Adapting and Validating WEE Indicators in an Experimental Study of Savings

Last registered on November 30, 2022

Pre-Trial

Trial Information

General Information

Title
Adapting and Validating WEE Indicators in an Experimental Study of Savings
RCT ID
AEARCTR-0010534
Initial registration date
November 29, 2022

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
November 30, 2022, 5:00 PM EST

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

Locations

Region

Primary Investigator

Affiliation
Harvard Kennedy School

Other Primary Investigator(s)

PI Affiliation
FINCA International
PI Affiliation
University of San Francisco

Additional Trial Information

Status
On going
Start date
2022-10-11
End date
2024-05-30
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This measurement study is part of a larger randomized controlled trial (RCT) that aims to produce evidence on how goal-based digital savings accounts and services might improve the financial health and well-being of low-income people in Uganda. Preliminary data from the RCT revealed that women were more responsive to financial coaching than men. This discovery is in line with existing research that illustrates the potential for DFS to empower women. However, in order to advance this understanding, more work is needed to improve and expand the measurement of women’s economic empowerment (WEE) indicators with a focus on context-specific indicators.

Layering a measurement study onto the existing RCT will help uncover why women are more responsive than men to financial coaching and savings. Additionally, the study will identify how these interventions contribute to women’s agency, defined as setting goals, acting on them, and achieving them. The measurement study will be informed by qualitative research that is already underway. Utilizing input from two complementary investigative techniques, focus group discussions (FGD) and cognitive interviews (CI) iteratively, indicators are being developed and adapted to a Ugandan context (content validation). The measurement study involves increasing the female sample size in the RCT from 400 to 1,600 women (1,200 additional women will be recruited) to allow for more variables associated with WEE to be included in the analysis. The women will be evenly split between a treatment and a control group. In the treatment arm, the sample population will receive personalized financial coaching emphasizing the importance of savings. Finally, the third stage will consist of construct validation using machine learning algorithms that will identify which WEE indicators have the greatest classification power and the strongest ability to predict women’s agency demonstrated by the aptitude to devise concrete savings goals, achievement of goals and the ability to act upon these goals.
External Link(s)

Registration Citation

Citation
Agasha, Ester, Joeri Smits and Anahit Tevosyan. 2022. "Adapting and Validating WEE Indicators in an Experimental Study of Savings." AEA RCT Registry. November 30. https://doi.org/10.1257/rct.10534-1.0
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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-12-15
Intervention End Date
2024-05-30

Primary Outcomes

Primary Outcomes (end points)
Savings outcomes are transaction counts and account balances. A main aim of the study is to obtain a set of construct-validated WEE indicators with strong classification power in profiling women who are (as measured by their savings behavior and response to the coaching treatment), able to set, act-upon and achieve savings goals.
Primary Outcomes (explanation)
Through qualitative research (Focus Group Discussions, Cognitive Interviews) prior to commencement of this trial, a set of candidate questions was identified as being potentially associated with women's’ ability to set, act upon, and achieve savings goals. These questions will be included in the end line survey of the trial. Construct validation using machine learning algorithms will then identify which WEE indicators have the greatest classification power and the strongest ability to predict women’s agency demonstrated by the aptitude to devise concrete savings goals, and the ability to act upon (as measured by transaction counts) and achieve these goals (account balance, % progress towards the savings goal).

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
1200 new female clients are recruited from churches, local social welfare groups, medical associations and other women groups churches and public gathering places around the 28 FINCA Uganda branches by explaining the account features of the FINCA Goal account, which is a commitment savings account with one free withdrawal per month. New clients set personal savings goals during onboarding. After having opened an account, half of these new female clients are randomized into being offered savings coaching by phone and SMS.

The experimental design of the 400 female clients that are part of the analysis sample who were recruited earlier: see AEA registry #7378.
Experimental Design Details
Not available
Randomization Method
Programmed into the recruitment tool
Randomization Unit
Household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
All 28 branches of FINCA Uganda
Sample size: planned number of observations
1600 women (400 from RCT, 1200 newly recruited women)
Sample size (or number of clusters) by treatment arms
The 400 female clients from the completed RCT sample were assigned randomly to bare account, savings-driven loan, and savings coaching (probability 1/3rd each), see its AEA registry #7378. The 1200 newly recruited female clients are randomized into half (600) bare account and half (600) savings coaching.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
MUREC
IRB Approval Date
2022-10-11
IRB Approval Number
#REC REF 1003-2021