As a Ph.D. student at Princeton, Emil Verner’s growing interest in financial crises took him across the world—to the Central Bank of Hungary and back. After talking to his advisor Atif Mian about a new research idea, Verner went on the hunt for data that would help him answer his question. He found it in Budapest.
“I said, okay, they have this data in Hungary. I have to go to Budapest. What should I do? And I remember you basically said, you know, get on the plane, and go to Budapest. Go there.”
Verner is now the Class of 1957 Career Development Professor and an Assistant Professor of Finance at MIT’s Sloan School of Business. Here, he joins our Alumni Conversations series to talk to Mian, the John H. Laporte Jr. Class of 1967 Professor of Economics, Public Policy, and Finance, about:
We’re so grateful to Emil for taking the time for this chat. You can read a lightly-edited transcript of the conversation below.
Atif Mian: Hi, everyone. I’m Atif Mian, and we are doing this series with alumni to hear about what their experience was like at Princeton and how their life is going these days and what we can learn from them.
I’m very happy to introduce Emil Verner, who is currently an Assistant Professor of Finance at MIT’s Sloan School of Business. Emil graduated with a Ph.D. in economics from Princeton, and I had the good fortune of having Emil as my advisee at Princeton. And we had, at least I had, a fun time while he was here. I don’t know, we will learn about his experience, I guess. So you can be honest, Emil. It’s good to have you.
We will spend 20, 25 minutes chatting about your time at Princeton, what you’re working on these days, and what advice you may have for people listening to us and thinking about careers in academia and thinking about coming to Princeton for economics, in particular.
Emil Verner: That’s great. Yeah. Looking forward to the chat. It’s great to see you again.
Atif Mian: So let’s start with your experience at Princeton. What were you thinking of doing coming into Princeton and how did Princeton change you? Good and bad?
Emil Verner: Yeah, well, it’s a good question. I think when I came in to Princeton, I had two interests. I was interested in development and macro, kind of long run growth type questions motivated by this quote from Solow that, you know, once you start thinking about income differences across countries, it’s hard to think about anything else.
Then at the same time, this was 2012, so it was right in the immediate aftermath of the global financial crisis, and I soon realized that Princeton was really at the heart of the most exciting research on the financial crisis, on macroeconomics and finance.
As luck would have it, you had actually just arrived in Princeton that year, as well, from Berkeley, and you were obviously doing a lot of very exciting work in that area.
I gradually started gravitating more and more toward finance and thinking about the financial crisis and trying to understand it. I realized that there were many things that I just didn’t understand as well as I could, and so that was kind of a very exciting time and place to be interested in those types of questions.
Then I really used the opportunity at Princeton, the broad, you know, depth of the faculty, the different fields, to really kind of focus on macro, international economics, and finance and that became what I was focused on, in a variety of different ways, for basically the next five or six years in my time there.
We started working together, I think, the summer after my second year as a research assistantship for you, and then the ball started rolling from there and I got very interested in kind of empirical macroeconomics and finance, understanding, you know, recessions, financial crises, where they come from, what causes them, can we predict them? All those types of exciting questions that were very important you know, at the time, and I think are still of great interest.
Atif Mian: Emil, tell us something about your dissertation and in particular your job market paper, which, by the way, obviously did very well, was the lead article at the American Economic Review.
But what I want to talk about is the process leading up to the paper. Everyone can read the paper and see how successful that project became. But of course, you don’t know that starting out. And I want to get a little bit into the process of developing that project and what broader lessons there might be for students starting out research.
Emil Verner: Yeah, absolutely. It definitely was a consequence of a bit of luck, a bit of persistence, and things, I think, coming together.
For those who don’t know the paper studies how a large exchange rate shock is transmitted to the real economy through household balance sheets in the context of an emerging market where households have a lot of debt denominated in foreign currency.
When there’s a depreciation of the exchange rate, that leads to a big increase in real debt burdens for households that have foreign currency debt. And I was interested in understanding why did households borrow in foreign currency in the first place, or why do they often do this in emerging markets? And how do they adjust when these types of shocks happen? And what are the real consequences of that of these types of shocks?
