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Can Discounted Withdrawal Fees Catalyse Mobile Money Usage? Field Experimental Evidence from Gambia

Last registered on October 12, 2018

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Pre-Trial

Trial Information

General Information

Title

Can Discounted Withdrawal Fees Catalyse Mobile Money Usage? Field Experimental Evidence from Gambia

RCT ID

AEARCTR-0003372

Initial registration date

October 02, 2018

Last updated

October 12, 2018 5:13 PM EDT

Location(s)

Country

Gambia

Region

West Africa

Primary Investigator

Name

Hamidou Jawara

Affiliation

University of The Gambia

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2018-11-01

End date

2019-08-31

Keywords

Finance & Microfinance

Additional Keywords

Mobile money, transaction cost subsidies, developing countries, Gambia

JEL code(s)

D13, G21, O16, P34

Secondary IDs

PIERI 20165

Abstract

Digital financial products like mobile money are becoming ubiquitous in developing countries. Due to low access to financial services and high access to mobile phones, offering of financial services via mobile phones is heralded as an important tool that can revolutionize financial services adoption and usage in developing countries thereby fostering rapid financial inclusion. However, despite becoming rampant in many developing countries, the role of mobile money in revolutionizing formal financial account access and usage has so far been modest. One reason for this is that marginal costs of the services, such as transaction cost, remain high; in fact, in some cases, the cost are even higher than what commercial banks asked for similar services. Thus, such high cost can limit the attractiveness of digital products like mobile money. Therefore, in this project, we study whether subsidizing cash out fees could stimulate more adoption and usage of mobile services. In other words, we study the responsiveness of usage of mobile money services to changes in price of cash-out fees. To this effect, we use a randomized field experiment where we randomly vary the cost of cash-out charges among some randomly selected clients of a private mobile money service provider in Gambia called Qodoo. The clients are randomly assigned to one of three different withdrawals fees discount: 0%, 15% and 30%. We then study how the adoption of the new offer and usage of their mobile money accounts varies across different withdrawal or cash-out fees subsidies. Thus, by experimentally varying one element of transaction fee (cash-out fees) we can determine how this is relevant for usage rates.

External Link(s)

project description at website of Partnership for Economic Policy (PEP)

Registration Citation

Citation

Jawara, Hamidou. 2018. "Can Discounted Withdrawal Fees Catalyse Mobile Money Usage? Field Experimental Evidence from Gambia." AEA RCT Registry. October 12. https://doi.org/10.1257/rct.3372-4.0.

Former Citation

Jawara, Hamidou. 2018. "Can Discounted Withdrawal Fees Catalyse Mobile Money Usage? Field Experimental Evidence from Gambia." AEA RCT Registry. October 12. https://www.socialscienceregistry.org/trials/3372/history/35687.

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Experimental Details

Interventions

Intervention(s)

Our trial target inactive clients of a mobile money service provider in Gambia. inactivity is determined by whether a client uses an account regularly or not. Specifically, we target clients that have not made any transaction with their wallets for three months before the start of our project. By targeting this group, we hypothesise that high transaction fees (i.e. withdrawal fees) could be among the reasons for low account usage among these clients. Hence, to test this hypothesis, we expose a random sample of these clients to three different withdrawal subsidies. Each withdrawal subsidy involves the discounting of the current withdrawal fees of the service provider.

Intervention Start Date

2018-12-01

Intervention End Date

2019-06-30

Primary Outcomes

Primary Outcomes (end points)

1. Average number of cash-outs per month
2. Average number of cash-ins per month
3. Monthly average net Wallet balance
4. Average number of transfers per month

All the above stated outcomes will be collected from the administrative data of the partner financial institution. They will keep track of how the participants are using their accounts during the intervention and will share this information with us regularly.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

cash-out fees

Secondary Outcomes (explanation)

Experimental Design

In this experiment, we create exogenous variation in withdrawal fees to identify the effect of withdrawal subsidies on usage of mobile money services. To this effect, our experiment consists of three experimental arms; one control arm and 2 treatment arms. The three arms are one of three withdrawal fee discounts: 0%, 15%, and 30%. Selected Qodoo clients for the experiment are assigned to one of these three arms or withdrawal fee discounts. Therefore, the control group will consist of clients in the experimental sample that is randomly assigned to the 0% withdrawal discount. The two treatment arms, therefore, consist of participants in the experimental sample who are randomly assigned to either the 15% or 30% withdrawal discount treatment. For all treatments, the withdrawal fee discounts involve the discounting of the current cash-out schedule of the partner financial institution (Qodoo mobile money) by the withdrawal discount of the respective treatment, and is applicable to transaction amounts not more than 5,000.

Experimental Design Details

Randomization Method

Simple random assignment of selected participants into control and treatment arms. Randomization will be done using STATA.

Randomization Unit

In-active Clients of Qodoo Financial Services. That is Clients that have not used their wallets for three months before our Intervention.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

2625 inactive clients

Sample size: planned number of observations

2625 In-active clients

Sample size (or number of clusters) by treatment arms

Allocation of sample to 3 arms: 40% (1050 clients) to control and 60% (1575 clients) to treatment arm. Each treatment arm receives 1/2 of the 60% (about 788 clients).

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

The parameters used for the power analysis are calibrated based on net wallet balance and cash-ins of the target group, and sample size is determined after adjusting for 54% take-up rates; take-up rates in the literature ranges from 8.7% in Karlan & Zinman (2009) to about 54.7% in Kast et al. (2016). Thus, our assumption on take-up rates is on the upper bound of the range found in the literature. This is motivated by the fact that the intervention target existing clients, and there are strong incentives for participation. We also assume a MDE of 0.135 standard deviations on net monthly wallet balance and cash-ins; this is in line with the literature (such as Dupas et al.,2016; Karlan and Zinman, 2018) who find similar effect size for account balance in the case of commitment savings. Furthermore, we assume a 5% level of significance and 80% level of power.

Supporting Documents and Materials

IRB

INSTITUTIONAL REVIEW BOARDS (IRBs)

IRB Name

Partnership for Economic Policy PIERI Ethics Committee

IRB Approval Date

2018-08-24

IRB Approval Number

N/A

Analysis Plan