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Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1980-2016

Version
5
Resource Type
Dataset : administrative records data
Creator
  • Kaplan, Jacob (University of Pennsylvania)
Publication Date
2018-01-04
Free Keywords
arrest; arrest rates; Uniform Crime Reports; FBI; UCR; crime; crime statistics; arrest statistics
Description
  • Abstract

    Version 5 release notes:
    • Removes support for SPSS and Excel data.
    • Changes the crimes that are stored in each file. There are more files now with fewer crimes per file. The files and their included crimes have been updated below.
    • Adds in agencies that report 0 months of the year.
    • Adds a column that indicates the number of months reported. This is generated summing up the number of unique months an agency reports data for. Note that this indicates the number of months an agency reported arrests for ANY crime. They may not necessarily report every crime every month. Agencies that did not report a crime with have a value of NA for every arrest column for that crime.
    • Removes data on runaways.
    Version 4 release notes:
    • Changes column names from "poss_coke" and "sale_coke" to "poss_heroin_coke" and "sale_heroin_coke" to clearly indicate that these column includes the sale of heroin as well as similar opiates such as morphine, codeine, and opium. Also changes column names for the narcotic columns to indicate that they are only for synthetic narcotics.
    Version 3 release notes:
    • Add data for 2016.
    • Order rows by year (descending) and ORI.
    Version 2 release notes:
    • Fix bug where Philadelphia Police Department had incorrect FIPS county code.

    The Arrests by Age, Sex, and Race data is an FBI data set that is part of the annual Uniform Crime Reporting (UCR) Program data. This data contains highly granular data on the number of people arrested for a variety of crimes (see below for a full list of included crimes). The data sets here combine data from the years 1980-2015 into a single file. These files are quite large and may take some time to load.
    All the data was downloaded from NACJD as ASCII+SPSS Setup files and read into R using the package asciiSetupReader. All work to clean the data and save it in various file formats was also done in R. For the R code used to clean this data, see here. https://github.com/jacobkap/crime_data. If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com.

    I did not make any changes to the data other than the following. When an arrest column has a value of "None/not reported", I change that value to zero. This makes the (possible incorrect) assumption that these values represent zero crimes reported. The original data does not have a value when the agency reports zero arrests other than "None/not reported." In other words, this data does not differentiate between real zeros and missing values. Some agencies also incorrectly report the following numbers of arrests which I change to NA: 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, 100000, 99999, 99998.

    To reduce file size and make the data more manageable, all of the data is aggregated yearly. All of the data is in agency-year units such that every row indicates an agency in a given year. Columns are crime-arrest category units. For example, If you choose the data set that includes murder, you would have rows for each agency-year and columns with the number of people arrests for murder. The ASR data breaks down arrests by age and gender (e.g. Male aged 15, Male aged 18). They also provide the number of adults or juveniles arrested by race. Because most agencies and years do not report the arrestee's ethnicity (Hispanic or not Hispanic) or juvenile outcomes (e.g. referred to adult court, referred to welfare agency), I do not include these columns.

    To make it easier to merge with other data, I merged this data with the Law Enforcement Agency Identifiers Crosswalk (LEAIC) data. The data from the LEAIC add FIPS (state, county, and place) and agency type/subtype. Please note that some of the FIPS codes have leading zeros and if you open it in Excel it will automatically delete those leading zeros.

    I created 9 arrest categories myself. The categories are:
    • Total Male Juvenile
    • Total Female Juvenile
    • Total Male Adult
    • Total Female Adult
    • Total Male
    • Total Female
    • Total Juvenile
    • Total Adult
    • Total Arrests
    All of these categories are based on the sums of the sex-age categories (e.g. Male under 10, Female aged 22) rather than using the provided age-race categories (e.g. adult Black, juvenile Asian). As not all agencies report the race data, my method is more accurate. These categories also make up the data in the "simple" version of the data. The "simple" file only includes the above 9 columns as the arrest data (all other columns in the data are just agency identifier columns). Because this "simple" data set need fewer columns, I include all offenses.

    As the arrest data is very granular, and each category of arrest is its own column, there are dozens of columns per crime. To keep the data somewhat manageable, there are nine different files, eight which contain different crimes and the "simple" file. Each file contains the data for all years. The eight categories each have crimes belonging to a major crime category and do not overlap in crimes other than with the index offenses. Please note that the crime names provided below are not the same as the column names in the data. Due to Stata limiting column names to 32 characters maximum, I have abbreviated the crime names in the data. The files and their included crimes are:

    Index Crimes
    • Murder
    • Rape
    • Robbery
    • Aggravated Assault
    • Burglary
    • Theft
    • Motor Vehicle Theft
    • Arson
    Alcohol Crimes
    • DUI
    • Drunkenness
    • Liquor
    Drug Crimes
    • Total Drug
    • Total Drug Sales
    • Total Drug Possession
    • Cannabis Possession
    • Cannabis Sales
    • Heroin or Cocaine Possession
    • Heroin or Cocaine Sales
    • Other Drug Possession
    • Other Drug Sales
    • Synthetic Narcotic Possession
    • Synthetic Narcotic Sales
    Grey Collar and Property Crimes
    • Forgery
    • Fraud
    • Stolen Property
    Financial Crimes
    • Embezzlement
    • Total Gambling
    • Other Gambling
    • Bookmaking
    • Numbers Lottery
    Sex or Family Crimes
    • Offenses Against the Family and Children
    • Other Sex Offenses
    • Prostitution
    • Rape
    Violent Crimes
    • Aggravated Assault
    • Murder
    • Negligent Manslaughter
    • Robbery
    • Weapon Offenses
    Other Crimes
    • Curfew
    • Disorderly Conduct
    • Other Non-traffic
    • Suspicion
    • Vandalism
    • Vagrancy
    Simple
    • This data set has every crime and only the arrest categories that I created (see above).
    If you have any questions, comments, or suggestions please contact me at jkkaplan6@gmail.com.

Temporal Coverage
  • 1980-01-01 / 2016-12-31
    Time Period: Tue Jan 01 00:00:00 EST 1980--Sat Dec 31 00:00:00 EST 2016
Geographic Coverage
  • United States
Sampled Universe
Police agencies in the United States
Smallest Geographic Unit: Police agency jurisdiction
Availability
Download

Update Metadata: 2019-01-07 | Issue Number: 1 | Registration Date: 2019-01-07

Kaplan, Jacob (2018): Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1980-2016. Version: 5. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E102263V5-10021