Crime in a planned city: The case of Brasília

Faria, Jo�ão Ricardo; Ogura, Laudo M.; Sachsida, Adolfo

doi:10.1016/j.cities.2013.03.002

Cited by 14 publications

(15 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Population density was negatively correlated with both crime risks. The clear association between population density and crime found in the present study is in accordance with other studies showing that residential density can lower crime rates [26,27]. This may be due to the closer and easier street monitoring possible when there is a larger population density [30].…”

Section: Discussionsupporting

confidence: 93%

“…Policing did not have a clear association with both types of crime. This is not in line with Faria et al [27], who found that there was a positive relation between policing and burglaries. Nevertheless, our results are not entirely unexpected.…”

Section: Discussioncontrasting

confidence: 54%

“…This may influence the risk estimations and bias the assessment of contextual influences on crime risks in ecological crime studies as indicated by recent research [66][67][68][69]. Third, the measures used to represent socioeconomic status (i.e., the unemployment rate and percentage of highly educated) may not be powerful enough, as other related variables, such as average household income [27], percentage of individuals below the poverty line [70] and percentage of high occupational status [14], were not included. In addition, socioeconomic status is only one indicator of social disorganization.…”

Section: Discussionmentioning

confidence: 99%

“…It was included to control for differences in neighborhood sizes and populations [26,27]. It is generally believed that a larger population density usually leads to a higher crime rate [28,29].…”

Section: Datamentioning

confidence: 99%

“…Policing rooms are set up by local police stations and staffed by several police officers to guarantee neighborhood's security. The relationship between policing and crime has been investigated in previous studies [15,27].…”

Section: Datamentioning

confidence: 99%

See 4 more Smart Citations

Joint Modeling of Multiple Crimes: A Bayesian Spatial Approach

Liu

Zhu

2017

IJGI

View full text Add to dashboard Cite

A multivariate Bayesian spatial modeling approach was used to jointly model the counts of two types of crime, i.e., burglary and non-motor vehicle theft, and explore the geographic pattern of crime risks and relevant risk factors. In contrast to the univariate model, which assumes independence across outcomes, the multivariate approach takes into account potential correlations between crimes. Six independent variables are included in the model as potential risk factors. In order to fully present this method, both the multivariate model and its univariate counterpart are examined. We fitted the two models to the data and assessed them using the deviance information criterion. A comparison of the results from the two models indicates that the multivariate model was superior to the univariate model. Our results show that population density and bar density are clearly associated with both burglary and non-motor vehicle theft risks and indicate a close relationship between these two types of crime. The posterior means and 2.5% percentile of type-specific crime risks estimated by the multivariate model were mapped to uncover the geographic patterns. The implications, limitations and future work of the study are discussed in the concluding section.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Discussioncontrasting

confidence: 54%

Section: Discussionmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

See 3 more Smart Citations

Joint Modeling of Multiple Crimes: A Bayesian Spatial Approach

Liu

Zhu

2017

IJGI

View full text Add to dashboard Cite

show abstract

Violence and Local Development in Fortaleza, Brazil: A Spatial Regression Analysis

Oliveira

Medeiros

Carvalho

2017

Appl. Spatial Analysis

View full text Add to dashboard Cite

Fortaleza is the fifth largest city of Brazil, and has become the most violent state capital in the last years. In this paper, we investigate whether violent crime rates are associated with the local development of the city. Using an unexplored data source about georeferenced murders and deaths due to bodily injury and theft, we show that violent crime rates exhibit a positive spatial dependence across clusters of census tracts. In other words, small urban areas with high (low) violent crime rates have neighbors, on average, with similar pattern of violent crime rates. Investigating the relationship between violent crime rates and variables associated with local development, spatial regressions suggest that high violent crime rates are related with low-income neighborhood, with high spatial isolation of poor households, low access to urban infrastructure, and high prevalence of illiterate adolescents and young black males. The study also provides important evidence about spillover effects that helps to understand how the absence of local development can expose neighbors to violence.

show abstract