I was coming at those questions actually from, inspired by, some work that you had done and also that we had done together looking at household credit cycle. It turns out that, you know, the big booms in lending to households and household credit, they often end in big busts. And that was that was something that, you know, our work had helped establish.
When I was putting together some of the data that we were using, I realized that in some countries around 2008, 2009, there were big spikes in household debt. I was wondering what’s going on. Everyone’s talking about, you know, bank credit contracting, it’s hard to get a loan. Why are these contexts of household debt actually jumping in places like Iceland and Austria and Poland and Hungary?
It turned out it was because these countries had a lot of foreign currency denominated debt. And those spikes in some of the data we were looking at were actually due to reevaluations of that debt, not due to new lending. And so I think remember, we were in your office kind of talking about different potential ideas, and you said to me, you know, why don’t you look into some of this foreign currency debt? It’s something that people aren’t really talking that much about, but it seems like it’s potentially an interesting topic to investigate.
It turned out, you know, The New York Times, The Wall Street Journal, they had written a bit about mortgage borrowers in Poland or Hungary that had gotten themselves into big trouble because of these risky loans that they had taken on. But there wasn’t really so much academic research.
You basically said, you know, try to see if you can find some data. And so I kind of sent a few emails around and was trying to, you know, be a bit persistent in terms of finding the data. And it turned out that at the Central Bank of Hungary, they had this credit registry that had loan currency denomination. That was the key variable that was hard to find.
All of the loans that had been originated in Hungary from starting around 2000 up until the present, so we could see, you know, every single borrower how much they had taken, what they were taking the loan for, where they lived, and so on.
I said, okay, they have this data in Hungary. I have to go to Budapest. What should I do? And I remember you basically said, you know, get on the plane, go to Budapest, go there.
I spent a summer there, and no one had really used the data for research yet. It had been used a bit in policy. The first month I spent there with a person who became my coauthor, Győző Gyöngyösi, and we were cleaning the data, making sure it made sense, making sure that, you know, it looked like a reasonable series when we aggregated all those types of things that you want to do.
Then it gradually evolved into actually a series of different papers that we wrote, including my job market paper, which was really this iterative process of going looking at looking at the data, coming back to Princeton, presenting it within the seminar in Princeton, getting feedback, trying to refine it, get more data. And that iterative process then turned into a job market paper.
I went for the first time in the summer of 2016, and then the paper was basically ready in the fall of 2017. It took about a year and a half or so.
Then we were working on follow-up projects, actually even to this day. Ex-post it might look like it was an obvious thing to do, but ex-ante, it was really just kind of being a bit lucky and persistent and looking for data and finding interesting patterns in the data once I got my hands on them.
Atif Mian: Yeah, exactly. I wanted to just highlight the ex-ante uncertainty and risk that goes on in these kind of endeavors. But one has to be, this is one thing I remember about you in particular, is if one has a conversation like the one you mentioned, I was always amazed by how quickly you would come back with like having made a lot of progress.
I think that was always impressive, but it also is like a wide set of skills that you need, not just on the technical side, but also reaching out to people, being persistent, being nice when you talk to them so they are willing to partner with you, they’re willing to talk to you, they are willing to work with you. I mean, all of those things matter.
Emil Verner: And let me also say, I mean, for grad students or potential grad students watching this, I think I probably applied to about ten different sources of data, and I think two or three of them worked out. One of them, I think they only got back to me once I was already on the job market, two years too late. So you know, there were many unsuccessful attempts, as well. That whole process is also you learn a lot by doing it because then you realize, you know, there might be other sources of data that you didn’t even know about or had thought about asking for, and then you start to talk to people. So that’s kind of a part of doing, I think, applied research as well.
Atif Mian: And that batting average, right, two to three out of ten. I mean, that sounds just about right. I mean, I think that’s it’s…baseball is a good metaphor. I think a good batting average is, you know, if you can get one out of three, that’s like really, really good. Right? And so that’s that’s the way to think of it.
