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Promoting digital payments technology among female migrant factory workers
Last registered on March 04, 2020

Pre-Trial

Trial Information
General Information
Title
Promoting digital payments technology among female migrant factory workers
RCT ID
AEARCTR-0005455
Initial registration date
March 03, 2020
Last updated
March 04, 2020 12:00 PM EST
Location(s)
Region
Primary Investigator
Affiliation
University of Michigan
Other Primary Investigator(s)
PI Affiliation
UMich
PI Affiliation
IDInsight
Additional Trial Information
Status
On going
Start date
2019-11-08
End date
2020-04-30
Secondary IDs
Abstract
Many of the female workers at Shahi Exports, our industry partner, are rural migrants who move temporarily to the city due to financial distress in their villages. According to our exploratory research and baseline data, they tend to remit a large share (close to 50%) of their wages back home. The standard modus operandi is to cash out their salary from their bank account and transfer the money through over-the-counter agent/shopkeeper services (92% of our sample at baseline). By saving time and money, digital payment services have the potential to improve their financial wellbeing.

While these workers are aware of the existence of digital payment platforms, our scoping work and baseline data showed that they do no know how to use digital payment apps and are wary of losing money on these platforms (i.e., the level of trust in digital transfer technology is low). In addition to this, workers face other issues that prevent them from signing up for and using digital payment applications.

In this context, the research studies the impact of training female migrant workers in India to use digital payment applications. Our team, a collaboration between Good Business Lab and IDinsight, in conjunction with Shahi Exports, designed a randomized controlled trial that studies the effect of a workplace intervention -- training sessions to use a digital payments application -- on take-up and use of digital payment applications. The study sample size is 819 migrant women, randomized at the individual level, and split equally across three experimental arms.

We are interested in studying the extent to which training programs of differing intensities may be effective and cost-efficient in improving take-up.
External Link(s)
Registration Citation
Citation
Adhvaryu, Achyuta, Karan Nagpal and Anant Nyshadham . 2020. "Promoting digital payments technology among female migrant factory workers ." AEA RCT Registry. March 04. https://doi.org/10.1257/rct.5455-1.0.
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Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2020-01-27
Intervention End Date
2020-02-05
Primary Outcomes
Primary Outcomes (end points)
1. Use of digital payment applications for remittances
In the primary surveys, we ask whether the respondent uses digital payment applications to remit money. The variable is coded as 1 if the respondent reports using any of the following channels to remit money: mobile money, UPI-based digital payments app, net banking/bank application, and 0 otherwise.



2. Effectiveness of training sessions
During the training sessions, we collect data on whether the participant can send money to someone’s UPI id. It is coded as 1 if she can send money to someone’s UPI id during the session, and 0 otherwise.

During the training sessions, we also collect data on whether the participant can send money to someone’s bank account similar to the modus operandi to remit home through digital payment platforms. It is coded as 1 if she can send money with someone’s bank account during the session, and 0 otherwise. We will use this as a robustness check.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
3. Quantification of the extent of the different barriers:
We collect the following indicators from the participants during the training sessions, which are all the necessary steps enabling participants to send and receive money:
1) Whether the participant attended the training
2) Whether the participant has her mobile phone linked to her bank account
3) Whether the participant has mobile balance to send verification SMS from her phone
4) Whether the participant has the required elements (ATM card, mobile phone and SIM card)
5) Whether the participant was able to download the app
6) Whether the participant was able to set up her UPI id

4. Use of digital payment applications for non-remittance purposes

We collect data on whether the respondent uses her phone for the following tasks:
1) to make bill payments, not for goods
2) to buy goods
3) to receive money from someone living in the city
4) to receive money from someone living outside of the city
5) to repay money she had borrowed
6) to lend money to someone

We will create an outcome variable equal to one if any of the above indicators is 1 and 0 otherwise.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The eligible population for the study is female garment workers at Shahi Exports Private Limited, Karnataka, India, who live in 19 selected Janodaya hostels (Janodaya is the NGO managing migrant hostels linked to Shahi factories). Our sample consists of 819 migrant women in these 19 hostels, all of whom use smartphones.
There are two treatment arms and one control arm. Both treatment arms include information on digital payments with facilitated sign-up, opportunities for practice, and financial incentives.

Randomization was carried out at the individual level, stratified by units and reported mobile phone registration at baseline. Within each stratum, a third of the sample was randomized into the soft intervention treatment group (n=273), a third of the sample was randomized into the intensive intervention treatment group (n=273), while the remaining third of the sample in a control group (n=273) did not receive any intervention.

The unit of analysis is the individual/respondent. The primary unit of treatment is also the individual. We chose to conduct randomization at the individual-level as we believe spillover risks are very limited, considering the barriers at stake.
Experimental Design Details
The eligible population for the study is female garment workers at Shahi Exports Private Limited, Karnataka, India, who live in 19 selected Janodaya hostels (Janodaya is the NGO managing migrant hostels linked to Shahi factories) and own a smartphone. These hostels were sampled out of convenience and availability but reflect the overall population of migrant workers in Shahi garment industry in the Karnataka region. Our sample consists of 819 migrant women in these 19 hostels, all of whom use smartphones.
There are two treatment arms and one control arm. Both treatment arms include information on digital payments with facilitated sign-up, opportunities for practice, and financial incentives. In the “Classroom treatment” arm, the batch size is between 20 and 30 participants per trainer; in the “Individualized treatment” arm, one trainer works with up to 5 participants. Participants in both treatment arms also receive two reminder SMS messages.

Randomization was carried out at the individual level, stratified by units and reported mobile phone registration at baseline. Within each stratum, a third of the sample was randomized into the soft intervention treatment group (n=273), a third of the sample was randomized into the intensive intervention treatment group (n=273), while the remaining third of the sample in a control group (n=273) did not receive any intervention.

The unit of analysis is the individual/respondent. The primary unit of treatment is also the individual. We chose to conduct randomization at the individual-level as we believe spillover risks are very limited, considering the barriers at stake.

With only two treatment arms, this impact evaluation will not provide evidence on the relative effects of each intervention type (training sessions and SMS reminders). We expect the bundle (training plus SMS reminder) to have a stronger effect than smaller combinations (training sessions and SMS reminders alone). We do not expect any negative complementarities between the interventions.
Randomization Method
Randomization took place using the statistical software package Stata. We conducted randomization using the following procedure:
1) Collect baseline data from hostels: Prior to randomization, we conducted baseline data collection in 19 hostels, saturating each hostel
2) Stratified random assignment by unit and mobile registration dummy: Within each stratum, we randomly assigned a third of the sample to control, a third of the sample to the soft intervention and a third of the sample to the intensive intervention. In case the total number of individuals in a stratum is not divisible by 3, we randomly decided whether the last individual (and second-last individual) was in either of the treatment arms or control.

We conducted randomization once, after baseline was completed.

Randomization Unit
Randomization took place at the individual level
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
819 participants (migrant women)
Sample size: planned number of observations
819
Sample size (or number of clusters) by treatment arms
273 (equally divided)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
10pp
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Good Business Lab
IRB Approval Date
2019-11-08
IRB Approval Number
N/A
Analysis Plan
Analysis Plan Documents
Financial Inclusion : promoting digital payments among migrant factory workers

MD5: 11809d66c248ced385da3c3a297cbb6b

SHA1: 27d98f7e274b1123868e5151bf0a643fce10f3df

Uploaded At: March 03, 2020

Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS