In the framework of the analysis of spatially distributed quantitative phenomena, as for instance the economic ones, it is necessary to adopt specific tools able to deal with the spatial autocorrelation issue. In the last decade, thanks to the deployment of software for spatial data analysis and visualization, the number of spatial economic studies progressively increased. In the most of cases the available software allow for efficient data representation. The present work aims at introducing cartography as an intermediate but crucial result in the Spatial Shift Share Analysis. A preliminary graphical analysis of the neighborhood, conducted by considering an algorithm based on the spatial autocorrelation, can be fundamental in order to obtain meaningful and interpretable results. Theoretical results regarding the modification of the well-known AMOEBA neighboring method are developed here and the spatial analysis is applied to the occupation data observed in Friuli Venezia Giulia. Data are collected in the Statistical Business Register, socalled ASIA, administered by the Italian National Statistical Institute (ISTAT). Both the intermediate cartography and the spatial decomposition algorithms are developed in R integrating the available spatial libraries with an ad-hoc script.

La cartografia come strumento di interpretazione dei risultati di un modello di scomposizione spaziale: nuove proposte con applicazione al caso dell’occupazione in Friuli Venezia Giulia

ZACCOMER, Gian Pietro;GRASSETTI, Luca
2014-01-01

Abstract

In the framework of the analysis of spatially distributed quantitative phenomena, as for instance the economic ones, it is necessary to adopt specific tools able to deal with the spatial autocorrelation issue. In the last decade, thanks to the deployment of software for spatial data analysis and visualization, the number of spatial economic studies progressively increased. In the most of cases the available software allow for efficient data representation. The present work aims at introducing cartography as an intermediate but crucial result in the Spatial Shift Share Analysis. A preliminary graphical analysis of the neighborhood, conducted by considering an algorithm based on the spatial autocorrelation, can be fundamental in order to obtain meaningful and interpretable results. Theoretical results regarding the modification of the well-known AMOEBA neighboring method are developed here and the spatial analysis is applied to the occupation data observed in Friuli Venezia Giulia. Data are collected in the Statistical Business Register, socalled ASIA, administered by the Italian National Statistical Institute (ISTAT). Both the intermediate cartography and the spatial decomposition algorithms are developed in R integrating the available spatial libraries with an ad-hoc script.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1094634
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