Claudia Sahm on the Sahm Rule and Using Big Data to Inform Policymaking

Claudia Sahm is the director of macroeconomic policy at the Washington Center for Equitable Growth, and was formerly at the Board of Governors as a section chief in the Consumer Community Affairs Division as well as serving on the staff macro forecast. Claudia specializes in macroeconomics and household finance, and she joins the show today to talk about some of her work. David and Claudia also discuss her experience working at the Federal Reserve Board of Governors, the conception of the Sahm Rule, and the importance of big data for economic research and policymaking.

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Note: While transcripts are lightly edited, they are not rigorously proofed for accuracy. If you notice an error, please reach out to [email protected].

David Beckworth: Welcome to Macro Musings, the podcast series where each week, we pull back the curtain and take a closer look at the important macroeconomic issues of the past, present, and future. I'm your host, David Beckworth of the Mercatus Center. We are glad you've decided to join us.

Our guest today is Claudia Sahm. Claudia is the director of macroeconomic policy at Equitable Growth, and formally was at the board of the governors as a section chief in the consumer community affairs division as well as serving on the staff macro forecast. Claudia specializes in macroeconomics and household finance and joins us today to discuss some of her work. Claudia, welcome to the show.

Sahm: Thank you. I'm so excited to be here.

Beckworth: Well, I'm glad to have you on. We have been Twitter friends for a long time. Been trying to get you on the show, so finally, you have arrived, so glad to get you on board. Now, you've had an exciting career. You’ve worked at the Board of Governors for 12 years?

Sahm: 12 years.

Beckworth: 12 years, so you've been inside the belly of the beast. You've seen it all. You probably have chuckled a few times when those of us on the outside make our comments about the things going on.

Sahm: Mm-hmm (affirmative).

Beckworth: You're probably smirking. Maybe sometimes you're gritting your teeth at us. But here we are. You've now joined us on the outside. You're a director at the macroeconomic policy part of Equitable Growth. This is exciting. But I want to begin the show by asking, how did you get into economics? What made you choose this path for a career?

Sahm: Well, so obviously, I went to undergrad. I went to Denison University, and before I started, I really thought I'd be an English major, so that was in my head. Sometimes before I went to actually sign up for classes and summer orientation, I was like, "I don't really want to do that. I don't want to study what people wrote a long time ago," so when I signed up for my classes, I took an economics, a political science, German, and then a third-year math class. It so turned out that I had a triple major in economics, political science, and German, and I figure after doing an economics PhD, I basically picked up the math. It would've been good to have done an undergrad not at night after being a research assistant.

First of all, I mean, I am a very liberal arts person. I love economics, but I appreciate the political economy aspect, and the education I got at Denison was unlike what I got when I went to Michigan, which, great education at Michigan. I had my advisor, Sohrab Behdad, who was excellent. He was actually my first economics professor and gave me a lot of positive feedback on how I was doing in economics, so I think that matters. There's research that shows that matters, especially for women students. I mean, I got really good grades, too, so I had affirmation in different places. He was a Marxist.

Beckworth: Oh, really.

Sahm: That is his background. He had training that was more traditional at Michigan State. He was from Iran, went back, then had to leave when the politics turned against, and he was my thesis advisor. I wrote a thesis, I was very interested in what was happening in the eastern part of Europe. I graduated in 1998, so it was well past the wall coming down in '89, but I was very interested in the economic transition, and him being who he is, he said, "Well, you're going to go back and study the formation of capitalism, the industrial revolution. Then you'll read Marx, and then ...", so I spent a year reading a lot of history of economic thought. My thesis… I like to impress Brad Delong with the fact that I actually have read up on history, and I did a lot of it. It was a really interesting project.

After I graduated from Denison, I went to Germany and spent a year in Dresden at the Technical University. I was studying economics, and there I was really interested in the transformation, a little more modern-day. Living in Germany for a year, I definitely saw that. My husband, well, actually, it was right before we married. We're now co-parents, but he's from Dresden. I love German and Germany. So I did a full Fulbright, and I will say, that year was the closest I came to not becoming an economist. I thought I'd learn about East Germany. What I did come to understand is the East German economics professors were some of the first to lose their job after the wall came down. In many ways, this makes sense. They were very tied to the socialist government. It was time for a change.

The professors who were there were West German. Mainly, they just came in for some classes during the week and went back home. There was nothing in the instruction that focused on East Germany and its transformation, and I can remember I took their masters-level courses. I was in a class that was game theory. It was all in German. I mean, it wasn't hard for me to find game theory textbooks, and I can do the little trees and whatever, so I got through the class, but I was just like, "This is not the economics that I was taught and fell in love with.

This isn't policy. What is this?" When I was coming back to the United States, I had another professor at Denison, Dick Lucier, who had spent a year at the Brookings Institution. I was really fishing around and applying to HR jobs. I didn't know what I was going to do, and he said, "You should apply to be a research assistant at Brookings." He said, "That's a great place. It'd be a great experience for you." That was the only research assistant application I put in, because this was not something I'd been exposed to.

I was very fortunate. I was hired. Barry Bosworth and Gary Burtless were my senior fellows. They're amazing. They've been extremely good mentors. So, they hired me. That was an amazing year. That got me totally back. I want to be an economist.

Beckworth: Loving economics again.

Sahm: They had me co-author on a paper towards the end, and what I realized is I could do a lot, very empirical, work hard, but I got to a place where I couldn't contribute. There were aspects of the theory and building the macro model, and so I knew I needed to go to graduate school, so I went with a purpose. I found that very important to get through the first year, which reminded me a lot of German. It's very technical and theoretical. Michigan has a strong applied macro program. I did macro and labors of field. Obviously, labor, they have excellent applied labor folks. Matthew Shapiro was my advisor at Michigan. Again, an excellent mentor, so I had a whole string of professors and senior fellows at Brookings who were incredible mentors. I never had a woman economist as a mentor until I was years into the Fed. Now, I feel like I do, and I, you know ... So I really feel like you can be a good mentor and an ally regardless of whether on some demographic dimension or life experience dimension you match up.

