Prashant Garg Profile picture
Dec 3 11 tweets 4 min read Read on X
🚨China's export bans on Gallium & Germanium 🚨
Why it matters: Gallium is central to countless downstream industries: semiconductors, aerospace, telecommunications, & more. This image shows how interconnected it is.
Public data, method & our paper in thread 🧵Image
Each node is a product. Size of node based on how "important" or "central" product is in international trade. Blue nodes are capital goods, silver are intermediates and green are final consumption good.
In our paper, AI-Generated Production Networks (2024), joint with with @fetzert, @pj_lambert and @bennetlf, we used AI to build AIPNET, a detailed map of global production networks.
It shows how critical materials like Gallium & Germanium underpin industries worldwide—and the disruptions export bans can cause.Image
Why AIPNET? Global trade relies on complex relationships between >5,000 products. Mapping these with traditional methods is slow. We built AIPNET using AI, which connects products like Gallium to their downstream uses. Here's what we found 👇
Trend 1: Global trade is shifting toward upstream & intermediary goods—like Gallium—are becoming central. Countries are focusing on inputs critical to supply chain resilience. Gallium isn't alone. AIPNET shows rising importance of:
1. Digital integrated circuits 🖥️
2. Lithium compounds 📷products.CapitalImage
Trend 2: Diverging strategies of U.S. vs. China in global trade. China: Importing more upstream products like Gallium to build advanced domestic industries. US: Importing more downstream goods, relying on global supply chains. Image
Why This Matters China's dominance in Gallium (98% of global production) is a prime example of its leverage. Export bans on Gallium/Germanium disrupt entire supply chains, with ripple effects across semiconductors, defence, & tech.
China's recent export ban on gallium and germanium to the U.S. underscores the fragility of global supply chains. For instance, U.S. Geological Survey estimates that a complete ban could reduce U.S. GDP by $3.4 billion (…)doi.org/10.3133/ofr202…
For context, this move is a direct response to U.S. export controls on semiconductor technology to China. Such escalating tit-for-tat measures highlight the urgent need for nations to reassess their supply chain dependencies.
Our paper finds that global supply shocks on internationally traded goods have become more prevalent since 2016, particularly affecting consumer goods and processed intermediates. Here's a map of these supply shocks. Image
Explore the data, methods and paper at aipnet.io

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More from @Prashant_Garg_

Nov 4
🚨Thrilled to share our new paper "Causal Claims in Economics"! 🚨
@fetzert and I analysed over 44,000 economics papers using AI to create a knowledge graph of economics and map out causal relationships.
Here's what we found 🧵👇 Image
Our goal: Synthesize causal evidence from economics in graphical format.
We built the "Knowledge Graph of Economics" mapping how economic concepts are causally linked.
Check out examples graphs of Chetty et al. and Banerjee et al.Image
Image
Want to see your own research or favourite papers visualized?
Explore their causal graphs on our website!
Try it here: causal.claimsImage
Read 13 tweets
Jun 19
🚨 Exciting News! 🚨
Thrilled to announce our latest working paper with @fetzert:

Political Expression of Academics on Social Media

In this thread, we will highlight our key findings and contributions using a newly built dataset🧵👇Image
1/ Social media has revolutionized how academics disseminate knowledge. Yet, the subset of academics active on these platforms may shape public perceptions disproportionately. Our study explores these patterns using a dataset of 100,000+ scholars globally.
2/ The Dataset
We built a novel dataset linking Twitter profiles of 99,274 academics to their academic records. Data spans 2016-2022, covering posts, comments, shares, and more from 12,675 institutions across 174 countries and 19 disciplines.
Read 13 tweets

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