Conditionally Accepted at the Journal of Public Economics
with Andrew Bacher-Hicks and Joshua Goodman
Abstract: We use high frequency internet search data to study in real time how US households sought out online learning resources as schools closed due to the Covid-19 pandemic. By April 2020, nationwide search intensity for both school- and parent-centered online learning resources had roughly doubled relative to baseline. Areas of the country with higher income, better internet access and fewer rural schools saw substantially larger increases in search intensity. The pandemic will likely widen achievement gaps along these dimensions given schools’ and parents’ differing engagement with online resources to compensate for lost school-based learning time. Accounting for such differences and promoting more equitable access to online learning could improve the effectiveness of education policy responses to the pandemic. The public availability of internet search data allows our analyses to be updated when schools reopen and to be replicated in other countries.
Revise and Resubmit at the American Economic Review
Abstract: Counselors are a common school resource for students navigating complicated and consequential education choices. I estimate counselors' causal effects using quasi-random assignment policies in Massachusetts. Counselors vary substantially in their effectiveness at increasing high school graduation and college attendance, selectivity, and persistence. Counselor effects on educational attainment are similar in magnitude to teacher effects, but they flow through improved information and assistance, rather than through cognitive or non-cognitive skill development. Counselor effectiveness is most important for low-income and low-achieving students. Improving access to effective counseling may be a promising way to increase educational attainment and close socioeconomic gaps in education.
Revise and Resubmit at the Quarterly Journal of Economics
with Adam Altmejd, Andres Barrios-Fernandez, Marin Drlje, Joshua Goodman, Michael Hurwitz, Dejan Kovac, Christopher Neilson and Jonathan Smith
US Only Version: NBER Working paper 26502 (with Joshua Goodman, Michael Hurwitz, and Jonathan Smith)
Abstract: Family and social networks are widely believed to influence important life decisions but identifying their causal effects is notoriously difficult. Using admissions thresholds that directly affect older but not younger siblings’ college options, we present evidence from the United States, Chile, Sweden and Croatia that older siblings’ college and major choices can significantly influence their younger siblings’ college and major choices. On the extensive margin, an older sibling’s enrollment in a better college increases a younger sibling’s probability of enrolling in college at all, especially for families with low predicted probabilities of enrollment. On the intensive margin, an older sibling’s choice of college or major increases the probability that a younger sibling applies to and enrolls in that same college or major. Spillovers in major choice are stronger when older siblings enroll and succeed in more selective and higher-earning majors. The observed spillovers are not well-explained by price, income, proximity or legacy effects, but are most consistent with older siblings transmitting otherwise unavailable information about the college experience and its potential returns. The importance of such personally salient information may partly explain persistent differences in college-going rates by geography, income, and other determinants of social networks.
Forthcoming at the Journal of Labor Economics
Abstract: Choosing where to apply to college is a complex problem with long-term consequences, but many students lack the guidance necessary to make optimal choices. I show that a technology which provides low-cost personalized college admissions information to over forty percent of high schoolers significantly alters college choices. Students shift applications and attendance to colleges for which they can observe information on schoolmates' admissions experiences. Responses are largest when such information suggests a high admissions probability. Disadvantaged students respond the most, and information on in-state colleges increases their four-year college attendance. Data features and framing, however, deter students from selective colleges.