Beckworth: So for those out there who have the opportunity to mentor, do it. Take advantage of it. And you yourself are doing this. I've seen this evidenced on Twitter of all places, but you have taken it upon yourself to go above and beyond what you have to do at work, at home, you've got children, that you go and you read job market candidates, their papers, so these are freshly minted PhDs right now on the job market, they're all getting nervous because this is the time of the year when you hope and you pray you get some interviews, and you're helping them. You're taking time out to advise them on their papers, giving them advice, so that's great. That's great that you're doing it, and I know a number of listeners on the show are grad students. They've come and talked to me, so I'll say on their behalf, thank you, Claudia, for doing that.

But any advice you would give them? Because you've been many years inside the Federal Reserve, so some of them might be headed there, or you've been inside the other government agencies. You've toured those as well. Now, you're coming outside. Any career advice you would give a freshly minted PhD?

Sahm: I think especially those who are getting ready to do their interviews, the annual meetings, have an open mind about what comes next in your career. When I was applying for jobs, and so I told my advisor, Matthew Shapiro, "I'm not going to apply to the board." There was something about going to the board that reminded me of the never-ending macro seminar. I loved macro. That seminar was a little different than the labor seminar, and I was just like, "This is a pretty heavy dose of macroeconomics." Michigan sent a lot of people to the board, and my advisor in particular, and I am kind of one of these, I like to be the odd duck and do something different. Those who follow me on Twitter know this, and my colleagues at the board, so I wasn't going to apply.

Matthew looked at me, he's like, "You are going to apply to the board. You'll be a perfect board economist." I was like, "Okay," so I applied. I think that's this open-mindedness, you don't-

Beckworth: So cast your net wide.

Sahm: Yeah, and even when you go to think about jobs you accept, pay a lot of attention to the department. I had some fly-outs where it was really clear early on that it was a viper's nest, and this happens with faculty. Like, somebody has a favorite person. Someone has another favorite person.

Beckworth: Oh, faculty are the worst at times. Yeah.

Sahm: And that should be in the faculty meetings when they go to vote. When you can see that in your job talk, that is a huge red flag. And I also had a university where, in one of my office visits, the faculty member badmouthed their grad students, not being high enough quality. And I'm like, "I am out of here." I almost tried to cancel the dinner, because I'm like, "I'd rather go home and sleep."

Pay attention to that. I had a colleague when I started the board, and she's like, "Well, this is the best job I got. Best offer," and I'm like, "Well, frankly, that's ..." For all of us, right? We go where it's the best, but best has a lot of dimensions to it, and it's feeling like you fit, it fits your life, you think there are colleagues there, more than one, that you'd be close with. I mean, every department's got a jerk in it, and you can stay away from them.

Beckworth: Normally, several.

Sahm: Yeah. So, ask the students. Ask the faculty. “What's it like to be here?” And think about government, private sector and academia. I think some students unfortunately have advisors and committees that are maybe not to a fault of themselves, but they try to create little mini-me’s, so for them, it's the academic placement. That's what you should go for. That was not the mentoring I got at Michigan, but even when I was choosing between jobs at the board and I had some options, I was like, "You want me to be a macro forecaster?" I mean, that wasn't my research, and I couldn't see it, but the people who were hiring me, they could see it. So sometimes, you don't even know where you fit best, and you've got to be open-minded, so I think that's that.

My other big advice is be kind to your peers. This is a high-anxiety time. Economists with PhDs are highly employable, especially if they keep an open mind about where they could go. First step. It's not like it's a job for life. You can go to another job. But it's a really high-stress time, and it's important to find ways to both reduce the anxiety in your own life, like stay off that job market rumors blog because that's only anxiety.  That was my first year on the market, and it created more anxiety for me.

You don't want to see who got the offer at the place you were really gunning for. So, find ways to keep your anxiety level low, and be kind to your classmates. And I will say, you mentioned this, I've been reading these job market papers, which has been so much fun. Like, I don't read widely in macro anymore because I read for my research papers things that we need to cite and be aware of. I work in a lot of consumer consumption behavior. I mean, I've read so many rejections of the permanent income hypothesis, I'm just like, "This is great."

My other big advice is be kind to your peers. This is a high-anxiety time. Economists with PhDs are highly employable, especially if they keep an open mind about where they could go. First step. It's not like it's a job for life. You can go to another job. But it's a really high-stress time, and it's important to find ways to both reduce the anxiety in your own life, like stay off that job market rumors blog because that's only anxiety. So, find ways to keep your anxiety level low, and be kind to your classmates.

Anyways, and I read my referee reports. So again, that ties back to my research. I don't have a lot of time to read widely.

Beckworth: Yeah, we all specialize in areas.

Sahm: When I have research time, I'm writing my research. Anyway, so what I realize, I had asked for all job market papers in macro, and I had so much fun because I was reading really widely in macro. What I had offered them is I would read the abstract, the introduction and all their table and charts, because I believe communication is extremely important. One of my jobs as a section chief for the last two years was to read the papers of my economists. I have to sign off on them before they become Fed working papers, and I had early-career researchers, actually, frankly, some of them were further along, who their introductions weren't good. The technical part of their paper was so sound, and I said, "You know, as a referee, if I'm falling asleep on page five, this is not going to help you." They were getting desk rejects on some papers, and I'm like, "This is your problem."

So I had one person who, he's like, "You made me revise it, like, 12 times." I'm like, "Yeah, you're going to do 13. You're getting close, but ..." So I realized this was a gap in a lot of economists' education, and so I wanted to help these job market candidates, give them tips. I had no idea how much fun it would be. I underestimated that. Second, I had no idea how bad the writing would be, and I read papers from MIT, Stockholm, India, UC, the California's.

I mean, I read them from all over, and they were all bad. The core of their papers were amazing, and they would hide things like their contribution to economics in the fifth sentence of a 10-sentence paragraph, and I was like, "No." So I felt like I had really contributed to them, they were all very thankful. When they asked me as a group, "What can we do to pay this back?" I was like, "You can be kind to your classmates on the job market."

