Inferring supply networks from mobile phone data to estimate the resilience of a national economy
Tobias Reisch, Georg Heiler, Christian Diem, Stefan Thurner

TL;DR
This paper demonstrates that mobile phone data can be used to accurately reconstruct firm-level supply networks, enabling real-time assessment of systemic economic risks and identification of high-risk companies.
Contribution
It introduces a novel method to infer supply networks from telecommunication data, providing a cost-effective and timely alternative to traditional firm-level transaction data.
Findings
Conditional probability of identifying true links is about 90%
Able to estimate systemic risk profile of a country
Identified 65 firms with high potential to trigger economic cascades
Abstract
National economies rest on networks of millions of customer-supplier relations. Some companies -- in the case of their default -- can trigger significant cascades of shock in the supply-chain network and are thus systemically risky. Up to now, systemic risk of individual companies was practically not quantifiable, due to the unavailability of firm-level transaction data. So far, economic shocks are typically studied in the framework of input-output analysis on the industry-level that can't relate risk to individual firms. Exact firm-level supply networks based on tax or payment data exist only for very few countries. Here we explore to what extent telecommunication data can be used as an inexpensive, easily available, and real-time alternative to reconstruct national supply networks on the firm-level. We find that the conditional probability of correctly identifying a true…
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Taxonomy
TopicsEconomic and Technological Innovation · Supply Chain Resilience and Risk Management · Regional resilience and development
