Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Clusters of firms in an inhomogeneous space: The high-tech industries in Milan
Ist Teil von
Economic modelling, 2012, Vol.29 (1), p.3-11
Ort / Verlag
Amsterdam: Elsevier B.V
Erscheinungsjahr
2012
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
Why do industrial clusters occur in space? Is it because industries need to stay close together to interact or, conversely, because they concentrate in certain portions of space to exploit favourable conditions like public incentives, proximity to communication networks, to big population concentrations or to reduce transport costs? This is a fundamental question and the attempt to answer to it using empirical data is a challenging statistical task. In economic geography scientists refer to this dichotomy using the two categories of
spatial interaction and
spatial reaction to common factors. In economics we can refer to a distinction between
exogenous causes and
endogenous effects. In spatial econometrics and statistics we use the terms of
spatial dependence and
spatial heterogeneity. A series of recent papers introduced explorative methods to analyse the spatial patterns of firms using micro data and characterizing each firm by its spatial coordinates. In such a setting a spatial distribution of firms is seen as a point pattern and an industrial cluster as the phenomenon of extra-concentration of one industry with respect to the concentration of a benchmarking spatial distribution. Often the benchmarking distribution is that of the whole economy on the ground that exogenous factors affect in the same way all branches. Using such an approach a positive (or negative) spatial dependence between firms is detected when the pattern of a specific sector is more aggregated (or more dispersed) than the one of the whole economy. In this paper we suggest a parametric approach to the analysis of spatial heterogeneity, based on the so-called
inhomogeneous K-function (Baddeley
et al., 2000). We present an empirical application of the method to the spatial distribution of high-tech industries in Milan (Italy) in 2001. We consider the economic space to be non homogenous, we estimate the pattern of inhomogeneity and we use it to separate spatial heterogeneity from spatial dependence.
► TWe detect spatial concentration of high-tech firms in Milan. ► Disentangling empirically spatial heterogeneity and spatial dependence is problematic. ► Inhomogeneous K-function allows to assess the net effect of spatial dependence. ► Spatial dependence has an important effect on the cluster of high-tech firms in Milan.