A Spatial Analysis of Robbery Rate in the City of Detroit using Exploratory Data Analysis Approach (original) (raw)
Related papers
A spatial Analysis of Crime and Neighborhood Characteristics in Detroit Census Block Groups
Proceedings of the ICA
Crime has an inherent geographical quality and when a crime occurs, it happens within a particular space making spatiality essential component in crime studies. To prevent and respond to crimes, it is first essential to identify the factors that trigger crimes and then design policy and strategy based on each factor. This project investigates the spatial dimension of violent crime rates in the city of Detroit for 2019. Crime data were obtained from the City of Detroit Data Portal and demographic data relating to social disorganization theory were obtained from the Census Bureau. In the presence of spatial spill over and spatial dependence, the assumptions of classical statistics are violated, and Ordinary Least Squares estimations are inefficient in explaining spatial dimensions of crime. This paper uses explanatory variables relating to the social disorganization theory of crime and spatial autoregressive models to determine the predictors of violent crime in the City for the period. Using GeoDa 1.18 and ArcGIS Desktop 10.7.1 software package, Spatial Lag Models (SLM) and Spatial Error Models were carried out to determine which model has high performance in identifying predictors of violent crime.
Not ‘Islands, Entire of Themselves’: Exploring the Spatial Context of City-Level Robbery Rates
The current study examines spatial dependence in robbery rates for a sample of 1,056 cities with 25,000 or more residents over the 2000-2003 period. Although commonly considered in some macro-level research, spatial processes have not been examined in relation to city-level variation in robbery. The results of our regression analyses suggest that city robbery rates are not spatially independent. We find that spatial dependence is better accounted for by spatial error models than by spatial lag models. Further exploration of various spatial weights matrices indicates that robbery rates of cities within the same state are related to robbery rates of other cities within the same state, regardless of their proximity. Our analyses illustrate how systematic inquiry into spatial processes can alert researchers to important omitted variable biases and identify intriguing problems for future research.
Robust Spatial Analysis of Rare Crimes
2004
Research Goals and Objectives: The main goal of this project was to develop an analytical approach that will allow researchers to incorporate spatial error structures in mod els of rare crimes. In order to examine the causes of violence, researchers are frequently confronted with the need to apply spatial econometric methods to models with discrete out comes. Appropriate methods for doing so when the outcomes are measured at intracity areal units are lacking. The aim of this research was to fill that gap. This research effort developed and applied the framework to a realworld empirical problem. It examined the socioeconomic and demographic determinants of disaggregate homicide rates at two different intracity levels of areal aggregation and compared infer ences derived from several sets of models. The analysis was conducted on disaggregated homicide counts (198991) recorded in Chicago’s census tracts and neighborhood clusters using explanatory factors obtained from census so...
British Journal of Criminology, 2001
Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential for studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.
EXPLORATORY SPATIAL DATA ANALYSIS TECHNIQUES FOR EXAMINING URBAN CRIME
Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential for studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.
Statistical Analysis of Spatial Crime Data
Handbook of Quantitative Criminology, 2009
While the geography of crime has been a focal concern in criminology from the very start of the discipline, the development and use of statistical methods specifically designed for spatially referenced data has evolved more recently. This chapter gives an overview of the application of such methods in research on crime and criminal justice, and provides references to the general
The spatial patterning of county homicide rates: an application of exploratory spatial data analysis
1999
The possibility that homicides can spread from one geographic area to another has been entertained for some time by social scientists, yet systematic efforts to demonstrate the existence, or estimate the strength, of such a diffusion process are just beginning. This paper uses exploratory spatial data analysis (ESDA) to examine the distribution of homicides in 78 counties in, or around, the St. Louis metropolitan area for two time periods: a period of relatively stable homicide (1984)(1985)(1986)(1987)(1988)) and a period of generally increasing homicide (1988)(1989)(1990)(1991)(1992)(1993). The findings reveal that homicides are distributed nonrandomly, suggestive of positive spatial autocorrelation. Moreover, changes over time in the distribution of homicides suggest the possible diffusion of lethal violence out of one county containing a medium-sized city (Macon County) into two nearby counties (Morgan and Sangamon Counties) located to the west. Although traditional correlates of homicide do not account for its nonrandom spatial distribution across counties, we find some evidence that more affluent areas, or those more rural or agricultural areas, serve as barriers against the diffusion of homicides. The patterns of spatial distribution revealed through ESDA provide an empirical foundation for the specification of multivariate models which can provide formal tests for diffusion processes.
Spatial spillover effects and analysis of burglary crime
The aim of this paper is to address two critical but largely neglected issues in the spatial analysis of urban crime which are spatial spillover effects of crime penetrating neighborhood boundaries and non-stationarity regarding the relationships between contextual factors and neighborhood crime. We use a GIS-based spatial approach to normalize the estimate of burglary crime at block group level and use the geographically weighted regression (GWR) to investigate the correlates of neighborhood crime. Results suggest that the use of normalized measure of neighborhood crime helps better reveal the spatial patterns of burglary crime and the use of GWR accounts for the spatial variations of relationships between contextual factors and crime. In particular, the normalized measure of crime has implications for improving the measurement accuracy of the risk of crime across urban neighborhoods and can be applied to the spatial analysis of other socioeconomic issues such as housing foreclosures and environmental hazards which are also plagued by the spatial spillover issue when geographically contiguous data are analyzed.
2000
The new century brings with it growing interest in crime places. This interest spans theory from the perspective of understanding the etiol- ogy of crime, and practice from the perspective of developing effec- tive criminal justice interventions to reduce crime. We do not attempt a comprehensive treatment of the substantial body of theoretical and empirical research on place and crime