Data and Code for: Preferences, access, and the STEM gender gap in centralized high school assignment

Principal Investigator(s): View help for Principal Investigator(s) Andrew Dustan, William & Mary; Diana Ngo, Occidental College

Version: View help for Version V1

Name	File Type	Size	Last Modified
code			08/06/2023 09:22:PM
data			08/06/2023 09:22:PM
log			08/07/2023 12:32:AM
maps			08/06/2023 09:22:PM
results			08/06/2023 09:22:PM
LICENSE.txt	text/plain	28.2 KB	08/06/2023 05:22:PM
README.pdf	application/pdf	356.8 KB	08/06/2023 05:22:PM
master.do	text/plain	9.2 KB	08/06/2023 05:22:PM

Project Citation:

Dustan, Andrew, and Ngo, Diana. Data and Code for: Preferences, access, and the STEM gender gap in centralized high school assignment. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-08-16. https://doi.org/10.3886/E193134V1

Project Description

Summary: The gender gap in science, technology, engineering, and mathematics (STEM) widens during high school, due both to differences in student choices and institutional barriers to accessing STEM education. Using rich data from Mexico City's centralized assignment system and a structural model of high school choice, we document strong demand for elite STEM and relatively weak demand for non-elite STEM programs. Decomposition and counterfactual simulations demonstrate that most of the gap is due to gendered choices, with males more strongly preferring STEM. Test-based assignment restricts elite STEM access for females, who have lower placement test scores despite similar low-stakes exam scores.

Scope of Project

Subject Terms: School choice; STEM education; gender disparities

JEL Classification:
      I24 Education and Inequality
      I25 Education and Economic Development
      O10 Economic Development: General

Geographic Coverage: Mexico

Time Period(s): 2007 – 2008

Universe: Public high school applicants in the Mexico City metropolitan area in years 2007 and 2008.

Data Type(s): administrative records data; geographic information system (GIS) data; program source code

Methodology

Unit(s) of Observation: Individual

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Published Versions

V1 [2024-08-16]

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