The effect of losing a competition: the role of gender, unfairness and feedback

Last registered on May 21, 2021
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Pre-Trial

Trial Information

General Information

Title
The effect of losing a competition: the role of gender, unfairness and feedback
RCT ID
AEARCTR-0007651
Initial registration date
May 20, 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 21, 2021, 9:33 AM EDT

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

Locations

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Primary Investigator

Name
Roel van Veldhuizen
Affiliation
Lund University
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Other Primary Investigator(s)

PI Name
Marica Valente
PI Affiliation
ETH Zurich and DIW Berlin
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PI Name
Stefano Piasenti
PI Affiliation
Humboldt University of Berilin
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PI Name
Gregor Pfeifer
PI Affiliation
University of Sydney
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Additional Trial Information

Status
In development
Start date
2021-05-20
End date
2022-06-30
Keywords
Gender, Lab
Additional Keywords
Competitions, Fairness
JEL code(s)
Secondary IDs
Abstract
Women are underrepresented at every level of the corporate ladder. A growing and important experimental literature suggests that women are both more likely to avoid competition and drop out of competitive environments after experiencing disappointment than men. These laboratory measures seem also to predict career choices and, hence, partly explain the gender gap. We study the role of perceived unfairness in explaining gender differences in willingness to compete again in response to losing a competition. We ask whether men and women differ in how they respond to losing or winning a competition and whether these differences increase or decrease in presence of unfair conditions. Moreover, we aim to understand which women and men drive the gender gap. For this purpose, we run a post-experiment survey to elicit a large number of socio-economic characteristics and personality traits. We estimate heterogeneous treatment effects using machine learning methods that allow to control for a large number of covariates.
External Link(s)

Registration Citation

Citation
Pfeifer, Gregor et al. 2021. "The effect of losing a competition: the role of gender, unfairness and feedback." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.7651
Sponsors & Partners

Sponsors

Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-05-20
Intervention End Date
2021-06-30

Primary Outcomes

Primary Outcomes (end points)
1) Gender gap in tournament entry, within a given treatment and also across treatments, both for the full sample and for round-2 losers only.

2) Beliefs about own performances

3) Variation in gender gap within treatments with observables characteristics

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1) Gender gap in tournament entry, within a given treatment and also across treatments for round-2 winners only.

Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We conduct an online experiment on Prolific in which participants work on a real effort task for three rounds. In the first round they receive piece rate pay, in the second they take part in a two-person tournament and in the third round they choose between tournament and piece rate pay. Prior to making their tournament entry decision in round 3, participants receive feedback whether or not they won the previous round's tournament. We vary whether the tournament in round 2 is fair (the best performer wins) or unfair (the best performer might lose) and, for unfair tournaments, vary whether participants find out whether they won or lost fairly or unfairly. We also elicit performance beliefs prior to the tournament entry decision, and collect socio-economic characteristics and personality traits in a final questionnaire.
Experimental Design Details
Not available
Randomization Method
Randomization done by Prolific online platform's algorithm
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Between 1200 and 1800 participants.
Sample size: planned number of observations
Our target sample size is between 1200 and 1800 participants.
Sample size (or number of clusters) by treatment arms
400-600 participants in each of the three treatments, spread evenly across both genders.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
see Analysis plan
Supporting Documents and Materials

Documents

Document Name
Ethics committee approval
Document Type
irb_protocol
Document Description
Ethics committee approval
File
Ethics committee approval

MD5: 39d0042186df6e44713c23281c7cb6ea

SHA1: df0bebf6a0b20f53eb02609f21a2808ceeb450fe

Uploaded At: May 20, 2021

IRB

Institutional Review Boards (IRBs)

IRB Name
WZB Ethics Committee
IRB Approval Date
2021-02-05
IRB Approval Number
2021/0/110
Analysis Plan

Analysis Plan Documents

Pre analysis plan

MD5: dfbdcf4e159619ca9eb1c01113853ae6

SHA1: bf620e7ab8e5a7fb0f7574a39d5f6022e947eaa3

Uploaded At: May 20, 2021