Selection into Leadership and Perceptions of Inequality: The Case of Consistency

Last registered on March 30, 2023


Trial Information

General Information

Selection into Leadership and Perceptions of Inequality: The Case of Consistency
Initial registration date
March 22, 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
March 30, 2023, 3:19 PM EDT

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



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.
In this research project, we investigate the role "selection by consistency" plays in unequal career outcomes in leadership positions, and how the selection process and outcomes are perceived in terms of fairness. To this end, we run both lab and survey experiments in an attempt to answer the questions: Who behaves consistently and why? How are the selection outcomes and the process perceived? In the lab experiment, we run a selection contest to examine whether competing leadership aspirants act consistently to signal their competency and whether selecting principals pick up on these signals by selecting the consistent candidates. In those treatments with a principal, agents can try to signal their ability by reporting consistent answers, while in the control treatments their best response is to be as accurate as possible. We collect multi-faceted information on individuals and their characteristics to identify the determinants of consistent behavior and to learn more about the outcomes of selection-by-consistency. To study the potential implications of the selection for the perceptions of inequality, we analyze fairness perceptions in an incentivized manner in a follow up experiment, which will be registered separately.
External Link(s)

Registration Citation

Chadi, Adrian et al. 2023. "Selection into Leadership and Perceptions of Inequality: The Case of Consistency." AEA RCT Registry. March 30.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Consistency, probability of selection
Primary Outcomes (explanation)
Consistency is broadly defined as the absolute difference between the first two estimates of an agent, while taking into account potential changes in the dominant color. Given specific behavioral patterns that principals may find to be indicative of low effort (e.g. difference of 0) or guessing (e.g. multiples of 5), the definition for strategic consistency as a specific form of consistency could be different as a result. Other forms of consistency include intrinsic consistency (intentionally behaving consistently without any strategic intent, as a preference to be consistent) and ability-based consistency (unintentionally behaving consistently in consequence of high task performance).

Probability of selection is determined by the principals' choices in the contest between agents. We will also study the decisions of the principals to learn more about the determinants of their selection choices, such as preferences for consistency or gender. By focusing on specific types of principals, we are able to determine the implications for inequality due to selection-by-consistency, depending on the characteristics of the decision-makers. In particular, selection choices by principals with economic motives might inform about the outcomes of real-world leadership contests in companies where individuals in selection committees deciding on top-level positions also share particular characteristics and preferences.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We run a selection contest with two agents who compete by performing a two-period estimation task. Agents will be paid based on their performance, which is measured by the accuracy in the estimation task (i.e. the difference between the estimate and the correct solution). Furthermore, a principal selects one of the two agents as the winner of the contest. This agent will thereby get a selection bonus as well as an additional payoff by playing a third part of the estimation task that is also paid based on accuracy. The principal will be paid based on the selected agent’s accuracy in the third period, which incentivizes the principal to select the best-performing agent. With this basic framework, we follow the seminal work by Falk and Zimmermann (2017) on consistency as a signal of skills in selection contests with asymmetric information. We build upon their work to find out who benefits from selection-by-consistency by analyzing the selection of specific types of individuals and the role of consistency across different contexts.

To this end, we vary the stability of the decision environment by manipulating the level of information agents receive. First, in the ChangingDifficulty treatment, we provide agents with an easier task in the second period, to reflect the idea that leaders may still stick to their initial decisions, even when they realize there were wrong, because they may benefit from that. Second, in the ChangingSolution treatment, we change the solution of the task in the second period, to capture the idea of a changing or volatile environment in which a leader may be required to be flexible and to adjust to a new situation.

We also vary the selection mechanism, introducing selection based on luck and selection based on merit for two main reasons. The first is to distinguish between those who behave consistently for strategic reason from those who behave consistently for intrinsic reasons or those who are consistent as a byproduct of being highly able. Here, we eliminate the strategic reasons by replacing principals with a computer programme that selects agents randomly or based on their accuracy of estimates. The second reason is to inform our subsequent analyses on the perceptions of inequality where we intend to find out how selection-by-consistency is perceived compared to selection by merit and luck, as prominent considerations for fairness views regarding the sources of inequality in the literature.

