I am an
Assistant Professor of Economics and Education at Teachers College, Columbia University. My research focuses on information problems in human capital development. I use behavioral economics, big data and randomized controlled trials (RCTs) to identify low-cost, scalable interventions that improve education outcomes.
I am an Assistant Professor of Economics and Education at Teachers College, Columbia University. My research focuses on information problems in human capital development. I use behavioral economics, big data and randomized controlled trials (RCTs) to identify low-cost, scalable interventions that improve education outcomes.
Email: bergman [at] tc [dot] columbia [dot] edu Phone: (212) 678-3932 Office: 417 Thorndike Curriculum Vitae (pdf)
This paper studies information frictions between parents and their children, and how these affect
human capital investments. I provide detailed, biweekly information to a random sample of
parents about their child's missed assignments and grades and find parents have upwardly-biased
beliefs about their child's effort. Providing additional information attenuates this bias and
improves student achievement. Using data from the experiment, I then estimate a persuasion
game between parents and their children that shows the treatment effect is due to a combination
of more accurate beliefs and reduced monitoring costs. The experimental results and policy
simulations from the model demonstrate that improving the quality of
school reporting or providing frequent information to parents about their child's effort
in school can produce gains in achievement at a low cost.
This paper studies the impact of a desegregation court ruling on several medium-run outcomes.
This ruling mandates that seven school districts, which serve higher-income, predominantly-white families,
accept a group of minority elementary school students each year who apply to transfer from a nearby,
predominantly-minority school district. The fixed number of slots are allocated to families via lottery.
The offer to transfer increases the number of students who enroll in college by 10 percentage points.
This result is driven by greater attendance to two-year and public colleges and particularly for male students.
There is suggestive evidence male students are also more likely to vote.
In contrast, the offer to transfer increases the likelihood of arrest, most often for non-violent offenses.
There is increasing evidence that tax credits for college do not affect college enrollment. This may be because prospective students do not know about tax benefits for credits or because the design of tax credits is not conducive to affecting educational outcomes. We focus on changing the salience of tax benefits by providing information about tax benefits for college using a sample of over 1 million students or prospective students in Texas. We sent emails and letters to students that described tax benefits for college and tracked college outcomes. For all three of our samples---rising high school seniors, already enrolled students, and students who had previously applied to college but were not currently enrolled---information about tax benefits for college did not affect enrollment or reenrollment. We test whether effects vary according to information frames and found that no treatment arms changed student outcomes. We conclude that salience is not the primary reason that tax credits for college do not affect enrollment.
We partner text-messaging technology with school information systems to automate
the gathering and provision of high-frequency information on students' academic
progress to parents. In an experiment across 22 schools, we use this technology
to send weekly automated messages to parents about their child's missed assignments,
grades, and class absences. We pre-specified five primary outcomes. The intervention
reduces course failures by 38%, increases class attendance by 17% and increases
retention. The positive effects are particularly large for students with below-average
GPA and students in high school, which persisted into a second year. There are no
effects on state test scores, though the exams, which were new and zero stakes
for students, were subsequently discontinued; students used substantially less
than the expected amount of time to complete them. In contrast, we find significant
improvements on in-class exam scores. Our results show this technology
can improve student performance relatively cheaply and at scale.
We conduct a field experiment to understand how enrollment defaults affect the take up and
impact of an education technology designed to help parents improve student achievement. The
standard strategy schools use to introduce this system to parents—online signup—induces negligible
adoption. Simplifying the enrollment process modestly increases adoption, primarily among parents of
higher-performing students. Automatically enrolling parents dramatically increases adoption.
Automatic enrollment significantly and meaningfully improves student achievement. Survey results
suggest that automatic enrollment is uncommon, and that it may be uncommon because its impact is
unanticipated by policymakers. Surveyed superintendents, principals, and family engagement
coordinators overestimate the take-up rate of the standard condition by 38 percentage points and
underestimate the take-up rate of automatic enrollment by 31 percentage points. After learning the
actual take-up rates under each enrollment condition, there is a corresponding 140% increase in the
willingness to pay for the technology when shifting implementation from opt-in enrollment to opt-out
Truancy correlates with many risky behaviors and adverse outcomes. We use detailed administrative data to construct social networks based on students who miss class together. We simulate these networks and use permutation tests to show that certain students systematically coordinate their absences. Leveraging a parent-information intervention on student absences, we find spillover effects from treated students onto peers in their network. We show that a simple optimal-targeting algorithm that incorporates machine-learning techniques to identify heterogeneous effects, as well as the direct effects and spillover effects, improves the efficacy and cost-effectiveness of the intervention subject to a budget constraint.
The Effects of Making Performance Information Public: Regression Discontinuity Evidence from Los Angeles Teachers with Matt Hill, (Revise and Resubmit, Economics of Education Review)
Abstract: The publication of performance ratings has ambiguous
implications for performance. This paper uses school-district data and discontinuities in publication to study
the effects of publically rating teachers. Relative to unpublished teachers, we find that high-performing
students sort into classrooms with highly-rated teachers. Conditional on publication, ratings labels
induce sorting as well as teacher attrition: low-rated teachers teach lower-performing students and
are more likely to leave the district in subsequent years relative to higher-rated teachers. There
is no effect of publication on test scores and heterogeneous effects by ratings labels that may
increase achievement gaps between low and high performing students.
Given significant expenditures on education technologies,
important questions are who adopts these technologies and
why, and whether promoting usage impacts student outcomes.
This paper studies the adoption and ability to promote usage
of one type of technology that is increasingly ubiquitous:
school-to-parent communication technologies. Analyzing usage
data from a Learning Management System across several hundred
schools and then conducting a two-stage experiment across 59
schools to nudge the use of this technology by families, I
find that 57% of families ever use it and adoption correlates
strongly with measures of income and student achievement.
Using a survey experiment I find that informing families about
research on the value of school-to-parent communication
technologies can promote adoption and there is evidence
that social norms influence adoption as well. While a
simple nudge increases usage and modestly improves
student achievement, without more significant intervention
these technologies may exacerbate gaps in information access
and student performance across income and performance levels.
This paper studies the ability to foster parent skills and resolve information problems as a means to improving student achievement.
We conducted a three-arm randomized control trial in which community-based organizations provided
regular information to families about their child's academic progress in one arm and supplemented
this with home visits on skills-based information in a separate arm. Math and English test scores
improved for the treatment arm with home visits. There are large effects on retention for both
groups during the year, though learning gains tend to accrue for students with average-and-above
baseline performance and students at the lower-end of the distribution appear marginally retained.
Engaging Parents as a Means to Address Educational and Health
Behavioral Outcomes: Evidence from a Field Experiment
with Rebecca Dudovitz and Mitchell Wong (paper available on request)
Testing whether engaging parents in their child's education reduces teens' risky behaviors.
Research in Progress
Information Frictions and the Search for Housing: Evidence from a Randomized Controlled Trial with Eric Chan and Adam Kapor
Using Predictive Analytics to Track Students:
Evidence from a 7 College Experimentwith Elisabeth Barnett and Vikash Reddy
Bridging the Digital Divide:
A Randomized Controlled Trial Providing Internet Access to 10,000 Low-Income Familieswith Susha Roy and Elizabeth Setren
Does Information on School Quality Impact Residential Choice? Evidence from a Nation-wide Field Experiment with Eric Chan, Matt Hill and Heather Schwartz
CNN: Parental Involvement Overrated?
Columbia Committee on the Economics of Education
Email: bergman [at] tc [dot] columbia [dot] edu
Phone: (212) 678-3932
Office: 417 Thorndike
Curriculum Vitae (pdf)