Income inequality and the geography of residential burglaries: A spatial model applied to Campinas, Brazil

Ramos, Rafael G.; Melo, Silas Nogueira de

doi:10.1016/j.apgeog.2022.102787

Cited by 4 publications

(4 citation statements)

References 49 publications

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“…However, economic deprivation positively influenced both house and store burglary risks. This agrees with the inference of Johnson and Bowers (2010) that high levels of economic disadvantage and social disorganization are more prone to criminal activities, Ramos and Melo (2022), also submitted that there is a positive relationship between economic deprivation and burglary risks and alluded that areas with a larger proportion of economically deprived residents may have limited access to legitimate economic opportunities, leading to increased involvement in illegal activities such as burglary. Additionally, population density showed a negative association with both crime types, indicating that higher population density led to reduced burglary risks.…”

Section: Discussionsupporting

confidence: 89%

“…Additionally, Ramos and Melo (2022) investigated the connection between income inequality and the geographic distribution of residential burglaries in Campinas, Brazil, and discovered a statistically significant positive correlation between the two. Their finding suggests that neighborhoods with higher income inequality are more likely to experience burglaries.…”

Section: Introductionmentioning

confidence: 99%

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Spatial Heterogeneity Modeling of the Neighbourhood Effects and Socio-economic Factors on Burglary Crimes in Nigeria

Adeyemi,

Ibrahim,

Olumoh

2024

Preprint

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This paper examines the geographical patterns of distribution in burglary crimes (residential and nonresidential) in Nigeria for the incidence year 2017. Our novel approach integrates spatial structures into the traditional regression framework and evaluates the spatial disparities in neighborhood effects and the socio-economic characteristics of burglary crimes at sub-national levels. The study proposed four spatially varying models to demonstrate the importance of incorporating spatial dependence components in the models. The determinant factors included in the model are; the unemployment rate, education index, and poverty indices, alongside demographic variables, to understand crime patterns. A Bayesian analysis was performed via Markov chain Monte Carlo simulations to estimate the model parameters. The analysis revealed that the proportional contribution due to neighborhood (clustering) effect was estimated as 24.7% for the house-breaking and the estimated neighborhood contribution as 29.0% for the store-breaking occurrence. This approach demonstrates superiority in model performance, as indicated by the lowest Deviance Information Criterion. Findings reveal negative associations between burglary and multi-dimensional poverty, while young male adults show a positive relationship with store-breaking incidents. Hot spot areas and spatial variations in crime patterns are identified, offering insights for criminologists and informing policing strategies for effective crime prevention.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Spatial Heterogeneity Modeling of the Neighbourhood Effects and Socio-economic Factors on Burglary Crimes in Nigeria

Adeyemi,

Ibrahim,

Olumoh

2024

Preprint

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“…Thus, publicly available crime data are typically crime records posted on police departments' official websites, recording the location, time, and other attributes of each case. Crime point sets released by national police departments have been widely used in crime research [21][22][23][24][25][26]. For example, UCR (uniform crime reporting) has been applied to the study of the spatiotemporal evolution and prediction of crime [27][28][29].…”

Section: Crime Data Characteristicsmentioning

confidence: 99%

Construction and Analysis of Space–Time Paths for Moving Polygon Objects Based on Time Geography: A Case Study of Crime Events in the City of London

Yin

Chen

Ying

2023

IJGI

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Time geography considers that the motion of moving objects can be expressed using space–time paths. The existing time geography methods construct space-time paths using discrete trajectory points of a moving point object to characterize its motion patterns. However, these methods are not suitable for moving polygon objects distributed by point sets. In this study, we took a type of crime event as the moving object and extracted its representative point at each moment, using the median center to downscale the polygon objects distributed by the point sets into point objects with timestamps. On this basis, space–time paths were generated by connecting the representative points at adjacent moments to extend the application scope of space–time paths, representing the motion feature from point objects to polygon objects. For the case of the City of London, we constructed a space–time path containing 13 nodes for each crime type (n = 14). Then, each edge of the space–time paths was considered as a monthly vector, which was analyzed statistically from two dimensions of direction and norm, respectively. The results showed that crime events mainly shifted to the east and west, and crime displacement was the greatest in April. Therefore, space–time paths as proposed in this study can characterize spatiotemporal trends of polygon objects (e.g., crime events) distributed by point sets, and police can achieve improved success by implementing targeted crime prevention measures according to the spatiotemporal characteristics of different crime types.

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“…This can be explained by the economic law of diminishing marginal propensity of consumption (Wan et al, 2022). Income inequality is often regarded as an important cause of crimes (Choe, 2008;Enamorado et al, 2016;Ramos & Melo, 2022). Moreover, evidence shows that income inequality is also associated with health problems of the poor, such as heart failure (Dewan et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

On the Accessibility of Financial Services and Income Inequality: An International Perspective

Liu

2023

Technological and Economic Development of Economy

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Income inequality has long been an important issue in development economics. Applying international data from 119 countries between 2004 and 2018, this study discusses the relationship between the accessibility of financial services and income inequality. Using the density of the bank branch network to represent the accessibility of financial services, we discover that income inequality is negatively related to the accessibility of financial services, especially in less developed countries and regions. In this nexus, the poverty ratio serves as an intermediary variable. The significance of the nexus is weaker in countries where fintech is more popularized, indicating the substitution effect between fintech and traditional banking services. Nevertheless, the substitution effect is limited, and bank branches will keep playing an important role in delivering financial services. For countries with inadequate banking services, bank branches should be increased to encourage residents to participate in the financial system, while it is no longer necessary to add a large number of branches in countries where fintech has been popularized. Faced with the trend of financial digitalization and the economic shock caused by the COVID-19 pandemic, banks should launch more online services and increase intelligent machines in the branches. By doing so, financial services are more resilient to social changes, so as to alleviate the inequality of income distribution in the long term.

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Income inequality and the geography of residential burglaries: A spatial model applied to Campinas, Brazil

Cited by 4 publications

References 49 publications

Spatial Heterogeneity Modeling of the Neighbourhood Effects and Socio-economic Factors on Burglary Crimes in Nigeria

Spatial Heterogeneity Modeling of the Neighbourhood Effects and Socio-economic Factors on Burglary Crimes in Nigeria

Construction and Analysis of Space–Time Paths for Moving Polygon Objects Based on Time Geography: A Case Study of Crime Events in the City of London

On the Accessibility of Financial Services and Income Inequality: An International Perspective

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