Advancing the Understanding of Immigration, Crime, and Crime Reporting at the Local Level with a Synthetic Population, United States, 2019 (ICPSR 39318)

Version Date: Apr 16, 2026

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Principal Investigator(s):
Christopher Inkpen, RTI International

https://doi.org/10.3886/ICPSR39318.v1

Version V1

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Summary

This study investigated the complex relationship between unauthorized immigration and crime at the local level. Through a mix of data fusion, synthetic population modeling, and detailed crime reporting from selected jurisdictions, the study sought to produce nuanced insights to challenge prevailing assumptions about immigration and crime, ultimately aiding in informed policy-making and resource allocation.

This study employed crime and crime reporting data from ten jurisdictions across the United States paired with synthetic data which estimated the unauthorized immigrant population. This research aimed to provide an in-depth analysis at the census tract level. Analyses focused on unauthorized immigration and its correlation with drug, property, and violent crime rates, while accounting for crime reporting in traditional and emerging immigrant destinations along with sites with low foreign populations.

Citation

Inkpen, Christopher. Advancing the Understanding of Immigration, Crime, and Crime Reporting at the Local Level with a Synthetic Population, United States, 2019. Inter-university Consortium for Political and Social Research [distributor], 2026-04-16. https://doi.org/10.3886/ICPSR39318.v1

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Funding

United States Department of Justice. Office of Justice Programs. National Institute of Justice (2020-R2-CX-0027)

Subject Terms

Geographic Coverage

Distributor(s)

Inter-university Consortium for Political and Social Research
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Time Period(s)

2019

Date of Collection

2019
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Study Purpose

The purpose of this study was to analyze unauthorized immigration and its correlation with drug, property, and violent crime rates, while accounting for crime reporting in traditional and emerging immigrant destinations along with sites with low foreign populations.

Study Design

This study included a development of synthetic population data and a development of crime and crime reporting data.

Synthetic Population Development: This study built on the work of model-based imputation methods by developing models that predict unauthorized status in a survey dataset and applying them to a synthetic population of the United States, based on U.S. Census Bureau survey datasets. This approach allowed for granular estimates of unauthorized immigrant populations at the Census tract level. By combining data from the Survey of Income and Program Participation (SIPP) and the American Community Survey (ACS), the study developed a robust model to predict unauthorized status and produced Census tract-level estimates of the unauthorized immigrant population for 2019. Validation efforts for these estimates included comparisons with county- and state-level estimates from sources like the Migration Policy Institute and Pew Research Center along with scaling local estimates to meet state-level figures.

Crime and Crime Reporting Data Sources: The study utilized Records Management System (RMS) and Calls for Service (CFS) data from multiple police jurisdictions in 2019. These data were standardized and cleaned to ensure consistency across different regions and different case management systems.

Sample

For the synthetic population development, this study utilized the Survey of Income and Program Participation (SIPP) and the American Community Survey (ACS) to develop a robust model to predict unauthorized status and produced Census tract-level estimates of the unauthorized immigrant population for 2019. Additionally, Records Management System (RMS) and Calls for Service (CFS) data from multiple police jurisdictions in 2019 were used for the crime and crime reporting data.

Time Method

Cross-sectional

Universe

Census tracts in a selection of participating jurisdictions distributed geographically across the United States of America.

Unit(s) of Observation

Census tract

Data Type(s)

Mode of Data Collection

Description of Variables

This study contained aggregated variables regarding crimes committed (property, violent, drug-related), unauthorized immigration population, foreign born population, home ownership, and demographics per census tract jurisdictions.

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Original Release Date

2026-04-16

Version History

2026-04-16 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Notes

  • 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.

  • ICPSR usually offers files in multiple formats for researchers to be able to access data and documentation in formats that work well within their needs. If you have questions about the accessibility of materials distributed by ICPSR or require further assistance, please visit ICPSR’s Accessibility Center.