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Are Community College Students Increasingly Choosing High-Paying Fields of Study? Evidence from Massachusetts
The labor-market payoff to workers with associate degrees in healthcare and STEM occupations is very high in Massachusetts. We examine whether this induced a growing proportion of students in MA community colleges (MACCs) to earn an associate degree (AD) in one of these fields. We do this by using multinomial logit analysis to compare trends across 12 cohorts of MACC entrants in the proportion of students who earned an AD in a healthcare or STEM program within six years of entry.
We find a substantial increase across cohorts in the proportion of students who earned an AD in a STEM program, but not in the proportion who earned an AD in a healthcare program. We found differences in degree attainment by student gender, race/ethnicity, family income, and 10th-grade mathematics score. Interviews with MACC program leaders revealed that supply constraints hinder expansion of many healthcare AD programs, but not STEM programs.
The Returns to Education over time and the Effect of COVID-19
This paper examines the effects of the COVID-19 pandemic on the returns to education in the United States. Using data from the Current Population Survey 2011-2022, the analysis reveals that, after a period of decline, returns to education increased significantly because of COVID, particularly for men and those with university education. The returns to university for men increased by 1 percentage points. The results underscore the importance of continued investment in education to mitigate the adverse effects of future crises.
Distance to Degrees: How College Proximity Shapes Students’ Enrollment Choices and Attainment Across Race-Ethnicity and Socioeconomic Status
Leveraging rich data on the universe of Texas high school graduates, we estimate how the relationship between geographic access to public two- and four-year postsecondary institutions and postsecondary outcomes varies across race-ethnicity and socioeconomic status. We find that students are sensitive to the distance they must travel to access public colleges and universities, but there are heterogeneous effects across students – particularly with regard to distance to public two-year colleges (i.e., community colleges). White, Asian, and higher-income students who live in a community college desert (i.e., at least 30 minutes driving time from the nearest public two-year college) substitute towards four-year colleges and are more likely to complete bachelor’s degrees. Meanwhile, Black, Hispanic, and lower-income students respond to living in a community college desert by forgoing college enrollment altogether, reducing the likelihood that they earn associate’s and reducing the likelihood that they ultimately transfer to four-year colleges and earn bachelor’s degrees. These relationships persist up to eight years following high school graduation, resulting in substantial long-term gaps in overall degree attainment by race-ethnicity and income in areas with limited postsecondary access.
Toward a Comprehensive Model Predicting Credit Loss in Vertical Transfer
A growing body of research has documented extensive credit loss among transfer students. However, the field lacks theoretically driven and empirically supported frameworks that can guide credit loss research and reforms. We develop and then test a comprehensive framework designed to address this gap using novel administrative credit loss data from Texas. Our results demonstrate how the likelihood of credit loss varies across course characteristics, majors, pretransfer academics, student characteristics, and sending and receiving institutions. Additionally, we are able to disentangle general credit loss from major credit loss and examine how they vary across institutions, majors, and the combination of both. The extensive variation in credit loss among universities in particular underscores the need for future research and reform.
Credit Loss, Institutional Retention, and Postsecondary Persistence Among Vertical Transfer Students
Although community colleges have served as a gateway to universities for millions of students—disproportionately so for students from populations historically underrepresented in higher education—prior research has demonstrated that the majority of vertical transfer students lose at least some of their pretransfer credits. However, researchers examining how credit loss relates to subsequent college outcomes have been hindered by data limitations. For this study, we drew from the literature on academic momentum and examined the relationship between credit loss, institutional retention, and postsecondary persistence. Our use of novel administrative data from Texas enabled us to disentangle major credit loss from general credit loss and study the contribution of each credit loss type to posttransfer outcomes. Our analyses show that both forms of credit loss are inversely related to institutional retention, but the relationships between credit loss and postsecondary persistence are far less consistent. We found evidence suggesting that major credit loss is more strongly related to both retention and persistence than general credit loss. We did not find evidence that the relationship between credit loss and posttransfer outcomes is moderated by students’ race/ethnicity, economic status, or gender, and we found only limited evidence of moderation by major.
