Geographical Distribution of Crime in Italian Provinces: A Spatial Econometric Analysis

For a long time social sciences scholars from different fields have devoted their attention to identifying the causes leading to commit criminal offences and recently lots of studies have included the analysis of spatial effects. Respect to the Italian crime phenomenon some stylized facts exist: hig...

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Bibliographische Detailangaben
1. VerfasserIn: Maria Francesca Cracolici (VerfasserIn)
Beteiligte: Teodora Erika Uberti
Medienart: Elektronisch Buch
Sprache:Englisch
Online-Zugang: Volltext (kostenfrei)
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520 |a For a long time social sciences scholars from different fields have devoted their attention to identifying the causes leading to commit criminal offences and recently lots of studies have included the analysis of spatial effects. Respect to the Italian crime phenomenon some stylized facts exist: high spatial and time variability and presence of “organised crime” (e.g. Mafia and Camorra) deep-seated in some local territorial areas. Using explanatory spatial data analysis, the paper firstly explores the spatial structure and distribution of four different typologies of crimes (murders, thefts, frauds, and squeezes) in Italian provinces in two years, 1999 and 2003. ESDA allows us to detect some important geographical dimensions and to distinguish crucial macro- and micro- territorial aspects of offences. Further, on the basis of Becker-Ehrlich model, a spatial cross-sectional model including deterrence, economic and socio-demographic variables has been performed to investigate the determinants of Italian crime for 1999 and 2003 and its “neighbouring” effects, measured in terms of geographical and relational proximity. The empirical results obtained by using different spatial weights matrices highlighted that socioeconomic variables have a relevant impact on crime activities, but their role changes enormously respect to crimes against person (murders) or against property (thefts, frauds and squeezes). It is worthy to notice that severity does not show the expected sign: its significant and positive sign should suggest that inflicting more severe punishments does not always constitute a deterrence to commit crime, but it works on the opposite direction.Crime, Spatial Econometrics 
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