Beliefs about gender bias and hiring decisions

Last registered on June 03, 2024

Pre-Trial

Trial Information

General Information

Title
Beliefs about gender bias and hiring decisions
RCT ID
AEARCTR-0013679
Initial registration date
May 23, 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
May 30, 2024, 3:22 AM EDT

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

Last updated
June 03, 2024, 2:24 PM EDT

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

Locations

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Primary Investigator

Affiliation
University of Wyoming

Other Primary Investigator(s)

PI Affiliation
George Mason University
PI Affiliation
PI Affiliation
Fletcher Group

Additional Trial Information

Status
In development
Start date
2024-05-24
End date
2024-06-28
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
People may expect gender biases in contexts where there is none, and such biased expectations may be consequential. We design an experiment to test whether inaccurate beliefs about the existence of gender biases may cause employers to favor men employees. Our experiment has three groups of agents: experts, experts’ employers, and customers. The employers’ task is to hire either a man or a woman expert with identical credentials. The employers’ payoff depends on the customers’ willingness to pay (WTP) for the expert’s service (advice). Hence, the employers’ expected payoff, and therefore the payoff from their hiring decision, depends on their expectations of customers’ WTP for advice from a woman versus a man expert. Customers may buy expert advice in an incentivized Becker-DeGroot-Marschak (BDM) auction, to help with their task in the experiment. The customers’ task is to predict the inflation rate in the U.S. economy, and the customer whose prediction is the most accurate gains a relatively large monetary reward. The payoffs of the employers in the experiment are designed to eliminate the existence of altruistic motives for hiring experts, and we control for other potential mechanisms causing employers to favor any particular gender, beyond beliefs about gender biases amongst customers.
External Link(s)

Registration Citation

Citation
Ashworth, Madison et al. 2024. "Beliefs about gender bias and hiring decisions." AEA RCT Registry. June 03. https://doi.org/10.1257/rct.13679-1.1
Experimental Details

Interventions

Intervention(s)
Our study has three groups of agents: economic Experts, experts’ Employers, and Customers. We are interested in the behavior and beliefs of Customers and Employers.

Customers` participate in an RCT, and are tasked to make a prediction of the inflation rate for 2024. The Customer who makes the most accurate prediction (as determined by the comparison of the prediction to the official actual inflation rate in May -- a number made official by US govt agencies in mid June 2024) wins a bonus of $200. Customers therefore have an incentive to make the best possible prediction.

To help them successfully predict the inflation rate, Customers can buy advice from economic Experts, consisting of the Expert's prediction of the inflation rate in May 2024. Each Customer is randomly paired with either a man or a woman Expert, from whom they can buy advice. This advice consists of a prediction of the inflation rate in May made by the economic Expert. Economic Experts are identical in their qualifications, but differ in gender. Customers' WTP for advice is elicited in a Becker-DeGroot-Marschak (BDM) auction. This design allows us to examine whether Customers do exhibit a gender bias, i.e., differ in their WTP for advice from a man vs a women Expert, even though the Experts have identical qualifications.

Experts only role in our study is to make a prediction of the inflation rate for May 2024 that gets provided to the Customer they are paired with, should that Customer win the BDM auction.

Employers’ task is to hire an Expert. They can choose between hiring either a woman or a man Expert, with identical credentials. The Employer has an incentive to hire the Expert that they believe will generate the highest WTP from Customers -- the Employers’ payoff depends on Customers’ willingness to pay (WTP) for the Expert’s service (advice). We elicit Employers' incentivized beliefs about Customers' WTP for advice from a man and a woman Expert. We also elicit Employers' own beliefs about the value of Expert advice from a man vs a woman Expert. This design allows us to examine if Employers believe that Customers are biased against women Experts, and therefore choose to hire a male Expert, even if they themselves do not exhibit any gender bias.

