An experiment to include gender-related material in introductory microeconomics

Last registered on December 06, 2023


Trial Information

General Information

An experiment to include gender-related material in introductory microeconomics
Initial registration date
November 29, 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
December 06, 2023, 8:19 AM EST

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


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Primary Investigator

University of Washington

Other Primary Investigator(s)

PI Affiliation
University of Washington
PI Affiliation
University of Washington

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
We assess whether an intervention that introduces gender-related material into an introductory economics course improves students’ sense of relevance and belonging, test scores, and application to the economics major.
External Link(s)

Registration Citation

Heath, Rachel, Yael Jacobs and Melissa Knox. 2023. "An experiment to include gender-related material in introductory microeconomics." AEA RCT Registry. December 06.
Experimental Details


We will begin fall 2023 and continue throughout the academic year 2023-2024 and possibly longer. Students will be assigned to treatment (gender economics curriculum) or control (labor economics curriculum), which consists of two lectures lasting approximately as long as a regular class session (1 hour and 20 minutes). The gender curricula was developed by PI Heath, whose research focuses on gender and labor markets in low-income countries, and who teaches a gender in economics undergraduate course. The material in that course can frequently be explained using simple tools developed in introductory microeconomics, and the gender in economics module in particular focuses on:
1. introduce models of labor market discrimination, explain statistical versus taste-based discrimination, and explore empirical evidence on policies designed to close gender wage gaps (pay transparency, flexibility in wage setting). (Lecture 1)
2. introduce models of family economics and the economics of fertility, including the impacts of access to contraception (Lecture 2)
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1. A survey-based measure of ``relevance, belonging, and growth mindset"
2. Final exam score, exclusive of questions on the supplementary material.
3. Taking Econ 300
Primary Outcomes (explanation)
Our survey-based measure of ``relevance, belonging, and growth mindset'' is similar to Bayer et al, 2020. We calculate an ``RBG index'' that averages together fifteen questions intended to measure a student's sense of relevance, belonging, and growth. The index is defined to be the equally weighted average of z-scores of its components. Each question's z-score is calculated by subtracting that question's mean from the student's response and dividing by that question's standard deviation. See appendix table A1 in our PAP for a list of all fifteen questions.

Secondary Outcomes

Secondary Outcomes (end points)
Enrollment in introductory macroeconomics (Econ 201)
Application to the economics major
Acceptance to the economics major
Successful completion of graduation requirements (within 4 and 5 years).
Enrollment in math courses that serve as gateway courses to the major (Math 300 or Applied Math 301).
Application to the math major
Acceptance to the math major
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We randomly saturate TA sections, treating 25%, 50%, and 75% of students. Following Banerjee et al (2020) we conduct 10 randomizations and choose the randomization that contains the fewest differences between treatment and control among the following variables: student gender (we group students who identify as nonbinary with students who identify as women), status as an underrepresented minority, first generation, and location of origin (US/international).
Experimental Design Details
Not available
Randomization Method
Stata dofile
Randomization Unit
Individual level randomization, with random saturation of TA sections.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
1537 students
Sample size: planned number of observations
1537 students
Sample size (or number of clusters) by treatment arms
We randomly saturate TA sections, treating 25%, 50%, and 75% of students.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Washington
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents


MD5: 9a5a6caf27e81158b0dd839da24a72f6

SHA1: 3729bf0595641062feadb479bfc2ad9ae50a9163

Uploaded At: November 29, 2023