trade of more “central” upstream products—those critical inputs used in the production of many downstream goods.
Figure 1: Global Trade has increased most for “High Importance” products central to production processess
This shift suggests that countries are increasingly focusing on importing essential capital and intermediary components, potentially due to heightened awareness of supply chain vulnerabilities and the desire to enhance domestic production capabilities.
Diverging Trends Between Major Economies
Our analysis reveals contrasting strategies among major economies:
- China has significantly increased its imports of upstream products, indicating a move toward more sophisticated and self-reliant domestic production.
- The United States has shifted toward importing more downstream products, which may reflect a reliance on foreign production for finished goods.
Figure 2: Comparison of China’s and the US’s Import Centrality
These divergent trends highlight how different countries are adapting their trade strategies in response to global economic changes and geopolitical events.
The Rise and Fall of Specific Products
AIPNET allows us to track the changing importance of specific products within the global production network.
Emerging Products:
- Digital Integrated Circuits (Chips)
- Lithium Compounds (used in battery technology)
These products have seen a significant increase in importance, reflecting the growing demand for technology and renewable energy components.
Figure 3: Rise of Emerging Technologies in Global Trade
Onshoring and Supply Chain Resilience
Our research explores how countries respond to supply shocks—sudden and sustained increases in the prices of certain goods. We found that when faced with disruptions in the supply of downstream products, countries tend to increase imports of upstream goods connected to those products. This behavior indicates a strategic shift toward onshoring, where countries bring production processes closer to home to enhance supply chain resilience.
Case Study: The Qatar Blockade
The 2017 blockade of Qatar by neighboring countries provided a unique opportunity to study the effects of severe supply shocks on trade patterns.
Figure 4: Impact of the Qatar Blockade on Imports
Key Findings:
- Imports of Blockaded Goods Declined Sharply: Products that were previously imported from blockading countries saw a significant drop in imports.
- Increase in Upstream Imports: Qatar responded by increasing imports of upstream goods necessary to produce the affected products domestically.
- Evidence of Onshoring: This shift underscores a strategic move toward self-sufficiency in critical goods and highlights the role of production networks in adapting to trade disruptions.
Implications for Global Trade and Policy
Our findings have several important implications:
- Supply Chain Resilience: Understanding production networks helps policymakers and businesses enhance resilience against future disruptions.
- Industrial Policy and Onshoring: The trend toward onshoring may influence global trade policies and economic strategies.
- Emerging Technologies: Tracking the rise of critical products like chips and lithium compounds can inform investment and development priorities.
- Sanctions and Trade Wars: AIPNET can be used to analyze the effectiveness of sanctions and the potential for trade realignment.
Conclusion
The AI-generated Production Network (AIPNET) provides a powerful tool for visualizing and analyzing the intricate connections within global production processes. By leveraging generative AI, we’ve offered a granular view of how products and countries are interlinked, shedding light on important trends in globalization, supply chain dynamics, and economic policy.
For any inquiries or further information, please contact us at team@appliedeconomics.ai.