Female Entrepreneurship and Trust in the Market

Last registered on November 19, 2024

Pre-Trial

Trial Information

General Information

Title
Female Entrepreneurship and Trust in the Market
RCT ID
AEARCTR-0014859
Initial registration date
November 18, 2024

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 19, 2024, 4:42 PM 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
Bocconi University

Other Primary Investigator(s)

PI Affiliation
LSE
PI Affiliation
Princeton University
PI Affiliation
Harvard University

Additional Trial Information

Status
In development
Start date
2024-10-23
End date
2025-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study examines whether improved contract enforcement disproportionately benefits female-led small-scale enterprises. Stronger enforcement mechanisms may enable women to overcome scale constraints and achieve better economic outcomes by fostering collaborative partnerships with others, particularly men. To investigate this, we design a lab-in-the-field experiment aimed at identifying the causal effects of institutional improvements on business performance and gender disparities. The intervention is designed uncover potential channels driving gender-specific effects.
External Link(s)

Registration Citation

Citation
Ashraf, Nava et al. 2024. "Female Entrepreneurship and Trust in the Market." AEA RCT Registry. November 19. https://doi.org/10.1257/rct.14859-1.0
Experimental Details

Interventions

Intervention(s)
This study explores how contract enforcement impacts trust and collaboration between businesses, focusing on gender dynamics. Through a lab-in-the-field experiment, we engage entrepreneurs in modified trust games with exogenous variation in institutional support and the potential gender bias of this support. These activities examine how institutional support influences decision-making and economic outcomes, particularly for female-led businesses.
Intervention Start Date
2024-11-19
Intervention End Date
2025-06-30

Primary Outcomes

Primary Outcomes (end points)
The primary outcome we are interested in is trust by the senders, measured as the number of tokens sent by the sender to the receiver, and gender differences in this measure across treatment arms.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
We will also explore effects on measures of: i) trustworthiness (return ratio by the receiver). Given that the receiver will play with a strategy method, we will compute the average return ratio across all possible amounts sent by the sender, ii) earnings of the sender and the receiver, iii) total surplus created (efficiency).
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Participants are small scale businesses located across markets in Lusaka, Zambia.
After a short survey, participants are assigned to participate in a trust game designed to simulate real-world economic interactions. In this game, a “sender” decides how much money to send to a “receiver” for a business opportunity framed as a partnership, knowing that the amount sent will be multiplied by three. The receiver then decides how much of the multiplied amount to return to the sender. To incorporate institutional support, senders are given the option to complain to the their market chief if they think the amount returned back by the receiver is not fair. The market chief acts as an adjudicator and decides on the final allocation of tokens (that represent real money). There are two experimental treatments: 1) in the gender-blind treatment, the sender can complain to the market chief with a complaint form that only shows to the chief the choices of the two players, nothing else about their identity, 2) in the gender-revealed treatment, the sender can complain to the market chief using a complaint form that also shows the sender’s gender, in addition to the choices made by the sender and the receiver in the game. The receiver knows that the sender can complain and that complaints keep both players’ identities anonymous, but does not know about the existence of two possible complaint forms.

The sampling strategy aims to achieve balance in gender and industry (manufacturing vs non manufacturing). Our main target industries for senders are manufacturers, hairdressers/barbers and restaurants. For receivers, we target all the remaining industries.

We complement this main experiment with three additional activities:
- At the end of the experiment, we elicit incentivized beliefs about the chief’s choices when s/he has to arbitrate complaints coming from men or women. The assignment of complaints brought by men or women will be randomized between subjects, stratifying by the main strata and treatment assignment. This exercises will give us a proxy of player’s perceptions of the chief’s gender bias in the game.

- We conduct a survey with the chiefs that are involved in the trust game which asks about their behavior in arbitrating inter-gender disputes, and also how they would arbitrate in different types of complaints coming from female or male player in the trust game. Chiefs will answer about a set of trust game complaints for both female and male players, so we can compare differences in their arbitration behavior between the two genders. The survey questions and the complaints’ questions will give us measures of the chief’s gender bias. For the survey questions, we will build an index of the chief’s gender bias as in Ashraf, Delfino & Glaeser (2022).

We will perform treatment heterogeneity analysis on measures of these perceived and actual chief’s gender bias measures, by gender.

- In the pre-games survey, we will ask several questions about the players’ experiences with their market chief, other institutions, disputes with other businesses and harassment in business. This will allow us to understand more broadly how past experiences may shape behavior in the game. We will do heterogeneity analysis also on this aspect.

The main hypothesis is that trust by women in the gender-revealed arm will depend on the perceived and/or actual gender bias. Women may send more (less) in the gender-revealed treatment than the gender-blind one if they think the chief is biased in favor of (against) women.
Experimental Design Details
Not available
Randomization Method
Randomization occurs at several stages to ensure representative sampling and balance in treatment assignment. The order in which enumerators approach potential participants is randomized within gender and industry categories to ensure representativeness.

Treatment assignment is stratified by market, industry (manufacturers vs non-manufacturers) and gender.

Randomization happens on the spot in the field according to pre-determined assignment rules (which are based on the random interview order within gender and industry).
Randomization Unit
Individual (= business owner or main manager)
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
500 to 600 participants
Sample size: planned number of observations
250 to 300 men, 250 to 300 women across 10 to 15 markets
Sample size (or number of clusters) by treatment arms
Between 120 and 150 participants in each of the two treatment arms
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
ERES Converge
IRB Approval Date
2024-10-23
IRB Approval Number
2024-Jul-010
IRB Name
LSE
IRB Approval Date
2024-06-13
IRB Approval Number
395658
IRB Name
Bocconi University
IRB Approval Date
2024-07-29
IRB Approval Number
RA000771