Accordingly, we will have five conditions to which participants will be randomly assigned (by a computer):
a) Principal-Agent treatments
• Main treatment (perfect stability in terms of the solution and the level of difficulty)
• ChangingDifficulty treatment (second estimate becomes easier)
• ChangingSolution treatment (correct answer may change)
b) Agents treatments
• RandomSelection treatment (selection by a uniformly-mixing computer)
• PerformanceSelection treatment (selection by a computer choosing the more accurate agent)

In case of selection effects due to differences in task ability, such as gender-specific ability to solve the task, we could consider further control conditions without principal.

We collect multiple observations per individual across three periods. The longitudinal nature of the data allows us to learn more about the potential dynamics in our experiment, such as learning effects. For example, it is possible that some agents learn how to exploit the option to behave strategically over time, while the first estimates from the first period may only inform about the strategic behavior of agents with a very good understanding of the strategic context. Additionally, in each period, we collect multiple observations from each principal who makes selection choices for five pairs of agents, while one selection choice is randomly determined as relevant to the payments.

To learn more about the potential implications of selection-by-consistency and to identify the determinants of consistent behavior, we collect multi-faceted information on individuals and their characteristics prior to the start of the consistency experiment, including dishonesty, risk attitude, competitiveness, overconfidence, and pro-sociality. In each case, we use incentivized elicitation methods to capture these traits. This also applies to a measure of strategic ability. To complement the information at the individual level, we ask subjects further questions about their socio-demographic background, inclinations, and personality traits, such as Big Five.

We expect strategic consistency to play a role in the Principal–Agent Treatments. Since strategic motives are plausibly related to several traits, we expect that those could be predictive of consistent behavior in our experiment. First, as the success of strategic consistency is uncertain and depends on a variety of different factors, including the behavior of other individuals in the experiment, risk-tolerant individuals are more likely to employ strategic consistency. Second, since winning a selection contest over another person is more attractive to agents with preferences for competition, more competitive individuals are more likely to employ strategic consistency. Third, as the (expected) success of strategic consistency depends on the (expected) lack of strategic ability of competitors, overconfident individuals are more likely to employ strategic consistency. Fourth, strategic consistency could imply a need to deviate from the best possible estimate in the absence of any strategic incentive; accordingly, dishonest individuals are more likely to employ strategic consistency. Fifth, because strategic consistency is inefficient from a social perspective when individual payoffs are increased at the expense of overall payoffs, more pro-social individuals are less likely to employ strategic consistency.

Since all these characteristics and preferences are potentially gender-specific, we expect there could be a gender gap in consistent behavior. The same could occur if intrinsic consistency is found to be gender-specific. As we suspect that consistency varies with gender for a variety of reasons, we will balance treatment assignment using a stratified randomization by a computer.

In addition to the determinants of strategic consistency, we investigate the consequences for selection outcomes and hence inequalities, based on the notion that the more successful the consistency strategy is, the more likely inequalities along the lines of our above predictions could occur. If for examples male agents benefit strongly from strategic consistency, we expect that they also have a higher likelihood of being selected, all else being constant.

Experimental Design Details
Randomization Method
Randomization will be done by a computer
Randomization Unit
At the individual level (within sessions)
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
500+ Individuals
Sample size: planned number of observations
1500+ Observations
Sample size (or number of clusters) by treatment arms
Main: 90 Agents, 45 Principals
ChangingDifficulty: 90 Agents, 45 Principals
ChangingSolution: 90 Agents, 45 Principals
RandomSelection: 50 Agents
PerformanceSelection: 50 Agents
Sum: 505 Individuals (370 Agents, 135 Principals )
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
German Association for Experimental Economic Research e.V.
IRB Approval Date
IRB Approval Number


Post Trial Information

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Data Publication

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Reports & Other Materials