Gender and leadership
Last registered on February 12, 2020

Pre-Trial

Trial Information
General Information
Title
Gender and leadership
RCT ID
AEARCTR-0005385
Initial registration date
February 11, 2020
Last updated
February 12, 2020 1:44 PM EST
Location(s)

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Primary Investigator
Affiliation
Victoria University of Wellington
Other Primary Investigator(s)
PI Affiliation
University of New South Wales
PI Affiliation
University of New South Wales
Additional Trial Information
Status
In development
Start date
2020-02-17
End date
2020-05-15
Secondary IDs
Abstract
In this project, we explore gender differences in leadership.
External Link(s)
Registration Citation
Citation
Dobrescu, Loretti , Jan Feld and Alberto Motta. 2020. "Gender and leadership." AEA RCT Registry. February 12. https://doi.org/10.1257/rct.5385-1.0.
Experimental Details
Interventions
Intervention(s)
In this project, we explore gender differences in leadership.
Intervention Start Date
2020-02-17
Intervention End Date
2020-05-15
Primary Outcomes
Primary Outcomes (end points)
1. Differences in average level of happiness between countries that are led by male compared to female presidents.

2. Differences in inequality of happiness between countries that are led by male compared to female president.

Primary Outcomes (explanation)
Explanation for primary outcome 1. Each student will get a happiness score that is generated by the simulation. This happiness score resembles the concept of utility and depends exclusively on each student’s consumption. Higher levels of happiness lead to higher grades. We take the average level of happiness within each country as one observation. The first primary outcome is the difference in country average happiness scores between countries that are led by female presidents (treatments 1-2) compared to countries led by male presidents (treatments 3-4).

Explanation for primary outcome 2. Within each country, we measure the inequality of happiness scores using the Gini coefficient. The second primary outcome is the differences in average country level Gini coefficients between countries that are led by female compared to male presidents.
Secondary Outcomes
Secondary Outcomes (end points)
1. Differences in average happiness and inequality of happiness (main outcomes) between countries in which the presidents’ gender is visible compared to countries in which it isn’t.

2. Gender differences in preferences for redistribution among presidents.

3. Gender differences in preference for redistribution among all students.

4. Differences in average GDP per capita between countries that are led by female compared to male presidents.

5. Differences in inequality of GDP between countries that are led by female compared to male president.

6. Gender differences in other aspects of countries’ economies (e.g. investments in public goods, taxes)

7. Differences in students’ course satisfaction and evaluation of the performance of the president between students led by female compared to male presidents.

8. Differences in students’ behavior in economic games (trust, dictator, ultimatum game) between students who are in simulations with female compared to male presidents.
Secondary Outcomes (explanation)
Explanation for secondary outcomes 1: We will compare the average happiness (main outcome 1) between countries with female presidents in which presidents gender was visible (treatment 1) and countries with female presidents in which presidents gender was not visible (treatment 2). The difference between these two treatments allows us to explore to what extent a country’s performance depends on the students knowing that the president is female. We’ll do the same for male presidents (comparing treatments 3 and 4) and for the Gini coefficient of happiness (main outcome 2) for presidents of both genders.

Explanation for secondary outcomes 2-3: Before starting the simulations, all students are asked to fill in a questionnaire. In this questionnaire, students can state how much they agree with 5 statements that measure attitudes towards redistribution. Students possible answers range from 1 “strongly disagree” to 5 “strongly agree”. These are the 5 statements:
1. It is the responsibility of the government to reduce the differences in income between people with high incomes and those with low incomes.
2. The government should take more responsibility to ensure that everyone is provided for.
3. The government should do everything to improve the standard of living of all poor citizens.
4. The government should do only those things necessary to provide the most basic government functions.
5. The government should take active steps in every area it can to try and improve the lives of its citizens.
To get our measure of attitudes towards redistribution, we will reverse the score for question 4 so that higher values indicate more support for redistribution. Our final measure of preferences of redistribution will then be the average of all 5 scores.

Explanation for secondary outcomes 4-6: From the simulation, we can generate several measures that describe the economic activities of each economy. For example, we can measure GDP per capita, tax rates, investments in public goods and inflation. We will explore gender differences in these measures without having any specific hypothesis a priori how these might be affected by having a female president.

Explanation for secondary outcomes 7: The measure of course satisfaction and satisfaction with the president are taken from a survey that students fill out towards the end of the course.

Explanation for secondary outcomes 8: We will play the ultimatum game, trust game, and dictator game with all students in the course. Some of these games will be played using monetary incentives. The other games will be played using simulation money as incentives. We will compare the behaviour in these economic mini-games between students who are in simulations with female presidents compared to male presidents. We have no a priori hypothesis how having a female president will affect these outcomes.
Experimental Design
Experimental Design
Nothing to report before the experiment.
Experimental Design Details
Not available
Randomization Method
Randomization will be carried out by a computer.
Randomization Unit
Each student will be randomly assigned to a country (randomization unit = student).

Each country will be randomly assigned to one of four treatment groups (randomization unit = country).

Within each country in the female president treatment groups (treatments 1-2), one woman will be randomly selected among all women in the country to be president (randomization unit = student).

Within each country in the male president treatment groups (treatments 3-4), one man will be randomly selected among all men in the country to be president (randomization unit = student).
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
We expect around 104 countries. The actual number of clusters depends on the number of students enrolled.
Sample size: planned number of observations
For our main analysis, we expect to have 104 observations (one per country). For some secondary outcomes, like the preference for redistribution, we expect to have around 1,560 observations (one per student).
Sample size (or number of clusters) by treatment arms
We will have 4 treatment arms:
• Treatment group 1 (female presidents, gender visible): 26 countries
• Treatment group 2 (female presidents, gender not visible): 26 countries
• Treatment group 3 (male presidents, gender visible): 26 countries
• Treatment group 4 (male presidents, gender not visible): 26 countries
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
UNSW Human Research Ethics Committee
IRB Approval Date
2020-02-12
IRB Approval Number
HC200015