That was a great experience. I think for mentoring and doing work like this, I spend a lot of time on Twitter talking about why I think diversity and inclusion in economics is so important. On a lot of dimensions, but on one important dimension for the economics and the policy advice, and then I thought, "I got to put my money where my mouth is." Time is our greatest asset, so I was like, "Ah. I'll do this."

Beckworth: Well, that's very nice of you to do that, and I'm sure they appreciate it. And I've heard it before too, economists sometimes aren't good communicators, and that's a big part of the battle, right. The messenger might destroy the message in the way they bring the message to the public.

Sahm: Mm-hmm (affirmative).

Beckworth: Well, let's talk a little bit more about the Fed, and then move on to some of your research. I'm just curious, working at the Fed, did you run into Jay Powell and all, "Hey, Jay, how's it going?", or, "Hey, Leal, what's up?" That kind of casual ... Or when you met him is like, "Yes, Governor Brainard?" I mean, what was a typical day like at the board of governors?

Claudia’s Experience at the Board of Governors

Sahm: That typical day has changed over time. I've been there 12 years, and I've seen a change in our culture. That was an intentional change from the very top, and I think that's good. But I came in, my first year, my first forecast at the board was in January of 2008. I follow consumer spending. My first year I did it, and I did well, but it was a mixture of impostor syndrome, all of our models broke, stress does not bring out the best in people, and I'm an emotional person, and watching that data come in and how it was hurting people, and how-

Beckworth: That's rough, huh.

Sahm: And they were being super creative. It just, it was bad. So for me, on a lot of levels, that was a really tough introduction to the Fed. I came in, Bernanke had not been there that long when I came in. There was an aura of Alan Greenspan at the Fed. I started in the summer of 2007. I had some research time, was kind of watching things start to move around in the economy, but I decided, "I need to read Greenspan's memoir, because I got to figure out what this is here." I made it through more of that than I made through Bernanke's memoir. That's another story. The culture was a lot more buttoned-down, much more structured and strict and formal. Bernanke wanted to change that, but he just, what he stepped into, we didn't need to ease up, we just needed to hold on and do the work.

So I was trained, and there's a lot of training. We go to briefer's school before we're allowed to do a briefing in the boardroom as a staff person. We go to a week-long school. We learn how to write the briefings. We are videotaped talking, and then we do a mock briefing in the boardroom, which in some ways is scary because these are our senior colleagues, and that's the first time you sit in there. Anyway, so it's a lot of training. That training goes on. When I did it, it was formal because at that point, the staff briefings, and we do the data briefings, and then before the FOMC meeting, there's a briefing. You have to be more experienced to do the more important ones. They're written, prepared text. We have a meeting where we edit as a group and go line by line, word by word.

Beckworth: Sounds painful.

Sahm: But you learn something. Like, I have the Fed decoder ring now. I know what words mean, and a lot of the words sound like people words, but they have a quantitative meaning. Anyway, so when I started, it was chairman this, governor that, and actually, some of the most obnoxious things that were said to me and hoops I had to jump through would be somebody in my office saying, "The chairman wants this. The chairman wants that. The chairman doesn't care about your research, doesn't care about what you think about monetary policy." Anyways, and those were not pleasant experiences. There was a set of them that were really unpleasant and early in my career, before I knew how to tell people, "Get out of my office. You're being unfair and unkind."

I actually had a set of them because I had emailed Ben Bernanke because the American Economics Association is doing a lot. They put out a harassment policy, and I sent it around at the board because I think it's really important, and especially to my team, I wanted to emphasize, like, "This is a real thing," and so I emailed him to be like, "This is the email I sent around to my staff. I'm so happy you're doing this," and I said, "It's so important because I had these experiences."

I shared some of the things, not in his name, but in his title, and I told him, I was like, "I knew you didn't initiate that, but I also knew if I caught you in the elevator," which, we'd see him, and sometimes he'd sit at lunch with us. "If I'd asked you if he'd ..." The boom would've come down. Not from him, but... So that just wasn't allowed, and that's fine. I knew. But he confirmed in this email. He's like, "I didn't start any of that," and I was like, "I know," but I got yelled at, or scolded, multiple times after I walked out of his office in some kind of a staff… because I didn't use the right words, or I got a little too feisty.

Beckworth: But you're saying it got better over time, that culture?

Sahm: I got better at handling it.

Beckworth: You got better ... Okay.

Sahm: And I think broadly the culture has gotten better. I think we're still very hard on new people, mainly because, I mean, a research assistant hadn't gone to econ PhD. They have not chosen to be in our culture. I like how economists are direct and we fix problems and work. I think there's a difference between being critical and direct and being… undercutting someone and trying to make them feel bad. Anyway, so I think it's gotten better, but it's gotten better because, and I am not alone in this, is because there are many staff and leaders of the board who have put a priority on, "We're going to fix this."

Beckworth: Fix the culture of the Fed.

Sahm: Yeah.

The Sahm Rule

Beckworth: Well, good for you, and you've put forth some effort toward that. Lots of war stories I'm sure you could tell, and maybe we should have another whole episode on that. Of course, I'm sure you want to keep some things close to your chest. Let's talk about some of your work, because you've done some things that are pretty fascinating. I want to go to something that I would think is probably something you've received the most notice, recognition for, especially lately, and that's called the Sahm Rule. That's your last name, Sahm Rule. This is something that you wrote as part of an article for the book *Recession Ready*. The article was titled *Direct Stimulus Payments to Individuals*, and it's a rule. We'll get into what the rule is, but before we do that and explain what this rule is, I just want to explain to our listeners, those who aren't in this econ world. To have a rule named after you is a pretty big feat, a pretty big accomplishment.

