On the Detecting of Clusters and other Regional and Urban Structuring Elements by a Use of Spatial Econometric Techniques

Abstract

The author grounds his contribution on the fact that throughout the twentieth century cities all
around the world underwent dramatic changes as to their urban landscape. For this reason, a
signifi cant portion of the modern geographical literature has been devoted to examine the degree
of spatial concentration of urban population and employment in order to underscore regularities in
urban structure. The focus on these regularities or “patterns” highlights the signifi cance of location
and distance, two central concepts in spatial data analysis. This interest has generated an
increasing demand for methods, techniques and tools that allow for an explicit treatment of space
in its empirical applications. In fact, the spatial patterns of economic clustering and urban forms
can be uncovered and made visible by Exploratory Spatial Data Analysis (ESDA) and Geographical
Information Systems (GIS), which are powerful instruments particularly designed to analyze
spatially geo-referenced data. This paper aims at highlighting the main ESDA methods that are
used to explore and depict geographic agglomerations of population and economic activity as
within regional and urban areas. The paper concentrates upon those ESDA instruments used in
spatial econometrics that allow for the fi nding of otherwise hidden spatial trends, clusters, outliers
and diffusion processes in databases as these offer a greater and better understanding of the
phenomena processed and/or predictive image of observed human behaviour.