Local Labor Market Alignment of Short-Term Certificate Programs
Short-term certificate (STC) programs at community colleges represent a longstanding policy priority to align accelerated postsecondary credentials with job opportunities in local labor markets. Despite large investments in developing STCs, little evidence exists about where and when STCs are opened and whether community colleges open new programs of study in coordination with labor market trends. Using public workforce and postsecondary data, I examine health and manufacturing STC program openings to understand alignment with labor market activity in related industries. I find that STCs are spatially aligned across labor markets within a state, but not necessarily temporally aligned with county-specific trends. One additional STC per college is associated with labor markets that had 2-3 percentage points more total employment and new hires in related industries. Large launches of clustered STC programs occurred before periods of growth in health employment but declines in manufacturing. Large launches preceded earnings growth of 2-5 percentage points in both sectors.
More Money for Less Time? Examining the Relative and Heterogenous Financial Returns to Non-Degree Credentials and Degree Programs
There is a large and growing number of non-degree credential offerings between a high school diploma and a bachelor's degree, as well as degree programs beyond a bachelor’s degree. Nevertheless, research on the financial returns to non-degree credentials and degree-granting programs is often narrow and siloed. To fill this gap, we leverage a national sample of individuals across nine MSAs and four industries to examine the relative financial returns to a variety of non-degree credentials and degree programs. Leveraging two-way fixed-effect models, we explore the relationship between completing a credential or degree and earnings premiums. We find that an associate’s, bachelor’s, master’s and doctorate degree follows a similar model of returns in which the number of schooling years is linearly related to proportional earnings premiums. However, students completing sub-baccalaureate certificates and earning non-school credentials appear to get larger financial returns for less time. Additionally, while we noticed subtle differences across degree programs, we noticed substantial differences in non-school credentials: only women experienced a significant earnings premium from a non-degree credential. Finally, in terms of race/ethnicity, students of color often experienced larger economic returns to undergraduate certificates and degree programs.
Foreign Student Share and Supply of STEM-Designated Economics Programs
Over the past decade, there has been a significant increase in the number of U.S. institutions offering STEM-eligible degree programs in economics. This paper documents the trends in STEM-degree offerings across degree levels and examines the share of foreign students and other characteristics of institutions that offer STEM-eligible programs. Using a difference-in-differences design, this paper finds that departments with a proportion of foreign students above the sample median are 6 and 9 percentage points more likely to offer a STEM-eligible degree program at the bachelor's and master's levels, respectively, after the STEM designation in 2013. Additionally, the tobit regression results suggest that early adopters of STEM-eligible programs are associated with a higher share of foreign students, private institutions and doctoral and research institutions.
Classifying Courses at Scale: a Text as Data Approach to Characterizing Student Course-Taking Trends with Administrative Transcripts
Students’ postsecondary course-taking is of interest to researchers, yet has been difficult to study at large scale because administrative transcript data are rarely standardized across institutions or state systems. This paper uses machine learning and natural language processing to standardize college transcripts at scale. We demonstrate the approach’s utility by showing how the disciplinary orientation of students’ courses and majors align and diverge at 18 diverse four-year institutions in the College and Beyond II dataset. Our findings complicate narratives that student participation in the liberal arts is in great decline. Both professional and liberal arts majors enroll in a large amount of liberal arts coursework, and in three of the four core liberal arts disciplines, the share of course-taking in those fields is meaningfully higher than the share of majors in those fields. To advance the study of student postsecondary pathways, we release the classification models for public use.
Diversity Trends Among Faculty in STEM and non-STEM Fields at Selective Public Universities in the U.S. from 2016 to 2023
During the 2015-16 academic year, racial protests swept across college campuses in the U.S. These protests were followed by large university investments in initiatives to promote diversity, which combined with existing diversity dynamics, have helped to shape recent faculty diversity trends. We document diversity trends among faculty in STEM and non-STEM fields since the protests in 2015-16. We find that recent diversity trends are narrowing the gender gap among faculty in STEM and non-STEM fields, but widening racial-ethnic gaps, especially among Black faculty. A large body of prior research suggests these trends will affect students’ college experiences and how they choose majors.