Mapping the US Physical Economy: A network visualization of 346 industries and 1,100+ supply chain dependencies [OC]

[OC] Data Sources & Tools

• Data Source: Industrial classifications based on 2022 NAICS (U.S. Census Bureau). Connectivity and Contagion Scores were calculated using a deterministic heuristic algorithm mapping input-output dependencies across 346 manufacturing nodes.
• Tools Used:
  • Python: For data cleaning and the heuristic classification engine.
  • NetworkX: For topological edge generation and directed graph analysis.
  • vis.js: For the interactive physics-driven network visualization.
• The Research Context: This visualization was built to address the Visibility Gap between financial taxonomies (GICS) and the physical economy (NAICS). Research indicates that the U.S. physical economy faces a $1.1T Visibility Gap where systemic supply chain shocks remain hidden until they cause catastrophic decay.

Key Findings from the Visualization:

• Risk Aggregation: By mapping the topology into four tiers, we found that critical systemic risks aggregate most heavily at Tier 3 (Primary Extractors) and Tier 2 (Intermediate Processors).
• The Delayed Effect: Tier 1 (Final Assembly) is often the last to feel the impact, usually when it is too late to circumvent the disruption.
• The Goal: We have open-sourced this dataset and the heuristic logic to provide a digital twin of industrial topology, helping analysts and risk managers identify these invisible bottlenecks.
• Interactive Version: See Hugging Face
• Source Code/Data: See GitHub