Labeling Effect in Social Benefit Take-Up

Last registered on September 29, 2025
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Pre-Trial

Trial Information

General Information

Title
Labeling Effect in Social Benefit Take-Up
RCT ID
AEARCTR-0016007
Initial registration date
September 24, 2025

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 29, 2025, 10:42 AM EDT

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

Locations

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Primary Investigator

Name
Vanessa Sticher
Affiliation
MIT
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2025-09-25
End date
2026-12-31
Keywords
Behavior, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Previous research has established that benefit labels influence spending decisions, leading recipients toward spending in labeled categories even when benefits are fungible. In this project, I study whether labels similarly affect individuals' decisions to apply for benefits, proposing that mental accounting---allocating money to specific categories and failing to reallocate---shapes these decisions.
I will conduct an experiment with individuals who are potentially eligible for benefits. Participants provide information about their financial situation and indicate expense categories in which they face financial strain. Then, they see information about a benefit program and are asked if they are interested in learning more about the program and how to apply. I randomize the program suggestion: the program label matches the category of financial strain ("match"), the program does not match the category of financial strain ("mismatch"), or the program does not have a label that is linked to a category ("generic"). I will test whether alignment of program label and financial strain affects interest in the program. I additionally elicit participants' beliefs about the program (e.g., eligibility, perceived helpfulness etc.).
External Link(s)

Registration Citation

Citation
Sticher, Vanessa. 2025. "Labeling Effect in Social Benefit Take-Up." AEA RCT Registry. September 29. https://doi.org/10.1257/rct.16007-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Participants are recruited from Prolific, screened to be live in the US and being potentially eligible for benefit programs. I define being potentially eligible as follows: Prolific screener question on after-tax household income < (0.9*[200% FPL amount for relevant household size] rounded to the nearest 10,000).

The intervention is a Qualtrics survey that randomly varies whether participants are suggested a benefit program that matches their main reported financial strain (match), does not match (mismatch), or has a generic label (control).
Intervention Start Date
2025-09-25
Intervention End Date
2025-09-29

Primary Outcomes

Primary Outcomes (end points)
Binary indicator for whether the participant clicks the link leading to official government website about the program
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Beliefs about the program (eligibility, perceived helpfulness...)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants first answer questions on demographics, household characteristics, and household financial situation (income, spending, benefits etc.). Next, they are asked if struggle to afford items in different categories. Participants are then randomized into one of three arms and suggested a program: (i) match: program label matches a category they struggle with (e.g., SNAP for food); (ii) mismatch: program label does no match a category they struggle with (e.g., Section 8 for food); or (iii) control: program label is generic (e.g., TANF). Participants who do not yet participate in the program they would be suggested see the suggestion and are then asked questions about their beliefs about the program and shown a link to the respective program's official website.
Experimental Design Details
Not available
Randomization Method
Qualtrics' built-in randomization function.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Equal to the number of observations (see below)
Sample size: planned number of observations
I intend to recruit 4,000 individuals. There is some uncertainty if I can recruit that many individuals given the Prolific pool size and the screening criteria.
Sample size (or number of clusters) by treatment arms
Participants are randomized into the three arms: 1/3 control, 1/3 mismatch, 1/3 match.

The treatment can only be implemented if there is a combination of reported financial strain categories and programs the participant does not currently receive that fits the treatment arm alignment criteria. This restriction will determine the final sample size.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Committee on the Use of Humans as Experimental Subjects (COUHES)
IRB Approval Date
2024-11-15
IRB Approval Number
2410001467
Analysis Plan