Just by comparison, there's a famous economist named John Taylor, and there's a rule called the Taylor Rule, which is huge in macroeconomics. Most central banks in one form or the other follow something like a Taylor Rule, whether they are explicit or implicit about it, and it's named after him. Here's the interesting thing, I was thinking about this in getting ready for the show, Claudia. You're there about a decade, okay, 12 years at the Fed, I'll say a decade, approximately, and you got a rule named after you. John Taylor started, I looked this up, '73. His paper where the Taylor rule comes out is '93, so that's two decades, and it probably took a few years after that article, so it took him two decades. It took you about one decade, so you really have kind of set a pace it's going to be hard to match for anybody else in the future. You have a rule named after you. You've done it at a blazing pace.

This rule now is on Haver, it’s on Bloomberg. Haver is a place you can get your data. Bloomberg, same thing, FRED. All these data sources have the Sahm Rule, so are you pinching yourself and you go onto Fred or Bloomberg and you see this rule named after yourself?

Sahm: Yes.

Beckworth: That's pretty amazing.

Sahm: It was a surprise to me. It was a recession indicator in the book.

Beckworth: So you don't call it Sahm Rule in the book?

Sahm: No, absolutely not. They've blindsided me. So *Recession Ready* was a co-sponsored volume between the Hamilton Project of Brookings and Equitable Growth, so the employer now. The whole book, and I really would recommend it to people who are interested in economic policy and macroeconomic stabilization, so fighting recessions. Every chapter was on a different automatic stabilizer, some of them exist right now, like unemployment insurance, like extended benefits, how to strengthen those automatic stabilizers. My chapter, and there was another one on infrastructure, was taking a fiscal stimulus policy that's often turned on in recessions and making it automatic. I was looking at direct payments to individuals. In 2001, there was a tax rebate. In 2008, there was a stimulus, economic stimulus payment-

Beckworth: Yes, those checks we got from-

Sahm: Right. There were checks, electronic funds transfer. There was money that went out to households in chunks. 2001 was like 500. 2008 was 1000.

Beckworth: But it was kind of ad-hoc is your point?

Sahm: Well, they were what we call discretionary.

Beckworth: Discretionary.

Sahm: So there was a past precedent of it, but there was legislation drafted on the Hill when it was clear the economy was having some trouble, and then it had to pass Congress. Often in fighting recessions, everybody gets on board. Especially when a recession starts, this is not typically a time of partisan bickering. But it takes time. It takes time to draft legislation. It takes time to get it through Congress. One of the things, and seriously, the public servants at the Internal Revenue Service and Social Security Administration should've gotten a medal for how quickly they were actually able to do the logistics.

My proposal was to make these automatic. To make something automatic, you have to have a trigger that says, "Now it goes." This could all be agreed in legislation before, when we're not in a recession. There's actually been a lot of interest recently in maybe we could do this. Well, maybe we could. Or, there's a whole volume now that you could pull off the shelf when it does like a recession and get going on legislation.

My proposal, I think it's really important, another aspect of the automatic is you would give time for the logistics to be put together. The government actually does not have, and this may be a good thing, the address, the bank account, of every American, so they had to pull ... I mean, the IRS has information because they do the tax returns. That's timely. The 2008 went out to retirees, people who didn't have a tax liability. Social Security Administration, they cut checks, they know where people are. You had to have collaboration. No, this was more 2001.

You can only push out so many checks. The government can only cut so many checks in a week, so there were just all kinds of logistic things. In my chapter, and I talk about this, we could get this ready. If you had a system in place, it wouldn't be a mad dash. You could turn them out during tax season, which was impossible in 2008.

In any case, I think there's a lot to be gained, and I drew on the research that I've done on fiscal stimulus since 2008. I studied the 2008 tax payments, or the stimulus payments, making work pay, which was tax credits that went out over time, and then the payroll tax cut. I had to follow this literature because this was stuff we put in the forecast, so I had learned a lot. I had a lot of opinions about how to do stimulus, and really, that was the core of my chapter. That was what I thought I was writing the chapter for, but of course, you need this trigger.

I kind of knew this would work from the beginning. I spent many a Saturday morning fiddling with this thing. I eventually pulled the real-time data, so data that was available at the time, because that's a much more legitimate test. When I presented it the first time at an author's conference, it was either late January, early February, and Jay Shambaugh, who'd been the member I worked for-

Beckworth: A previous guest of the show.

Sahm: ... When I was at the Council of Economic Advisors... Oh, yes. Jay is great. He said, "Claudia, this is good." Because he'd worked on something in early 2016 when the economy wasn't looking so hot, so he was at the council, and so he had kind of fiddled around, and even Jason Furman, who was the chair then, he's like, "Half a percentage point. This is bad." But I knew this from working at the Fed. If the unemployment rate rises a small amount, this is not a good sign.

Beckworth: Tell us the trigger. We're kind of walking around it. What actually is the Sahm Rule, and what is the trigger amount?

If the difference is half a percentage point or more, we're in a recession, so this is not a forecasting device, this is an indicator that says, "We're in a recession, and we're early in it." It triggers two to four months. This is helpful because at that moment in a recession, we don't know we're in a recession.

Sahm: Okay, so what I do is I take the monthly unemployment rate, I calculate the three-month average, so the current rate and the two prior. Why do that as monthly data? Any monthly data's noisy, so you don't want to overreact to little ups and downs, so take the three-month average. Then I look at the current month, and I compare it to the low of that same series over the prior 12 months. So I take 13 months of data [for] this comparison. If the difference is half a percentage point or more, we're in a recession, so this is not a forecasting device, this is an indicator that says, "We're in a recession, and we're early in it." It triggers two to four months. This is helpful because at that moment in a recession, we don't know we're in a recession. Because at the National Bureau of Economic Research, there is a recession dating committee, which is not a fun-sounding dating committee. This is a group that sits down, very senior economists who work in macroeconomics, I think largely or all academics. I don't think there's any government economists.