Which just briefly, maybe can you mention one unsuccessful one so people know it’s not always a good story?
Emil Verner: Yeah. I mean, so I was interested in a related question about how firms choose their currency denomination of their debt at the same time as how they choose what currency to price their goods in.
One of the ways to look at that, where you can actually see currency invoicing, is in the BLS’ micro data from the international price program. And those are very nice data that, you know, other people have used. I applied to get access to those, and actually they did get back to me, but it was just a little bit too late relative to the job market. I think it took a little bit too long and I was a bit too late in applying.
That’s another thing. If you want to apply for data, whether it’s Census data or something, you need to give yourself a lead time of, you know, a couple of years at least. And then there are others. I’ve already you know some of them I’ve forgotten, which just, you never even hear from.
Atif Mian: Yeah, exactly. And the other thing to keep in mind is when you start and if you’re successful, then you can build an agenda around it. So then often it’s not just one paper, but you know, one thing leads to another kind of thing.
When you’re starting out your career, it’s almost by definition much harder. It gets easier over time because, you know, you have something built up so you can use that capital you have built up and then continue to build incrementally in your capital. But it always takes a little bit of time to have the fixed cost of starting your career for the first time. I think that’s important to keep in mind, a perspective for students.
Emil Verner: Exactly, yeah. And it can be also a bit of an uncertain and a bit stressful time because you’re looking for the hook. You’re trying to get your hands on something. But then once you get it, then, you know, often there’s other ideas that you can generate from the same data, and you can write multiple papers within the same area.
We were able to do something similar. When we wrote one paper, which was more on the macrofinance side of how this type of shock was transmitted, and then we realized, well, there’s lots of things happening on the political economy side of cleaning up from the crisis, and it turned out that there were some interesting patterns in the relationship between people’s foreign debt exposure and their voting behavior and how that changed during the crisis. That was, you know, a very different set of questions than what I was initially interested in.
It turned out to actually be related because I think the political side is an important side of financial crises that I started thinking about only later. So in some sense, you have to also keep the faith a little bit and kind of trust the process that, you know, your ideas will come out of the process, out of looking for data, working with data.
Atif Mian: Exactly. I sometimes tell students, look, the real world is a lot more interesting than your models. And so when you go look at the data and you think about the real world, you’ll actually get even more exciting ideas than you might at first think of with a paper and pencil.
There’s something else you did when you were at Princeton, which is you started forming partnerships and collaborations on these long historical projects, collecting long-term historical data, which is a different enterprise than working with administrative data of the sort you worked on for your job market paper in Hungary. Tell us tell us about that. Like how you’ve continued to do that. Maybe if you have time, we’ll come back to your recent very nice work with Karsten Müller, as well. How did you get into the working on more of history and microfinance?
Emil Verner: Yeah it’s a good question. So initially, but kind of going way back when I thought about what I wanted to study, I think top of my list was I wanted to study history. I’ve always really been fascinated by history. And then for a variety of reasons, I decided maybe that wasn’t the best field to study in undergrad. So for example, what the impact of monetary policy was.
Well, a lot of the received wisdom has come from the major monetary policy shocks or events like, you know, the return to the gold standard in the 1920s or leaving the gold standard in the 1930s during the Great Depression and that work was always kind of very influential in thinking about macrofinance.
I definitely felt that at Princeton, too. Many professors, you know, would talk about the Great Depression or talk about history and motivating kind of you know, empirical or theoretical work. And at the same time there was this trend, I think because it’s become cheaper and the cost of collecting, you know, lots of data and long run data has come down, there was kind of this trend within microfinance to do those types of endeavors.
For example Jordà, Schularick, and Taylor have done a lot of important work in that area, and my coauthor, Matt Baron, who was a few years ahead of me, has also, you know, written some very, very good and interesting papers using that approach getting long run time series, for example, on credit, on GDP, on banking crises and trying to just understand what are the basic microfinance facts, what is it that we should try to understand in our models. What is the connection?
