Uniform Crime Reports: Monthly Weapon-Specific Crime and Arrest Time Series, 1975-1993 [National, State, and 12-City Data] (ICPSR 6792)

Time Period(s) View help for Time Period(s)

Date of Collection View help for Date of Collection

Data Collection Notes View help for Data Collection Notes

Study Purpose View help for Study Purpose

These data were prepared in conjunction with a project using Bureau of Labor Statistics data (not provided with this collection) and the Federal Bureau of Investigation's Uniform Crime Reporting (UCR) Program data to examine the relationship between unemployment and violent crime. Past research on the relationship between unemployment and crime using national, annual, United States time-series data had produced results that were contrary to theoretical expectations, particularly for violent crime rates. One hypothesized reason for the anomalous findings in these studies was that the data used in past investigations of the unemployment-crime relationship were aggregated across space, time, types of weapons used, and unemployment across race/sex/age groups in such a way that differences in the relationship across units that were aggregated canceled out to produce misleading results. This research project explored this hypothesis by disaggregating the analysis of unemployment and violent crime in four ways. First, monthly and quarterly averaged time-series data were used to allow direct examination of seasonal effects on crime rate trends, to test whether violent crime rates respond to increases in unemployment immediately or only after some time has elapsed, and to reveal any bias due to time aggregation. Second, weapon-specific data were used to show what, if any, differences exist in the relationship between violent crime and unemployment by type of weapon used. Of particular interest was the relationship of unemployment and the use of firearms in robbery and aggravated assault. If economic distress in the form of unemployment affects weapon-specific forms of violence differently, these variations may cancel each other out and produce null results when only total rates are examined. Third, to examine the possibility of a spatial aggregation bias, the present study prepared monthly weapon-specific violent crime data for the nation as a whole, for the 50 states and the District of Columbia, and for 12 selected cities. The national-level data served as the benchmark for assessing the impact of spatial aggregation. Fourth, unemployment data were disaggregated by race (white and non-white), sex (for males only), and age using the most crime-prone years of 16-19, 20-24, and 25-34. These unemployment data were selected to test the proposition that economic distress among younger Black men is most likely to produce increases in violent crime rates. Models were also estimated for white males in the same age group.

Study Design View help for Study Design

Three separate time-series data files were created as part of this project: a national time series, a state time series, and a time series of data for 12 selected cities: Baltimore, Buffalo, Chicago, Columbus, Detroit, Houston, Los Angeles, Newark, New York City, Paterson (New Jersey), and Philadelphia. Each time-series data file was constructed to include 82 monthly time series: 26 series containing the number of Part I (crime index) offenses known to police (excluding arson) by weapon used, 26 series of the number of offenses cleared by arrest or other exceptional means by weapon used in the offense, 26 series of the number of offenses cleared by arrest or other exceptional means for persons under 18 years of age by weapon used in the offense, a population estimate series, and three date indicator series. For the state file, the population estimate is equal to the sum of the three population estimates provided for each agency in the UCR annual data file aggregated by state. Creation of each time-series file began with aggregating the agency-level data in each UCR annual data file to the appropriate level using the SPSS AGGREGATE procedure. For the national and state data, agencies from the 50 states and Washington, DC, were included in the aggregated data file if they reported at least one month of information during the year. In addition, agencies that did not report their own data (and thus had no monthly observations on crime or arrests) were included to make the aggregated population estimate as close to Census estimates as possible. For the city time series, law enforcement agencies with jurisdiction over the 12 central cities were identified and the monthly data were extracted from each UCR annual file for each of the 12 agencies. The above procedures, performed for each time series file, produced files containing one record for the national file, 51 records for the state file, and 12 records for the city file, each with 937 observations per record comprised of the 12 monthly observations for each of the 78 weapon-specific crime and arrest variables, and an annual population estimate. The state file also included a numeric state identifier and the city file a numeric city identifier. To convert to time series, 12 population variables were created, each equal to the annual aggregated estimate from the UCR data, and then the data were written to ASCII files in the 12F12 format. For each file, the resulting data matrix had 12 columns containing the population variables with each row containing the 12 monthly observations of a weapon-specific crime or arrest variable. The matrix for the national, state, and city files had 79 rows, 4,080 rows, and 960 rows, respectively. Each data matrix was transposed, the SPSS date variables (year_, month_, and date_) were added to the new data matrix, and the file was saved as an SPSS save file. Once the monthly time series had been extracted from each of the 19 annual tapes, the 19 SPSS save files were sequentially concatenated using the SPSS MERGE FILES/ADD CASES procedure. The final national time-series file contains 82 time series, the state file contains 4,083 time series, and the city file contains 963 time series, each with 228 monthly observations per time series. The total number of aggravated assaults was calculated by subtracting the number of simple nonaggravated assaults from the total number of assaults. From the national file, the annual crime rates for the seven index offenses were computed using the aggregated UCR file and compared to the annual rates published each year in "Crime in the United States" by the Federal Bureau of Investigation. With the exception of robbery, the majority of the crime rates calculated with the aggregated data were lower than the published figures. However, less than 10 percent of the rates based on the aggregated UCR data differed from the annual FBI figures by more than 5 percent.

Sample View help for Sample

The national and state data include crime and arrest information from all 50 states and the District of Columbia. The selection of cities was based on policy-relevant similarities and differences. Factors included: (1) an increase in the city's poverty rate during the 1970s, (2) a change in the concentration of African-Americans residing in the city limits, (3) differences in the political-economic experiences, (4) robbery and aggravated assault rates that were substantially above the national levels, and (5) differences in the states' handgun control policies.

Universe View help for Universe

All crimes and arrests in the United States from 1975-1993.

Unit(s) of Observation View help for Unit(s) of Observation

Data Source View help for Data Source

Data Type(s) View help for Data Type(s)

Description of Variables View help for Description of Variables

Monthly crime and clearance totals are provided for homicide, negligent manslaughter, total rape, forcible rape, attempted forcible rape, total robbery, firearm robbery, knife/cutting instrument robbery, other dangerous weapon robbery, strong-arm robbery, total assault, firearm assault, knife/cutting instrument assault, other dangerous weapon assault, simple nonaggravated assault, assaults with hands/fists/feet, total burglary, burglary with forcible entry, unlawful entry-no force, attempted forcible entry, larceny-theft, motor vehicle theft, auto theft, truck and bus theft, other vehicle theft, and grand total of all actual offenses.

Response Rates View help for Response Rates

Not applicable.

Presence of Common Scales View help for Presence of Common Scales

None.

Original Release Date View help for Original Release Date

1998-12-07

Version History View help for Version History