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Does Greater Flexibility of Online labor Markets Encourage Female Participation? Evidence from Online Freelance Market

Last registered on November 18, 2021

Pre-Trial

Trial Information

General Information

Title
Does Greater Flexibility of Online labor Markets Encourage Female Participation? Evidence from Upwork
RCT ID
AEARCTR-0008570
Initial registration date
November 15, 2021

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 18, 2021, 12:10 PM EST

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

Locations

Region
Region

Primary Investigator

Affiliation
Southwestern University of Finance and Economics

Other Primary Investigator(s)

PI Affiliation
University of Western Australia Business School
PI Affiliation
University of Exeter Business School
PI Affiliation
Bentley University
PI Affiliation
University of Sussex Business School

Additional Trial Information

Status
In development
Start date
2021-11-15
End date
2021-12-12
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The online labor market affords greater flexibility that may favor women. And yet, female labor force participation in the online labor market remains limited. We conduct an online experiment on the freelance hiring platform Upwork to study the impact of greater flexibility in choosing work hours within a day on female participation. We post identical job advertisements that differ randomly only in job flexibility and the fee offered. We compare the responses to job postings with different levels of wages and flexibility to understand whether and how much women value flexibility. From the information collected in the pilot, we find that the share of women applicants indeed increases when jobs pay more or are more flexible.
External Link(s)

Registration Citation

Citation
Banerjee, Rakesh et al. 2021. "Does Greater Flexibility of Online labor Markets Encourage Female Participation? Evidence from Upwork." AEA RCT Registry. November 18. https://doi.org/10.1257/rct.8570-1.0
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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-11-15
Intervention End Date
2021-12-12

Primary Outcomes

Primary Outcomes (end points)
Number of female applicants, number of total applicants, share of female applicants
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
The difference between the bid to the job and the wage offered by the job
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We collect data from applicant profiles in response to job postings on the online labor marketplace, Upwork. To select the sample for the study, we followed a three-step sampling protocol. First, we chose seven subcategories of job specialization from twelve broad job categories advertised on Upwork. These categories are Admin Support, Data Science & Analytics, Design & Creative, IT & Networking, Translation, Web, Mobile & Software Development, and Writing. Other subcategories, like Sales & Marketing, are not included because of logistic constraints. Second, we look for job postings in each of these subcategories that meet two criteria -- (i) are commonly posted on Upwork, and (ii) are within the range of the research budget. We identify 80 tasks that meet these criteria and prepare our own job posting in a format and language that are similar to those posted on the platform. This is important because we want the jobs that are posted as part of the experiment to resemble other job posts that are regularly seen on the website so that the experimental job posts do not stand out. Third, for each task, we create four job postings that differ only in flexibility to choose work hours within a day and wages. In high-flexibility jobs, freelancers can choose any 2-hour window on a specified date. For low-flexibility jobs, freelancers have to complete the work during a specified two-hour window during the day. The high-wage jobs pay USD $ 40 for the two hours and the low-wage job pays USD $30 for the two hours. Therefore, the four treatment arms of the experiment are:

1. Low wage, low flexibility
2. High wage, low flexibility
3. Low wage, high flexibility
4. High wage, high flexibility

In total, our sample will consist of 320 job postings (80 tasks time 4 postings/task). The experiment will be conducted over the span of four weeks. We will randomly pick one job posting from each of the 80 tasks to be posted in the first week of the experiment. For each of these 80 job postings, we will randomly assign a day of the week to publish the job. The same process will be followed in subsequent weeks for 4 weeks (using sampling without replacement). Job postings will be active for twenty-four hours, and applicant information will be collected at the end of the twenty-four hours. Once a posting is closed, we will randomly hire one of the applicants to complete the assigned job. This candidate will receive the promised payment.
Experimental Design Details
Randomization Method
Stratified randomization by a computer using Stata. Stratification at the task level.
Randomization Unit
Job postings
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
320 job postings
Sample size (or number of clusters) by treatment arms
80 job posting with low wage and low flexibility, 80 job postings with high wage and low flexibility, 80 job posting with low wage and high flexibility, and 80 job postings with high wage and high flexibility.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Two treatment arms–high flexibility v.s. low flexibility Share of Female Applicants: Data type– proportion; MDE–0.14; Jobs in the Treatment Group–160; Jobs in the Control Group–160; Power–0.78. The number of female Applicants: Data type–mean; SD–4.5; MDE–1.5; Jobs in the Treatment Group–160; Jobs in the Control Group–160; Power–0.84. The number of total Applicants: Data type–mean; SD–16.6; MDE–6; Jobs in the Treatment Group–160; Jobs in the Control Group–160; Power–0.90.
IRB

Institutional Review Boards (IRBs)

IRB Name
Human Ethics Office at University of Western Australia
IRB Approval Date
2021-09-22
IRB Approval Number
2021/ET000599

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials