Spatial Modeling and Analysis of the Determinants of Property Crime in Portugal

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Abstract

Many researchers have unraveled innovative ways of examining geographic information to better understand the determinants of crime, thus contributing to an improved understanding of the phenomenon. Property crimes represent more than half of the crimes reported in Portugal. This study investigates the spatial distribution of crimes against property in mainland Portugal with the primary goal of determining which demographic and socioeconomic factors may be associated with crime incidence in each municipality. For this purpose, Geographic Information System (GIS) tools were used to analyze spatial patterns, and different Poisson-based regression models were investigated, namely global models, local Geographically Weighted Poisson Regression (GWPR) models, and semi-parametric GWPR models. The GWPR model with eight independent variables outperformed the others. Its independent variables were the young resident population, retention and dropout rates in basic education, gross enrollment rate, conventional dwellings, Guaranteed Minimum Income and Social Integration Benefit, purchasing power per capita, unemployment rate, and foreign population. The model presents a better fit in the metropolitan areas of Lisbon and Porto and their neighboring municipalities. The association of each independent variable with crime varies significantly across municipalities. Consequently, these particularities should be considered in the design of policies to reduce the rate of property crimes.
Original languageEnglish
Article number731
Pages (from-to)1-18
Number of pages18
JournalISPRS International Journal of Geo-Information
Volume10
Issue number11
DOIs
Publication statusPublished - 1 Nov 2021

Keywords

  • Crime concentration and hot spot analysis
  • Spatial regression analysis
  • Geographic crime analysis
  • Geographically Weighted Poisson Regression
  • Spatial heterogeneity
  • Portugal

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