Criminal justice researchers and crime geographers have long recognized the importance of understanding where crimes happen as well as to whom and by whom. Although past research often focused on violent crimes, calls for research into non-lethal white-collar crimes emerged in the 1970s. Today, identity theft is among the fastest growing white-collar crimes in the United States, although official recognition of it as a criminal act is a relatively recent development. Remaining largely unmet, the need for white-collar crime research has greatly intensified considering the escalating identity theft problem. Furthermore, many studies conclude that identity theft will continue to rise due to increasing technology-driven offenses via the Internet and widespread use of digital consumer databases. Utilizing theoretical framework established in crime geography, GIS mapping and spatial statistics are employed to produce a spatial analysis of identity theft in the U.S. from 2002-2006. Distinct regional variations, such as high rates in the western and southwestern states, and low rates in New England and the central plains states, are identified for identity theft as reported by the FTC. Significant spatial patterns of identity theft victims alongside social demographic variables are also revealed in order to better understand the regional patterns that may indicate underlying social indicators contributing to identity theft. Potential social variables, such as race/ethnicity and urban-rural populations, are shown to have similar patterns that may be directly associated with U.S. identity theft victims. To date, no in-depth geographic studies exist on the geographic patterns of identity theft, although numerous existing studies attempt basic spatial pattern recognition and propose the need for better spatial interpretation. This thesis is the first empirical study on the geographies of identity theft. It fills in a void in the literature by revealing significant geographical patterns of identity theft in the digital age, attempts at understanding the social factors driving the patterns, and examines some of the social implications of identity theft.

Many tools exist to assist law enforcement agencies in mitigating criminal activity. For centuries, academics used statistics in the study of crime and criminals, and more recently, police departments make use of spatial statistics and geographic information systems in that pursuit. Clustering and hot spot methods of analysis are popular in this application for their relative simplicity of interpretation and ease of process. With recent advancements in geospatial technology, it is easier than ever to publicly share data through visual communication tools like web applications and dashboards. Sharing data and results of analyses boosts transparency and the public image of police agencies, an image important to maintaining public trust in law enforcement and active participation in community safety.