Outside Options and Gender Gap in Tournament Entry

Last registered on March 19, 2024


Trial Information

General Information

Outside Options and Gender Gap in Tournament Entry
Initial registration date
March 18, 2024

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 19, 2024, 5:27 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

Austin Peay State University

Other Primary Investigator(s)

PI Affiliation
Trinity College

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Persistent gender inequalities in economic outcomes and leadership representation pose significant challenges, with women consistently earning less and being underrepresented in senior roles. Recent research suggests that differences in behavioral traits, particularly the willingness to compete, may contribute to these disparities. Earlier findings have shown that women are less likely to opt for competitive payment schemes, a tendency that may hinder their career progression and contribute to the wage gap. This project introduces an innovative approach to examine interventions that could mitigate the gender competitiveness gap. By employing an Outside Option treatment alongside the traditional tournament entry choices, we aim to explore the effects of providing participants with the flexibility to revise their payment choices after task completion. We aim to enhance our understanding of gender dynamics in competitive environments and discover potential strategies to promote gender equality in economic and professional settings.
External Link(s)

Registration Citation

Demiral, Elif E and Brianna Halladay. 2024. "Outside Options and Gender Gap in Tournament Entry." AEA RCT Registry. March 19. https://doi.org/10.1257/rct.13215-1.0
Experimental Details


Persistent gender inequalities remain a challenge in economic outcomes. This issue is particularly evident in the labor market, where women consistently earn less than men and are notably underrepresented in senior leadership roles. While factors like occupational segregation and discrimination contribute to these disparities, recent research has shifted focus to exploring how differences in behavioral traits between genders might provide additional insights (Blau and Kahn, 2017; Bertrand, 2018). Among these traits, the willingness to compete stands out as a key area of study.

In a groundbreaking study, Niederle and Vesterlund (2007) found that men are significantly more inclined to compete than women, which may contribute to slower career progression and the enduring wage gap women face. In a tournament entry experiment, Niederle and Vesterlund had women and men complete a simple math task for three rounds. The first round paid participants a fixed payment for each problem they solved correctly. In the second round, they were matched in random groups of four and completed the same task but with a competitive twist: they could earn four times the fixed payment if they outperformed their group members and nothing if they didn't. The third round is where the participants get to choose how they want to get paid: Piece rate (as in round 1) or tournament (as in round 2 but compared to others' round 2 scores). In such an experimental condition, which has been replicated numerous times, women are found to be less likely than men to choose the competitive tournament payment. This phenomenon is not confined to laboratory settings but is echoed in real-life scenarios, further evidenced by subsequent research (Buser et al., 2014; Rueben et al., 2015).

Various replications of this study consistently show women being less likely to choose the competitive payment scheme. Recent research highlights that this competitiveness gap especially surfaces in contexts where the risk and confidence differences across genders are prominent (Gillen et al., 2019; Charness et al.,2022; Van Veldhuizen, 2022). Women's reluctance to compete often stems from a greater risk aversion, lower confidence in their abilities, and a tendency to undervalue their performance relative to others.

