Entry in Digital Financial Markets

Last registered on January 01, 2024


Trial Information

General Information

Entry in Digital Financial Markets
Initial registration date
September 15, 2020

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
September 17, 2020, 8:08 AM EDT

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

Last updated
January 01, 2024, 3:49 AM EST

Last updated is the most recent time when changes to the trial's registration were published.


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Primary Investigator

University of California, Berkeley

Other Primary Investigator(s)

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
How do markets reorganize endogenously when there is exogenous entry of new entrants? When and how does this influence consumer demand and trust? We study this in the context of markets for retail digital financial services (DFS) / mobile money in Ghana. As markets for DFS evolve, new actors will enter the business environment; thus, influencing market competition. How these markets will reorganize themselves under entry and competition is an important and first-order question, yet poorly understood. We ask, specifically — (i) what price and non-price dimensions do retail mobile money businesses compete on (Quality or Firm Conduct or Transparency or Location)?; (ii) what are the general equilibrium impacts of competition on incumbents and other businesses?; (iii) can retail DFS unlock the potential of existing small business retailers — by adding retail DF as another line of business?; (iv) when and how does the induced competition affect consumer demand and trust in DFS? To answer these questions, we partner with MTN Mobile Money (the largest MNO-led DF provider) and GCB Ltd’s G-Money (the largest Bank-led DF provider) to randomize the expansion of new retail mobile money vendors across low-income localities.
External Link(s)

Registration Citation

Annan, Francis. 2024. "Entry in Digital Financial Markets." AEA RCT Registry. January 01. https://doi.org/10.1257/rct.6451-1.4
Sponsors & Partners

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Experimental Details


We randomize the expansion of new retail mobile money vendors across low-income localities. Our design creates 3 different exogenous variations at the locality / market-level — all guided by theory and practice — (i) some local markets receive the entry of new retail vendors vs not, (ii) for the entry localities, we vary the intensity of entrants across markets, and (iii) from an identified pool of “eligible“ local retail shops, we randomly onboard some as new mobile money vendors vs not.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
We successfully piloted our experiment (key protocols, instruments, proposed design, recruitment and enrollment processes) between January - June 2021.

(1) Producer welfare-related:
*Business outcomes (including: revenues, profits, number of customers, business expenses, employment, wagebill, household expenses) from market census and surveys, supplemented with administrative data (on sales revenue, vendor entry / exit, consumers' usage) from the commercial providers to examine broader impacts, including persistence and entry of new vendors across the localities.

(2) Consumer welfare-related:
(i) Misconduct - Quality: prices charged for retail services; overcharging consumers or illegal markups (incidence and severity).
(ii) Transparency: whether price list posted, visible and clear; including whether vendor attempts to inform consumers about transaction tariffs before conducting transaction (verbal disclosure of price).
(iii) Reliability - Quality: whether vendor is present/absent at the retail outlet; whether transaction successful; likelihood of vendors’ declining transactions due to liquidity shortfalls or poor liquidity management; both transaction and service times.
(iv) Innovation: bundling M-Money with other non-M-Money services (or expansions to other lines of business); including total exits; changing vendor locations; hours of operations; vendor's accessibility to previously unbanked / unserved households.
(v) Service - Quality: consumers' views and experiences about safety, privacy, invasion, harassment, discrimination, and respect after visiting vendor points.
We will adapt Annan (2020, 2021) audit study protocols (and surveys) to measure vendor outcomes objectively (and subjectively respectively). We will combine the outcomes to derive an index of overall service quality.
*We also plan to examine the impacts on consumers' usage and trust outcomes.
(i) We will field questions that will provide subjective measures of trust in M-Money providers, market vendors, carrying out vendor-involved transactions on M-Money, consumers’ family and friends, commercial and rural banks, and the regulator of financial services in Ghana (Bank of Ghana) if they have heard enough about them to say.
(ii) We will supplement this with objective measures of trust measured from trust games between consumers and their local vendors. In its simple form: this entails a real monetary payoff game between the consumers (i.e., trustors) and one randomly selected (anonymous) local vendor (i.e., trustee). We impose vendor anonymity to mitigate against issues of social and individual preferences. Consumers will be endowed with 40GHS and will decide how much to send to another person (i.e., M-Money vendor). We will triple it, so that the vendor receives three times the amount of money the consumer sent. The vendor will then decide how much he/she wants to send back to the consumer. The total payoffs depend on the choices made between the consumers and vendor. Our objective measure of consumer trust will reflect the amount they sent and expected the vendor to send back to them.

