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The equity-efficiency tradeoff and cumulative return theories predict larger returns to school spending in areas with higher previous investment in children. Equity – not efficiency – is therefore used to justify progressive school funding: spending more in communities with fewer financial resources. Yet it remains unclear how returns to school spending vary across areas by previous investment. Using county-level panel data 2009-2018 from the Stanford Education Data Archive, the F-33 finance survey, and National Vital Statistics, we estimate achievement returns to school spending and test whether returns vary between counties with low and high levels of initial human capital (measured as birth weight), child poverty, and previous spending. Spending returns are higher among counties with low previous investment (counties that also have a high percent of Black students). Evidence of diminishing returns by previous investment documents another way that schools increase equality and establishes another argument for progressive school funding: efficiency.
Infant sex ratios that differ from the biological norm provide a measure of gender status inequality that is not susceptible to social desirability bias. Ratios may become less biased with educational expansion through reduced preference for male children. Alternatively, bias could increase with education through more access to sex-selective medical technologies. Using National Vital Statistics data on the population of live births in the U.S. 1969-2018, we examine trends in infant sex ratios by parental race/ethnicity, education, and birth parity over 5 decades. We find son-biased infant sex ratios among Chinese and Asian Indian births that persist in recent years and regressions suggest son-biased ratios among births to Filipino and Japanese mothers with less than high school education. Infant sex ratios are more balanced at higher levels of maternal education, particularly when both parents are college educated. Results suggest greater equality of gender status with higher education in the U.S.
Can public university honors programs deliver the benefits of selective undergraduate education within otherwise nonselective institutions? We evaluate the impact of admission to the Honors College at Oregon State University, a large nonselective public university. Admission to the Honors College depends heavily on a numerical application score. Nonlinearities in admissions probabilities as a function of this score allow us to compare applicants with similar scores, but different admissions outcomes, via a fuzzy regression kink design. The first stage is strong, with takeup of Honors College programming closely following nonlinearities in admissions probabilities. To estimate the causal effect of Honors College admission on human capital formation, we use these nonlinearities in the admissions function as instruments, combined with course-section fixed effects to account for strategic course selection. Honors College admission increases course grades by 0.10 grade points on the 0-4 scale, or 0.14 standard deviations. Effects are concentrated at the top of the course grade distribution. Previous exposure to Honors sections of courses in the same subject is a leading potential channel for increased grades. However, course grades of first-generation students decrease in response to Honors admission, driven by low performance in natural science courses. Results suggest that selective Honors programs can accelerate skill acquisition for high-achieving students at public universities, but not all students benefit from Honors admission.
We study the conditional gender wage gap among faculty at public research universities in the U.S. We begin by using a cross-sectional dataset from 2016 to replicate the long-standing finding in research that conditional on rich controls, female faculty earn less than their male colleagues. Next, we construct a data panel to track the evolution of the wage gap through 2021. We show that the gap is narrowing. It declined by more than 50 percent over the course of our data panel to the point where by 2021, it is no longer detectable at conventional levels of statistical significance.
This paper introduces a new measure of the labor markets served by colleges and universities across the United States. About 50 percent of recent college graduates are living and working in the metro area nearest the institution they attended, with this figure climbing to 67 percent in-state. The geographic dispersion of alumni is more than twice as great for highly selective 4-year institutions as for 2-year institutions. However, more than one-quarter of 2-year institutions disperse alumni more diversely than the average public 4-year institution. In one application of these data, we find that the average strength of the labor market to which a college sends its graduates predicts college-specific intergenerational economic mobility. In a second application, we quantify the extent of “brain drain” across areas and illustrate the importance of considering migration patterns of college graduates when estimating the social return on public investment in higher education.
Von Hippel & Cañedo (2021) reported that US kindergarten teachers placed girls, Asian-Americans, and children from families of high socioeconomic status (SES) into higher ability groups than their test scores alone would warrant. The results fit the view that teachers were biased.
This comment asks whether parents’ lobbying for higher placement might explain these results. The answer, for the most part, is no. Measures of parent-teacher contact explained little variation in children’s ability group placement, and did not account for the higher placement of girls, Asian-Americans, or high-SES children. In fact, Asian-American parents had less teacher contact than did white children. It appears that the biases observed by von Hippel & Cañedo resided primarily in teachers, not in parents.
