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There is substantial variation in the returns to a college degree. One determinant is whether a worker's employment is "matched" with their education. With a novel education-industry crosswalk and panel data on 295,000 graduates, we provide the first estimates of an education-industry match premium leveraging within-person variation in earnings. We document which majors have the most and least matching, how earnings premia vary across fields and gender, and how premia evolve over time. With robust estimators, we show that workers in industries "matched" with their degree experience an average earnings premium of 7-11%, with variation by degree level and major.

This brief is part of the Affirming Equity, Ensuring Inclusion, and Empowering Action initiative. The brief describes the emerging practice of direct admissions, including how the practice has been designed, what outcomes it has produced, and considerations for policymakers debating the implementation of a direct admissions program in their state or system. Direct admissions policies address the barriers associated with the admissions process. Direct admissions removes complexity, simplifying the college application process, saving students time and money, and eliminating barriers that disproportionately impact students from minoritized backgrounds due to unevenly distributed social and cultural capital. Direct admissions policies provide students with an early guarantee of college admission at a critical point in high school. This guarantee of acceptance signals the students' college-going potential and reduces the uncertainty and risk of applying. Direct admissions programs tell students that they are college material and that there is a place for them. This holds the potential to overcome wide racial gaps in college-going beliefs. This brief provides summaries of how Idaho, Hawai'i, and Minnesota have adopted and designed direct admissions programs for the public institutions in their states. [Eileen and Harold Brown provided additional funding for this series of briefs.]

The Postsecondary Data Partnership (PDP) is a service of the National Student Clearinghouse established in 2017 to empower institutions with more comprehensive data, easier analysis, centralized reporting functions, and interactive visualizations. Since its inception, over 500 colleges and universities have participated in the PDP. The 2022 PDP Insights report focuses on two primary metrics: students' first year credit completion ratio (CCR) and credit accumulation rate (CAR). The CCR is the ratio of credits earned to credits attempted. This measure of student success and credit attainment can provide insights into students' overall course completion outcomes and measure the efficiency of students' movement through coursework. The CAR directly measures students' timely accumulation of college credits by identifying the share of students who surpassed specific credit-hour thresholds within a given period. This early momentum measure can offer insights into students' progression toward degree completion and provide indicators of when and where gaps in ultimate degree attainment between groups may begin. Students in this analysis are first-time (including first-time in college and first-time, transfer-in), degree-seeking students entering a PDP-participating institution in the 2019-20 cohort.

In 2015, Idaho adopted the nation's first direct admissions system and proactively admitted all high school graduates to a set of public institutions. This reimagination of the admissions process may reduce barriers to students' enrollment and improve access across geographic and socioeconomic contexts by removing many human capital, informational, and financial barriers in the college search and application process. Despite a lack of evidence on the efficacy of direct admissions systems, the policy has already been proposed or implemented in four other states. Using synthetic control methods, we estimate the first causal impacts of direct admissions on institutional enrollment outcomes. We find early evidence that direct admissions increased first-time undergraduate enrollments by 4-8% (50-100 students per campus on average) and in-state levels by approximately 8-15% (80-140 students) but had minimal-to-no impacts on the enrollment of Pell-eligible students. These enrollment gains were concentrated among two-year, open-access institutions. We discuss these findings in relation to state contexts and policy design given the emergence of literature highlighting the varied efficacy of similar college access policies. [This paper was published in "Research in Higher Education."]

While research has documented outcomes for students served by promise programs, few studies have considered the behavior of institutions themselves in the promise era. A new source of revenue combined with larger and more diverse cohorts is likely to motivate changes in spending and staffing--decisions instrumental to student access and success. We employ complementary difference-in-differences and synthetic control strategies to estimate impacts of the first statewide promise program on these two outcomes. Findings suggest institutions diverted expenditures away from instruction, academic support, and institutional support toward greater institutional grant awards. We find no meaningful impact on staffing levels. While some institutional actions may further support the access and success goals of promise programs, the diversity of programs across the nation suggests not all may follow suit. This study should inform policymakers considering the full extent of outcomes of free-college programs and invigorate further research on institutional responses. [This paper was published in "AERA Open."]

System governing boards fulfill roles as both regulators and protectors for their multiple constituent campuses. While centralized control provides many benefits to institutional members, such advantages are also be accompanied by limitations upon campuses to pursue expanded missions, fully compete, and spend according to individual rather than collective priorities. In this study, I leverage a natural experiment where one state "freed" six public universities by removing the oversight of a centralized board. Given a novel opportunity to assess how institutions respond to a new intra-state market characterized by deregulation and increased competition for students, faculty, and other scarce resources, I first focus on changes in three institutional expenditure areas closely tied to entrepreneurship, competition, and prestige-seeking: executive compensation, faculty salaries, and spending on research activities. After constructing a novel dataset with administrative records on compensation and public data on expenditures, I employ complementary difference-in-differences and synthetic control approaches which yield robust evidence suggesting that newly independent universities increased the salary of their president/chancellor by approximately 6.2% (or $19,000), increased the average full professor salary by 2.2% (nearly $2,000), and increased research expenditures by an average of 12% (or $2 million). These findings not only advance the nascent literature on how state governance structures influence institutional behaviors but also provide useful evidence for policymakers considering the intended (and potentially unintended) consequences of similar governance reorganizations. [This paper will be published in "Research in Higher Education."]

As college promise programs proliferate across the United States with noted intentions to promote access through increased affordability, it is necessary to understand the relationship between these programs and other forms of financial aid, including loans. Using federal, state, and program-level data, we leverage a natural experiment to estimate causal impacts of the nation's first statewide program (Tennessee Promise) on students' borrowing behaviors in a community college system. In the difference-in-differences framework, we find robust evidence to suggest Tennessee Promise reduced the percent of first-time, full-time students borrowing by 8-10 percentage points on average after implementation--an over 40% decline--and reduced the average community college cohort loan by $230-360 (nearly 32%). While consistent with prior work on grant aid, these findings are among the first to explore promise students' financial outcomes. We discuss these results in relation to Tennessee Promise's programmatic features and identify important implications for policy and research. [This paper will be published in "The Journal of Higher Education."]

Working for pay is the reality for many undergraduate students. Higher rates and intensity of employment among students from underserved backgrounds and those attending under-resourced institutions suggest employment during college reinforces inequity in higher education opportunity and outcomes. Compared with higher-income students, students from lower-income families work more hours and are more likely to experience negative consequences from working. More must be done to minimize the costs and maximize the benefits of working, especially for students from low-income families, Black, Hispanic, American Indian/Native American, and first-generation students, and independent single parents, as well as students attending community colleges and institutions with high shares of low-income and underserved groups of students.

Reverse transfer associate degrees are credentials retroactively awarded to current bachelor's degree seekers, combining four-year credits with credits previously earned at a community college. Using administrative data from Tennessee, we use a difference-in-difference design to compare students before and after receipt of a reverse transfer degree to similar students over time. We find reverse transfer degrees have little impact on students' academic outcomes (GPA, credits, and bachelor's degree attainment) and labor market outcomes (employment and earnings). Our findings contrast with existing descriptive work reporting large benefits of such degrees, due to our methodological improvements and more robust data. The null effect on earnings suggests that returns to an associate degree are driven by human capital gains rather than signaling in the reverse transfer student population. [This paper will be published in "Journal of Policy Analysis and Management."]

A coarse-grained model is developed to allow large-scale molecular dynamics (MD) simulations of a branched polyetherimide derived from two backbone monomers [4,4'-bisphenol A dianhydride (BPADA) and m-phenylenediamine (MPD)], a chain terminator [phthalic anhydride (PA)], and a branching agent [tris[4-(4-aminophenoxy)phenyl] ethane (TAPE)]. An atomistic model is first built for the branched polyetherimide. A systematic protocol based on chemistry-informed grouping of atoms, derivation of bond and angle interactions by direct Boltzmann inversion, and parameterization of nonbonded interactions by potential of mean force (PMF) calculations via gas-phase MD simulations of atomic group pairs, is used to construct the coarse-grained model. A six-pair geometry, with one atomic group at the center and six replicates of the other atomic group placed surrounding the central group in a NaCl structure, has been demonstrated to significantly speed up the PMF calculations and partially capture the many-body aspect of the PMFs. Furthermore, we propose a correction term to the PMFs that can make the resulting coarse-grained model transferable temperature-wise, by enabling the model to capture the thermal expansion property of the polymer. The coarse-grained model has been applied to explore the mechanical, structural, and rheological properties of the branched polyetherimide., Comment: 19 pages, 11 figures, 4-page Supporting Information

