A computational exploration and open codebase supporting the findings of Matias Nehuen Iglesias, Utrecht University.
Keywords: spatial economics, co-location, cosine similarity, MAUP, economic geography, industry clustering, employment density, continuous space modeling, spatial analysis, kernel density, economic complexity, GIS.
This repository contains the source code, computational experiments, and data structures supporting the research paper:
📄 “The Overlooked Insights from Correlation Structures in Economic Geography”
Papers in Evolutionary Economic Geography, Working Paper #21.05
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This project studies the mathematical and empirical conditions under which continuous spatial models (e.g., radial influence around establishments) and discrete areal data models (e.g., county-level employment statistics) yield comparable measures of industrial co-location.
Traditional spatial analyses rely on administrative units that may distort the real patterns of economic co-location due to the Modifiable Areal Unit Problem (MAUP). This repository:
- Formalizes coexistence measures in continuous space.
- Compares them with cosine similarity metrics computed on discrete areal data.
- Offers code to replicate analytical derivations and computational simulations.
- Helps identify when discrete spatial indicators are reliable proxies for true spatial proximity.
/notebooks/ # Exploratory and replication notebooks
/models/ # Density function models and simulation engines
/data/ # Sample geospatial datasets (synthetic and real)
/experiments/ # Setup for controlled spatial displacement simulations
/utils/ # Math helpers, kernel generators, area integrators
- Kernel density estimation (Gaussian & Laplace)
- Cosine similarity over employment vectors
- Numerical integration of joint density functions
- Systematic decomposition of co-location pairs (A/B/C/D types)
- Simulation of influence decay and spatial shifting
- Comparative experiments across area sizes (e.g., 10km², 100km²)
If you use this codebase or ideas in your work, please cite:
@techreport{iglesias2021correlation,
title={The Overlooked Insights from Correlation Structures in Economic Geography},
author={Matias Nehuen Iglesias},
year={2021},
institution={Utrecht University},
series={Papers in Evolutionary Economic Geography},
number={21.05}
}
Matias Nehuen Iglesias
PhD in Economics – SSSUP Univ di Pisa
Researcher in economic geography, spatial modeling, and applied AI.