Reducing Racial Disparities in Bail Decisions: An Experiment on Public Accountability and Feedback in Texas

Last registered on April 05, 2021


Trial Information

General Information

Reducing Racial Disparities in Bail Decisions: An Experiment on Public Accountability and Feedback in Texas
Initial registration date
December 09, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
December 10, 2020, 6:37 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
April 05, 2021, 2:05 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.


Primary Investigator

Harvard Kennedy School

Other Primary Investigator(s)

PI Affiliation
Harvard Law School

Additional Trial Information

On going
Start date
End date
Secondary IDs
Racial disparities exist at every stage of the U.S. criminal justice system and are particularly prominent in the setting of bail. These racial disparities in bail are even larger for the sizeable youth population. In settings like Harris County, TX, a site in our study, almost 40 percent of arraigned defendants are between the ages of 14-24 and black defendants are more than 34 percent more likely to be detained compared to whites. In this project, we are collaborating with the Texas Criminal Justice Coalition (TCJC) to test the effectiveness of a two-pronged intervention that can reduce racial disparities in bail decisions for individuals in 4 sites in Texas. This intervention includes a public report card for judges on their bail decisions, in particular for youth and minorities, which we believe can increase accountability and transparency. The intervention also includes detailed private feedback and personalized tips to judges on their decisions, giving them the motivation, information, and tools to reduce racial disparities in their pretrial decisions. We will estimate the causal effect of our intervention on pretrial release and misconduct rates (in the aggregate and racial gaps), with a particular focus on youth.
External Link(s)

Registration Citation

Dobbie, Will and Crystal Yang. 2021. "Reducing Racial Disparities in Bail Decisions: An Experiment on Public Accountability and Feedback in Texas." AEA RCT Registry. April 05.
Sponsors & Partners



Experimental Details


We have designed a combined intervention with two components to improve decision-making and reduce racial disparities at the pretrial justice stage.

(1) Public Report Cards by Race: The first part of our intervention is to build off existing practice of the Texas Criminal Justice Coalition (TCJC) and to provide and heighten awareness of public report cards for bail judges. These public report cards will report statistics on each judge such as the number of individuals detained and average cash bail amounts (used in virtually all cases in Texas), as well as report racial gaps in these metrics. In other settings, providing information to citizens has been shown to be highly effective at improving the provision of public services (see Dranove and Jin 2010), such as in medicine (Xi 2015), schooling (Andrabi et al. 2017; Hastings and Weinstein 2008), and food services (Jin and Leslie 2003).

(2) Individualized Feedback on Release and Misconduct Rates by Race: We also plan to provide judges with individualized feedback on their past performance, including their own release and good conduct rates, where the good conduct rate is defined as the percent of released defendants who are not rearrested for another crime pretrial. We will provide separate performance information for defendants in the aggregate and by race. We will also provide performance information for youth offenders under the age of 25. We plan to start by providing historical information, before providing updated information on a regular basis (e.g., every 3 months) as the experiment progresses. This individualized feedback intervention therefore gives judges a chance to see if their changed behavior maps to improved outcomes. This type of individualized feedback is a standard practice used in other settings such as using teacher value added to evaluate teachers (Harris 2009), surgeon report cards for medical professionals (Dranove et al. 2003), school report cards for failing school districts (No Child Left Behind Act 2001), and so on.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Pretrial Release Rates, Pretrial Misconduct Rates, Racial Disparities in Pretrial Release Rates, Racial Disparities in Pretrial Misconduct Rates
Primary Outcomes (explanation)
We will evaluate the effect of our combined intervention on pretrial release rates, misconduct rates, and racial disparities in these outcomes.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will conduct a randomized controlled trial (RCT) to identify the causal impact of our combined intervention (public report card + feedback) on our two main outcomes of interest: (1) pretrial release rates and (2) rearrest rates (on average and on racial disparities), focusing in particular on youth offenders between the ages of 14-24, who comprise almost 40 percent of individuals in the felony system in our sites.

Randomization and Data: Half of the judges will be randomized to the treatment group and we will follow outcomes for at least 12 months. Both during and after the intervention, we will obtain publicly-available administrative data on pretrial release decisions and misconduct outcomes at the case level. These data will also include judge and defendant identifiers, defendant demographics, and additional case and defendant details such as the crime type and prior criminal history.
Experimental Design Details
Randomization Method
Randomization will be conducted using a computer random number generator.
Randomization Unit
We will randomize at the level of the individual judge within each county.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
Approximately 50 bail judges.
Sample size (or number of clusters) by treatment arms
Approximately 25 judges in control arm and 25 judges in treatment arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Harvard University-Area Committee on the Use of Human Subjects
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials