Crime in Lima: an approximation with district data
DOI:
https://doi.org/10.21754/iecos.v18i0.1182Keywords:
Crime, clusters, districtsAbstract
Lima suffers from a high crime rate, but one that is heterogeneously distributed throughout its districts. However, little is known about one of the basic questions regarding crime in the city: what causes crime among and across these districts? We constructed a data pool consisting of six years of data from the Encuesta Nacional de Programas Estratégicos (2010-2016) in order to obtain a representative sample for 35 districts in Lima (N=53,787). This allowed us to respond to the study’s two main objectives: (1) analyze the extent of the heterogeneity of crime (and its cau-ses) among Lima’s districts (cluster analysis) and (2) identify the drivers that cause certain districts to have higher crime rates than others (multilevel modeling). Results show that we should not treat Lima as a homogenous city in terms of crime rate. Rather, we found that the city’s districts could be classified into three groups (Latent Protection, Limited Protection and Permanent Defenselessness). We found that the theories of the origins of crime that we assessed in each group (social disorganization, routine activity theory, and social capital) differed in relation to the type of district. The policy implications of this research highlight the multicausality of crime, suggest improvements and assessments of police participation at the local level, as well as improving local management of economic incentives.
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