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As affirmative action loses political feasibility, many universities have implemented race-neutral alternatives like top percent policies and holistic review to increase enrollment among disadvantaged students. I study these policies’ application, admission, and enrollment effects using University of California administrative data. UC’s affirmative action and top percent policies increased underrepresented minority (URM) enrollment by over 20 percent and less than 4 percent, respectively. Holistic review increases implementing campuses’ URM enrollment by about 7 percent. Top percent policies and holistic review have negligible effects on lower-income enrollment, while race-based affirmative action modestly increased enrollment among very low-income students. These findings highlight the enrollment gaps between affirmative action and its most common race-neutral alternatives and reveal that available policies do not substantially affect universities’ socioeconomic composition.
Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models -- one predicting course completion, the second predicting degree completion. Our results show that algorithmic bias in both models could result in at-risk Black students receiving fewer success resources than White students at comparatively lower-risk of failure. We also find the magnitude of algorithmic bias to vary within the distribution of predicted success. With the degree completion model, the amount of bias is nearly four times higher when we define at-risk using the bottom decile than when we focus on students in the bottom half of predicted scores. Between the two models, the magnitude and pattern of bias and the efficacy of basic bias mitigation strategies differ meaningfully, emphasizing the contextual nature of algorithmic bias and attempts to mitigate it. Our results moreover suggest that algorithmic bias is due in part to currently-available administrative data being less useful at predicting Black student success compared with White student success, particularly for new students; this suggests that additional data collection efforts have the potential to mitigate bias.
This paper estimates a dynamic model of college enrollment, progression, and graduation. A central feature of the model is student effort, which has a direct effect on class completion and an indirect effect mitigating risks on class completion and college persistence. The estimated model matches rich administrative data for a representative cohort of college students in Colombia. Estimates indicate that effort has a much greater impact than ability on class completion. Failing to consider effort as an input to class completion leads to overestimating ability’s role by a factor of two or three. It also promotes tuition discounts based on a pre-determined student trait—ability—rather than effort, which can be affected through policy, thus limiting higher education’s potential for social mobility.
Despite the growing popularity of free college proposals, countries with higher college subsidies tend to have higher enrollment rates but not higher graduation rates. To capture this evidence and evaluate potential free college policies, we rely on a dynamic model of college enrollment, performance, and graduation estimated using rich student-level data from Colombia. In the model, student effort affects class completion and mitigates the risk of performing poorly or dropping out. Among our simulated policies, universal free college expands enrollment the most but has virtually no effect on graduation rates, helping explain the cross-country evidence. Performance-based free college triggers a more modest enrollment expansion but delivers a higher graduation rate at a lower fiscal cost. While both programs lower student uncertainty relative to the baseline, performance-based free college does it to a lower extent, which in turn promotes better student outcomes. Overall, free college programs expand enrollment but have limited impacts on graduation and attainment due to their limited impact on student effort.
This paper estimates the heterogeneous labor market effects of enrolling in higher education short-cycle (SC) programs. Expanding access to these programs might affect the behavior of some students (compliers) in two margins: the expansion margin (students who would not have enrolled in higher education otherwise) and the diversion margin (students who would have enrolled in bachelor’s programs otherwise). To quantify these responses, we exploit local exogenous variation in the supply of higher education institutions (HEIs) facing Colombian high school graduates in an empirical multinomial choice model with several instruments. According to our findings, the presence of at least one HEI specialized in SC programs in the vicinity of the student’s high school municipality increases SC enrollment by 3.7-4.5 percentage points (40-50% of the SC enrollment rate). The diversion margin largely drives this effect. For female compliers, enrollment in SC programs increases formal employment relative to the next-best alternative. For male compliers, in contrast, it lowers formal employment and wages. These results should alert policymakers of the unexpected consequences of higher education expansionary policies.