Glass transition temperature ($T_{\text{g}}$) plays an important role in controlling the mechanical and thermal properties of a polymer. Polyimides are an important category of polymers with wide applications because of their superior heat resistance and mechanical strength. The capability of predicting $T_{\text{g}}$ for a polyimide $a~priori$ is therefore highly desirable in order to expedite the design and discovery of new polyimide polymers with targeted properties and applications. Here we explore three different approaches to either compute $T_{\text{g}}$ for a polyimide via all-atom molecular dynamics (MD) simulations or predict $T_{\text{g}}$ via a mathematical model generated by using machine-learning algorithms to analyze existing data collected from literature. Our simulations reveal that $T_{\text{g}}$ can be determined from examining the diffusion coefficient of simple gas molecules in a polyimide as a function of temperature and the results are comparable to those derived from data on polymer density versus temperature and actually closer to the available experimental data. Furthermore, the predictive model of $T_{\text{g}}$ derived with machine-learning algorithms can be used to estimate $T_{\text{g}}$ successfully within an uncertainty of about 20 degrees, even for polyimides yet to be synthesized experimentally., Comment: 12 pages, 10 figures, 25-page Supporting Information

Students enter the college application process on unequal footing--with various levels of financial, social, and cultural capital they can rely on to navigate it. At least 10 states and hundreds of colleges and universities have begun "direct admissions" programs, which proactively admit students using data like their GPA and ACT/SAT scores rather than asking them to apply. Simplifying the college application process is one necessary but still insufficient way to broaden access to higher education. New evidence has helped identify those who are most disadvantaged by the current college application process and shed light on emerging strategies to reduce the negative impacts of applications on students' college-going behaviors. This post reviews two important areas of research: (1) students who start applications but do not submit, and (2) direct admissions.