What they do at that time, and they do not call recessions until 12 months, more afterwards. And at that point, they have a whole host of data that they look at, including the unemployment rate, and they will choose the month in which the recession started, and then they will later choose the month in which it ended. This is important news, but 12 months into a recession? I mean, we should still be doing stimulus, but this is not the first time you want to push something out to the economy, and so you can't wait for the dating committee. You also… there's a very common belief, which has some basis to it, that two months of negative GDP growth is a recession. Okay, so there's a problem with using that also as an early recession indicator because GDP growth, that's quarterly, it takes time, it gets revised. When you've got two months of negative GDP growth, you're also well into it.

12 months into a recession? I mean, we should still be doing stimulus, but this is not the first time you want to push something out to the economy, and so you can't wait for the dating committee.

Beckworth: I was going to say, that's quite a delay, six months. I mean, that's ...

Sahm: Yeah. So that's a tough one. What I used works. The thing that really caught attention, there were a few things that caught attention. One, there are no false positives. Since the 1970s, when it turns on, we're in a recession.

Beckworth: It's always worked. Yes.

Sahm: It's always worked. There is a case after the 1975 recession where it kicks back on, but in my proposal, that's one of the big recessions, and I not only have a stimulus payment go out at the beginning of the recession if it's a big one. In '75, 2008, obviously, I think '81 or something like that, they were all big. They had more than a two-percentage point increase in unemployment in the first year. This is bad, bad. So for those, I said, "Okay, once that happens, you're going to send out a check every single year until the unemployment rate comes down not to its pre-recession level, but gets a lot closer." So for me, my policy, we were still into the cutting checks when this thing went a little bit above .5. In any case, no false positives. And this actually was a design principle, and I thought this was important, I talked about it in the chapter: it is so simple. It's the unemployment rate. That is the most followed national indicator, and it matters.

To me, that is the core of why a recession is so bad is people lose their jobs. That is really a problem. In the recession, many households do not have a lot of money sitting by the side, and certainly not to cover months of pay. So it's bad in recessions, and there is a lot of research that shows this. If you lose your job in a recession, it takes a long time, and maybe even has a career negative effect. So to me, the unemployment rate is just where it's at in terms of thinking about a recession. It's easy to calculate, it's a monthly series, it comes out very soon after the month is done, and frankly, I think the transparency is important.

To me, that is the core of why a recession is so bad is people lose their jobs. That is really a problem. In the recession, many households do not have a lot of money sitting by the side, and certainly not to cover months of pay.

Beckworth: Yeah, and I think what makes this appealing probably on both sides of the aisle is what you're proposing, at least in the way I see it, is a plan that makes it systematic, makes it rules-based, makes it predictable, and of course, the goal would be to actually do it now. Get Congress to maybe legislate this now so as you head into a recession, you're prepared. In fact, I would argue if you have a rule like this in place, it might actually reduce the severity of a future recession. Just the anticipation that there's going to be that backstop, people will be less likely to get panicked, to hoard funds, to save more, cut back on spending, so on many levels, just the preparation, the mental psyche part, that would be useful.

Beckworth: Okay. Yeah, so I talked to your now current boss, Heather Boushey, about this. We interviewed her about the book. She agreed that one of the things you want to do is to get these ideas in play now ahead of time, systematic, because we know what will happen. What will happen is Congress will do something, and I think particularly so now that interest rates are getting low, my worry is the Federal Reserve's going to be very limited in the next few recessions. In fact, the minutes from the past few FOMC meetings, the staff forecasts have the Fed basing the effective lower bound, zero. They can't cut their rates, and it looks like long-term rates are going down as well, so the Fed, I think, will be kind of limited in what it can do with conventional tools, so what you're proposing is a predictable, systematic way of addressing it instead of having Congress make things up on the run and hoping it works.

So I hope they take it seriously, they think about it, they're proactive. With all that said, though, I want to go back. How did the name come about? You had this great idea, this great trigger. The Sahm Rule, the now-famous Sahm Rule, is about the trigger, not the whole package. You have a package, how it works. I think that's the point you were making, but let's play this up. I mean, it's a rule named after you. Who called it the Sahm Rule? Was it Jay Shambaugh that called it the Sahm Rule, or someone else?

Sahm: I've gotten some of the history from Jay, but again, they totally blindsided me at the launch event in May. I was going to be a panel in the middle. Karen Dynan was going to talk to me about the book. Everyone else who had a chapter, there were two other panels. They open the event with kind of a fireside chat with Christy Romer and Ben Bernanke, because they were very key players. Christy was the head of CEA, and Ben was obviously the Fed chair. Even in that talk, that first one, the Sahm Rule came up somewhere in there, and then it started. I'm sitting there, and I'm like, "What's happening?"

Beckworth: "Hey, that's my rule."

Sahm: Jay told me later that they actually had been calling it internally the Claudia Rule, but then they decide before the launch event, they had to get it a little more serious…

Beckworth: One syllable.

Sahm: Well, and to tie it to my last name, which is more unique than Claudia. Anyway, so I'm sitting there, and they also know I'm not the kind of person that would've named it after myself, so it was kind of fun, I think, to watch me want to crawl under my chair. But after the event, Christy Romer, I was talking to her for various reasons related to my proposal and some of the comments she made in the panel.

That was all recorded. I think it's a really nice event, especially that beginning, to listen to. After the event, I said, "Oh, the Sahm Rule," and she looked to me, and she's like, "Claudia, you have got to own this. Any man economist would own this," and I was like, "This is true. I've never heard John Taylor push back on the Taylor rule," so I've tried really hard. I have gotten pushback. I've gotten pushback from the staff.

Beckworth: Really?

Sahm: I can come back to that, the Fed. But what's hilarious, and this is… I think everyone should have an ego check, having a teenage daughter is an excellent ego check. She said a few things. When it came out the first time and it was getting some attention, she was like, "Mom, that's dad's name, not your name." We're co-parents now. I was like, "Well, child, I kept it because I like to have your last name." Anyways.

Beckworth: Brutal.

Sahm: So then, like, two or three weeks ago when it got more coverage, I think this was when the Wall Street Journal article came out, we were driving home in the car, and she looked at me, and she's like, "Mom, are you worried that you've peaked with the Sahm Rule?"

Beckworth: Wow.