We will also separately collect data from Employers where we correct for their biased beliefs, i.e., inform them about the Customers' actual WTP for advice from a man vs a woman Expert. This enables us to examine whether correcting for biased beliefs of any gender bias amongst their Customers changes their willingness to hire male and female Experts.
Intervention Start Date
2024-05-24
Intervention End Date
2024-06-28

Primary Outcomes

Primary Outcomes (end points)
Employers' beliefs about Customers' WTP for Expert advice from a man vs a woman Expert
Employers' choice to hire a man vs a woman Expert
The difference in Customers' WTP for advice from a man vs a woman Expert
The difference between Customers' actual WTP for advice and Employers' beliefs about their WTP
Primary Outcomes (explanation)
Employers' beliefs about Customers' WTP for Expert advice from a man vs a woman Expert -- elicited in a BDM auction, and stated as an amount between $0 and $5.
Employers' choice to hire a man vs a woman Expert -- a binary variable that indicates the choice to hire a woman expert or not
The difference in Customers' WTP for advice from a man vs a woman Expert -- stated as an amount between $0 and $5.
The difference between Customers' actual WTP for advice and Employers' beliefs about their WTP -- stated as an amount between $0 and $5.

Secondary Outcomes

Secondary Outcomes (end points)
Customers' and Experts' assessment of the Experts' characteristics (competent, knowledgeable, trustworthy, confident)
Customer's perceived usage of the Expert's advice
Secondary Outcomes (explanation)
Customers' and Experts' assessment of the Experts' characteristics (competent, knowledgeable, trustworthy, confident) -- measured on a Likert scale, 1-7; strongly agree to strongly disagree
Customer's perceived usage of the Expert's advice -- measured as the difference between the inflation rate they think they would have predicted, had they not taken the Expert's advice, and their prediction with the Expert's advice.

Experimental Design

Experimental Design
Our study has three groups of agents: economic Experts, experts’ Employers, and Customers. We are interested in the behavior and beliefs of Customers and Employers. Our participants get randomized into the role of Customer or Employer.

Customers` participate in an RCT, and are tasked to make a prediction of the inflation rate for 2024. The Customer who makes the most accurate prediction (as determined by the comparison of the prediction to the official actual inflation rate in May -- a number made official by US govt agencies in mid June 2024) wins a bonus of $200. Customers therefore have an incentive to make the best possible prediction.

To help them successfully predict the inflation rate, Customers can buy advice from economic Experts, consisting of the Expert's prediction of the inflation rate in May 2024. Each Customer is randomly paired with either a man or a woman Expert, from whom they can buy advice. This advice consists of a prediction of the inflation rate in May made by the economic Expert. Economic Experts are identical in their qualifications, but differ in gender. Customers' WTP for advice is elicited in a Becker-DeGroot-Marschak (BDM) auction. This design allows us to examine whether Customers do exhibit a gender bias, i.e., differ in their WTP for advice from a man vs a women Expert, even though the Experts have identical qualifications.

Experts only role in our study is to make a prediction of the inflation rate for May 2024 that gets provided to the Customer they are paired with, should that Customer win the BDM auction.

Employers’ task is to hire an Expert. They can choose between hiring either a woman or a man Expert, with identical credentials. The Employer has an incentive to hire the Expert that they believe will generate the highest WTP from Customers -- the Employers’ payoff depends on Customers’ willingness to pay (WTP) for the Expert’s service (advice). We elicit Employers' incentivized beliefs about Customers' WTP for advice from a man and a woman Expert. We also elicit Employers' own beliefs about the value of Expert advice from a man vs a woman Expert. This design allows us to examine if Employers believe that Customers are biased against women Experts, and therefore choose to hire a male Expert, even if they themselves do not exhibit any gender bias.
Experimental Design Details
Not available
Randomization Method
By a computer.
Randomization Unit
Individual.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
0
Sample size: planned number of observations
920
Sample size (or number of clusters) by treatment arms
360 Customers (they are in turn randomized into being paired with either a man or a woman Expert)
360 Employers with no information on the actual WTP for advice amongst Customers
200 Employers with information on the actual WTP for advice amongst Customers, including whether Customers exhibit a gender bias
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB University of Wyoming
IRB Approval Date
2024-05-31
IRB Approval Number
IRB-2024-173