Reducing Bias in Estimates for the Law of Crime Concentration

The law of crime concentration states that half of the cumulative crime in a city will occur within approximately 4% of the city's geography. The law is demonstrated by counting the number of incidents in each of N spatial areas (street segments or grid cells) and then computing a parameter bas...

Full description

Saved in:  
Bibliographic Details
Authors: Mohler, George (Author) ; Brantingham, P. Jeffrey 1970- (Author) ; Carter, Jeremy G. 1982- (Author) ; Short, Martin B. (Author)
Format: Electronic Article
Language:English
Published: 2019
In: Journal of quantitative criminology
Year: 2019, Volume: 35, Issue: 4, Pages: 747-765
Online Access: Presumably Free Access
Volltext (Resolving-System)
Journals Online & Print:
Drawer...
Check availability: HBZ Gateway
Keywords:
Poisson process
Negative binomial
Crime concentration
Crime hotspot
Gini index
CrimCrime concentration
Description
Summary:The law of crime concentration states that half of the cumulative crime in a city will occur within approximately 4% of the city's geography. The law is demonstrated by counting the number of incidents in each of N spatial areas (street segments or grid cells) and then computing a parameter based on the counts, such as a point estimate on the Lorenz curve or the Gini index. Here we show that estimators commonly used in the literature for these statistics are biased when the number of incidents is low (several thousand or less). Our objective is to significantly reduce bias in estimators for the law of crime concentration.
ISSN:1573-7799
DOI:10.1007/s10940-019-09404-1