The Effect of Salary History Bans

Last registered on June 13, 2023
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Pre-Trial

Trial Information

General Information

Title
The Effect of Salary History Bans
RCT ID
AEARCTR-0003088
Initial registration date
July 11, 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
July 19, 2018, 6:50 PM EDT

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

Last updated
June 13, 2023, 10:53 AM EDT

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

Locations

Country
United States of America
Region

Primary Investigator

Name
Amanda Agan
Affiliation
Rutgers University
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Other Primary Investigator(s)

PI Name
Laura Gee
PI Affiliation
Tufts University
Contact Investigator
PI Name
Bo Cowgill
PI Affiliation
Columbia University
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Additional Trial Information

Status
Completed
Start date
2018-07-11
End date
2019-05-31
Keywords
Labor
Additional Keywords
JEL code(s)
J3, J31, J38, M52
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
How does banning firms from seeking applicants’ wage histories affect employment and salary offers? We implement a field experiment in which recruiters evaluate job applications that randomly include or exclude salary information questions and disclosures. The experiment mimics laws passed in Massachusetts, California, New York City, and Chicago banning these questions. Applicants also vary by gender and whether their previous salaries are high or low in the distribution of their previous firms salaries. We test several hypotheses about how salary disclosure might impact wage offers and gender inequality. We will also run one arm of the trial with subjects who are aware they are in an experiment. This takes the form of altered recruitment language that is clearly from academics and the addition of a signed informed consent form (everything else being the same) to test how this changes average outcomes.
External Link(s)

Registration Citation

Citation
Agan, Amanda, Bo Cowgill and Laura Gee. 2023. "The Effect of Salary History Bans." AEA RCT Registry. June 13. https://doi.org/10.1257/rct.3088-2.0
Former Citation
Agan, Amanda, Bo Cowgill and Laura Gee. 2023. "The Effect of Salary History Bans." AEA RCT Registry. June 13. https://www.socialscienceregistry.org/trials/3088/history/182461
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
There will be three main treatments, which involve the salary history question the recruiters see on the job applications:

- Salary history question is mandatory
- Salary history question is optional
- Salary history question is not there
* When salary history is not there, in some treatments applicants will still disclose salary history "unprompted" in "additional information" section

There will also be an arm where subjects are aware they are in an experiment and are asked to sign informed consent forms, everything else being similar in that treatment arm.
Intervention Start Date
2018-07-11
Intervention End Date
2019-05-31

Primary Outcomes

Primary Outcomes (end points)
- The salary the individual applicant is offered by the recruiter
- Whether the applicant is suggested for an interview
- The variation in salaries the recruiter offers to all applicants they see
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
- Maximum offer we should accept from applicants
- Salary distribution for candidate suggested by recruiter
- Expected outside offer distributions
- Expected outside offer range
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Recruiters will be randomly given a set of 8 applications. This set of applications will fall into one of 11 unique potential treatments, some treatments will be run twice for a total of 14 potential treatments. Each set of applications x treatment will be evaluated by two recruiters. The 11 unique treatments involve whether the salary history is disclosed or not, as well as the mix of salaries that are disclosed conditional on disclosure. Recruiters will then respond to several questions about whether the applicant should be interviewed and the take-it-or-leave-it salary they should be offered, as well as some additional questions about salary offers, via an online survey.

There will also be an arm where subjects are aware they are in an experiment and are asked to sign informed consent forms, everything else being similar in that treatment arm
Experimental Design Details
The 11 treatments - with some repeated for a total of 14 - are:

# Treatment 1: All Disclosed. All high salaries.
# Treatment 2: All Disclosed. All Low salaries.
# Treatment 3: All Disclosed. Assign "high within firm" one man/woman each from a high wage firm a low wage firm. The rest are "low within firm."
# Treatment 4: All Disclosed - Flip 3
# Treatment 5: Same as 4.
# Treatment 6: Prompted, Half Disclosed "uniform". Take Treatment 3. Disclose max male and female and min male and female.
# Treatment 7: Prompted, Half Disclosed. "more high." Take Treatment 3. Randomly disclose the 3 on the high end of the distribution 1 on the low end
# Treatment 8: Prompted, Half Disclosed. "more low." Take Treatment 3. Whoever didn't disclose in treatment 7 now discloses. Whoever did disclose in treatment 7 now does not.
# Treatment 9: Unprompted, Half Disclosed. Same as 6, but unprompted.
# Treatment 10: Unprompted, Half Disclosed. Same as 7, but unprompted.
# Treatment 11: Unprompted, Half Disclosed. Same as 8, but unprompted.
# Treatments 12-14 Banned (unprompted, undisclosed)

Plus a treatment where subjects are aware they are in an experiment and are asked to sign informed consent forms, everything else being similar in that treatment arm (uses Treatments 1-4, 6-12 above)
Randomization Method
Randomization done by computer
Randomization Unit
Recruiter
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Approximately 256 recruiters in the non-informed consent condition.

Approximately 56 recruiters in the informed consent condition
Sample size: planned number of observations
256 recruiters x 8 applications = 2048 applications reviewed non-informed consent 56 x 8 applications = 448 applications in informed consent
Sample size (or number of clusters) by treatment arms
2048 in non-informed consent spread across 14 treatments - where some treatments are duplicates.

448 in informed consent spread across 11 treatments - where some treatments are duplicates.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Given that there is little, if any, research on how salary disclosures or salary disclosure bans affect salary offers, we have little basis for guessing the baseline or variance of the effects we hope to estimate, making any estimation of MDE difficult and with too many potential degrees of freedom.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Columbia Human Research Protection Office
IRB Approval Date
2018-01-26
IRB Approval Number
IRB-AAAR7201
IRB Name
Rutgers University Institutional Review Board
IRB Approval Date
2018-11-19
IRB Approval Number
Pro2018002246
IRB Name
Social, Behavioral & Educational Research Institutional Review Board Tufts University
IRB Approval Date
2018-10-05
IRB Approval Number
1809004
Analysis Plan

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