We also ask whether teachers who used more objective assessment techniques were less biased in placing children into higher and lower ability groups. The answer, again, was no. Unfortunately, biases persisted in the face of objective information about students’ skill. Fortunately, the biases were not terribly large.
Existing research indicates that racially minoritized students with similar academic preparation are less likely than their represented peers to persist in STEM, raising the question of factors that may contribute to racial disparities in STEM participation beyond academic preparation. We extend the current literature by first examining race-based differences in what students expect to receive and their actual grades in introductory STEM college courses, a phenomenon termed as overestimation. Then, we assess whether overestimation differentially influences STEM interest and persistence in college. Findings indicate that first-year STEM students tend to overestimate their performance in general, and the extent of overestimation is more pronounced among racially minoritized students. Subsequent analyses indicate that students who overestimate are more likely to switch out of STEM, net academic preparation. Results from regression models suggest that race-based differences in overestimation can be explained by pre-college academic and contextual factors, most notably the high school a student attended.
Public discussions of racial inclusion and equal opportunity initiatives in the U.S. are often met with claims that expanding access to an institution, space, or public good is likely to diminish its quality. Examples of this pattern include: anticipated (and real) property value declines when predominantly white neighborhoods become more racially diverse; fears that the excellence of white schools will decline when the population of Black and brown students grows; apprehensions that equitable hiring practices necessarily entail lower standards for job candidates. In this paper, we examine how a federal agency, the Fund for the Improvement of Postsecondary Education (FIPSE), charged with addressing the aftermath of the ‘access wave’ of new college students promulgated by the Higher Education Act of 1965, came to reconcile its commitments to educational equity and quality. Through a novel examination of the historical development of what we term (e)quality politics in the administration of civil rights policy in higher education, we trace how two concepts - equity and quality – became discursively linked and contested in American politics. (E)quality politics refers to the introduction of a policy paradigm that reframes equity discussions and goals around the professed need to preserve and advance institutional “quality” using measures and standards that are, importantly, defined and instantiated under the era of segregation that precedes equal access policies. In particular, we uncover the discursive patterns by which the perceived threats to “quality” posed by racial diversity can prompt administrators to compensate, protect, and maintain the prerogatives of high-status institutions or groups that benefited under previous eras of exclusion. Understood as part of a backlash to egalitarian reforms, we argue, these quality measures undermine equity goals.
Promoting equality in college enrollment and completion must start early in students’ college-going journeys, including with their expectations to first earn a college degree. With a nationally representative sample of high school students, I evaluate the ability of a recent collection of college access policies (place-based “promise” scholarships or “free” college programs) to increase students’ college expectations and test the heterogeneity of these impacts across students’ race and family income. Evidence from a difference-in-differences design and lagged-dependent-variable regressions suggest the introduction of promise programs increased the likelihood a student expected to attain an associate degree or higher by 8.5 to 15.0 percentage points by the end of high school, with larger effects for low-income and racially minoritized students. This study is the first to test the power of “free” college in shaping pre-college students’ educational plans, and, in doing so, not only addresses an existing gap in the literature but also identifies a key mechanism through which many of the positive college-going impacts observed across promise programs in the current literature may in fact originate. Given the rapid proliferation of promise programs across the nation, this study provides policymakers with a fuller view of the potential impacts of these programs, particularly concerning how they influence students’ outcomes along dimensions of race and income.
Despite documented benefits to college completion, more than a third of students who initially enroll in college do not ultimately earn a credential. Completing college requires students to navigate both institutional administrative tasks (e.g., registering for classes) and academic tasks within courses (e.g., completing homework). In postsecondary education, several promising interventions have shown that text-based outreach and communication can be a low-cost, easy to implement, and effective strategy for supporting administrative task navigation. In this paper, we report on a randomized controlled trial testing the effect of a text-based chatbot with artificial intelligence (AI) capability on students' academic task navigation. We find the academic chatbot significantly shifted students’ final grades, increasing the likelihood students received a course grade of B or higher by eight percentage points. We find large and significant treatment effects for first-generation students, estimating the intervention increased their final course grades by about 11 points on a 100-point scale (and a 16 percentage point increase in earning a B or higher) as well as their completion of and performance on individual course deliverables (e.g., readings, activities, exams).