You know, are banking crises completely unpredictable, or do they seem to, for example, follow certain types of macroeconomic trends or booms? I think that historical work has put together a lot of facts that, some of them maybe we could have intuited before by reading narrative history, but we really sharpened that work. I was kind of lucky to be at Princeton around that time and to kind of get excited by that area.
It started actually with a paper that we wrote together with Amir Sufi where we were looking at longer-run trends in household credit and documenting the importance of household credit cycles for business cycles. That was, you know, long run data going back to 1960. And then it turned out, well, you can actually in some cases add another 50 or 60 years, go back to the pre-war World War II period, the Great Depression and even earlier and learn things.
In a subsequent paper with Wei Xiong and Matt Baron, we started looking a bit more at, you know identifying what were the major banking crises and what were the characteristics of those types of banking crises? Were there bank failures? Were there banking panics? What’s the difference between those two things? Can we try to measure them in the data? What are the salient features of a banking crisis? How should we try to think about that?
I think long run data is very important for those types of questions. If you want to do empirical work, mainly because we just don’t have that many experiences of banking crises in a given country and time period. One wants to look at the long run historical perspective for that. I think that’s been quite a fruitful approach that complements the more kind of well-identified, micro-data based approach in modern data. I see them kind of as two ways of adding our knowledge in macrofinance.
Atif Mian: That’s right. And in fact, if you think of some of the more influential work in economics, it’s about bringing you facts out there. And that’s fundamentally about data construction. That’s one thing I think when, maybe because of the bootcamps we have in the beginning, the Ph.D. students coming in, they might overemphasize the value of technique which is, of course, important, not to take anything away from that.
There’s also, you know, a lot of value in just thinking about putting new facts together, putting new data together in ways that hasn’t been done before to shed light on, you know, what we may have been missing in the past. That’s a great way to kind of develop your career, and you’re continuing to do that. You’re continuing to work in developing new datasets.
Tell us about your transition from being a student to going, you know, obviously faculty at MIT. How is it different? You have to think differently about managing your work, your 24 hours in a day. How has the transition been for you, or what advice would you have for young academics starting out?
Emil Verner: Yeah, that’s a very good question. I think one thing I would say to people who are still Ph.D. students is I remember thinking it was very stressful and having a lot of anxiety, but you really also want to enjoy that time. One because you really have a lot of time actually to do work and to build skills, and maybe read a little bit more broadly than you can do later in your career.
Because the main thing that I’ve noticed is the way that I work has changed a little bit in the sense that I have a bit less time myself, but I have more resources, as well. It becomes about thinking a little bit more at a higher level, trying to be organized and think about how to get research progressing when you can’t necessarily work on a given paper 10 hours per day every day because you have all of a sudden other responsibilities, whether it’s more responsibilities for teaching, advising, lots of other things that they ask us to do.
In that sense, the way that I work has maybe changed a little bit, but I still try you know, every day, I make sure I block out at least a few hours, if not more, to be working with data myself or to be working on writing myself. So, still trying to work like a Ph.D. student in some sense and taking advantage of the more, you know, resources that you have once you become an assistant professor.
Other than that, I mean, in some ways MIT and Princeton are not so different. I’m in the finance group at Sloan and so in that sense, I’ve noticed that I’m getting a bit more exposure to finance relative to macro, whereas at Princeton, because the finance group is within the economics department, it was maybe a little bit more integrated with the whole economics community.
Here we’re in the same building. You just have to go down one elevator and another elevator and you’re in the economics department.
I’ve been trying to kind of keep that connection to other areas of economics, especially going to the macro seminar and interacting with macro folks, and I think that’s nice. But so that’s kind of similar relative to Princeton.
Atif Mian: How about teaching business school students? Obviously, you were not in the business school before.
Emil Verner: Yeah, no. I wasn’t in a business school. I didn’t know that much about business schools before I went on the job market. I will say I think that the preparation that we get at Princeton just for going on the job market—so preparing to present new research, distilling ideas in a clear and simple way and explaining it so that people who are maybe not in your field will understand it—that skill actually, I think, translates relatively well into teaching, because that’s the same thing that we’re trying to do, is take ideas that are maybe complicated, make them simple, make sure that students can understand them.
