Understanding Gender Inequities in the Ethiopian Labor Force
Last registered on December 18, 2018


Trial Information
General Information
Understanding Gender Inequities in the Ethiopian Labor Force
Initial registration date
July 04, 2017
Last updated
December 18, 2018 5:46 PM EST
Primary Investigator
UC Merced
Other Primary Investigator(s)
PI Affiliation
Arsi University
PI Affiliation
UC San Diego
Additional Trial Information
Start date
End date
Secondary IDs
We are interested in documenting gender gaps in Ethiopia by observing the administrative sector at a large University and decomposing factors that may contribute to the wage (and position) gap using institutional data. We propose to rigorously explore two potential explanations for the gender gap: 1) whether the evaluation of potential job candidates are a function of the candidate's gender, and 2) whether following advice is a function of the gender of the advisor.
External Link(s)
Registration Citation
Ayalew, Shibiru, Shanthi Manian and Ketki Sheth. 2018. "Understanding Gender Inequities in the Ethiopian Labor Force." AEA RCT Registry. December 18. https://doi.org/10.1257/rct.2304-2.0.
Former Citation
Ayalew, Shibiru et al. 2018. "Understanding Gender Inequities in the Ethiopian Labor Force." AEA RCT Registry. December 18. http://www.socialscienceregistry.org/trials/2304/history/39139.
Experimental Details
We randomly assign gender to resumes and advisors to measure differences in appraisals and willingness to follow advice.
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Our key outcome variables for one experiment is competancy, likeability, willingness to hire, and salary offers.

Our key outcome variables for the second experiment is perceived ability of self, perceived ability of team leaders, and likelihood of following advice.
Primary Outcomes (explanation)
Outcome variables are explained in more detail in the preanalysis plan.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experiment randomizes gender on resumes and of "team leaders" an experimental logic games.
Experimental Design Details
We provide subjects with hypothetical resumes in which the gender of the potential candidate is randomly determined for evaluation.

In a second experiment, we implement two logic games in which subjects are paired with a "team leader', whose gender is randomly assigned. For the first logic game, we observe whether female subjects are more likely to perceive themselves as having lower ability, and how they rate the ability of the team leader. In the second logic game, the team leader provides advice to the subject on how best to play the game. We observe whether this advice is more likely to be followed when the team leader is male. In addition, we randomly provide some subjects with signals of the team leader's ability to determine whether gender differences in the willingness to follow advice diminishes when there is a signal of the team leader's ability.
Randomization Method
Randomization done in office by computer.
Randomization Unit
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
For the resume component, sample size is 600. For the experimental game component, sample size is 300.
Sample size: planned number of observations
For the resume component, number of observations is 600 subjects * 2 resumes = 1200. For the game component, number of observations will be at the subject level (300 observations) and per round of the game (300 subjets * 11 rounds) = 3300.
Sample size (or number of clusters) by treatment arms
For the resume component, 300 individuals per treatment arm (female resume, male resume).

For the game component, 75 individuals per treatment arm (male + no ability signal, female + no ability signal, male + ability signal, female + ability signal). In addition, we will randomly determine the ordering of how beliefs are elicited (150 individuals per ordering).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
UC Merced
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post Trial Information
Study Withdrawal
Is the intervention completed?
Is data collection complete?
Data Publication
Data Publication
Is public data available?
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)