Our project seeks to examine interventions that could narrow the gender competitiveness gap. Specifically, we introduce an Outside Option treatment, allowing participants to revise their payment choice selection after the task completion, providing the flexibility to switch between the piece rate and a competitive pay scheme. While the control treatment closely follows the Niederle and Vesterlund (2007) design, our Outside Option treatment will allow participants to revise their choices post-decision and after completion of the round. Specifically, while deciding whether to compete, participants will know they can switch back to a fixed-rate pay scheme if they initially opted for competition, or vice versa. We expect this flexibility in decision-making will mitigate the effects of risk aversion and confidence disparities, contributing to a narrowing of the gender gap in tournament entry. In sum, this study aims to investigate whether providing an outside option alongside traditional tournament entry choices can narrow the gender competitiveness gap.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Ex-ante competition entry of men and women in Control and Outside Option treatments
Ex-post competition entry of men and women in Control and Outside Option treatments
Task 3 score
Primary Outcomes (explanation)
i. Ex-ante competition entry between Control vs. Outside Option treatments: We investigate the ex-ante (prior to task 3) tournament entry rates of men and women between the Control and the Outside Option treatments.
ii. Ex-post competition entry between Control vs. Outside Option treatments: We investigate the ex-post (after task 3) tournament rate choices of men and women between the Control and the Outside Option treatments.
iii. Ex-post and ex-ante competition entry in the Control treatment: We compare the ex-ante (prior to task 3) tournament entry rates of men and women with the ex-post (after task 3) tournament entry rates in the Control treatment.
iv. Ex-post and ex-ante competition entry in the Outside Option treatment: We compare the ex-ante (prior to task 3) tournament entry rates of men and women with the ex-post (after task 3) tournament entry rates in the Outside Option treatment.
v. Ex-post and ex-ante competition entry between the Control and Outside Option treatments: We compare the change in competitive entry choices of men and women before and after the task and across treatments. This allows us to detect the role of prior information on competition entry decisions by gender.
vi. Task 3 score comparisons between treatments: We compare the task 3 scores across treatments to detect the role of information about choice revisions on task performance.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We plan to run a controlled online experiment using Prolific with two treatments. Our objective is to examine the potential for an outside option to influence competitive decisions and address gender gaps in tournament entry behavior.

Control Treatment: The control treatment follows the framework established by an experiment by Niederle and Vesterlund (2007). Here, the participants complete a task for three rounds. Participants earn a fixed rate of 25 cents for each correct answer in the first round. In the second round, they are matched with three other participants, making each group consisting of four subjects. The subject with the highest score in task 2 receives four times the piece rate for every correct answer in task 2 (100 cents). In the third task, participants choose their preferred compensation method: the piece rate or the competitive rate. If they choose the piece rate (as in task 1), they receive 25 cents for each correct answer. If they choose the tournament pay (as in task 2), their task 3 performances are compared to the task 2 performances of their group numbers. If they perform better than all three other group members did in task 2, they get 100 cents per correct answer, and nothing otherwise. The control treatment closely follows the design from Niederle and Vesterlund until here. Beyond replicating their methodology, our control treatment introduces a novel element: it allows participants to revise their competition entry choice after the completion of task 3. This additional step, presented to participants only after they have finished task 3, does not affect the initial competition entry decision they made before task 3, and serves as another control treatment where switching is an option and is not known by the participants.

Outside Option Treatment: Our outside option treatment mirrors tasks 1 and 2 of the control treatment. The distinguishing feature of this treatment lies in the pre-disclosed flexibility regarding payment choice for task 3. Specifically, participants are informed from the outset that they will have the option to modify their selected payment method upon the completion of task 3. This means that before deciding whether to choose the competitive payment scheme for task 3, participants are aware that they will be able to revise this choice after task 3 is completed.

Task: For the task, we will adopt the math addition matrix (Cassar and Rigdon, 2021) (Figure 1), which is appropriate in an online context. This task involves participants identifying two numbers that add up to 100 from a grid of numbers. We chose this task to reduce the possibility of cheating, ensuring the results are as reliable.
Experimental Design Details
Not available
Randomization Method
All randomization will be conducted by Qualtrics.
Randomization Unit
Randomization will be at the individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Two treatments, no clusters
Sample size: planned number of observations
1000-1500 in total
Sample size (or number of clusters) by treatment arms
Based on the findings from similar work (Apicella et al., 2017), our power analyses suggest we need at least 500 observations to detect a significant gender difference in competition entry in the control treatment (at a 5% significance level with 80% power).

We, therefore, plan to collect a total of 1,000 – 1,500 observations for both treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
To detect a 12-percentage point significant (at 5 percent) gender difference (28 percent women vs. 40 percent men choosing to compete) in the control treatment (based on the findings from Apicella et al., 2017), we need 488 observations (with 80 percent power).

Institutional Review Boards (IRBs)

IRB Name
Trinity IRB
IRB Approval Date
IRB Approval Number
Trinity IRB Application #3184