Violence and Economic Development in Colombian Cities: A Dynamic Panel Data Analysis

Poveda, Alexander Cotte

doi:10.1002/jid.2819

Cited by 82 publications

(19 citation statements)

References 63 publications

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“…The fact that the predominance of urban homicides in young men coincides with the slowdown in the reduction of homicides at the end of the period cannot be underestimated. In fact, it has been found that economic growth, inequality, poverty, and human capital, as well as different levels of development, also influence the levels of urban violence in Colombia [48].…”

Section: Discussionmentioning

confidence: 99%

“…According to this study's findings, it is important to prioritize a greater understanding of urban youth violence in Colombia by gathering more evidence and reviewing and updating the time series on the subject in the country [48–55]. It is also important to emphasize that strategies which have been shown to be effective in reducing homicides in localized areas of large cities [55–58] should be more widely studied and implemented.…”

Section: Discussionmentioning

confidence: 99%

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Trends of Rural/Urban Homicide in Colombia, 1992-2015: Internal Armed Conflict and Hints for Postconflict

Vallejo

Tapias

Arroyave

2018

BioMed Research International

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Objective. To analyze the relationship between rural and urban homicide rates in Colombia between 1992 and 2015 and the fluctuations in these rates. Methods. Individual records of homicides and population aggregates in men and women aged 15-64 years were used. The adjusted rates of annual homicides were calculated for urban/rural areas and standardized by age. Rate Ratios (RRs) adjusted by region were calculated. A joinpoint analysis was performed to identify inflection points and the Annual Percentage Change (APC). Results. Four joinpoints were identified in rural and urban rates: after peaking in 1992, homicide rates fell until 1997, and then increased until 2002. From this point on there was a continuous reduction until 2015, although this reduction slowed down from 2005 onward. During almost the whole period, the rates of rural homicides were higher than those of urban homicides, although they equalized at the end of the period. Conclusions. Unlike in other countries, during the study period Colombian homicide rates, which coincided with the dynamics of the armed conflict, were higher in rural than in urban areas. In recent years, a predominance of urban homicides committed by younger men has been identified, which could pose a challenge to postconflict in Colombia.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Trends of Rural/Urban Homicide in Colombia, 1992-2015: Internal Armed Conflict and Hints for Postconflict

Vallejo

Tapias

Arroyave

2018

BioMed Research International

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“…Early studies in criminology have tried to demonstrate the relationship between crime and various influencing factors such as demographics [ 1 ], economics [ 10 , 14 , 22 ], and unemployment [ 12 , 13 , 15 ]. Even recently, these studies are being continued to demonstrate relationships between crime and various influencing factors.…”

Section: Related Workmentioning

confidence: 99%

Prediction of crime occurrence from multi-modal data using deep learning

Kang

2017

PLoS ONE

176

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In recent years, various studies have been conducted on the prediction of crime occurrences. This predictive capability is intended to assist in crime prevention by facilitating effective implementation of police patrols. Previous studies have used data from multiple domains such as demographics, economics, and education. Their prediction models treat data from different domains equally. These methods have problems in crime occurrence prediction, such as difficulty in discovering highly nonlinear relationships, redundancies, and dependencies between multiple datasets. In order to enhance crime prediction models, we consider environmental context information, such as broken windows theory and crime prevention through environmental design. In this paper, we propose a feature-level data fusion method with environmental context based on a deep neural network (DNN). Our dataset consists of data collected from various online databases of crime statistics, demographic and meteorological data, and images in Chicago, Illinois. Prior to generating training data, we select crime-related data by conducting statistical analyses. Finally, we train our DNN, which consists of the following four kinds of layers: spatial, temporal, environmental context, and joint feature representation layers. Coupled with crucial data extracted from various domains, our fusion DNN is a product of an efficient decision-making process that statistically analyzes data redundancy. Experimental performance results show that our DNN model is more accurate in predicting crime occurrence than other prediction models.

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“…(FAJNZYLBER;LEDERMAN;LOAYZA, 2000). Poveda (2012) estudou os determinantes socioeconômicos da violência, nas sete cidades mais importantes da Colômbia, com dados de painel, entre 1984 e 2006. Ressalta-se que a hipótese inicial foi de que o nível de desenvolvimento das cidades e a alta densidade populacional eram fortes preditores de taxas de homicídio.…”

Section: Revisão De Literaturaunclassified