Crime And Economic Performance. A Cluster Analysis Of Panel Data On Italy'S Nuts 3 Regions
AbstractCrime is a complex phenomenon which needs to be investigated at appropriate disaggregate temporal and territorial levels of analysis. The speci c issue addressed in this paper concerns the possibility of classifying Italian provinces in groups by using a new methodology that combines cluster analysis with panel time series data regarding a wide range of crime indicators, economic performance indicators and other socio-demographic variables. Our main contribution is to show that crime is not inextricably linked to geographic location as is usually believed. From this point of view, the position of the Italian Mezzogiorno has two facets; one is found in those relatively not affluent provinces which are resistant to random street and organized crime while the other facet is encountered in those provinces which are caught in a vicious circle where increasing criminal activity and weak economic performance feed on each other to undermine the security of the population. The pattern for the Center-North of Italy is much more varied and composed of a series of four clusters. In particular, there is a relatively large cluster of provinces which should be considered at risk because of an increasing value added per capita, high rates of population replacement and female employment; all conditions that might attract and encourage criminal activity.
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Bibliographic InfoPaper provided by Università della Calabria, Dipartimento di Economia, Statistica e Finanza (Ex Dipartimento di Economia e Statistica) in its series Working Papers with number 201112.
Length: 33 pages
Date of creation: Oct 2011
Date of revision:
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Postal: Università della Calabria, Dipartimento di Economia, Statistica e Finanza, Ponte Pietro Bucci, Cubo 0/C, I-87036 Arcavacata di Rende, CS, Italy
Phone: +39 0984 492413
Fax: +39 0984 492421
Web page: http://www.unical.it/portale/strutture/dipartimenti_240/disesf/
More information through EDIRC
Law-breaking behavior; Local economic development; Socio-economic factors; Cluster analysis; Time-series-cross-section data;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
- K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
- O1 - Economic Development, Technological Change, and Growth - - Economic Development
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-07 (All new papers)
- NEP-HME-2011-11-07 (Heterodox Microeconomics)
- NEP-LAW-2011-11-07 (Law & Economics)
- NEP-URE-2011-11-07 (Urban & Real Estate Economics)
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