Sahm: And I was like, "Wow, child."

Beckworth: Mean.

Sahm: Later, she was like, "Well it was a question,” And I was like, "Still," but I looked at her, and I told her, I said, "I aspire not to be a one-trick pony, but if this is the only trick I've got, I am proud of this one."

Beckworth: That's a great one.

Sahm: So, yeah. Teenagers are great. The ego is in check. I still am amazed at the reception. I was amazed at the reception at the event. We had a discussion before with a lot of the contributors, and a gentleman who has worked for decades in economic policy in DC, not monetary, but a lot of advising on fiscal policy at a research think tank, and he told me, he's like, "When I heard about your rule," this half a percentage point increase, he's like, "There was no way that can work," and he's like, "Then I saw it does." That was a clue to me that something I knew that would work, I mean, I didn't know exactly what the formula would have to be, but I knew it was going to work, and I had people with a lot of experience in policy, like, "I had no idea." So I was like, "Okay." That's why it's gotten the reception. That's why it didn't use three databases.

And like you say, I don't expect the automatic stabilizer policy to go into place before… I don't expect this to happen now, but people are following the Sahm Rule, so they'll be in awareness of when the economy is starting to have trouble. I had an individual who works in the Ohio government who said they're thinking about using it to tie some of their safety net adjustment…

Beckworth: Oh, really?

Sahm: I was just floored. Now, the reason, there was a Wall Street Journal article that in the headline, Kate Davidson wrote this, whoever is her editor I want to send a thank-you-note to, because the headline was amazing, but the end of the headline was, "The Experts Agree: Ask Claudia Sahm." Okay, this ran. I got a lot of emails at work about this.

I am sure that if those experts were 80 percent Fed economists, former Fed economists, there's no way if you asked them they would say Claudia Sahm. Which is fine. Again, remember, I thought it was obvious. I never worked on the labor forecast at the Fed. Andrew Figura was my first group manager. His research is in labor. After this event and the Sahm Rule, when I was like, "Oh, people are paying attention to this," so I asked him, I was like, "Andrew, did I scoop the inside Fed rule? Because I know there's this increases..."

He's like, "No, Claudia." He's like, "Our go-to is a three-tenths increase." I was like, "Thank goodness. I didn't scoop." At that point, it wouldn't have been the Sahm Rule. If I had scooped it, it was going to be the Fed rule or something, and so I was like, "Okay." Now, at that point, I knew three-tenths has false positives. I mean, I'd spent enough time with that spreadsheet, and I know where at least one of them is at, and so I was like, "Okay." But you did, like, small increases, and I'm like, "That's fine." You do that. I remember at the time in the press, and I think even someone had mentioned to me on a deep background call with the journalist, he said, "Well Bill Dudley has a three-tenths rule, so like yours isn't special."

And I was like, "Yeah, okay, nice person.” He didn't write an article about me. And I actually got an email from Bill Dudley like a week or two ago. And the subject line of the email was, for what it's worth, here's my three-tenths rule I put it in a Goldman Sachs newsletter in 2000, 2001 and he did a little screenshot of the Goldman thing, highlighted the sentence, he'd written and then there was a table. A table, not a chart of like how it worked in recession. I didn't reply to him. I don't plan to, this is an opportunity to the world to reply to him. And it really encapsulated a lot of things that I had trouble with at the Fed and are part of why I feel pretty good about having left the Fed. 

One, I mean, I really don't appreciate this. Like you're doing a good job. I'm going to undercut your work, but whatever, that's an ego thing. And not saying that he has an ego, but I mean, I've seen this pattern before, so whatever. And okay, I know I have no false positives, right? So, and I know his three-tenths does but it's a good rule. Like in print, there's a lot of shared principles, so fine. The piece I had the most problem with was telling me it was in a Goldman Sachs newsletter and private sector macro people, they're important, they're great, it is important. The financial sector knows what the heck is going on in the economy. But that gentleman who works in the Ohio government, I would lay good money that he does not get the Goldman Sachs newsletter. I got attention because people didn't know about it outside the Fed or outside of the places Fed bank presidents and Fed staff go to work. So I understand that and there's a lot of examples-

Beckworth: That's a great point though, that....

Sahm: ... In the Fed.

Beckworth: That the few people have access to those newsletters from Wall Street and you're kind of like tearing down that veil, opening the veil that everyone now has access to the truth. So great, great stories and great rule and we can talk a lot more about this, but it's in the book *Recession Ready* and we'll provide a link to it in your article on the webpage for the podcast. So Sahm Rule is great. Again, kudos to you for not just having a rule named after you, but a practical rule that can make the world a better place if it is paid attention to along with your proposal that goes with it.

Sahm: Thank you.

Beckworth: But I want to move on to something else you've done and you talked about being a one trick pony, but that's not you. You're being very harsh on yourself because you've done some interesting work with some colleagues at the Fed, I believe. And this is using big data to inform policymaking. So I believe the paper, you have an NBER working paper and you have a bunch of notes, that surrounds this. It’s not the only thing, but I think your big paper, correct me if I'm wrong, is *From Transaction Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending.* And that paper constructs kind of a real-time measure of economic activity spending, I believe based on credit cards and transactions. So talk us through that. How would it be useful for policy? How would it be useful to FOMC meetings, for example?

Using Big Data to Inform Policymaking

Sahm: Yeah, so the working paper, which is a little bit of a mouthful with its title, so that's our method's paper. It will appear as forthcoming in the NBER, has a volume called Big Data for the 21st Century. I think I'm getting that about right. And that volume has… we're contributing to that. Another flagship, a big data project at the board using ADP data. So looking at labor market, it has a chapter, many different government agencies, Bureau of Labor Statistics, Bureau of Economic Analysis. Many of them have these big data where they're taking private company data that was not intended to be an economic statistic and they're transforming it into something that can be used potentially in official statistics. And in our case, our statistics are developed primarily for internal use. Like we're years away from publishing these on, I mean the Fed publishes economic statistics. We might get there, but not yet. 

