The Impact of Cash Transfers for Rapid Rehousing Clients

Last registered on May 13, 2024


Trial Information

General Information

The Impact of Cash Transfers for Rapid Rehousing Clients
Initial registration date
May 02, 2024

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
May 13, 2024, 11:57 AM EDT

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


There is information in this trial unavailable to the public. Use the button below to request access.

Request Information

Primary Investigator

University of Notre Dame

Other Primary Investigator(s)

PI Affiliation
University of Notre Dame
PI Affiliation
Stanford University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Rapid Re-Housing (RRH) is a program designed to help people transition from homelessness to stable housing. RRH offers a combination of temporary benefits that typically last between 6 and 24 months, such as housing identification assistance, rental subsidies, and case management. Yet, RRH is a short-term solution. Of those who do not explicitly re-experience homelessness, individuals may still face housing instability, financial insecurity, and poor health. Qualitative evidence generated by our partner Abode Services, a provider of homeless housing and services in CA’s Bay Area, suggests that a primary reason many return to homelessness is they still do not have a sufficiently stable income stream when the rental subsidies expire. We explore one possible way to bridge the gap: offering cash transfers to participants the year after exiting RRH. We quantify the impact of cash transfers through a randomized controlled trial (RCT), randomly offering monthly payments totaling approximately $13,000-$16,000 over 12 months. Our target sample is 545 individuals exiting RRH across five counties in the San Francisco Bay area. Using administrative data, we will measure the impact of cash transfers on homelessness, housing stability, financial security and other outcomes one and two years after study enrollment.
External Link(s)

Registration Citation

Batistich, Mary Kate, Adrienne Sabety and James Sullivan. 2024. "The Impact of Cash Transfers for Rapid Rehousing Clients." AEA RCT Registry. May 13.
Experimental Details


Beginning in Spring 2024, clients who exit Abode Services’ RRH programs will have the option to participate in a cash transfer program. 2-3 months before RRH exit, case managers will ask their clients if they are interested in participating in a program that provides monthly cash payments of $50 or more for one year.
Once the RRH exit date has been confirmed and the client has chosen to participate in the program, they will be randomized into one of two groups. Those who are randomized into the control group will receive $50 per month for 12 months. The treatment group will receive much larger monthly payments ranging from $800 to $2,000 depending on family type and month in program. These payments are roughly comparable to the average payment made by Abode’s RRH programs ($1,400) and will on average cover one-half to two-thirds of monthly rent ($2,100). Motivated by feedback from prior Abode RRH clients, the payments will be larger in the initial months than in later months to help with bigger expenses such as car repairs.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Primary Outcomes (explanation)
We are primarily interested in whether cash transfers reduce homelessness. The homelessness outcome will be defined as any use of homelessness services within 12 and 24 months after random assignment as recorded in HMIS, measured using an indicator variable. Alternative measures include use of emergency shelters and/or street outreach as identified in HMIS.

Secondary Outcomes

Secondary Outcomes (end points)
Housing Stability
Financial Wellbeing
Secondary Outcomes (explanation)
Our secondary outcome of housing stability will be measured primarily by an indicator for any address move within 12 and 24 months after random assignment based on Infutor address data. We will also measure housing stability via indicators for moving to higher socioeconomic status neighborhoods, former address ending, and new address beginning, as well as neighborhood characteristics of the most recent address. We will also consider an index of these outcomes.

We will measure financial well-being via an indicator for whether a participant’s credit score increased within 12 and 24 months after random assignment as recorded in Experian. We will also use the following alternative measures based on Experian data: credit score, an indicator for a credit score decrease, account balance, delinquent accounts, collections, debt, and credit inquiries. We will also consider an index of these outcomes.

Experimental Design

Experimental Design
Following the construction of this study as a randomized control trial, those assigned to treatment and control groups should look equivalent to each other on average. Thus, any difference in outcomes between the groups could be attributed to their treatment status. After applicants have been randomized into these groups and the study begins, LEO will monitor outcomes into the future and compare them. For our analysis, we will estimate differences in outcomes between treatment and control group applicants using an intent-to-treat (ITT) framework controlling for baseline covariates. Baseline covariates will come directly from Abode’s administrative data or from data collected during the study intake process.

Specifically, we will estimate the following equation:
yi =β0 + Tiβ1 + xiβ2 + εi
where yi represents key outcome variables, such as returns to homelessness in the time period of interest, and xi represents a vector of observed characteristics for person i. The variables in x will include baseline characteristics such as age, age squared, categorical race variables, and indicators for ethnicity and gender. It will also include randomization strata fixed effects (county of residence and single/adults-only vs. household). The key covariate in the analysis will be the indicator variable Ti which equals 1 if the respondent is assigned to a particular treatment arm and zero if in the respective control group. The term εi is an error term. We will measure the outcomes every year after randomization, determining short- and long-term effects of the intervention. Treatment-on-the-treated (TOT) effects will be estimated via an instrumental variable (IV) model, using assignment to treatment as an instrument for participation in services.
Experimental Design Details
Not available
Randomization Method
Computer-based randomization
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
545 families
Sample size: planned number of observations
545 families
Sample size (or number of clusters) by treatment arms
327 control families; 218 treatment families
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We will be powered to detect an 8.87 percentage point (31.6 percent) decrease in the probability of becoming homeless 12 months after exit from RRH, assuming an untreated mean of 28 percent. Given the nature of the intervention, we expect take-up to be very high. One group which may not want to participate in the study is those receiving SSI benefits, because the study transfer payments may compromise their SSI eligibility. Since about 4 percent of Abode’s RRH clients receive SSI benefits, we conservatively assume that all SSI recipients in the treatment group will decline to take up the cash transfers, resulting in a 96 percent take-up rate.

Institutional Review Boards (IRBs)

IRB Name
The University of Notre Dame Institutional Review Board
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan

MD5: e87a7bace997aa1dc48d9a8176306446

SHA1: fe8b8476e0df46bd561f4fe182ab913a73a4e347

Uploaded At: May 02, 2024