Jacob Kaplan's Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1974-2020
Principal Investigator(s): View help for Principal Investigator(s) Jacob Kaplan, Princeton University
Version: View help for Version V14
Name | File Type | Size | Last Modified |
---|---|---|---|
ucr_arrests_monthly_alcohol_or_property_1974_2020_dta.zip | application/zip | 332.7 MB | 09/24/2021 12:53:PM |
ucr_arrests_monthly_alcohol_or_property_1974_2020_rds.zip | application/zip | 342.5 MB | 09/22/2021 01:57:PM |
ucr_arrests_monthly_all_crimes_race_sex_1974_2020_dta.zip | application/zip | 685.3 MB | 09/24/2021 06:01:PM |
ucr_arrests_monthly_all_crimes_race_sex_1974_2020_rds.zip | application/zip | 861.7 MB | 09/22/2021 01:47:PM |
ucr_arrests_monthly_drug_1974_2020_dta.zip | application/zip | 344.9 MB | 09/22/2021 01:07:PM |
ucr_arrests_monthly_drug_1974_2020_rds.zip | application/zip | 383.6 MB | 09/22/2021 01:25:PM |
ucr_arrests_monthly_index_1974_2020_dta.zip | application/zip | 297.2 MB | 09/22/2021 01:57:PM |
ucr_arrests_monthly_index_1974_2020_rds.zip | application/zip | 306.6 MB | 09/22/2021 03:48:PM |
ucr_arrests_monthly_other_crimes_1974_2020_dta.zip | application/zip | 435.9 MB | 09/24/2021 05:16:PM |
ucr_arrests_monthly_other_crimes_1974_2020_rds.zip | application/zip | 480.9 MB | 09/22/2021 01:16:PM |
- Total of 12 records. Records per page
- « previous Page of 2
- next »
Project Citation:
Kaplan, Jacob. Jacob Kaplan’s Concatenated Files: Uniform Crime Reporting (UCR) Program Data: Arrests by Age, Sex, and Race, 1974-2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-09-27. https://doi.org/10.3886/E102263V14
Project Description
Summary:
View help for Summary
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/month 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) 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 codes (state, county, and place).
I created 9 arrest categories myself. The categories are:
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 five different files, four which contain different crimes and the "all_crimes" file. Each file contains the data for all years. The four 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
For a comprehensive guide to this data and other UCR data, please see my book at ucrbook.com
Version 14 release notes:
- Adds 2020 data.
- Please note that the FBI has retired UCR data ending in 2020 data so this will be the last Arrests by Age, Sex, and Race data they release.
Version 13 release notes:
- Changes R files from .rda to .rds.
- Fixes bug where the number_of_months_reported variable incorrectly was the largest of the number of months reported for a specific crime variable. For example, if theft was reported Jan-June and robbery was reported July-December in an agency, in total there were 12 months reported. But since each crime (and let's assume no other crime was reported more than 6 months of the year) only was reported 6 months, the number_of_months_reported variable was incorrectly set at 6 months. Now it is the total number of months reported of any crime. So it would be set to 12 months in this example. Thank you to Nick Eubank for alerting me to this issue.
- Adds rows even when a agency reported zero arrests that month; all arrest values are set to zero for these rows.
Version 12 release notes:
- Adds 2019 data.
Version 11 release notes:Version 5 release notes:
- Changes release notes description, does not change data.
Version 10 release notes:
- The data now has the following age categories (which were previously aggregated into larger groups to reduce file size): under 10, 10-12, 13-14, 40-44, 45-49, 50-54, 55-59, 60-64, over 64. These categories are available for female, male, and total (female+male) arrests. The previous aggregated categories (under 15, 40-49, and over 49 have been removed from the data).
Version 9 release notes:
- For each offense, adds a variable indicating the number of months that offense was reported - these variables are labeled as "num_months_[crime]" where [crime] is the offense name. These variables are generated by the number of times one or more arrests were reported per month for that crime. For example, if there was at least one arrest for assault in January, February, March, and August (and no other months), there would be four months reported for assault. Please note that this does not differentiate between an agency not reporting that month and actually having zero arrests.
- The variable "number_of_months_reported" is still in the data and is the number of months that any offense was reported. So if any agency reports murder arrests every month but no other crimes, the murder number of months variable and the "number_of_months_reported" variable will both be 12 while every other offense number of month variable will be 0.
- Adds data for 2017 and 2018.
Version 8 release notes:
- Adds annual data in R format.
- Changes project name to avoid confusing this data for the ones done by NACJD.
- Fixes bug where bookmaking was excluded as an arrest category.
- Changed the number of categories to include more offenses per category to have fewer total files. Added a "total_race" file for each category - this file has total arrests by race for each crime and a breakdown of juvenile/adult by race.
Version 7 release notes:
- Adds 1974-1979 data
- Adds monthly data (only totals by sex and race, not by age-categories).
- All data now from FBI, not NACJD.
- Changes some column names so all columns are <=32 characters to be usable in Stata.
- Changes how number of months reported is calculated. Now it is the number of unique months with arrest data reported - months of data from the monthly header file (i.e. juvenile disposition data) are not considered in this calculation.
Version 6 release notes:
- Fix bug where juvenile female columns had the same value as juvenile male columns.
- 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 (ASR) 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 1974-2019 into a single file for each group of crimes. Each monthly file is only a single year as my laptop can't handle combining all the years together. These files are quite large and may take some time to load.
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/month 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) 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 codes (state, county, and place).
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
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 five different files, four which contain different crimes and the "all_crimes" file. Each file contains the data for all years. The four 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
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
- DUI
- Drunkenness
- Liquor
- Forgery
- Fraud
- Stolen Property
- Embezzlement
- Gambling - Total
- Gambling - Other
- Gambling - Bookmaking
- Gambling - Lottery
Other Crimes
- Curfew
- Disorderly Conduct
- Other Non-traffic
- Suspicion
- Vandalism
- Vagrancy
- Offenses Against the Family and Children
- Other Sex Offenses
- Prostitution
- Negligent Manslaughter
- Weapon Offenses
- Other Assault
These are the age categories, which are also broken up by arrestee gender.
- Under 10
- 10-12
- 13-14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25-29
- 30-34
- 35-39
- 40-44
- 45-49
- 50-54
- 55-59
- 60-64
- 65 and older
Scope of Project
Subject Terms:
View help for Subject Terms
arrest;
arrest rates;
Uniform Crime Reports;
FBI;
UCR;
crime;
crime statistics;
arrest statistics;
UCR arrest;
Arrests by Age;
Arrest by Age Sex and Race
Geographic Coverage:
View help for Geographic Coverage
United States
Time Period(s):
View help for Time Period(s)
1974 – 2020
Universe:
View help for Universe
Police agencies in the United States
Data Type(s):
View help for Data Type(s)
administrative records data
Methodology
Data Source:
View help for Data Source
United States Department of Justice. Federal Bureau of Investigation
Unit(s) of Observation:
View help for Unit(s) of Observation
Police Agency
Geographic Unit:
View help for Geographic Unit
Police agency jurisdiction
Related Publications
This study is un-published. See below for other available versions.
Published Versions
Report a Problem
Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.
This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.