Speaker 1: Hello, and welcome to another episode of the Odd Thoughts Podcast.
Speaker 1: I'm Tracy Allaway and I'm Joe. Wasn't all so, Joe.
Speaker 1: I know we've been spending a lot of time on
Speaker 1: the question of inflation and whether or not it's transitory,
Speaker 1: but I feel like a lot of that discourse is
Speaker 1: sort of happening at the expense of a greater focus
Speaker 1: on the labor market. And I know that sounds like
Speaker 1: a weird thing to say, but if you think that
Speaker 1: what the FED is saying right now is that they're
Speaker 1: going to keep rates very, very low until the labor
Speaker 1: market fully recovers, or recovers even more than really we
Speaker 1: should be digging into the labor market and what full
Speaker 1: employment actually looks like, right, and that is I mean,
Speaker 1: I think there's two questions, or there's a million questions,
Speaker 1: but a as you say, what does quote full employment
Speaker 1: unquote our maximum employment which the FED is established as
Speaker 1: a precondition for rates liftoff, what does that look like?
Speaker 1: That's one thing? And then two, why have we not
Speaker 1: seen faster job market good growth? And that seems like
Speaker 1: a funny question to ask because the labor market growth
Speaker 1: has been incredibly fast since last year. Nonetheless, we do
Speaker 1: seem to be in this weird mismatch where there's lots
Speaker 1: of job openings and lots of people who are not employed,
Speaker 1: and why haven't they Well, what are the reasons that
Speaker 1: people who left the labor four US a year ago
Speaker 1: haven't come back yet? Right? This is the mystery of
Speaker 1: the labor market at the moment. So, on the one hand,
Speaker 1: unemployment is higher than it was before the pandemic. I
Speaker 1: think we're still something like four million jobs short of
Speaker 1: where we were back in February. And if you look at,
Speaker 1: you know, the line of where we would have been
Speaker 1: had the pandemic never actually happened, I think we're about
Speaker 1: seven million jobs short. And Yeah, at the same time,
Speaker 1: you have a lot of companies, and you know, we've
Speaker 1: spoken to at least one of them on the show
Speaker 1: talking about the idea of a labor shortage, that they
Speaker 1: can't get the right workers in the jobs that they
Speaker 1: have open at the moment. And it turns out there's
Speaker 1: really a perfect economic principle to capture this sort of
Speaker 1: tension between job openings and the unemployment rate, and that
Speaker 1: is something called the beverage curve. Yeah, you had a
Speaker 1: great post on this recently. Thank you. Um So, the
Speaker 1: beverage curve is basically the relationship. That's all I wanted
Speaker 1: you to say, Joe, Yeah, I just I just wanted
Speaker 1: to kick it back to you. Thanks. It's the relationship
Speaker 1: between the unemployment rate and the job opening rate. And
Speaker 1: you know, normally, if you look at the beverage curve
Speaker 1: in a usual business cycle, it would be expected to
Speaker 1: move in a sort of counter clockwise loop. So as
Speaker 1: the unemployment rate initially jumps, you would expect the rate
Speaker 1: of job openings to stay very small and then sort
Speaker 1: of gradually recover and start moving to the left as
Speaker 1: the economy healed. Uh, spoiler alert. That is not what
Speaker 1: has happened in this particular business cycle. Instead, we've seen
Speaker 1: something that is normally a curve. You know, the clue
Speaker 1: is in the name, the beverage curve. It's basically morphed
Speaker 1: into an up and down line, meaning that unemployment basically
Speaker 1: isn't moving even as the number of job openings is
Speaker 1: going higher and higher and higher. So something really appears
Speaker 1: to have changed in the labor market here. And I
Speaker 1: am pleased to say we have the perfect person to
Speaker 1: discuss all of this he's actually the author of a
Speaker 1: recent bulletin on the beverage curve on this exact topic,
Speaker 1: we're going to be speaking with Thomas Lubeck. He's a
Speaker 1: senior advisor in the research department at the Richmond fed So, Tom,
Speaker 1: thanks so much for coming on. Okay, thanks so much
Speaker 1: for having me, and thanks for the kind of introduction. Yeah,
Speaker 1: so I was really interested in this paper. Maybe just
Speaker 1: to begin with, you could lay out, you know, what
Speaker 1: is the beverage curve and how would you expect it
Speaker 1: to act in normal times. So I think you've already
Speaker 1: introduced the concept of the beverage curve perfectly, So just
Speaker 1: to restate what you discussed, the beverage curve is the
Speaker 1: relationship between the unemployment rate and the job openings rate.
