Hellenic Spatial Statistics Lab
The Hellenic Spatial Statistics Lab (HSSL) is an academic initiative dedicated to spatial statistics, spatial econometrics, and spatial data analysis, with particular emphasis on applications in Greece and Europe. Its aim is to contribute to understanding the mechanisms that shape regional and local development, spatial inequalities, and geographical interdependence.
HSSL connects Regional Science with Cartography, Spatial Statistics, and Spatial Econometrics in order to:
- map and analyse spatial inequalities,
- investigate processes of regional convergence and divergence,
- understand geographical dynamics across multiple spatial scales,
- develop reproducible applications and open educational resources.
Research and teaching
HSSL is closely connected to the forthcoming book Introduction to Spatial Econometrics by Leonidas Doukissas and Panagiotis Pantazis. It extends the book through online resources including:
- interactive notes,
- reproducible R code,
- applied case studies,
- interviews and academic conversations.
In this way, theoretical concepts are supported by practical examples linking spatial methods to real problems of regional development and spatial policy.
Open tools and tutorials
The team develops and shares educational guides and applications based on open-source tools. These resources support:
- thematic and interactive mapping,
- spatial statistical analysis,
- reproducible econometric modelling.
This approach promotes transparency, reproducibility, and broader access to contemporary spatial-analysis methods for students, researchers, and practitioners.
Areas of interest
HSSL aims to operate as a hub for producing and disseminating scientific content on topics such as:
- spatial inequality and spatial justice,
- regional convergence, divergence, and development dynamics,
- high-resolution spatial data analysis,
- spatial regression, spatial panels, and Bayesian models,
- spatial clustering and spatial inequality indicators,
- geospatial visualisation and modern cartographic methods,
- open science and reproducible research.