What Do Applicants Think Employers Want to See in Their Resumes? An Experiment on Second Order Beliefs

Last registered on July 06, 2026
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Pre-Trial

Trial Information

General Information

Title
What Do Applicants Think Employers Want to See in Their Resumes? An Experiment on Second Order Beliefs
RCT ID
AEARCTR-0018294
Initial registration date
June 25, 2026

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
July 06, 2026, 7:13 AM EDT

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

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Primary Investigator

Name
Ying Zhou
Affiliation
University of California, Santa Barbara
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Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2026-07-26
End date
2029-12-31
Keywords
Gender, Labor
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Existing research on the gender wage gap has considered gender differences in job attributes as possible explanations. However, the role of workers' belief about what traits employers want from them is underexplored. When seeking jobs, workers are likely to emphasize the achievements that they believe the employer values most from them. Gender differences in these beliefs may explain why women accept different tasks, write resumes differently than men, and ultimately sort themselves into different wages.
External Link(s)

Registration Citation

Citation
Zhou, Ying. 2026. "What Do Applicants Think Employers Want to See in Their Resumes? An Experiment on Second Order Beliefs." AEA RCT Registry. July 06. https://doi.org/10.1257/rct.18294-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2026-07-26
Intervention End Date
2026-12-31

Primary Outcomes

Primary Outcomes (end points)
Rank vector of (non-)promotable bullet points that are provided by the subjects in resume design. Outcome variables from full rankings could be (1) whether a promotable bullet point is ranked 1st, 2nd, ..., (2) whether a promotable BP is ranked top1, top2, ..., (3) the average rank of promotable bullet points.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Subjects are also asked to rank how much this fictitious worker enjoyed each of those activities in their current job. The secondary outcome is the subject's ranking of job enjoyment. In the second part of the experiment, resumes will be submitted to real job ads; thus, another secondary outcome is the callback rate.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
I ask experimental subjects to construct short resumes for fictitious male and female workers from a master list of previous achievements, to see which tasks subjects think will yield a job offer. More specifically, subjects need to select and rank achievements (in bullet point form). In the master list, some tasks are promotable (as defined by Babcock et al. 2022), meaning that they generate visible returns to the organization, and some are not. In the second phase of my experiment, I submit the created resumes to real job ads and use the resulting callback rates to reward my subjects. For comparison, I also ask subjects how they think different tasks would contribute to the worker’s job satisfaction.
Experimental Design Details
Not available
Randomization Method
Randomization was handled by Qualtrics' built-in features
Randomization Unit
The unit of randomization is the individual. Participants will be randomly assigned to see either the male or female version of the same resume content. To see how subjects react to fictitious workers of different genders, the treatment group is defined as those who see the female name, while the control group comprises those who see the male name.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1 participant pool
Sample size: planned number of observations
400 participants
Sample size (or number of clusters) by treatment arms
Although the gender of the subjects is a variable of interest, I cannot pre-determine the exact number of male and female participants. However, randomization should ensure that approximately half of the subjects will see a resume with a female name, while the other half will see a male name.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of California, Santa Barbara
IRB Approval Date
2025-08-20
IRB Approval Number
20-25-0496
Analysis Plan