Measurement of the Use of Instant Retail Payments

Last registered on March 03, 2025

Pre-Trial

Trial Information

General Information

Title
Measurement of the Use of Instant Retail Payments
RCT ID
AEARCTR-0015381
Initial registration date
February 26, 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
March 03, 2025, 8:16 AM EST

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
University of Sydney

Other Primary Investigator(s)

PI Affiliation
William and Mary
PI Affiliation
National University of Singapore
PI Affiliation
Ateneo de Manila University

Additional Trial Information

Status
In development
Start date
2025-04-01
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
An important methodological challenge for research on instant payment systems (IPS) is the measurement of use of instant payments. While in principle it would be desirable to access administrative data on payments, in practice it can be challenging to obtain access to private financial data, such as barriers to forming the necessary legal agreements with financial institutions or other data owners. Meanwhile, alternative data collection methods such as surveys can face challenges from recall bias.

The measurement of off-net payments raises even greater challenges for survey data collection than studies on other digital financial services (DFS), because it further challenges the respondent to recall off-net and on-net payments separately. Hence it is an open question to what extent relying on surveys leads to measurement bias relative to administrative data (which may not always be available), and whether there are alternatives to surveys that don’t rely on securing agreements with the parties that own and manage administrative data.

Working with an FSP partner providing access to transaction-level administrative data, this study aims to quantify the measurement bias and behavioral distortions from other data collection methods for the use of instant payments, including: (1) low-frequency survey, (2) high-frequency surveys, and (3) downloading transaction extracts. The study promises to contribute to fundamental insights for research on IPS, and more broadly on data collection in the context of DFS.
External Link(s)

Registration Citation

Citation
Gonzales, Joaquin et al. 2025. "Measurement of the Use of Instant Retail Payments." AEA RCT Registry. March 03. https://doi.org/10.1257/rct.15381-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The study tests alternative methods for the decentralized collection of data on the use of instant payment systems (IPSs).
Intervention Start Date
2025-04-01
Intervention End Date
2025-06-30

Primary Outcomes

Primary Outcomes (end points)
We are primarily interested in two sources of bias in using decentralized data collection methods to proxy more reliable sources such as administrative transaction data:
1. Selection bias. We will primarily quantify this through "meta" outcomes such as response rates and refusal rates.
2. Measurement bias, conditional on response. This will be based on measures of the use of instant payment transactions, principally transaction timing and frequency, and amount (monetary value).

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We will collect additional outcomes, such as respondents' satisfaction with different data collection methods.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study will randomly assign participants to a number of treatment groups, which will each be exposed to a different method for measuring their transaction behavior on an instant payment system.
Experimental Design Details
Not available
Randomization Method
Individual-level randomization done by computer (Stata).
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000
Sample size: planned number of observations
2000 individuals
Sample size (or number of clusters) by treatment arms
2000
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
NA; since we are testing measurement strategies, we are primarily interested in (1) documenting the extent of attrition or refusal for each method, (2) quantifying measurement bias conditional on response, comparing the decentralized methods to the administrative data. We will also quantify the extent of experimenter demand bias by comparing administrative data from respondents who receive the intervention and don't receive it, and the extent of experimenter demand bias caused by the initial consent/recruitment process, by comparing administrative data of an anonymous, uncontacted sample, to the sample that consents but does not receive an intervention.
IRB

Institutional Review Boards (IRBs)

IRB Name
Innovations for Poverty Action Institutional Review Board
IRB Approval Date
2024-11-07
IRB Approval Number
17225