So what this project is, and I've been working with an amazing team on this. So Aditya Aladangady, Shifrah Aron-Dine, she was actually a research assistant at the time and now is at Stanford for her PhD, Wendy Dunn, Laura Feiveson, Paul Lengermann and myself. That basically makes up the consumption analyst researcher group at the Fed. And we put aside a lot of our research time over the last three years to pour ourselves into this data. As you note, there are several Feds’ notes. We needed some output and we also needed it… I mean those Feds’ notes have a corollary of inside research, most of them. We also needed to do that to show these data can be used in policy settings. And the chapter has a lot more details on how we construct these.

We use the economic census to make sure that there's a representativeness to our data and that's really important for policy work. The numbers matter, not just the sign. So we did a lot of work. We partnered, I mean First Data gets a lot of credit for being willing to share their payment data. We did an in a very-

Beckworth: So this credit card and debit card transaction data?

Sahm: It's basically any card swipe. So First Data, they partner with merchants, those little machines you have to stick your card in. Many of them, not all of them, are First Data merchants or partners. So we get cards swipes, we get credit cards, debit cards, we get electronic benefit transfer cards. And so we have all this data, massive amount of data. First Data is a large payment processor and they had partnered with Palantir as their technology partner. So Palantir for just First Data's use was doing things with the data so they could make judgements about their business model.

So we worked with Palantir, we had an amazing programmer, Dan Moulton, who was the lead there in helping us transform the data. We worked with a lot of Palantir staff over time and we got it to a good place. So as two examples where this has been used, the first was in 2017. We used the data to do real time tracking of hurricane Irma and Harvey for the FOMC. I was writing Teal Book at the time, so I guess Harvey was first. I was writing Teal Book, which is our big forecast document that goes to the FOMC. And we had a section we added to that about the hurricanes. The data are extremely granular. They're daily data, they're geographically specific.

Beckworth: And they’re measuring transactions.

Sahm: Well, in what we do, the transactions are the underlying data after a lot of filtering. We create series that are comparable to the retail sales data that comes out of census.

And we didn't benchmark to them, but we're doing our comparisons to see how good the data were. We'd go to the place where there's overlap. So census, it's national, it's monthly. We spent a lot of time on seasonal adjustment. But then once we were comfortable with that, then we would use the granularity in our First Data series. The fact that it's daily, it has geographic specificity and we get that data within two days, three days. So-

Beckworth: It's amazing.

Sahm: Yeah, no, it is totally amazing. So when I'm working on this, writing it up, I mean, it's so exciting. We stuady weather a lot. And I'd never been able to do it in real time and I'd never been able to do it in real time for the FOMC, I will say, and this is the power of these data and I really wish everybody, particularly outside of the government, thought harder about what the ethics are of these data.

I can remember sitting at home revising the draft on my computer and I had the New York Times. I'd flipped over to it online. And it was the story about the woman who they found like floating through some drainage ditch holding her baby above her. The woman had drowned and the baby was alive. And I'm sitting here so excited about these data and people while I'm writing this up are in a really bad place. And we were actually instructed by David Wilcox, who was the division director at the time, that what we wrote up had to be sensitive. Like it could not, just in general, how we were talking about the hurricane. We did that. So it's really powerful data.

Beckworth: This is I guess where I see great opportunity here. So it sounds like this real time data has already been fed into FOMC meetings.

Sahm: There's another really good example. So this was this year in 2019, there was a federal government shutdown. That shutdown affected Census so they could not publish retail sales when they normally would. And even after the shutdown ended, they were delayed on their publishing because their source data and getting a survey and they would just, everything got thrown off. We had the First Data, this was a time where the economy was being a little uncertain and we were able to give that to the FOMC. They didn't have the official stuff. We look at a lot of data, so there's other stuff we could look at, but it's a real, the official statistics were the best thing we have. And if they're not there, there's a little bit, I don't want to say flying blind because I don't want to scare anybody, but it was really helpful to have those data and we didn't have that in the last shutdown.

So we had that and it was like, wow. And that is detailed in our working papers. I don't want [anybody to] think that I'm leaking stuff here. But that shows how powerful those data are. I do want to close with one point. Partnering with private companies can be difficult because they're there for profits. Totally important. I'm an economist, yay. Profit maximization. In the government putting these statistics together we're trying to create public goods. Those are not the same thing.

Partnerships happen because somebody in the company gets it. Like we've got information this can help the world. People changing companies, the cost of it is actually realized and then those partnerships fall apart. I don't know of a single big data effort within the consumption space… and these are academics… that hasn't shut down at some point because the match gets lost. So we are in a position where we are not going to have access to these data at least near-term. So we're working on it, but we've had to rejigger and we're high maintenance. And-

Beckworth: I guess kind of my couple of thoughts on this, my big kind of takeaway, to me, it's kind of surprising that we still use data based on surveys. I know the traditional data after several revisions is good, but to make policymaking in the 21st century seems like big data would be the first thing we turn to. I mean I understand it is still being developed. There's all kinds of seasonality. There's new different types of activity being done. There's a lot of issues to work through. But I would think this is something we would do already. I've heard many stories of hedge funds who use this type of data, credit card transactions, debit card transactions. I've heard of satellite lays, satellite pictures to measure economic activity. So my hope is that at some point policymakers will get to the point where that's kind of like their First Data they have, it's real time, they can see what's going on and you're making a valiant effort to get us there.

But it sounds like there may be some bumps along the road, which leads me to the second point I would make is, and again this is an outsider looking in, you can correct me here, but the Federal Reserve has a budget and it seems to me if they really wanted the data they could find the funds to make this a more reliable source of information. They could pay partners to get this anonymized information in. I mean they remit a lot of money back to treasury. They could take some of that and pay a vendor to regularly send this data. I mean, JPMorgan Chase has its big data set, I think it’s 64 million, 14 different metro areas. I mean getting a partner with someone like them or this vendor you mentioned earlier. I think that's essential. It's useful putting the government into the 21st century and how it makes decisions. Your thoughts?

