Project Activities
The researchers will conduct three phases of work. In phase 1, they will use a hashed linkage methodology to link de-identified data from three agencies to establish the Student Supports database and conduct a landscape scan to document existing outreach efforts at community colleges throughout the state. In phase 2, they will use this new data resource to simulate eligibility measures for SNAP and analyze students' take-up rates. In phase 3, they will examine the relationship between SNAP participation and learner outcomes (persistence in college, progress toward a certificate or degree, academic achievement, and credential completion).
Structured Abstract
Setting
The setting will be the state of California with a focus on the California community college system, which includes 115 colleges across the state serving over 2 million students each year.
Sample
The study sample includes over 9 million students who enrolled in a California community college between 2010 and 2020 and additional students who enroll between 2020 and 2025. Data on this population from California Community College Chancellor's Office (CCCCO) records will be linked to universe data from students' Free Applications for Federal Student Aid (FAFSAs) from the California Student Aid Commission (CSAC), and to CalFresh (SNAP) participation records from the California Department of Social Services (CDSS). Each agency will provide census data on the universe of relevant individuals in California from 2010 to 2025.
This study will examine the relationship between safety net program participation and learner outcomes (measured as persistence in college, progress toward a certificate or degree, academic achievement, and credential completion).
Research design and methods
First, the researchers will conduct descriptive analyses to estimate SNAP eligibility and rates of participation. They will use data from California community college records and from FAFSAs held by CSAC to construct measures of student eligibility. They will also create rules for the analysis based on unique eligibility criteria and will estimate SNAP eligibility and participation rates by student group, including by race, ethnicity, gender, financial aid status, county, and community college region.
Next, the researchers will examine the relationship between receiving benefits and student success. They will use propensity score weighting methods to provide estimates of the effect of participation in SNAP on learner outcomes for those receiving and not receiving SNAP benefits.
Control condition
In the propensity score weighting analysis, California community college students who do not receive SNAP benefits will serve as the control group. These students will be observably similar (on demographics, region, college attended, and financial circumstances) to those who receive SNAP benefits.
Key measures
The researchers will use measures of students' income and financial resources to construct measures of eligibility for enrollment in SNAP. They will analyze a host of postsecondary learner outcomes including persistence in college (continued enrollment); progress through college (number of credits earned, time between enrollment and completion); academic achievement (grade point average); and completion of degree, credential, or transfer to a 4-year institution. They will employ measures of student demographics (e.g., race, ethnicity, age) to understand subgroup differences in eligibility and uptake of benefits and to assess differences in their effects on learner outcomes.
Data analytic strategy
In phase 1, the researchers will use a hashed linkage methodology to link de-identified data from three agencies to create the Student Supports database. In phase 2, they will conduct descriptive analyses of the data in the database and conduct t-tests and chi-square tests to assess the significance of differences in program participation and take-up rates. They will explore heterogeneity in participation and take-up rates across a range of different student characteristics, including demographic characteristics, previous enrollment in any services (and/or family enrollment), student type (e.g., new or returning, enrolled in one or multiple campuses), and college and program type. They will also examine geographic variation in participation and take-up rates by county and community college region.
In phase 3, the researchers will use multivariate regression methods to compare students receiving SNAP benefits to other students who appear eligible but are not receiving benefits, using inverse propensity score weighting to ensure comparability between the groups. First, they will estimate a propensity score model via a logistic regression of an indicator of SNAP participation on students' observable characteristics and year and term fixed effects. Then, they will use the estimated propensity scores to form new weights for the control observations and generate a weighted control sample that will have approximately the same distribution of propensity scores as the treated sample. Finally, they will estimate weighted regression models of the outcomes on the treatment status that include covariates, campus fixed effects, and year fixed effects.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
The researchers aim to develop and share concise policy briefs for non-technical audiences, white papers documenting their methods, and peer-reviewed publications on the results of their work. The also aim to share information through multiple dissemination outlets, including the California Higher Education Basic Needs Alliance (CHEBNA) webinars and a convening of California program administrators and policymakers from partner agencies with academic experts on community college student success, in addition to traditional media outreach and academic conference presentations.
Publications:
ERIC Citations: Publications from this project are available here.
Questions about this project?
To answer additional questions about this project or provide feedback, please contact the program officer.
