I’m releasing the NAICS Contagion Map, a dataset designed to bridge the gap between the physical economy (NAICS) and financial market taxonomies (GICS).
The goal was to map how volatility in upstream raw materials (Tier 4) systematically ripples down to consumer-facing products (Tier 1). This is particularly useful for anyone doing economic modelling, supply chain resilience analysis, or ESG/Risk research.
What’s inside the CSVs:
- 340+ NAICS Nodes: Each assigned a Contagion Score (1.0 – 10.0) based on upstream concentration (HHI) and structural importance.
- 1,100+ Topological Edges: Mapping the exact flow from Tier 4 (Commodities) -> Tier 3 (Extractors) -> Tier 2 (Processors) -> Tier 1 (Assemblers).
- NAICS to GICS Bridge: Each node is mapped to its financial sector equivalent.
Methodology: This is a derived dataset. The structural tiers and contagion scores were generated via a deterministic heuristic algorithm I built that analyzes industrial interdependencies. While the raw NAICS data is from Census/GICS registries, the relationship mapping (edges) and risk scoring are my original derivation.
Full Disclosure : I am the creator of this project. I’m sharing this as a free open-source intelligence drop for the community to play with. I’d love to get feedback on the edge logic or hear how you’re using the topology in your own models.
submitted by /u/Vast-Village-2596
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