Background: Community colleges are the primary door to higher education for students of color and those from low-income backgrounds (Bailey et al., 2015; Calcagno et al., 2008). To raise attainment and reduce inequalities in completion, colleges have adopted many student success initiatives--from first-year experience programming and basic needs supports to early alert systems and curricular reforms (Crisp & Taggart, 2013; Goldrick-Rab, 2010). While many strategies are backed by causal evidence (WWC, 2016a, 2021a, 2021b), there is a dearth of information on their costs, including what resources are required to implement, scale, and sustain these strategies. Our work represents the most comprehensive set of cost studies around student success initiatives to date. Nested within a series of eight community college case across three states, we intensively (1) identify the resources required to operate a diverse array of student success programs, (2) pair these resources with national prices, and (3) identify an average cost of each initiative, including what costs are borne by various stakeholders. We then pair these costs with available causal evidence on impacts to identify which initiatives appear most cost-efficient. Purpose/Research Questions: This work makes a substantial contribution to the literature on student success programs, where existing cost studies rest scattered across few works (Belfield et al., 2016; Levin & Garcia, 2013). This work also serves as a guide for administrators and policymakers when considering which programs to implement and what resources are required to achieve equitable outcomes. By pairing causal impacts with costs, we provide immediately useful information for stakeholders seeking to efficiently and effectively raise attainment and equity. To achieve these aims, our work is guided by the following questions: 1. What resources are required to operate a given student success intervention? 2. What is the average cost of the intervention? What share of costs are borne by various stakeholders? 3. Which interventions are most cost-effective at raising outcomes? Setting/Interventions: Our work builds upon case studies that seek to understand how high-performing colleges achieve equitable student outcomes. Within each institution, they draw evidence from interviews with 20 or more internal and external stakeholders and identify a suite of interventions that (1) each college [individually and consistently] noted as essential to their student success strategy and (2) are backed by empirical evidence or internal institutional research. Our cost studies focus on these eight, diverse success interventions. Table 1 provides an overview of our partner colleges, including information on the size of each and their share of Pell-eligible and racially-minoritized students. Table 1 also identifies the interventions of interest, including: first- and second-year student experience (FYE/SYE), prison education/follow-up re-enrollment support; Black/men of color initiative; early alert with complementary supports; basic needs center; and college/career-readiness courses. Our final two colleges/interventions are currently being identified. Research Design, Data, and Analysis: We rely upon the ingredients method to holistically identify all resources (and quantities) required to operate each intervention (Levin et al., 2018). This includes a series of interviews with program leaders/staff, as well as iterative surveys and resource questionnaires. We use empirically-guided cost assumptions to price each ingredient and aggregate costs within functional categories (Shand & Bowden, 2021). Our prices are drawn from national sources (Amazon, BLS, CUPA-HR salary survey, and E$timator/CostOut). When necessary, each is adjusted for inflation, includes fringe, and amortized over time. Aggregating costs (sum of quantity x price) provides the total cost of each initiative, which we disaggregate to identify costs borne by stakeholders (informed by interviews/questionnaires; Levin et al., 2018). Finally, when causal evidence is available, we pair costs with impact estimates in a cost-effectiveness framework to identify which initiatives appear more (or most) efficient at raising a common student outcome (retention or completion; Levin et al., 2018). Findings/Results: Tables 2 and 4 present resource inventories and average costs for a basic needs center; Tables 3 and 5 for FYE/SYE. Cost studies for prison education/re-enrollment, Black/men of color, early alert, and college/career-readiness coursework are underway (to be completed by the end of spring). Cost studies for the remaining colleges and interventions will be completed by summer (in advance of the conference). The basic needs center provides students with food, clothing, and supplies, as well as grants for childcare, transportation, and emergency issues. It also connects students to community-based programs and services. These strategies are supported by causal evidence (WWC, 2020). A basic needs center of this scope uses approximately $1 million in resources/year. This particular center serves roughly 1,500 students/year, resulting in a resource use of $680/student. However, only 64% of costs are borne by the institution, while 36% are covered by donations/activities of external organizations. This FYE/SYE program provides priority registration, personal coaching, customized advising, and access to a Student Success Center. This is also supported by causal evidence (WWC, 2016b). A FYE/SYE program of this scope uses approximately $750,000 in resources/year. Given that it serves roughly 560 students/year, its resource use is $1,340/student. The vast majority of costs are in personnel who provide advising and coaching to each student for at least 4 hours per year, though students also face requirements to participate, including time commitments beyond that of coursework, resulting in induced costs of roughly $16,000/year. Upon the completion of all cost studies, we will leverage a cost-effectiveness framework to pair each cost with available evidence on the intervention's ability to raise a common retention or completion outcome, allowing us to identify which intervention(s) are most cost-efficient. Conclusion: In all, our work represents the most comprehensive set of cost studies around student success initiatives to date and not only makes a substantial contribution to existing literature on the costs of student success programs but also compiles actionable information for college administrators and policymakers when considering which programs to implement and what resources are required to achieve equitable student outcomes.

A Monte Carlo (MC) simulation method based on the Gillespie algorithm is developed for the polymerization of branched polyetherimides from two back-bone monomers [4,4'-bisphenol A dianhydride (BPADA) and m-phenylenediamine (MPD)], a chain terminator [phthalic anhydride (PA)], and a branching agent [tris[4-(4-aminophenoxy)phenyl] ethane (TAPE)]. This polymerization involves 4 reactions that all can be reduced to a condensation reaction between an amine group and a carboxylic anhydride group. By comparing the MC simulation results to the predictions of the Flory-Stockmayer theory on the molecular weight distribution, we show that the rates of the 4 reactions in the MC simulations should be set based on the concentrations of the functional groups on the monomers involved in each reaction. Using the MC simulations, we show that the Flory-Stockmayer theory predicts the molecular weight distribution well for systems below the gel point that is set by the functionality of the branching agent but starts to fail for systems around or above the gel point. However, for all the systems the MC simulations can be used to reliably predict the molecular weight distribution. Even for a macroscopic system, a converging distribution can be quickly obtained through the MC simulations on a system of only a few hundred to a few thousand monomers but with the same molar ratios of monomers as in the macroscopic system., Comment: 12 pages, 9 figures, 5 tables