Author(s) This pre-registration is currently anonymous to enable blind peer-review. It has one author.
Pre-registered on 2021/04/27 - 07:55 AM (PT)
1) Have any data been collected for this study already? No, no data have been collected for this study yet.
2) What's the main question being asked or hypothesis being tested in this study? We predict that participants will indicate higher values as highest acceptable pay gaps than ideal pay gaps.
Additionally, we predict that men will indicate higher pay gaps than women.
We also predict that participants who deem worker criteria more important will indicate lower pay gaps.
3) Describe the key dependent variable(s) specifying how they will be measured. Participants will be asked to indicate pay gap ratios between a CEO and a worker, through an open text box. Additionally, participants will be asked which motivations led them to choose the reported value, namely equality/fairness, merit, and quality of life. We will also include one item on maximum inequality and one on balance between the two categories. Participants will answer to these 8 items through a 7-point likert scale. Participants will also be asked to choose between equality and merit through a 6-point bipolar scale.
PREDICTORS. Participants will be asked to rate the importance of 7 wage setting criteria (7-point likert scale).
4) How many and which conditions will participants be assigned to? 2 conditions: highest acceptable (i.e. the highest possible difference) pay gap vs. ideal pay gap
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. The analyses will be run through both linear (t-test) and robust (Mann-Whitney U) tests using type of pay gap (highest acceptable vs ideal) as predictor and pay gap as dependent variable. We will also run linear regression models with CEO and worker wage setting criteria, condition, and the interaction between the two as predictors and pay gap as dependent variable. We will also test gender differences in pay gaps through a 2 (condition) x 2 (gender) ANOVA.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. We will exclude participants who do not complete the questionnaire, who do not give consent to data processing, who fail the manipulation check and who fail at least one attention check.
Additionally, for the linear tests (but not for the robust tests), we will exclude participants who are "extreme outliers" on the dependent variable(s) included in the analysis, according to the inter-quartile range method of outlier detection.
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. We will collect 150 participants for this study.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) SECONDARY ANALYSES
We aim to explore whether motivations are different for highest acceptable vs ideal pay gaps. As such, we will run t-tests to see whether type of pay gap predicts motivations, and regression models to test whether motivations predict pay gap ratios.
VARIABLES COLLECTED FOR EXPLORATORY PURPOSES
Participants will be asked whether they believe a law should exist in that country (own or hypothetical, based on the condition) to set a ceiling to the CEO-worker pay gap, and whether they deem the ideal or maximum pay gap more relevant for applied purposes.
OTHER
Data collection will be handled through Prolific Academic.
