Every Monday, the National Bureau of Economic Research, a nonprofit organization made up of some of North America’s most respected economists, releases its latest batch of working papers. The papers aren’t peer-reviewed, so their conclusions are preliminary (and occasionally flat-out wrong). But they offer an early peek into some of the research that will shape economic thinking in the years ahead. Here are a few of this week’s most interesting papers:
Title: “Flaking Out: Student Absences and Snow Days as Disruptions of Instructional Time”
Author: Joshua Goodman
What he found: Bad weather has a much bigger impact on student achievement when schools stay open and students miss class than when they close altogether.
Why it matters: One of the major goals of education-reform efforts in recent years has been increasing “instructional time,” the amount of time students spend in class each year. Those efforts have focused mostly on lengthening the school day or the school year. Absences — time away from class when school is in session — have gotten much less attention, even though the average U.S. student misses more than two weeks of school each year because of illness, bad weather or other factors. But Goodman finds that absences may be a bigger issue. Using data from Massachusetts, he compares the impact of severe storms, which lead to cancellations, to more moderate storms, when schools stay open but many students stay home. He finds that absences have a much bigger impact on student test scores than school closures. Moreover, because low-income students are much more likely to miss school because of bad weather, absences worsen the achievement gap; Goodman estimates absences could explain as much as quarter of the difference in math scores between poor and nonpoor students.
Key quote: “An absent student presents a teacher with one of two choices upon his return to the classroom. The teacher may take time out of the classroom schedule to catch the absent student up on missed material, in which case his classmates lose instructional time from the teacher. Or the teacher may not set aside such time, in which case the student himself has lost instructional time and may disrupt his classmates’ future lessons because he has fallen behind. … School closures present no such challenge of coordinating students to be on the same page.”
Data he used: Massachusetts Department of Elementary and Secondary Education’s Student Information Management System.
Title: “Income Inequality, Social Mobility, and the Decision to Drop Out of High School”
Authors: Melissa S. Kearney, Phillip B. Levine
What they found: Low-income teenagers, especially boys, are more likely to drop out of high school when they live in places with high income inequality and low economic mobility.
Why it matters: Education researchers have long known that poverty makes students much less likely to finish high school. In this paper, the authors find evidence that inequality makes the problem even worse. Their focus isn’t on the rich-vs.-poor gap that has dominated the recent debate over inequality. Instead, they look at the gap between the poor (those in the lowest 10 percent of income in a given area) and the median. They also look at economic mobility, or how easy it is for members of one generation to do better than the one before. They find that in cities and states with high inequality and low mobility, low-income students are more likely to drop out of high school, even after controlling for factors such as school financing.
Key quote: “These findings have real implications for the potential of disadvantaged youth to achieve economic progress or even sufficiency in the years ahead. We argue that high inequality and low mobility play a critical role in molding the perceptions of low-income youth. The evidence suggests that there may be substantial effects on economic mobility of policies that provide disadvantaged youth with reasons to believe that they have the opportunity to climb the economic ladder and to make those opportunities real.”
Data they used: Five longitudinal student surveys.
Title: “Paying on the Margin for Medical Care: Evidence from Breast Cancer Treatments”
Authors: Liran Einav, Amy Finkelstein, Heidi Williams
What they found: Health insurance plans that allow patients to pay extra for more expensive treatment options lead to more efficient treatment decisions.
Why it matters: Health insurance systems in different countries handle expensive treatments very differently. In the U.S., insured patients typically face no incremental cost if they opt for a pricier treatment option. In Britain, by contrast, the government determines which treatments are “cost-effective” and provides no coverage for alternative treatments, meaning patients who want a more expensive option must cover the full cost themselves. In this paper, the authors look at a middle ground “top-up” system, in which insurers cover the cost of a baseline treatment and patients can choose to pay the incremental cost of a more expensive treatment. They focus on breast cancer, for which patients can choose between a mastectomy, in which the breast is removed, and a lumpectomy, which removes only the tumor itself, plus radiation therapy. The mastectomy option is cheaper but no less effective in terms of patient survival. The authors argue the top-up system yields the most efficient outcome, because patients only choose the more expensive option if it is worth the marginal cost; they estimate the system would increase total welfare by $700 to $2,500 per patient compared to the existing U.S. system, and by $700 to $1,800 per patient compared to the British system.
Key quote: “We present a simple framework to illustrate the welfare gains from a health insurance policy that allows patients to pay the incremental price for more expensive treatment options. Such a policy eﬃciently sorts low willingness-to-pay patients to the cheaper treatment option, in contrast with the current status quo in the U.S. where the incentives for such sorting are minimal. At the same time, this policy does not ‘over price’ the more expensive treatment, as is common in the U.K. and several other high-income countries, which allocates too many patients to the cheaper treatment.”
Data they used: The California Cancer Registry, “a patient-level cancer registry dataset, and data on radiation treatment facility locations.”