DISTANCE-BASED MEASURES OF SPATIAL CONCENTRATION: INTRODUCING A RELATIVE DENSITY FUNCTION

Gabriel Lang (1) , Eric Marcon (2) , Florence Puech (3)

1 MIA-Paris - Mathématiques et Informatique Appliquées
2 UMR ECOFOG - Ecologie des forêts de Guyane
3 RITM - Réseaux Innovation Territoires et Mondialisation

For a decade, distance-based methods have been largely employed and improved in the field of spatial economics. Such tools are very powerful to evaluate accurately the spatial distribution of plants or retail stores for example (Duranton and Overman, 2008; Jensen and Michel, 2011). In the present paper, we introduce a new statistic measure based on distances to evaluate the spatial concentration of economic activities. As far as we know, the m function is the first relative density function proposed in the economic literature. This tool completes the typology of distance-based methods recently drawn up by Marcon and Puech (2014). By working on several theoretical and empirical examples, we prove the advantages and the limits of the m function to gauge the spatial structures in spatial economics.

Mots clés: Spatial concentration; Aggregation; Point patterns; Agglomeration; Economic geography

Domaines: Economies et finances

Gabriel Lang, Eric Marcon, Florence Puech. DISTANCE-BASED MEASURES OF SPATIAL CONCENTRATION: INTRODUCING A RELATIVE DENSITY FUNCTION. 2014. ⟨hal-01082178v1⟩