Does pay transparency in salary lead to inequality in non-transparent benefits?

Last registered on November 01, 2023


Trial Information

General Information

Does pay transparency in salary lead to inequality in non-transparent benefits?
Initial registration date
October 24, 2023

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 01, 2023, 2:45 PM EDT

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


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Primary Investigator

Bryant University

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
There have been increased calls for pay transparency law across the developing world. Literature showed that pay transparency law has been shown to reduce pay inequality while others have found evidence of employees’ increasing idiosyncratic requests for non-transparent benefits. Yet, little is known how employers allocate between salary and the benefit when salary becomes transparent, and benefits remains to be non-transparent. In this paper, I would like to ask that when two workers are randomly assigned with unequal total compensation, and the employers have opportunities to allocate bonus between the two workers, how would the employers allocate the bonus. Would they allocate the bonus in a way so that the total compensation would equal, or would they allocate in a way so that the salary component would equal, or would they aim to equally split the bonus without changing any of the previous inequality in total compensation. Moreover, I would like to know whether their behavior is impacted by whether the allocated component (salary or benefit) is transparent. I am also interested to know whether the allocator's gender impacts their decisions.
External Link(s)

Registration Citation

Pan, Xiaofei. 2023. "Does pay transparency in salary lead to inequality in non-transparent benefits?." AEA RCT Registry. November 01.
Experimental Details


The main intervention treatments is about the transparency of the earnings that the allocators are making decisions on. The salary category is transparent, it suggests that the two workers can view each other's salary amount both before and after the bonus earnings allocations. Benefit category is non-transparent, it suggests that the two workers can not view each others' benefits earnings at any time of the project.
The allocator, who allocate the bonus earnings between the two workers, would allocate either through the transparent salary category, or through the non-transparent benefits category. I investigate how allocator's decisions are impacted by the two different categories.
If I observe asymmetric allocation behavior between salary and benefit. More robust treatments will be added.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
How decision makers allocate the bonus earnings between two workers.
I would also examine workers productivity in respond to these salaries or benefit. Though this is not my main focus.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
First, two workers are randomly endowed with some amount of salary and benefit. Yet, one worker's total compensation is lower than the other.
Then, the allocators can allocate some bonus earnings between the two workers. They will allocate these bonus earnings either through the transparent salary category, or through the non-transparent benefit category. The allocators will face several possible scenarios where the two workers are endowed.
In particular, the have several allocation options. The option could allow them to equalize the total compensation between the two workers. The option could also allow the allocator to realize equalization in the allocated category. These above goals sometimes can be realized together through the same option. We could also view the options as whether it keeps the current inequality, remove the inequality, or enlarge the inequality.
That is, I would like to study whether allocators decisions are influenced by transparency.
Experimental Design Details
Not available
Randomization Method
It is randomized by the computer.
Randomization Unit
The randomization is based on the individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
They are all recruited from the same online platform.
Sample size: planned number of observations
300- 400
Sample size (or number of clusters) by treatment arms
About 150 observations per treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Bryant University Institution Review Board
IRB Approval Date
IRB Approval Number
IRB Proposal #2023-1012b