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Reconstructing production networks using machine learning

Abstract:

The vulnerability of supply chains and their role in the propagation of shocks has been highlighted multiple times in recent years, including by the recent pandemic. However, while the importance of micro data is increasingly recognised, data at the firm-to-firm level remains scarcely available. In this study, we formulate supply chain networks’ reconstruction as a link prediction problem and tackle it using machine learning, specifically Gradient Boosting. We test our approach on three diffe...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jedc.2023.104607

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Mathematical Institute
Role:
Author
Publisher:
Elsevier
Journal:
Journal of Economic Dynamics and Control More from this journal
Volume:
148
Article number:
104607
Publication date:
2023-02-01
Acceptance date:
2023-01-30
DOI:
EISSN:
1879-1743
ISSN:
0165-1889
Language:
English
Keywords:
Pubs id:
1326673
Local pid:
pubs:1326673
Deposit date:
2023-02-03

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