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Current public pension funding policy has arguably failed on both theoretical and empirical grounds. The traditional actuarial approach elides the risk-return tradeoff at the heart of finance economics and has resulted in steadily rising contribution rates, instead of a sustainable steady state. We propose an economic reformulation of funding policy based on steady-state analysis of the fundamental equations of motion for pension asset and liability growth, incorporating both an expected return on risky assets and a low-risk discount rate for liabilities. Our steady-state result simultaneously conveys the benefit of risky investment and the cost of the associated risk. We integrate our analysis into a simple social welfare function to re-examine the basis for pre-funding and elucidate the net benefits of using risky assets to defray contributions. We also formally derive a family of transition policies for convergence to the expected steady state. We illustrate how the parameters of our proposed policy can be adjusted to manage the tradeoff between long-run contribution rate risk and short-term responsiveness. We believe our analysis provides the basis for reformulating contribution policy in a way that better supports sustainability and coherently conveys the tradeoffs consistent with finance economics.
Billions of dollars are invested in opt-in, educational resources to accelerate students’ learning. Although advertised to support struggling, marginalized students, there is no guarantee these students will opt in. We report results from a school system’s implementation of on-demand tutoring. The take up was low. At baseline, only 19% of students ever accessed the platform, and struggling students were far less likely to opt in than their more engaged and higher achieving peers. We conducted a randomized controlled trial (N=4,763) testing behaviorally-informed approaches to increase take-up. Communications to parents and students together increase the likelihood students access tutoring by 46%, which led to a four-percentage point decrease in course failures. Nonetheless, take-up remained low, showing concerns that opt-in resources can increase—instead of reduce—inequality are valid. Without targeted investments, opt-in educational resources are unlikely to reach many students who could benefit.
Books shape how children learn about society and norms, in part through representation of different characters. We introduce new artificial intelligence methods for systematically converting images into data and apply them, along with text analysis methods, to measure the representation of race, gender, and age in award-winning children’s books from the past century. We find that more characters with darker skin color appear over time, but the most influential books persistently depict a greater proportion of light-skinned characters than other books, even after conditioning on race; we also find that children are depicted with lighter skin than adults. Relative to their growing share of the U.S. population, Black and Latinx people are underrepresented in these same books, while White males are overrepresented. Over time, females are increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. We then report empirical evidence for predictions about the supply of and demand for representation that would generate these patterns. On the demand side, we show that people consume books that center their own identities. On the supply side, we document higher prices for books that center non-dominant social identities and fewer copies of these books in libraries that serve predominantly White communities. Lastly, we show that the types of children’s books purchased in a neighborhood are related to local political beliefs.
We investigate whether and how Achieve Atlanta’s college scholarship and associated services impact college enrollment, persistence, and graduation among Atlanta Public School graduates experiencing low household income. Qualifying for the scholarship of up to $5,000/year does not meaningfully change college enrollment among those near the high school GPA eligibility thresholds. However, scholarship receipt does have large and statistically significant effects on early college persistence (i.e., 14%) that continue through BA degree completion within four years (22%). We discuss how the criteria of place-based programs that support economically disadvantaged students may influence results for different types of students.
Increased exposure to gender-role information affects a girl's educational performance. Utilizing the classroom randomization in Chinese middle schools, we find that the increased presence of stay-at-home peer mothers significantly reduces a girl's performance in mathematics. This exposure also cultivates gendered attitudes towards mathematics and STEM professions. The influence of peer mothers increases with network density and when the girl has a distant relationship with her parents. As falsification tests against unobserved confounding factors, we find that the exposure to stay-at-home peer mothers does not affect boys' performance, nor do we find that stay-at-home peer fathers affect girls' outcomes.
