Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale

Quick, Matthew, Li, Guangquan and Brunton-Smith, Ian (2018) Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale. Journal of Criminal Justice, 58. pp. 22-32. ISSN 0047-2352

[img] Text
jcj-crimegeneral-final.pdf - Accepted Version
Restricted to Repository staff only until 5 July 2020.

Download (2MB) | Request a copy
Official URL: http://dx.doi.org/10.1016/j.jcrimjus.2018.06.003

Abstract

Purpose - To examine if, and how, spatial crime patterns are explained by one or more underlying crime-general patterns.

Methods - A set of Bayesian multivariate spatial models are applied to analyze burglary, robbery, vehicle crime, and violent crime at the small-area scale. The residual variability of each crime type is partitioned into shared and type-specific components after controlling for the effects of population density, deprivation, residential instability, and ethnic heterogeneity. Shared components account for the correlations between crime types and identify the crime-general patterns shared amongst multiple crimes.

Results - Two shared components are estimated to capture the crime-general pattern for all four crime types and the crime-general pattern for theft-related crimes (burglary, robbery, and vehicle crime). Robbery and violent crime exhibit the strongest positive associations with deprivation, instability, and ethnic heterogeneity. Shared components explain the largest proportions of variability for all crime types. Burglary, robbery, and vehicle crime each exhibit type-specific patterns that diverge from the crime-general patterns.

Conclusions - Crime-general patterns are important for understanding the spatial patterning of many crime types at the small-area scale. Multivariate spatial models provide a framework to directly quantify the correlation structures between crimes and reveal the underlying crime-general patterns shared amongst multiple crime types.

Item Type: Article
Uncontrolled Keywords: Spatial pattern, Crime-general, Correlation, Multivariate, Bayesian model, Shared component
Subjects: G300 Statistics
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 16 Jul 2018 14:58
Last Modified: 11 Oct 2019 17:05
URI: http://nrl.northumbria.ac.uk/id/eprint/35005

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics