Economic stories are usually presented as lines: one event causes another, one company affects an industry, one constraint changes a price. Economy Map starts from the idea that the underlying system is a graph with feedback, bottlenecks, missing edges, and relationships at several scales.
The project takes the form of a self-similar global-economy graph with tools for centrality, communities, flow constraints, missing relationships, and AI-assisted public research. Its purpose is to make economic systems explorable as linked mechanisms instead of disconnected headlines and statistics.
The question behind Economy Map
The graph is intended to be recursive. Industries contain firms and processes; processes depend on resources, infrastructure, labor, policy, and other industries. Research becomes the work of adding sourced relationships without rewarding the system for inventing a complete-looking world. Researchers, analysts, students, and decision-makers may benefit. Firms and communities represented in the graph can be mischaracterized if weak sources become asserted facts.
How Economy Map took shape
The prototype combines Neo4j, Python and LangGraph research flows, FastAPI, Celery, Redis, React, Cytoscape, and algorithms for centrality, communities, flows, and missing relationships. Unknown values are meant to remain null rather than being filled by plausible language. Josiah originated the recursive economy-map idea, specified the research and visualization behavior, and directed agent-assisted implementation.
What the evidence supports
Core application milestones and graph-analysis features were implemented in a working prototype. Economy Map is not a validated forecasting engine. Its contribution is a research interface for asking what a system depends on, where evidence is thin, and which relationships deserve investigation. A bounded public case study must demonstrate that reasoning without implying comprehensive economic truth.
The graph's conclusions are only as good as its sources, extraction, and coverage. It has not produced validated economic forecasts or comprehensive market truth. A credible public release would contain a bounded dataset and one reproducible investigation that makes both its insight and uncertainty visible.