These very large, detailed data sets allow us to study economic behavior and human behavior. It’s an exciting time to be doing research.
Growing up in rural Ohio, Susan Cherry experienced firsthand how systemic deficiencies can lead to unequal opportunities. “I was very aware that the area where I was living was a pretty underprivileged place, especially in comparison to other regions of the United States,” Cherry says. “My high school didn’t even have advanced placement classes. If you were a student who was doing well academically, there weren’t really courses to challenge you. That’s something that sort of stuck with me and made me start thinking about these questions of inequality, both personal and regional inequality.”
Now, as a doctoral student at Stanford GSB, Cherry uses data to look for answers related to economic disruptions and their effects across different populations. Working with finance professor Amit Seru, she examined why some lenders pause or reduce mortgage payments and others don’t, which regions and demographics recover fastest from economic hardship, and who benefits from policies meant to mitigate income inequality perpetuated by the pandemic.
Cherry envisions a career in academia, where her economic research can be used to write policy that helps people.“When I’m working on a research project, I want it to be about something that I think is meaningful, and something that has the potential to impact society in a positive way,” she says.
Tell us a bit about your upbringing.
I grew up in a rural part of southeastern Ohio, fairly close to West Virginia and within the Appalachian region. My family owns a small orchard, which my parents still operate. We grow apples, pears, and peaches. It was a beautiful place to grow up.
I was in the marching band, so I have these memories of being out late at the football game on Friday nights and then waking up at 6 a.m. the next morning to help my family at the farmer’s market. As a high schooler I thought that was the worst thing ever, but looking back, it was so much fun.
Even now, when I visit my family, I help out around the orchard. Most of the small orchards have gone out of business. We don’t really know what’s going to happen when my parents retire, because I am hoping to go into academia and my sister is a veterinarian with her own career.
Was there anything from that experience that has carried over to your academic career?
Watching my parents work on their orchard; they poured all their energy into their work. They were passionate about providing their community with fresh local foods. Seeing that sort of shaped how I view my own work.
What helped clarify your research interest?
I have these memories of being out late at the football game on Friday night and then waking up at 6 a.m. the next morning to help my family at the farmer’s market.
After receiving my master’s from Duke, I ended up working as a research assistant at Columbia for two years. That was where I started working on research projects related to the Great Recession.
I got acquainted with large, detailed data sets and developed the skills to work with them. As an undergrad, I majored in economics and I minored in math, but I didn’t really have the computational skills that you need to deal with datasets that are several terabytes in size.
You were in middle school when the Great Recession happened. Did your research at Columbia recontextualize anything that you had seen or experienced?
I think so. In some ways, I didn’t know exactly what was happening when it was happening, and the research allowed me to learn more about it from a data perspective. The research was looking at whether certain regions recovered from the Great Recession differently in terms of health prices, consumption, and unemployment rates. Some areas of the country recovered quickly, and at the time that we were working on this paper some regions had still not recovered. We were trying to dig into why that might be the case. Ultimately, the research found that regions that had higher unemployment prior to the Great Recession recovered more slowly. That was the first time I really learned to dig into these details — it was something that I never even thought about prior to working on this research.
Your findings demonstrated that some forms of inequality are self-perpetuating, and that economic hardship contributes to an inability to recover from financial setbacks.
Exactly. We found that generous forbearance policies can at least partially explain the low levels of debt delinquencies during the pandemic. This is in contrast with past crises, like the Great Recession, where delinquency rates rose with unemployment rates.
One of our findings is that forbearance relief flowed more to higher-income individuals than low-income, partially due to their higher debt balances. We also found that forbearance rates were higher in vulnerable populations, such as individuals with lower credit scores. Borrowers in regions more affected by COVID through higher case rates and reduced economic activities, were more likely to obtain debt relief through forbearance policies.
How has working with faculty shaped the way that you ask research questions or formulate hypotheses?
Working with the faculty here has been a great experience. I’ve found that just by talking to them, I can figure out if an idea is worth pursuing, or whether I’m approaching a question from the right direction. One piece of advice I’ve gotten is that I should tie research back to economic theory. One of the cool things about having these very detailed datasets is that we can use them to study economic theory. That sort of framing has been helpful.
What does having access to these large data sets mean for your work?
We can investigate questions that we might not have been able to investigate in the past. For our project, the data includes detailed monthly information on credit card, mortgage, auto loan, and student loan accounts for about 20 million individuals over 15 years. This amounts to roughly 130 million records per month for about 180 months, These very large, detailed data sets allow us to study economic behavior and human behavior. It’s a really exciting time to be doing economic and finance research.
You’ve said questions of inequality are what drive your research interests. What issues of inequality need further study?
One area that needs more research is related to student loans and student debt. We need to look at what can be done to help people who have a large amount of student debt, and how we can change the way that we fund education so that people aren’t saddled with these huge levels of debt. There’s still a lot of work that needs to be done.
Susan Cherry, Stanford Graduate Student