Spatial and temporal dynamics of neighborhoods and crime

George M Kikuchi, Purdue University

Abstract

The importance of neighborhoods and places in understanding crime has been widely noted in criminology. Using various units of analysis (e.g., states, counties, cities, neighborhoods, places), studies have found that crime tends to be spatially concentrated. Based on social disorganization theory and routine activities theory, relationships between the level of crime and various neighborhood characteristics have been noted in the literature. Reviews of the existing literature, however, have identified several limitations of neighborhood level studies of crime. First, many neighborhood level studies have utilized cross-sectional samples and failed to analyze temporal dynamics between neighborhood changes and crime. Second, until recently, criminological studies paid little attention to two spatial processes, spatial dependency and spatial heterogeneity, in developing spatial regression models. Third, most studies examined only places and neighborhoods where crimes were committed and failed to account for where offenders were coming from. By integrating newly developed statistical methods from interdisciplinary fields with social disorganization theory and routine activities theory, this dissertation pursued a series of research questions that examine the spatial and temporal dynamics of crime at the neighborhood level. First, a longitudinal analysis of crime between 1960 and 2005 in Seattle, WA, indicated that neighborhood crime rate trajectories were characterized by quadratic functions, although there was considerable variability in both the initial level of crime and rate of change over time. The results indicated that neighborhood characteristics based on social disorganization theory and routine activities theory were important in explaining the variability in crime rate trajectories. In particular, social disorganization predicted changes in crime rates decades later, while the level of crime also changed depending on time specific opportunities for crime. For example, racial heterogeneity and residential mobility predicted the initial level of crime in 1960, while the linear rate of change was predicted by socio-economic disadvantage. Furthermore, an increase in the percentage of employed women was related with high levels of burglary and auto theft, while an increase in the percentage of public transportation users increased robbery at each time point. Second, an analysis of spatial effects indicated the importance of considering both spatial dependency and spatial heterogeneity when examining the association between neighborhood characteristics and crime. In particular, although global regression models produce a single measure of association between an independent variable and a dependent variable that applies to a whole study area, the results indicated there was considerable variability in the local patterns of association between neighborhood characteristics and the level of crime. For example, the results indicated that the effects of racial heterogeneity on the level of crime varied in strength and direction across space. That is, although social disorganization theory predicts that racial heterogeneity hinders the realization of common goals among residents and increases crime, the results indicated racial heterogeneity may actually reduce crime in some neighborhoods. Variability in local patterns of association are important in further understanding social processes linking the structural characteristics of neighborhoods to the level of crime and developing place-focused crime prevention strategies. Third, an analysis of burglars’ target selection indicated that neighborhood characteristics were highly predictive of which neighborhoods burglars target. In particular, it was found that the likelihood of burglars selecting a neighborhood for the commission of their crimes increased as criminal opportunities for crime increased (e.g., weakened household guardianship due to high employment). Furthermore, the analysis also indicated that burglars’ target selection varied by burglars’ characteristics, such as age, race, and the presence of co-offenders. For example, burglars’ target selection was strongly affected by their race and the racial composition of the target neighborhood. Furthermore, younger offenders’ target selection was strongly influenced by distance from their residence to a target neighborhood, while, in addition to distance, various neighborhood characteristics also affected older offenders’ target selection. Overall, the three studies conducted in this dissertation found support for both social disorganization theory and routine activities theory in explaining crime at the neighborhood level. By empirically studying the spatial and temporal aspects of crime at the neighborhood level, this dissertation adds to existing research on the role that neighborhood characteristics play in producing crime-conducive environments.

Degree

Ph.D.

Advisors

Desmond, Purdue University.

Subject Area

Criminology

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