Short-cycle higher education programs (SCPs), lasting two or three years, capture about a quarter of higher education enrollment in the world and can play a key role enhancing workforce skills. In this paper, we estimate the program-level contribution of SCPs to student academic and labor market outcomes, and study how and why these contributions vary across programs. We exploit unique administrative data from Colombia on the universe of students, institutions, and programs to control for a rich set of student, peer, and local choice set characteristics. We find that program-level contributions account for about 60-70 percent of the variation in student-level graduation and labor market outcomes. Our estimates show that programs vary greatly in their contributions, across and especially within fields of study. Moreover, the estimated contributions are strongly correlated with program outcomes but not with other commonly used quality measures. Programs contribute more to formal employment and wages when they are longer, have been provided for a longer time, are taught by more specialized institutions, and are offered in larger cities.
Short-cycle higher education programs (SCPs) form skilled human capital in two or three years and could be key to upskilling and reskilling the workforce, provided their supply responds fast and nimbly to local labor market needs. We study determinants of SCP entry and exit in Colombia for markets defined by geographic location and field of study. We show greater dynamism in the market for SCPs than bachelor’s program, with greater turnover or “churn” of programs. Exploiting data on local economic activity and employment by field of study, we find that higher education institutions open new SCPs in response to local labor market demand as well as competition and costs. SCPs are more responsive to local labor market demand than bachelor’s programs; among SCP providers, private and non-university institutions are the most responsive. While private SCP entry is deterred by the presence of competitors and responds to cost considerations, these responses are weaker among public SCPs. Further, institutions often open and close programs simultaneously within a field, perhaps reflecting capacity constraints. These findings have implications for the regulation and funding of SCP providers.
Short-cycle higher education programs (SCPs) can play a central role in skill development and higher education expansion, yet their quality varies greatly within and among countries. In this paper we explore the relationship between programs’ practices and inputs (quality determinants) and student academic and labor market outcomes. We design and conduct a novel survey to collect program-level information on quality determinants and average outcomes for Brazil, Colombia, Dominican Republic, Ecuador, and Peru. Categories of quality determinants include training and curriculum, infrastructure, faculty, link with productive sector, costs and funding, and practices on student admission and institutional governance. We also collect administrative, student-level data on higher education and formal employment for SCP students in Brazil and Ecuador and match it to survey data. Using machine learning methods, we select the quality determinants that predict outcomes at the program and student levels. Estimates indicate that some quality determinants may favor academic and labor market outcomes while others may hinder them. Two practices predict improvements in all labor market outcomes in Brazil and Ecuador—teaching numerical competencies and providing job market information—and one practice—teaching numerical competencies—additionally predicts improvements in labor market outcomes for all survey countries. Since quality determinants account for 20-40 percent of the explained variation in student-level outcomes, quality determinants might have a role shrinking program quality gaps. Findings have implications for the design and replication of high-quality SCPs, their regulation, and the development of information systems.
This study examines the effects of the MATC Promise, a public-private partnership that offered to pay tuition at Milwaukee Area Technical College (MATC) for local high school graduates. The MATC Promise exemplifies the most common type of college promise program, a last-dollar community college tuition promise. If students completed academic milestones, applied for state and federal aid, and qualified based on low family income, then the Promise would cover any remaining tuition charges. In practice, the message of a promise was the main treatment, since most eligible students would not have any tuition charges remaining for the program to cover after applying state and federal aid. We evaluate the effects of the Promise on increasing college enrollment and degree completion after its introduction in 2016. Milwaukee is unique within the Wisconsin, making it difficult to find relevant comparison groups in statewide data. Examining the interrupted time series within the city’s school districts shows an increase in enrollment at MATC from 10 percent of high school graduates to 15 percent after the Promise was introduced. About half of the increase came from students who would not have enrolled at all, with the rest diverting from enrolling at other colleges and universities. These effects were concentrated among lower-income students and those in the inner city. These results indicate that the Promise positively influenced college attainment by encouraging students to access state and federal aid they already qualified for. We conclude that the message of college affordability was effective at encouraging students to overcome application barriers and enroll in college.
We used Critical Discourse Analysis to examine the racial discourse within recent attempts to reauthorize the Higher Education Act. Specifically, we interrogated congressional markup hearings to understand how members frame student debt and the racialized dynamics embedded within. Our findings highlight three types of discourse: “All Students” Matter, Paternalistic, Race-Evasive, and Explicit Racial Discourse. We offer recommendations for research and policymaking.