Speaker 1: So job openings are open positions that businesses um want
Speaker 1: to fill and looking to hire form. And this relationship
Speaker 1: is it's a negative relationship. So when the unemployment rate
Speaker 1: is high during a downturn, job openings are low because well,
Speaker 1: the economy is um not working very well and firms
Speaker 1: are reluctant to hire new workers because of the uncertainty
Speaker 1: of how the economy might improve. But as the economy
Speaker 1: improves um and the downturn turns into an upturn. The
Speaker 1: unemployment rate falls because the job openings are being filled,
Speaker 1: and as the economy improves, firm post more open positions,
Speaker 1: so the job openings rate rises as the unemployment rate falls.
Speaker 1: And this is what we see in every recession, and
Speaker 1: the beverage curve basically describes this relationship. So you can
Speaker 1: think of it as a scattered plot of monthly data
Speaker 1: on the unemployment rate and the job openings rate, and
Speaker 1: they line up nicely around this downward sloping beverage curve. Now,
Speaker 1: what is absolutely striking in the COVID recession and COVID
Speaker 1: recovery is that the beverage curve that we've seen in
Speaker 1: the last twenty years pre COVID has changed dramatically and
Speaker 1: in two ways. It has shifted outward, and it is
Speaker 1: also has become much more steep. So the outward shift
Speaker 1: of the beverage curve um that occurred right after the
Speaker 1: COVID shock hits, so essentially starting in March two thousand,
Speaker 1: twenty April, when the unemployment rate shot up um and
Speaker 1: then declined very very rapidly once the economy worked itself
Speaker 1: through the initial COVID shock. So, but this is connected
Speaker 1: with an outward shift in the beverage curve in the
Speaker 1: following sense. So, at any given unemployment rate in normal times, um,
Speaker 1: you can derive and shop openings rate that is required
Speaker 1: to maintain a certain employment level or unemployment level. Now,
Speaker 1: during the first few months of the COVID shock, the
Speaker 1: unemployment rate stayed high but declined, but so did the
Speaker 1: job openings rate. But the job openings rate was at
Speaker 1: a level that actually we hadn't seen before for this
Speaker 1: given unemployment rate. And this has been quite striking. I wanna,
Speaker 1: obviously why dive into why this relationship is the way
Speaker 1: it is right now. But actually before we get to that,
Speaker 1: I actually have a more straightforward question, which is how
Speaker 1: is the job openings rate derived? Where does that number
Speaker 1: come from? Because with the unemployment rate, you know, you
Speaker 1: imagine you ask a thousand people what percentage of you
Speaker 1: want a job and what don't have one now, etcetera,
Speaker 1: you can come up with one. How does how do
Speaker 1: they determine the job opening trade? So it comes from
Speaker 1: the so called trolls data, So the shop openings and
Speaker 1: Labor Turnover survey that the Borreau of Labor Statistics UM
Speaker 1: conducts and they ask businesses a set of questions where
Speaker 1: they really dig deep into what a job opening is.
