Unpacking the Gender Profit Gap: Evidence from Micro-Businesses in India

Last registered on October 16, 2018

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Pre-Trial

Trial Information

General Information

Title

Unpacking the Gender Profit Gap: Evidence from Micro-Businesses in India

RCT ID

AEARCTR-0003180

Initial registration date

July 31, 2018

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

August 03, 2018, 3:08 PM EDT

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

Last updated

October 16, 2018, 11:20 PM EDT

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

Locations

Country

India

Region

Rajasthan

Primary Investigator

Name

Solene Delecourt

Affiliation

UC Berkeley - Haas School of Business

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Odyssia Ng

PI Affiliation

Stanford University

Contact Investigator

Additional Trial Information

Status

In development

Start date

2018-08-06

End date

2019-01-31

Keywords

Firms & Productivity, Gender

Additional Keywords

JEL code(s)

Secondary IDs

Abstract

Large gender differences in earnings prevail worldwide in almost all occupations, and entrepreneurship is no exception. Women’s businesses are typically less productive, but also smaller and less capital-intensive than men’s. Despite the vast literature reporting the gender gap in profitability, its causes are not well understood. Our study examines the role of business characteristics and discrimination on gender disparities in profitability. We study small-scale produce businesses in India. We first conduct a survey to establish that women’s businesses are both less profitable and smaller than men’s in this context. Using a large-scale field experiment, we test whether giving men and women the same business closes the gap in profitability. We set up our own market stalls, to which we randomly assign male and female vendors. We thus exogenously vary gender, holding the business constant. The evidence from this experiment shows how much of the gender gap in this context is due to business characteristics alone. To examine the role of client discrimination more specifically, we conduct a second experiment with packaged goods instead of vegetables.

External Link(s)

Registration Citation

Citation

Delecourt, Solene and Odyssia Ng. 2018. "Unpacking the Gender Profit Gap: Evidence from Micro-Businesses in India." AEA RCT Registry. October 16. https://doi.org/10.1257/rct.3180-2.0

Former Citation

Delecourt, Solene and Odyssia Ng. 2018. "Unpacking the Gender Profit Gap: Evidence from Micro-Businesses in India." AEA RCT Registry. October 16. https://www.socialscienceregistry.org/trials/3180/history/35810

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Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2018-08-21

Intervention End Date

2019-01-31

Primary Outcomes

Primary Outcomes (end points)

Variables at the vendor level: Daily profit, daily revenue,number of "missed" clients, number of purchasing clients
Variables at the vegetable level: quoted price, price paid.

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Variables at the vendor level: number of male/female clients who approached and buy from the stall, inventory, markup per Rs.
Variables at the vegetable level: discount (bargaining).

Secondary Outcomes (explanation)

Experimental Design

Our main experiment consists in setting up vegetable stalls in a retail market, recruit one male and one female vendor every day to sell vegetables that we provide, and randomly assign the vendors to the stalls. Every day, we purchase vegetables from the wholesale market and equally divide them among the two stalls. Our experimental design enables us to exogenously vary gender, holding the business characteristics - quantity, quality of produce, location - constant. It is a form of extreme capital drop intervention: we provide vendors with the exact same business. To incentivize vendors to sell, they keep the day’s profits and are only charged for the vegetables they are able to sell.

We run the same experiment with packaged goods that are sold by men and women. To measure discrimination, we decrease the price of the packaged goods sold by women for a randomly chosen part of the day.

Experimental Design Details

Randomization Method

For recruitment: randomization done on the tablet through the software SurveyCTO.
Other randomizations are done in office by a computer (Stata). We select a random pair of one man and one woman to be assigned to our daily stalls.

Randomization Unit

We randomize at the individual level as we assign individuals to stalls.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

250 individuals (125 men and 125 women) for the vegetable experiment.
At least 60 individuals (30 men and 30 women) for the packaged goods experiment, depending on funding, we hope to get at least 100.

Sample size: planned number of observations

250 individuals (125 men and 125 women) for the vegetable experiment. At least 60 individuals (30 men and 30 women) for the packaged goods experiment, depending on funding, we hope to get at least 100.

Sample size (or number of clusters) by treatment arms

125 men and 125 women for the vegetable experiment.
At least 60 individuals (30 men and 30 women) for the packaged goods experiment, depending on funding, we hope to get at least 100.

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

Supporting Documents and Materials

IRB