ABSTRACT
A large body of research has focused on understanding mass incarceration in the United States through the lens of federal and state prison growth. However, local jail systems, with 11 million admissions each year, have received less research attention despite their broad impact on communities. Preliminary analysis conducted by the Vera Institute of Justice (Vera) uncovered geographical disparities in county jail incarceration rates. Contrary to assumptions that incarceration is an urban phenomenon, Vera discovered that, in recent decades, pretrial jail rates have declined or remained flat in many urban areas, whereas rates have grown in rural counties. In an effort to uncover factors contributing to continued jail growth in rural areas, Vera joined forces with Two Sigma’s Data Clinic, a volunteer-based program that leverages Two Sigma employees’ data science expertise. Determinants of local jail rates from 2000–2013 were examined using a generalized estimating equations (GEE) model to account for correlations within counties over time. Results revealed that county-level poverty, police expenditures, and spillover effects from other county and state authorities are significant predictors of local jail rates. Investigation of model residuals revealed clusters of counties where observed rates were much higher than expected conditioned upon county variables.
Acknowledgements
We thank the entire Vera team for the excellent work they do in the pursuit of equal justice, ending mass incarceration, and strengthening communities. We would like to acknowledge the broader Two Sigma Data Clinic team—Christine Zhang, Roxanne Zalucky, Jeffrey Saret, Ben Wellington, Greg Shih, Jim Charatan, Ris Sawyer, Katy Knight, Dave Hahn, and Thea Charles—for their expertise, support, and feedback on the project and manuscript. Lastly, a special thanks to Katy Knight for introducing this partnership.