Speaker 1: Search job opening is defined, it's a position that is
Speaker 1: immediately ready to be filled, for which there's funding, and
Speaker 1: for which firms actively engage in recruiting efforts. And the
Speaker 1: survey goes out to businesses and they report their shop
Speaker 1: openings to the Borough of Labor Statistics and this then
Speaker 1: ends up as the shop openings right, so at both
Speaker 1: total level, but also I'm relative to UM the labor
Speaker 1: force for instance, So I'm gonna jump to UM. The
Speaker 1: next obvious question that Joe just kind of foreshadowed, but
Speaker 1: what do you think is happening here? So you know,
Speaker 1: you mentioned this is sort of an unprecedented move in
Speaker 1: a relationship that has historically held across many different types
Speaker 1: of recessions in many different countries. What's your theory about
Speaker 1: what's happening? So, as you know, we've seen historically high
Speaker 1: shop openings rates, so UM we hit seven percent in
Speaker 1: truly has come down a little bit from this and
Speaker 1: the shop openings the level is about ten and a
Speaker 1: half millions when the unemployment total unemployment is around seven millions,
Speaker 1: so there's a huge gap, and this is the highest
Speaker 1: gap ever measured. So at this point, I think it
Speaker 1: is fair to say that we don't have one clear
Speaker 1: explanation of why the shop openings rate is so high.
Speaker 1: I think it's a combination of variety of things. We
Speaker 1: have seen even before COVID um relatively high shop openings rates.
Speaker 1: So even before COVID, we heard stories from all reports
Speaker 1: from the business sector about about mismatch if you will,
Speaker 1: that firms find it difficult to hire the right workers
Speaker 1: because they don't have the right skills. Even if they interview,
Speaker 1: they don't show up for um, the beginning of um
Speaker 1: of a job, and all kinds of things that we've
Speaker 1: heard anecdotally from firms. Now, in a sense, the COVID
Speaker 1: shock scaled this problem up, so we know that the
Speaker 1: economy shut down, the positions were still there. Funding for
Speaker 1: these positions was there through various programs, the Payment Action
Speaker 1: Program p p P first and foremost, and aggregate demand
Speaker 1: held up incredibly well during this recession. So all of
Speaker 1: these signs point towards a very strong demand for labor
Speaker 1: that shows up in the job openings rate. Now, the
Speaker 1: question is why is this so outsized? And I think
Speaker 1: one of the answers to this question is that there
Speaker 1: is a sense in amongst businesses that the labor market
Speaker 1: is changing, um that the requirements and workers is changing,
Speaker 1: and that in a way, businesses post open positions preemptively.
Speaker 1: So one aspect of this is the high quid rate.
Speaker 1: So we've seen historically high quid rates. So in the
Speaker 1: quid rates, they also come from the UM Job Openings
Speaker 1: and Labor Turnover Survey and they represent voluntary quids of workers,
Speaker 1: presumably into other positions. So there's a very high turnover
Speaker 1: in the labor market, a lot of churn. You can
Speaker 1: think of it this way. So a quit is connected
Speaker 1: with two shop openings. So if a worker quits to
Speaker 1: take another position, well that fills one shop opening, but
Speaker 1: it creates immediately a new shop opening for the firm
Speaker 1: that was left behind, so to speak. And firms businesses
Speaker 1: may respond to this preemptively and post open positions because
Speaker 1: there is concerned that they may not find the right
Speaker 1: workers or replace them. So this actually sort of gets
Speaker 1: back to my previous question, which is if that's the
Speaker 1: case as you describe, okay, firms are anticipating churn, they're
Speaker 1: anticipating quits. Is the nature of posting job openings? Has
Speaker 1: it changed such that at least part of the mismatch
Speaker 1: or part of the changing shape of the beverage curve
Speaker 1: is not simply a relate ship ship between employers and
Speaker 1: employees changing, but a reflection at least in part of
Speaker 1: the nature of how and when businesses say they're looking
Speaker 1: for an employee, and there is certainly it's a very
Speaker 1: good points so and this is certainly part of the story.
Speaker 1: So a lot of chop search, I would say, the majority,
Speaker 1: but now has no moved online, which also has reduced
Speaker 1: the cost of finding workers, right, And I think this
Speaker 1: is also one of the drivers. And this is actually
Speaker 1: what all economic models would tell us that if the
Speaker 1: cost of UM searching for workers of chop search UM
Speaker 1: is UM is slower than more vacancies, more open positions
Speaker 1: are being posted because it simply is less costly. So
Speaker 1: that makes me wonder, I mean, when I think what
Speaker 1: people look at these curves or when they look at
Speaker 1: these mismatches, and I my sense is that there's a
Speaker 1: lot of reasons, but we'll get into that. We look
Speaker 1: at these mismatches, and we say, oh, maybe it's people
Speaker 1: have all these savings that they're not rushing back to work.
