Establishing the statistical relationship between population size and UCR crime rate: Its impact and implications

Nolan, James J.

doi:10.1016/j.jcrimjus.2004.08.002

Cited by 61 publications

(39 citation statements)

References 17 publications

(14 reference statements)

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“…Consistent with our hypothesis (Hypothesis 5), the population exhibits a significant relationship with the homicide rate, which means that the higher the urbanism of a city (measured by population size), the higher the homicide rate in that city. This result concurs with Nolan () and Ellen and O'Regan () who demonstrated that the relationship between crime rate and population size is positive and significant in the cities, indicating that the higher populated cities reported the higher crime rates.…”

Section: Resultssupporting

confidence: 91%

“…Population size should promote criminality from different approaches: (i) the social control perspective , where urbanisation and population growth weaken informal mechanism of social control which, generate more crime and delinquency; (ii) the structuralist perspective , where population size promotes various social interactions, including criminal victimisations; (iii) the subcultural perspective , which suggests that more populous urban areas are expected to generate more criminal activity than less populous ones (Blau, ; Tittle, ; Fischer, ; Chamlin and Chochran, ). Therefore, urbanisation, population size, higher population density and changes in the area's economic conditions and lifestyles could generate a higher homicide rate (Nolan, ).…”

Section: Literature Reviewmentioning

confidence: 99%

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

Poveda

2012

J of Intl Development

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This paper studies the socio‐economic determinants of violence in the seven most important cities in Colombia. Derived from theories rooted in classic works, including Becker's paradigm, criminal inertia, social disorganisation, urbanism and strain, we formulate several hypotheses on the socio‐economic determinants of violence. To test these hypotheses, a dynamic panel data analysis is employed. The analysis shows that cities’ deprivation and high population density are strong predictors of homicide rates. Comparing the results among Colombian cities, we find support indicating that city‐level homicide rates are influenced by the city's level of development. Moreover, we find evidence that economic growth, inequality, poverty and human capital influence violence in the cities studied, which could generate negative effects on the economic and social development of Colombia. Copyright © 2012 John Wiley & Sons, Ltd.

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Section: Resultssupporting

confidence: 91%

Section: Literature Reviewmentioning

confidence: 99%

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

Poveda

2012

J of Intl Development

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“…In Nagykanizsa the city center had the highest number of crime incidents, whereas it was marked often as safe, of which a possible explanation could be the relatively high awareness of the area and the relatively high density of (dayor night-time) population. It assumes that crime frequency (at least certain forms of it) is in connection with population density [55], however, positive perception of places, as a result of nice, ordered and tidy neighborhood, may overwrite the feelings of safety. This assumption, though, should be tested by involving new datasets.…”

Section: Discussionmentioning

confidence: 99%

GIS-Based Statistical Analysis of Detecting Fear of Crime with Digital Sketch Maps: A Hungarian Multicity Study

Jakobi

Pődör

2020

IJGI

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This study evaluates fear of crime perception and official crime statistics in a spatial context, by applying digital sketch maps and statistical GIS methods. The study aims to determine explanatory motives of fear of crime by comparing results of selected large, medium and small sized Hungarian cities. Fear of crime information of residents were collected by using a web application, which gave the possibility to mark regions on a map, where respondents have a sense of safety or feel fear. These digital sketch maps were processed by GIS tools, and were converted to grid data, in order to calculate comparable explanatory variables for fear of crime analysis. The grid-based normalised model reflected some similarities and differences between the observed cities. According to the outcomes, examples were found both in coincidences and opposite correlations of crime statistics and perception of unsafe places, highlighting the importance of locality in fear of crime research. Additionally, the results mirrored that the size of the city or the respondent's sex does not significantly influence the overall judgment of places, rather the absolute number of safe markings and the local number of registered crime events could affect local results.Although numerous studies have proved that various spatial factors can trigger fear of crime, the fact is that crime rates in certain areas are not necessarily as high as expected [16,17], consequently, additional explanatory factors should be considered as well. Doran and Lees [18], for example, found relationship between fear of crime and physical disorder. Later, Doran and Burgess [3] proved that the environment in general plays an important role in fear of crime. It was recently shown that even improvements in the environment can have a positive effect on reducing fear of crime [19]. Furthermore, a large amount of studies confirmed that fears of crime are concentrated in areas, which can be described by definite environmental characteristics. For example Lederer and Leitner [20] concluded that fear of being a victim of burglary can be assigned to well-defined geographical hot spots, as well as it is connected with definite statistical features and even with areas having less technical protection.A typical problem of mapping fear of crime, though, is the lack of data on location perceptions. In many countries police have not completed any survey on this topic, therefore, their own data surveys should be made to accumulate information from, e.g., questionnaires [21] or from digital sketch maps, which would conceivably quantify-in a specific way-the level and the area of fear of crime within a city [22][23][24][25][26]. Additionally, several contemporary research papers on fear of crime apply modern IT technologies to draw a more precise picture of the issue. For example Solymosi et al. [27] developed a FOCA application (fear of crime application), which investigates fear of crime as a dynamic phenomenon by tracing the participants' activities, and in this way, the avoidance of ce...

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“…The larger the city, the larger its population, and the likelihood of crimes occurrence could expand. In general, urbanization and growth of the population (associated with the growth of cities) are highly correlated with the volume of crime [11,50].…”

Section: Discussionmentioning

confidence: 99%

Types of Crime, Poverty, Population Density and Presence of Police in the Metropolitan District of Quito

Cabrera-Barona

Jiménez

Melo

2019

IJGI

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This exploratory study identifies spatial patterns of crimes and their associations with the index of Unsatisfied Basic Needs (UBN), with Communitarian Policy Units (CPU) density, as well as with population density. The case study is the Metropolitan District of Quito. Correlation analyses were applied between number of registers of each type of crime, and the UBN index, CPU density and population density measures. The spatial autocorrelation index of Getis-Ord Gi* was calculated to identify hotspots of the different types of crime. Ordinary least squares regressions and geographically weighted regressions considering types of crime as dependent variables, were calculated. Larceny and robbery were found to be the predominant crimes in the study area. An inverse relationship between the UBN index and number of crimes was identified for each type of crime, while positive relationships were found between crimes and CPU density, and between crimes and population density. Significant hotspots of fraud, homicide, larceny, murder, rape and robbery were found in all urban parishes. Additionally, crime hotspots were identified in eastern rural parishes adjacent to urban parishes. This study provides important implications for crime prevention in the Metropolitan District of Quito (MDQ), and the obtained results contribute to the ecology of crime research in the study area.

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Establishing the statistical relationship between population size and UCR crime rate: Its impact and implications

Cited by 61 publications

References 17 publications

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

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

GIS-Based Statistical Analysis of Detecting Fear of Crime with Digital Sketch Maps: A Hungarian Multicity Study

Types of Crime, Poverty, Population Density and Presence of Police in the Metropolitan District of Quito

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