Screening Restrictions and Discrimination in Rental Markets

Last registered on September 24, 2026
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Pre-Trial

Trial Information

General Information

Title
Screening Restrictions and Discrimination in Rental Markets
RCT ID
AEARCTR-0019527
Initial registration date
September 04, 2026

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
September 21, 2026, 6:57 AM EDT

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

Last updated
September 24, 2026, 1:08 PM EDT

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

Locations

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Primary Investigator

Name
Henry Downes
Affiliation
University of Georgia
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Other Primary Investigator(s)

PI Name
Mingzhou Wang
PI Affiliation
University of Georgia
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Additional Trial Information

Status
In development
Start date
2026-09-04
End date
2028-06-30
Keywords
Behavior, Other
Additional Keywords
Housing, Discrimination, Mobility
JEL code(s)
R31, J15, R38
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines how restrictions on tenant screening affect landlord behavior and discrimination in rental housing. We conduct a correspondence experiment in Maryland around the October 1, 2026 implementation of two statewide renter-protection laws: HB 315, which restricts the use of income and credit information when screening applicants receiving income-based housing subsidies, and the Fair Chance Housing Act, which restricts criminal-history and substance-use screening. Rental inquiries independently vary applicants’ race, disclosed Housing Choice Voucher (HCV) status, and signals of applicant quality. We measure landlord responses, response timing, invitations to proceed, requests for additional information, and response content, as well as screening and subsidy-related language in rental advertisements. The study tests whether the policy changes alter landlords’ willingness to engage with subsidy recipients, affect racial disparities in landlord responses, increase reliance on race when other screening information is restricted, and change how landlords use race to infer unobserved subsidy receipt. We also examine heterogeneity across local legal regimes, neighborhood characteristics, property characteristics, and rents. The results will inform the design of fair-housing regulation and contribute to broader questions related to the economics of discrimination.
External Link(s)

Registration Citation

Citation
Downes, Henry and Mingzhou Wang. 2026. "Screening Restrictions and Discrimination in Rental Markets." AEA RCT Registry. September 24. https://doi.org/10.1257/rct.19527-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Effective October 1, 2026, Maryland implemented two statewide changes to tenant-screening rules. HB 315 restricts landlords’ use of certain income and credit information when evaluating prospective tenants who receive income-based housing subsidies. The Fair Chance Housing Act (FCHA) restricts pre-offer inquiries and screening based on criminal history and substance use and imposes related restrictions on rental advertising. The study examines how landlord behavior changes following implementation of these screening restrictions.

We describe these features in greater detail in our Pre-Analysis Plan.
Intervention Start Date
2026-10-01
Intervention End Date
2027-09-30

Primary Outcomes

Primary Outcomes (end points)
We examine two primary outcome families. First, we measure landlord engagement with prospective tenants, including whether the landlord responds, time to response, whether the unit is indicated as available, invitations to view/apply or otherwise proceed, requests for additional information or screening information, and the positive, neutral, or negative content of landlord responses. Second, we measure rental advertisement content, including mentions of credit, income requirements, criminal-background screening, drug or alcohol testing, and positive or negative language regarding Housing Choice Vouchers or other housing subsidies.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct a pre/post randomized correspondence experiment using publicly available rental listings. In each stage of measurement (pre and post Oct 1) we will identify eligible listings using pre-specified criteria, and we will attempt to send two inquiries to each eligible listing.

For the first inquiry, each eligible listing will be randomly assigned to one of 12 treatment cells defined by applicant race (Black- vs White-coded name), Housing Choice Voucher status (disclosed HCV receipt, disclosed non-receipt, or not disclosed), and applicant quality (high vs low). Race and quality are assigned with equal probability within each HCV condition; HCV=Yes and HCV=No each receive 32% of assignments and HCV=Not Disclosed receives 36%.

Race, voucher status, and quality for the second inquiry will be assigned conditional on assignments made for the first inquiry. We use pre-specified rules, as defined in our Pre-Analysis Plan, to generate second inquiry assignments.

We compare landlord responses and listing content before and after the October 1, 2026 policy changes.

Treatment effects will be estimated using regression models that compare outcomes across randomized treatment groups and policy periods, including interaction terms corresponding to the study’s primary hypotheses. Specifications include pre-specified covariates and fixed effects for listing and inquiry characteristics, with standard errors clustered at the landlord level. We also estimate higher-order interactions to test whether post-policy changes differ by race, HCV status, and applicant quality.

We describe these features in greater detail in our Pre-Analysis Plan.
Experimental Design Details
Not available
Randomization Method
Computer assigned randomization
Randomization Unit
The unit of randomization is one inquiry sent to a unique rental listing. Randomization of attributes for the first inquiry to a given listing will be conducted using pre-specified probabilities for 12 mutually exclusive treatment cells. Attributes for the second inquiry to a given listing will be conditional on randomly generated attributes of the first inquiry, and so will be partially deterministic and partially randomized, as defined in our Pre-Analysis Plan.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
There are no treatment clusters. Treatment is randomized at the individual listing-inquiry level.
Sample size: planned number of observations
Approximately 15,000 rental inquiries (approximately 5,000 in the pre-policy period and 10,000 in the post-policy period). The realized sample may be smaller because it depends on the number of eligible rental listings available during the sampling periods.
Sample size (or number of clusters) by treatment arms
Each sampled rental listing receives two inquiries. Treatment is assigned at the inquiry level using a blocked 2 (race) × 3 (HCV disclosure status) × 2 (applicant quality) design, with the two assignments within a listing jointly randomized subject to the prespecified pairing rules. Across the full set of inquiries, the design targets 50% Black-coded and 50% White-coded names, 50% high-quality and 50% low-quality inquiries, and approximately 25% HCV-Yes, 25% HCV-No, and 50% HCV-not-disclosed inquiries.

For a planned total sample of 15,000 inquiries, the target cell sizes are therefore:

HCV=Yes, White, Low Quality: 1,200
HCV=Yes, White, High Quality: 1,200
HCV=Yes, Black, Low Quality: 1,200
HCV=Yes, Black, High Quality: 1,200
HCV=No, White, Low Quality: 1,200
HCV=No, White, High Quality: 1,200
HCV=No, Black, Low Quality: 1,200
HCV=No, Black, High Quality: 1,200
HCV=Not Disclosed, White, Low Quality: 1,350
HCV=Not Disclosed, White, High Quality: 1,350
HCV=Not Disclosed, Black, Low Quality: 1,350
HCV=Not Disclosed, Black, High Quality: 1,350
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
University of Georgia Institutional Review Board
IRB Approval Date
2026-08-21
IRB Approval Number
N/A
Analysis Plan

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