I’ve been teaching the MBA now, Sloan Fellows MBA, which is a mid-career MBA program. I teach essentially a mix of investments and corporate finance, so basic kind of finance theory with a mix of some theory, and also a fair number of cases. Actually that’s gone quite well. I’ve learned a lot. I’ve learned a lot of more practical finance that’s actually served me quite well in some of my research, as well.
So there’s been some nice synergies there, and then the cherry on the cake is getting to do some Ph.D. teaching, as well, in the second year Ph.D. That’s a way to kind of force yourself to stay sharp and stay on top of recent papers. The transition has been quite smooth.
Atif Mian: Right, right, right. Looking forward, we are closing the end of our session here. But I want to talk to you about what you are thinking going forward just in terms of questions and ideas that you feel are important in this macrofinance space that you have been working on.
Now you have a lot more perspective, right? It’s been like a few years out since you finished a Ph.D. You’ve been remarkably successful. Hopefully that’s giving you pause, thinking about, okay, you know, I don’t at least you should not be anxious anymore, like you’ve done well, and you’re doing well.
So it gives you a different perspective. Right? And I want to hear you tell us what that transition is like. What kind of questions are you thinking about now that you maybe, you know, have a different perspective, have a different horizon looking forward and what motivates you in terms of research going forward.
Emil Verner: That’s a very good question. So I think in some sense, what I realized is for about ten years of my life or so, this is a realization I had kind of over the past one or two years, for about ten years of my life, I’d really been thinking about financial crises from one perspective or another, whether it was from the perspective of bank failures and panics or from the perspective of household debt and financial distress for households and firms.
And I think I kind of reached a stage where I felt like I had said what I wanted to say for now on that, and I wanted to look for some other topics. That was really the first time I kind of felt myself in that position. Not to say that I’m not going to write other papers or come back to that, but just for a for a little while, I wanted to think about other things and I got very interested in financial aspects of inflation, especially high inflation.
This is where kind of my interest in history, again, came back and was influential in my thinking. A lot of the ways that we’ve thought about inflation, especially high inflation, again, something that we’ve learned from history, whether it’s, you know, the 1970s inflation in the U.S. and other parts of the world, or the really big, you know, inflation, the hyperinflation in Europe in the 1920s.
I went back and I wanted to read and understand more how those inflations, high inflations, shaped economic activity and, you know, broader society, especially through financial channels. That’s some of the work that I’ve been doing more recently is going back and actually collecting a lot more data from the 1920s in Europe where we actually have a lot of data, not even just aggregate data, but actually firm-level data. So micro-level data on firms to try to understand, you know, for example, during the German hyperinflation, was that an economic catastrophe or did the economy actually do quite well?
What turns out actually for much of the hyperinflation, the economy was booming. People weren’t happy about it. It was a miserable time. Many people lost their savings, but lots of firms actually benefited a lot.
It turns out that, you know, many of the ideas that we think about that were useful for thinking about you know, big recessions or depressions are also useful for thinking about big inflation. For example, there’s a lot of redistribution that happens when there’s unexpected inflation because of nominal contracts, for example you know, nominal debtors winning and nominal savers losing.
My work at the moment that I’m most excited about, it’s kind of a series of projects trying to understand the real economic consequences of high inflations, especially through financial channels.
I have a recent paper on that and a few other projects that are exploring that side of it to look at some of these big historical episodes to see if we can maybe learn something, learn about some economic mechanisms that might even be relevant for current times like today, as well, even though it’s a very different type of inflationary experience that we’re having today.
Atif Mian: That’s right. Yeah. Inflation has certainly become a lot more salient now than before.
Thank you so much, Emil. It was a real pleasure. Obviously, we had limited time, so we can’t go into as much detail as we would like to. But it’s been terrific talking to you about your research and where you’re heading next. We wish you all the best, continued success. And thank you to all the audience who would listen to us.
Emil Verner: Yeah, thank you very much Atif. It’s great to see you. Hope to see you soon in person.
Atif Mian: Of course. Of course. All the best. Thanks.