The role of racial diversity at college campuses has been debated for over a half a century with limited quasi-experimental evidence from classrooms. To fill this void, I estimate the extent that classmate racial compositions affect Hispanic and African-American students at a large and over-subscribed California community college where they are minorities. I find that when minority students are exposed to a greater share of same race classmates, they are more likely to complete the class with a pass and are more likely to enroll in a same subject course the subsequent term. The findings are robust to first-time students with the lowest registration priority vs. all students and different combinations of fixed effects (e.g., student, class, and instructor race).
The disruption of in-person schooling during the Covid-19 pandemic has affected students’ learning, development, and well-being. Students in Latin America and the Caribbean have been hit particularly hard because schools in the region have stayed closed for longer than anywhere else, with long-term expected adverse consequences. Little is known about which factors are associated with the slow in-person return to school in the region and how these factors have had differential effects based on students’ socio-economic status. Combining a longitudinal national survey of the Chilean school system and administrative datasets, we study the supply and demand factors associated with students’ resuming in-person instruction and the socio-economic gaps in school reopening in Chile in 2021. We defined socio-economic status based on parents’ education and household income. Our results show that in-person learning in 2021 was limited mainly by supply factors (i.e., sanitary, administrative, and infrastructure restrictions). However, once the supply restrictions decreased, many low-income students and their families did not resume in-person instruction. We found vast inequalities in face-to-face instruction by school’s socio-economic characteristics. On average, schools in the highest 10% of the socio-economic distribution had three times higher attendance rates than the remaining 90%. We found no significant differences between schools in the lowest 90% of the distribution. After exceptionally long school closures, most school authorities, students, and their families did not return to in-person instruction, particularly those of low socio-economic status. These inequalities in in-person instruction will expand existing disparities in students’ learning and educational opportunities.
Youth voter turnout remains stubbornly low and unresponsive to civic education. Rigorous evaluations of the adoption of civic tests for high school graduation by some states on youth voter turnout remain limited. We estimate the impact of a recent, state-mandated civics test policy—the Civics Education Initiative (CEI)—on youth voter turnout by exploiting spatial and temporal variation in the adoption of CEI across states. Using nationally-representative data from the 1996-2020 Current Population Survey and a Difference-in-Differences analysis, we find that CEI does not significantly affect youth voter turnout. Our null results, largely insensitive to a variety of alternative specifications and robustness checks, provide evidence regarding the lack of efficacy of civic test policies when it comes to youth voter participation.
We study the importance of job-related and non-job-related factors in students’ college major choices. Using a staggered intervention that allows us to provide students information about many different aspects of majors and to compare the magnitudes of the effects of each piece of information, we show that major choices depend on a wide set of factors. While students do not change their choices when given information about earnings, they do update their choices when told about other aspects of majors. The non-job-related factors, such as a major’s course difficulty and gender composition, are important to students but not well-known to them. We also find that male and female students value different major characteristics in different ways. Lower-ability females flee from majors that they learn are more difficult than they had believed, while other students do not. On the other hand, male students are averse to being taught by female faculty, while female students are not. Overall, our results show that a variety of factors are important for students’ major choices and that different factors matter for male and female students.
Community schools are an increasingly popular strategy used to improve the performance of students whose learning may be disrupted by non-academic challenges related to poverty. Community schools partner with community based organizations (CBOs) to provide integrated supports such as health and social services, family education, and extended learning opportunities. With over 300 community schools, the New York City Community Schools Initiative (NYC-CS) is the largest of these programs in the country. Using a novel method that combines multiple rating regression discontinuity design (MRRDD) with machine learning (ML) techniques, we estimate the causal effect of NYC-CS on elementary and middle school student attendance and academic achievement. We find an immediate reduction in chronic absenteeism of 5.6 percentage points, which persists over the following three years. We also find large improvements in math and ELA test scores – an increase of 0.26 and 0.16 standard deviations by the third year after implementation – although these effects took longer to manifest than the effects on attendance. Our findings suggest that improved attendance is a leading indicator of success of this model and may be followed by longer-run improvements in academic achievement, which has important implications for how community school programs should be evaluated.