(3) Beliefs and expectations:
*For (all market participants: vendors, consumers, nearby stores), we plan to measure their beliefs and expectations about potential entry/competition effects if entry/competition is introduced on: (i) misconduct / overcharging, (ii) reliability / illiquidity (transaction declines due to liquidity shortfalls), (iii) transparency / tariff posting behavior of vendors, (iv) location of vendor's retail store, (v) innovation / bundling of M-Money with other non-M-Money services at agent points, (vi) consumer trust, and (vii) consumer experiences and usage.
*We will compare baseline expectations with observed effects.

(4) Heterogeneity:
*4 major dimensions (heterogenous TEs):
(i) baseline ex-ante vendor and consumer predictions about endline ex-post effects of entry (measure selection effects).
(ii) baseline no. of- + size of- incumbents x population (market strata).
(iii) geo-distance x competition (or x cooperation).
(iv) geo-distance x competition (or x unrelated test).
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Design: ~1/3rd of localities will randomly receive “no-entry” of new entrant vendors (Control program), while the remaining ~2/3rd of localities will receive entry of new entrant vendors (Treatment program). For the treatment localities, we will randomly vary the density of entering vendorships (i.e., new vendors who are not presently doing M-Money business but are local microentrepreneurs) from 1 to 3: half will receive 1 additional vendor each (Treatment I) and the other half will receive 3 additional vendors each (Treatment II). We refer to existing vendors as “incumbents” (averaging at 4-5 vendors per locality). Treatment I represents ~25% increase, while Treatment II represents ~67% increase in vendorship. We will use this to trace out impacts of the various exogenous vendor entry levels. In a locality, we will enroll only a random subset of eligible and existing microenterprises as new entrant vendors. Thus, overall, we create three experimental variations: (i) only a random subset of localities receive entry, so we can compare impacts of entered versus not; (ii) we vary the density of entry (1 vendor each=25% increase in vendorship versus 3 vendors each=67% increase in vendorship relative baseline vendorship), so we can trace out the equilibrium impacts of competition; and (iiii) we enroll only a random subset of eligible microenterprises, so we can compare business impacts on enrolled enterprises versus not enrolled.
Experimental Design Details
Not available
Randomization Method
Computer software and simple lotteries, while ensuring balance on observable characteristics (Bruhn and McKenzie [2009])
Randomization Unit
At the locality-level, and stratified by (i) population of locality (demand side) and (ii) number of incumbent vendors in locality (supply side).
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Number of localities (markets): 136
Number of districts (larger administrative units containing multiple localities): 13
Sample size: planned number of observations
(1). Number of “incumbent” retail vendors: 136 localities x roughly 4-5 per locality = ~627; (2). Number of “entrant” vendors: ~181 new entrant vendors, representing +45% combined increase in mean vendorship in treated markets; (3). Number of customers / households: 136 localities x roughly 35 per locality = ~4,765
Sample size (or number of clusters) by treatment arms
45 localities (Control program);
46 localities +1 entrant vendor each per locality (Treatment I);
45 localities +3 entrant vendors each per locality (Treatment II)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Georgia State University
IRB Approval Date
IRB Approval Number
IRB Name
UC Berkeley
IRB Approval Date
IRB Approval Number