Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/308393 
Year of Publication: 
2024
Series/Report no.: 
CESifo Working Paper No. 11497
Publisher: 
CESifo GmbH, Munich
Abstract: 
This paper leverages generative AI to build a network structure over 5,000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step 'build-prune' approach using an ensemble of prompt-tuned generative AI classifications. The 'build' step provides an initial distribution of edge-predictions, the 'prune' step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade.
Subjects: 
supply-chain network analysis
large language models
on-shoring
industrial policy
trade wars
econometrics-of-LLMs
JEL: 
F14
F23
L16
F52
O25
N74
C81
Document Type: 
Working Paper
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