Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone
Steven J. Davis
Nicholas Bloom
José María Barrero
Thomas Sampson
Adrien Matray
Natalie Bau
Darryl Koehler
Laurence J. Kotlikoff
Alan J. Auerbach
Irina Popova
Alexander Ludwig
Hakki Yazici
Slavík Ctirad
Kina Özlem
Tilman Graff
Tilman Graff
Yuri Ostrovsky
Martin Munk
Anton Heil
Maitreesh Ghatak
Robin Burgess
Oriana Bandiera
Claire Balboni
Jonna Olsson
Richard Foltyn
Minjie Deng
Iiyana Kuziemko
Elisa Jácome
Juan Pablo Rud
Bridget Hofmann
Sumaiya Rahman
Martin Nybom
Stephen Machin
Hans van Kippersluis
Anne C. Gielen
Espen Bratberg
Jo Blanden
Adrian Adermon
Maximilian Hell
Robert Manduca
Robert Manduca
Marta Morazzoni
Aadesh Gupta
David Wengrow
Damian Phelan
Amanda Dahlstrand
Andrea Guariso
Erika Deserranno
Lukas Hensel
Stefano Caria
Vrinda Mittal
Ararat Gocmen
Clara Martínez-Toledano
Yves Steinebach
Breno Sampaio
Joana Naritomi
Diogo Britto
François Gerard
Filippo Pallotti
Heather Sarsons
Kristóf Madarász
Anna Becker
Lucas Conwell
Michela Carlana
Katja Seim
Joao Granja
Jason Sockin
Todd Schoellman
Paolo Martellini
UCL Policy Lab
Natalia Ramondo
Javier Cravino
Vanessa Alviarez
Hugo Reis
Pedro Carneiro
Raul Santaeulalia-Llopis
Diego Restuccia
Chaoran Chen
Brad J. Hershbein
Claudia Macaluso
Chen Yeh
Xuan Tam
Xin Tang
Marina M. Tavares
Adrian Peralta-Alva
Carlos Carillo-Tudela
Felix Koenig
Joze Sambt
Ronald Lee
James Sefton
David McCarthy
Bledi Taska
Carter Braxton
Alp Simsek
Plamen T. Nenov
Gabriel Chodorow-Reich
Virgiliu Midrigan
Corina Boar
Sauro Mocetti
Guglielmo Barone
Steven J. Davis
Nicholas Bloom
José María Barrero
Thomas Sampson
Adrien Matray
Natalie Bau
Darryl Koehler
Laurence J. Kotlikoff
Alan J. Auerbach
Irina Popova
Alexander Ludwig

Measuring racial discrimination in bail decisions

What is this research about and why did you do it?  

Racial disparities are pervasive in many stages of the criminal justice system, but are often challenging to interpret. For example, do disparities in the pretrial release rates of Black and white defendants reflect racial discrimination? Or do such disparities reflect legally relevant differences in defendants’ potential for pretrial misconduct, which bail judges partially observe? This study develops and applies new quasi-experimental methods to answer these questions. Specifically, we show how the quasi-random assignment of bail judges can be used to isolate release disparities among defendants with identical misconduct potential, a discrimination measure broadly linked to legal theories of disparate impact.

How did you answer this question?  

We develop an instrumental variables (IV) method that uses quasi-random bail judge assignment to estimate the average pretrial misconduct risk in the full populations of white and Black defendants.  We then show how these two average risk statistics can be used to adjust observed release rate disparities to correct for differences in pretrial misconduct potential. We apply these techniques to administrative data from New York City, home to one of the largest pretrial systems in the U.S. We also develop quasi-experimental methods to study whether racial bias or statistical discrimination drive the resulting disparate impact measure.

What did you find?  

Our most conservative estimates show that around two-thirds of the average release rate disparity between white and Black defendants in New York City is due to the disparate impact of release decisions, with the remaining one-third attributable to racial differences in misconduct potential. Judges differ significantly in their level of such disparate impact, although the vast majority (87 percent) release white defendants at a higher rate than equally-risky Black defendants.  Both racial bias and statistical discrimination play a role, and policy simulations suggest race-specific release rate quotas could significantly reduce the overall level of such disparate impact in bail decisions.

Distribution of Observed Release Rate Disparities and Unwarranted Disparities (Disparate Impact) Across NYC Bail Judges. This figure plots the distribution of observed disparities and disparate impact estimates across 268 bail judges in New York City. Judges with positive observed disparities judge release white defendants at a higher rate than Black defendants. Judges with positive disparate impact release white defendants at a higher rate than Black defendants with identical pretrial misconduct potential.

What implications does this have for the research on wealth concentration or economic inequality?  

Our analysis shows how a difficult challenge with measuring disparate impact in high-stakes decisions can be overcome with appropriate quasi-experimental variation, and that this form of racial discrimination is pervasive in New York City bail decisions. Importantly, and in contrast to standard discrimination metrics such as those from audit or correspondence studies, our measure accounts for both direct discrimination (on the basis of race itself) as well as indirect discrimination through seemingly race-neutral characteristics.

What are the next steps in your agenda?  

We plan to apply these new tools to other high-stakes decisions, such as in the context of lending and child protection. We are also studying how the tools can be extended to measure and potentially reduce discrimination in algorithmic decisions.

Citation and related resources

This paper can be cited as follows: Arnold, D., Dobbie, W., and Hull, P. (2022) "Measuring racial discrimination in bail decisions." American Economic Review, 112(9), pp. 2992-3038.

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About the authors