Gender gap in apologies

Last registered on February 16, 2024


Trial Information

General Information

Gender gap in apologies
Initial registration date
February 13, 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
February 16, 2024, 3:47 PM EST

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


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Primary Investigator

Stanford University

Other Primary Investigator(s)

PI Affiliation
Stanford University

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This project studies the gender gap in apologies and its consequences in the labor market. We hypothesize that women are more likely to apologize relative to men with similar performances. Apologies could be seen as a signal of incompetence which might hold women back in the labor market. We first document whether women apologize more frequently in a controlled setting and explore the reasons behind the gender apology gap. Second, we study whether employers infer lower ability from apologies and therefore promote women less. This project proposes a novel explanation of the gender promotion gap and suggests potential interventions to address this problem.
External Link(s)

Registration Citation

Liu, Lily and Marshall Mo. 2024. "Gender gap in apologies." AEA RCT Registry. February 16.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Apology messages from the worker experiment and promotion decisions from the employer experiment
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Beliefs and predictions from workers and employers
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will recruit a gender-balanced sample of respondents from Prolific, who will be randomly assigned to the roles of "worker" or "employer."
Experimental Design Details
Not available
Randomization Method
Randomization is done by a computer
Randomization Unit
Individual level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
The design is not clustered.
Sample size: planned number of observations
We plan to recruit 1000 workers and 400 employers in total.
Sample size (or number of clusters) by treatment arms
Baseline and non-strategic treatment each has 500 workers and 200 employers.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Stanford University
IRB Approval Date
IRB Approval Number