Exploratory Spatial Data Approach to Identify the Context of Unemployment-Crime Linkages in Virginia, 1995-2000 (ICPSR 4546)
This research is an exploration of a spatial approach to identify the contexts of unemployment-crime relationships at the county level. Using Exploratory Spatial Data Analysis (ESDA) techniques, the study explored the relationship between unemployment and property crimes (burglary, larceny, motor vehicle theft, and robbery) in Virginia from 1995 to 2000. Unemployment rates were obtained from the Department of Labor, while crime rates were obtained from the Federal Bureau of Investigation's Uniform Crime Reports. Demographic variables are included, and a resource deprivation scale was created by combining measures of logged median family income, percentage of families living below the poverty line, and percentage of African American residents.
The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.
Sridharan, Sanjeev, and Jon'a Meyer. Exploratory Spatial Data Approach to Identify the Context of Unemployment-Crime Linkages in Virginia, 1995-2000. ICPSR04546-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2006-08-31. http://doi.org/10.3886/ICPSR04546.v1
Persistent URL: http://doi.org/10.3886/ICPSR04546.v1
This study was funded by:
- United States Department of Justice. Office of Justice Programs. National Institute of Justice (2002-IJ-CX-0010)
Scope of Study
The files are provided in a WinZip archive with 12 files in three folders. The Statistical Data Files folder provides the data in Microsoft Excel files. The Geographic Data Files folder provides the geographic files for use with mapping software. The Report Files folder provides the final report, the cover for the final report, and two lists of measures.
Study Purpose: The purpose of this research was to develop and implement an exploratory spatial approach to identifying the contexts of unemployment-crime (U-C) relationships, focusing on the utility of the Exploratory Spatial Data Analysis (ESDA) in finding the county level contexts of U-C linkages.
Study Design: Exploratory Spatial Data Analysis (ESDA) techniques were used to study both the global and the local context of unemployment rates, index crimes, and resource deprivation. Annual data on unemployment rates were obtained from the United States Department of Labor's Bureau of Labor Statistics Web site for the years 1995 through 2000. Information on reported crime rates was obtained from the Geospatial and Statistical Data Center of the University of Virginia from data collected by the United States Department of Justice and the Federal Bureau of Investigation (Uniform Crime Reports). The study focused on crimes classified as property crimes under the Uniform Crime Reports (burglary, larceny, motor vehicle theft, and robbery) and on total index crimes. The Crime Index total is the sum of selected serious offenses including murder and non-negligent manslaughter, rape, robbery, aggravated assault, and the three property crimes, and was included in the study because reporting rates are most valid for index crimes. Finally, information on both age distributions and measures used in the resource deprivation scale were obtained from the county-level census files of the Geospatial and Statistical Data Center at the University of Virginia. The resource deprivation scale was created from 1990 Census data combining the following measures: logged median family income, percentage of families living below the poverty line, and percentage of African American residents.
Unemployment data were obtained from the United States Department of Labor's Bureau of Labor Statistics Web site. Reported crime rates data were obtained from the United States Department of Justice and the Federal Bureau of Investigation's Uniform Crime Reports. Age distributions and measures used in the resource deprivation scale were obtained from the Geospatial and Statistical Data Center at the University of Virginia.
Description of Variables: The data include the Federal Information Processing Standards (FIPS) county codes for the state of Virginia, the name of county or city, and region variable to indicate if the county is in the western, northern, or eastern region of the state. Crime rate variables include burglary crime rates, larceny crime rates, motor vehicle theft crimes rates, robbery crime rates, and the index crime rates. Four measures of unemployment are provided: unemployment rates, lagged unemployment rates, the average unemployment rates from 1995 to 2000, and the average unemployment rates from 1994 to 2000. Demographic variables included in the data are the number of males per 100 females, 1990, the percent of the population by age, 1990, and the Resource Deprivation Affluence Component scale.
Original ICPSR Release: 2006-08-31
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