An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls

Principal Investigator(s):  View help for Principal Investigator(s) Angela Zhou, UC Berkeley; Andrew Koo, Cornell University; Nathan Kallus, Cornell University; Rene Ropac, New York City Criminal Justice Agency; Richard Petersen, New York City Criminal Justice Agency; Stephen Koppel, New York City Criminal Justice Agency; Tiffany Bergin, New York City Criminal Justice Agency

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  data 12/04/2021 02:41:PM
final_incidents_2021-05-28.csv text/csv 243 MB 10/16/2021 10:22:PM

Project Citation: 

Zhou, Angela, Koo, Andrew, Kallus, Nathan, Ropac, Rene, Petersen, Richard, Koppel, Stephen, and Bergin, Tiffany. An Empirical Evaluation of the Impact of New York’s Bail Reform on Crime Using Synthetic Controls. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-12-04. https://doi.org/10.3886/E152641V1

Project Description

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This is the raw data compiled for the project, "An Empirical Evaluation of the Impact of New York's Bail Reform on Crime Using Synthetic Controls"

Abstract: 
We conduct an empirical evaluation of the impact of New York's bail reform on crime. New York State's Bail Elimination Act went into effect on January 1, 2020, eliminating money bail and pretrial detention for nearly all misdemeanor and nonviolent felony defendants. Our analysis of effects on aggregate crime rates after the reform informs the understanding of bail reform and general deterrence. We conduct a synthetic control analysis for a comparative case study of impact of bail reform. We focus on synthetic control analysis of post-intervention changes in crime for assault, theft, burglary, robbery, and drug crimes, constructing a dataset from publicly reported crime data of 27 large municipalities. Our findings, including placebo checks and other robustness checks, show that for assault, theft, and drug crimes, there is no significant impact of bail reform on crime; for burglary and robbery, we similarly have null findings but the synthetic control is also more variable so these are deemed less conclusive.
Funding Sources:  View help for Funding Sources National Science Foundation (Division of Information & Intelligent Systems) (1939704)



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