E-Government for social benefits

Last registered on May 09, 2024

Pre-Trial

Trial Information

General Information

Title
E-Government for social benefits
RCT ID
AEARCTR-0013095
Initial registration date
April 26, 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 09, 2024, 1:21 PM 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

Affiliation
ETH Zürich

Other Primary Investigator(s)

PI Affiliation
University of Zurich, Department of Economics
PI Affiliation
ETH Zurich, Department of Humanities, Social and Political Sciences

Additional Trial Information

Status
In development
Start date
2024-04-29
End date
2030-12-31
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
Using a randomized controlled study, we will investigate the role of digital application forms, as a potential barrier in the application process for individual health insurance subsidies. For this purpose, all eligible individuals are randomly divided into two groups (digital-only and digital & paper). The aim of this study is to understand the effects of e-government on the application rate for social benefits. The study design allows us to analyze the effects of the digital application barrier for different socio-economic groups on the number of applications and downstream effects on financial outcomes.
External Link(s)

Registration Citation

Citation
Hangartner, Dominik, Flavia Hug and Michel Maréchal. 2024. "E-Government for social benefits." AEA RCT Registry. May 09. https://doi.org/10.1257/rct.13095-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The experiment is conducted by a public institution in Switzerland. Each year, they send out a letter and an application form to approximately 30% of the households who are likely eligible for the health insurance subsidy. The field experiment is implemented by the collaboration partner with approximately 380,000 tax households. The current mailing includes two options to apply: (i) utilizing provided login code for online application or (ii) employing the provided paper application for mail submission. The partner organization is considering eliminating the paper application from their mailing.

We assist the partner organization in evaluating a phased implementation of the new digital-only policy, enabling us to gauge the policy's beneficiaries and those disadvantaged by its adoption. The experimental groups will either only receive access to the digital application form or to the digital and the paper application form.

Based on tax data the households are classified as likely eligible for health insurance subsidies. After restricting the experimental sample to households without prior experience with the digital application, they are randomly assigned to one of two experimental groups: either to the control condition (i.e., digital & paper) or to a treatment condition (i.e., digital-only).
Intervention Start Date
2024-05-25
Intervention End Date
2026-03-31

Primary Outcomes

Primary Outcomes (end points)
Our primary outcome is whether tax households apply for health insurance subsidies before the deadline in March 2026. We will assess this outcome for the entire study population.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We will try to obtain and explore two types of downstream outcomes. First, the downstream financial outcomes are whether an individual has an entry in the debt registry (i.e., “Betreibung”) and subsequently the health insurer’s certification for losses (i.e., “Verlustschein”). These outcomes encompass defaults on various types of bills from the health insurance and are not limited to premium payments. These measures will rely on the 2025 and 2026 data from the health insurance providers.

Second, the labor market outcomes will be assessed with the census data.

We will also try to explore whether the treatment has a spillover effect on other applications administered on the government level. For instance, people might benefit from the positive experience with the health insurance subsidy and are more likely to also apply for other assistance.
There are various types of other social benefits, but we are specifically interested in two additional outcomes that help people facing financial hardship: social aid ("Sozialhilfe") and supplementary pension benefits (e.g., "Ergänzungsleistung") that are linked to old-age and disability pensions. Social aid is managed at the municipal level, while supplementary pension benefits, like health insurance subsidies, are administered through the partner organization at the cantonal level.

The uptake of these social benefits may face similar barriers as the health insurance subsidy, as people's knowledge and experiences with one can shape their perceptions of the costs and benefits of other social benefits, potentially impacting the take-up. This data is possibly available from the partner organization.

A further government service that could be affected are applications for naturalizations. They are administered on the municipality level and the data could be accessed at the census level. For both categories, it is unclear if the data availability is feasible in this project.
We are primarily interested in the effect of the treatment on the propensity to submit an application. However, only households that apply and are in fact eligible will be granted the subsidy. The data on whether individuals were granted the health insurance subsidy is dependent on the 2025 tax data and will only be available after the year 2027.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Households will be assigned to either the control condition (digital & paper) or the treatment condition (digital-only). The control condition serves as the baseline for subsidy uptake, mirroring the status quo. It consists of three components: (i) a letter containing login data for the digital application, (ii) an application form in paper format, accompanied by an unstamped return envelope, and (iii) a collection of frequently asked questions (FAQ) to assist with the application process. In contrast, households assigned to the treatment condition will receive the same mailing as those in the control group, with one exception: the omission of the paper application form.

By comparing the outcomes between the control and treatment groups, we can assess the potentially heterogeneous impact of the digital-only policy on application rates.
Experimental Design Details
Not available
Randomization Method
Based on tax data, the project partner classified tax households as potentially eligible or ineligible for health insurance subsidies. Our unit of observation is the tax households that may consist of single individuals, married couples with or without underage children, or adult children. Consequently, a residential household, defined by the living unit, such as an apartment or house, can encompass multiple distinct tax households. Residential households are defined based on Swiss federal building and apartment identifiers (i.e., EGID, EWID). We cluster the treatments on these residential households to reduce spillovers.

After the eligibility and treatment clusters are defined, two steps are required to obtain the experimental groups: (i) sample restriction and (ii) group assignment. First, the study population is restricted to residential households, where no one has applied online in the last year. Clusters with previous experience with the online application are excluded from the experimental sample. Second, treatment clusters with tax households that are newly eligible in this year, have never applied before, or everyone has previously applied with the paper application will be randomly assigned to one of the two experimental groups with equal probability.

The randomization will be conducted by the research team, using the software R. We will then send the assigned treatment indicators to the social insurance office. These groups are then used to create batches that are sequentially forwarded for printing. The envelopes include letters informing tax households about their potential eligibility and how they can apply. The envelopes are assembled within these treatment batches to prevent mistakes. However, everything will be dispatched on the same day.
Randomization Unit
Residential households based on federal building and apartment identifier
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Approximately 136,000 residential households
Sample size: planned number of observations
Approximately 175,000 tax households
Sample size (or number of clusters) by treatment arms
Treatment Group: 87,500 tax households
Control Group: 87,500 tax households
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
OEC Human Subjects Committee, Faculty of Business Economics and Informatics, University of Zurich
IRB Approval Date
2024-03-06
IRB Approval Number
OEC IRB # 2024-020