Sahm: So I'll start with your second point, but I do want to come back to the first, because I disagree with you on the first. So we do pay First Data and Palantir for the data and is not trivial. I mean this is amazing data. So I mean we should get to the value of the marginal product. Well, money can be enough, but there are constraints on the Fed's data budget and it's large, but I mean we buy a lot of data because data's important. All kinds of data. So actually I will come back to your first point. I love all data. 

A lot of my research is using survey data. We just ask households directly. What'd you do with the stimulus, more or less? The official statistics are so important. So like retail sales where it's a firm survey, those are really important. The economic census… Well, many of those surveys to firms are mandatory reporting. That's important. 

I love big data. I love this idea of taking information that's just being kicked off by the process of doing data or doing business. I think that we should try to combine the data and use each to its comparative advantage. So I think that’s a lot of what we see right now in the landscape. I do agree that big data needs to be more developed, needs to be more integrated in official statistics where it's more helpful than the surveys. So I'm all on board with an integration. I'm not sure, I think it'll be a long time before the weight falls more on the big data. But let's see.

I love big data. I love this idea of taking information that's just being kicked off by the process of doing data or doing business. I think that we should try to combine the data and use each to its comparative advantage. So I think that’s a lot of what we see right now in the landscape. I do agree that big data needs to be more developed, needs to be more integrated in official statistics where it's more helpful than the surveys. So I'm all on board with an integration. I'm not sure, I think it'll be a long time before the weight falls more on the big data. But let's see.

Beckworth: Fair enough. And I know there's some big concerns also of using big data, even if you had this world that I'm dreaming of here, the problem is you're measuring like nominal transactions. You're not measuring value added. I mean, growth, GDP is value added. It's final sales and we're looking at total activity. So there's some conceptual problems.

Sahm: There are projects. So there's a project in the opening of this volume that looks at price data, right? So there's an understand we need prices that each of the chapters is focusing on a different sector of the economy. So there's this effort going on. I did want to say one more thing on your second point. So I was on a panel at the National Association of [Business] Economics. They have a tech conference that was in Seattle, this is recently, David Wessel organized a panel on using private data for economic statistics. So I was invited to be on the panel and I talked about this, our biggest challenge right now is getting these partnerships figured out.

It is not a technical problem. We do figure out how to create the statistics. It's just official statistics, or frankly the Fed. We can't rely on stuff that we think it's there and then it's not. And then there's this holdup problem because you double…anyways, so he gave this talk and I was kind of grumpy but I told him like, "Hey, I'm a macroeconomist, you're getting grump." And I also said, this mismatch in goals is that it is not my life dream to teach private companies how to monetize their data. Because we were basically helping them create data sets that they can sell to Goldman. They can sell to Wall Street, but their goal is not create public goods. So I get it, we just have different incentives and we can find partnerships that work.

And I also said, this mismatch in goals is that it is not my life dream to teach private companies how to monetize their data. Because we were basically helping them create data sets that they can sell to Goldman. They can sell to Wall Street, but their goal is not create public goods. So I get it, we just have different incentives and we can find partnerships that work.

Like I'm really happy with First Data, like what they have given us an opportunity to do. Okay, so then it gets to question and answer, because it's a tech conference. They come up on the iPad to David Wessel and someone from the audience is like, "Well, why doesn't the Fed just tell the companies that they have to give them the data?" And I was like, yeah, I'm on the West Coast. You all don't think too hard about burden. It's like that would be such a nonstarter and get the Fed in a lot of trouble. But it could be that we work… maybe industry groups come together and pool data and maybe there's a way to take the data and give it back to the companies in a way that's helpful for them. So I have hope, but these are not simple answers.

Beckworth: I wonder if the Office of Financial Research as part of Dodd-Frank with FSOC... I wonder if they could play a role on this somewhere.

Sahm: Well, in one of our earlier big data projects, and we've done several and this is the first one that worked. I mean we learned a lot from the failure. So I think that was good. We had one project where we were using the Y14 data and that's data that after Dodd-Frank, the Federal Reserve had the authority to collect. And it's also granular. It's like banks reporting monthly account balances. It probably gets a lot closer to what JPMorgan Chase has for data except it's more of a universe. Again, it's collected for supervisory purposes. It is not collected to create a twin to retail sales.

So there is regulatory data and the agencies, they're working with administrative data to do their big data project. There's a lot of issues about sharing data even within the government. IRS data doesn't go to a lot of other people for very good reasons, but it can be very helpful as administrative source for say income. So it's a really exciting area. I am so blessed to have gotten to work on this. And the Federal Reserve… this is an important mission that they have and there's multiple projects going. They're putting the resources behind it.

So it's a really exciting area. I am so blessed to have gotten to work on this. And the Federal Reserve… this is an important mission that they have and there's multiple projects going. They're putting the resources behind it.

Beckworth: So they are working on this.

Sahm: Yeah.

Beckworth: Yeah. So I mean I guess what my dream would be to make this concrete and clear as possible as one day we'll have something similar to the Billion Prices Project at MIT where they're scraping data off the Internet and they have this index of a billion prices I guess. They construct an index that looks a whole lot like the CPI, but it's real time. So one day we will have the billion transaction index along those lines. And I think it's hugely important because I think back in2008 when GDP was coming out in the second half of the year, we were in a steep fall, the economy. But the GDP data didn't show it until it was revised the next year. So you needed some kind of other indicators to push the Fed a little harder to move way more aggressively.

But with that said, you've been on the front end of this effort and you've done a lot of work and we appreciate what you're doing and what you continue to do and we'll look forward to more progress on this.

Beckworth: Well with that, our time is up. Our guest has been Claudia Sahmn. Claudia, thank you so much for coming on the show.

Sahm: Thank you.

Beckworth: Macro Musings is produced by the Mercatus Center at George Mason University. If you haven't already, please subscribe via iTunes or your favorite podcast app. And while you're there, please consider rating us and leaving a review, this helps other thoughtful people like you find the podcast. Thanks for listening.