Wage inequality and preferences for redistribution

Last registered on January 22, 2022


Trial Information

General Information

Wage inequality and preferences for redistribution
Initial registration date
May 27, 2021

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 28, 2021, 12:49 PM EDT

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

Last updated
January 22, 2022, 11:17 PM EST

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



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation
PI Affiliation

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Using new cross-country survey and experimental data, we investigate the nature of beliefs about wage inequality and the effect of these beliefs on people’s support for redistribution with over 9000 respondents across six high-income countries (Australia, France, Japan, Sweden, the United Kingdom and the United States). This study combines a flexible elicitation of beliefs about the distribution of full-time wages within each country and a randomized survey experiment where respondents are allocated into one of three groups, two of which receive different types of information about wage inequality.
External Link(s)

Registration Citation

Eckel, Catherine et al. 2022. "Wage inequality and preferences for redistribution." AEA RCT Registry. January 22. https://doi.org/10.1257/rct.7739-1.2000000000000002
Experimental Details


There are two treatment groups. One group receives information about the ratio of the average wage of a CEO of a publicly listed company relative to the average full-time worker and the other receives information about the P90/P10 ratio of full-time workers wages in their country. This data has been sourced from the OECD employment database and the Bloomberg Global CEO Pay Index.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
There are three main families of primary outcomes. The first is preferences for government led redistribution. The second is people’s beliefs about inequality and fairness in general. The third is real world actions people are willing to take to address wage inequality.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
There are two families of secondary outcomes. The first is people’s perception of the distribution of wages in their country. The second is people’s preferred distribution of wages in their country. These outcomes are measured to illustrate whether the treatment impacts people’s priors.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The impact of the information interventions outlined above will be evaluated via an online randomized survey experiment in 6 countries (Australia, France, Japan, Sweden, the United Kingdom and the United States) in mid 2021. In addition to the content of the treatment, respondents will also be randomly allocated to receive the treatment before or after they express their perception of and preferred level of wage inequality in their country (Sections B and C in the questionnaire). This will allow us to a) illustrate whether the treatment impacted people’s perceptions of and preferred levels of the wage distribution (when the treatment is provided prior to Sections B and C) and b) examine heterogenous treatment effects on the primary outcomes based on respondents prior perceptions of and preferences for the distribution of wages in their country (when the treatment is provided after Sections B and C). To conduct this analysis data will be pooled across countries and/or treatments. However we will also examine whether there are different treatment effects between countries.
Experimental Design Details
Not available
Randomization Method
Qualtrics Stratified Randomization (by age and gender)
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
1500 respondents in each of the 6 countries
Sample size (or number of clusters) by treatment arms
500 in each treatment and the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Power calculations have been conducted to estimate the sample size required based upon the average effect size in similar cross-country survey experiments on this topic (e.g. Alesina, Stantcheva and Teso 2018). The minimum detectable effect (MDE) is around 8 percentage points (with power 0.8 and alpha 0.05) for a specific outcome in each country. The MDE is substantially lower when the data is pooled across countries and/or treatments.
Supporting Documents and Materials

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Institutional Review Boards (IRBs)

IRB Name
Monash University Human Research Ethics Committee
IRB Approval Date
IRB Approval Number
Analysis Plan

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