Code for Replication of Neighbors' Effects on University Enrollment

Principal Investigator(s): View help for Principal Investigator(s) Andrés Barrios-Fernández, CEP (LSE) and VATT Institute for Economic Research

Version: View help for Version V1

Name	File Type	Size	Last Modified
Sample_data			05/09/2021 06:07:AM
00_master.do	text/plain	4.6 KB	05/09/2021 01:56:AM
01_01_00_neighborhood_units.do	text/plain	825 bytes	05/09/2021 01:18:AM
01_01_01_finding_neighbors.do	text/plain	2.4 KB	05/08/2021 05:20:AM
01_01_02_psu_scores.do	text/plain	1.6 KB	05/08/2021 04:35:AM
01_01_03_psu_applications.do	text/plain	1.7 KB	12/18/2020 10:54:PM
01_01_04_psu_ses.do	text/plain	6 KB	12/18/2020 10:54:PM
01_01_05_psu_siblings.do	text/plain	546 bytes	12/18/2020 10:58:PM
01_01_06_he_funding.do	text/plain	4.3 KB	12/19/2020 12:07:AM
01_01_07_he_enrollment.do	text/plain	3.4 KB	12/18/2020 11:26:PM

Project Citation:

Barrios-Fernández, Andrés. Code for Replication of Neighbors’ Effects on University Enrollment. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-06-15. https://doi.org/10.3886/E134781V1

Project Description

Summary: This paper provides causal evidence that close neighbors significantly influence potential applicants’ decision to attend university. I create a unique dataset combining detailed geographic information and individual educational records in Chile, and exploit the quasi-random variation generated by student loans eligibility rules. I find that potential applicants are significantly more likely to attend and complete university when their closest neighbor—defined as the closest individual applying to university the previous year—becomes eligible for a student loan and enrolls in university. This increase in enrollment is mediated by an increase in the probability of taking the admission exam and applying to university. The closest neighbor typically lives 0.09 km away, and neighbors’ influence decays with distance. My results highlight the importance of social influences for university enrollment decisions and suggest that financial aid and university access policies may have important spillover effects

Scope of Project

Subject Terms: Neighbors' effects; University access; Spatial spillovers

JEL Classification:
      I21 Analysis of Education
      I24 Education and Inequality
      R23 Urban, Rural, Regional, Real Estate, and Transportation Economics: Regional Migration; Regional Labor Markets; Population; Neighborhood Characteristics
      R28 Urban, Rural, Regional, Real Estate, and Transportation Economics: Government Policy

Geographic Coverage: Chile

Time Period(s): 2002 – 2016

Collection Date(s): 2016 – 2019

Universe: Individuals graduating from high school.

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

Collection Notes: Some of the data used in this project can only be accessed after submitting a research proposal and obtaining authorization from the public agencies that collect and manage it.

Methodology

Data Source: The data used in this project corresponds to administrative records managed by the following public agencies in Chile:

Ministerio de Educación (2002-2016):

Schools directory (2006, 2008, 2010, 2012).
Students' school performance (2002-2016).
Higher education enrollment (2006-2016).
Higher education graduation (2007-2019).
Funding for higher education (2006-2016).

Agencia de la Calidad de la Educación (2006-2012):

Standardized tests individual-level scores (2006, 2008, 2010, 2012).
Parents' answers to SIMCE survey (2006, 2008, 2010, 2012).

Departamento de Evaluación, Medición y Registros Académicos de la Universidad de Chile

Registration and scores in university admission exam (2004-2016).
Applications to university degrees (2004-2016).
Enrollment in university degrees (2004-2016).
Socioeconomic variables reported by students when registering for university admission exam (2004-2016).

Ministerio de Desarrollo Social y de la Familia:

Neighborhood units (2017).
National household survey: "Encuesta de caracterización socioecónomica nacional, CASEN" (2015).

Unit(s) of Observation: Students.

Related Publications

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Published Versions

V1 [2022-06-15]

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