Speaker 1: Maybe it's labor and gil's mismatch. Maybe it's unemployment insurance.
Speaker 1: Maybe it's people lack childcare. Maybe it's people don't want
Speaker 1: to go back into an office for fear of risking COVID.
Speaker 1: At some element, there is also just as change, as
Speaker 1: you point out being able to post a job opening online,
Speaker 1: at least some of it might just be that, all
Speaker 1: all things equal, firms maybe posting more openings today than
Speaker 1: they would have had similar economic condition to say occurred
Speaker 1: in the nine Yes, I think that's a very fair point. So,
Speaker 1: but to be clear, so in a way, but it's
Speaker 1: nice about this beverage curve idea that both the job
Speaker 1: openings rate and the unemployment rate are normalized by by
Speaker 1: the labor force. So essentially you can make this discussion
Speaker 1: about labor force participation, which we know has declined and
Speaker 1: is much below ware and it was a pre COVID,
Speaker 1: but the beverage curve essentially nets out label first participation effects.
Speaker 1: As we observe this relationship sort of breaking down, and
Speaker 1: and maybe it's because of this job creation condition that
Speaker 1: you just described, you know, the idea that employers are
Speaker 1: expecting churn, and so they're posting more and more potential
Speaker 1: jobs on various websites to sort of make up for that.
Speaker 1: But we still we still like come back to this
Speaker 1: problem or this issue of employers and employees struggling to
Speaker 1: match with each other. And I'm wondering, do you see
Speaker 1: that more as a problem of some sort of match
Speaker 1: inefficiency the way we're assigning jobs or hiring people for jobs,
Speaker 1: I should say, is just some are more inefficient than
Speaker 1: it used to be. Or is it that we're seeing
Speaker 1: more competition for workers and people are having to our
Speaker 1: employers are having to compete for a sort of smaller
Speaker 1: potential pool of employees. That's a very good point. I
Speaker 1: think it's both of these factors. So when we start
Speaker 1: back the club to the financial crisis, and this is
Speaker 1: when when I became first interested in the beverage curve.
Speaker 1: So during the financial crisis, the unemployment rate h ten percent,
Speaker 1: stayed around between nine and ten for a while and
Speaker 1: would not come down for a substantial period of time,
Speaker 1: and then it declined rapidly as the economy was working
Speaker 1: through this this unemployment overhang. But at that time we
Speaker 1: were talking a lot about precisely this mismatch phenomenon. So
Speaker 1: the mismatch phenomenon describes the idea that, well, simply speaking,
Speaker 1: that workers and firms don't find each other um on
Speaker 1: the matching market. So this could have geographic reasons. During
Speaker 1: the financial crisis, some regions in the United States were
Speaker 1: hit harder than others, which has an implication for job
Speaker 1: openings and open positions. There was a sexual change away
Speaker 1: from construction manufacturing to healthcare other services. So all of
Speaker 1: these issues combine into mismatch, the idea that workers and
Speaker 1: firms don't find each other. Now we see the same phenomenon,
Speaker 1: if you will, in the beverage curve, in the sense
Speaker 1: that this beverage curve relationship has shifted outward in the
Speaker 1: in the scatter plot sense. So in other words, for
Speaker 1: a given unemployment rate, now many more job openings need
Speaker 1: to be posted to reduce the unemployment rate. So this
Speaker 1: is I would say, prima fasci evidence that yes, there
Speaker 1: is mismatch going on. Now, the question is is this
Speaker 1: the same time type of mismatch that we've seen in
Speaker 1: the Great Recession. And I would argue likely not, because
Speaker 1: COVID hit most of the US in a similar way.
Speaker 1: Now we don't see many regional differences, and we know
Speaker 1: that the service sector was hit much harder by COVID
Speaker 1: than UM the financial services sector, for instance, So there
Speaker 1: may be some aspect to this, But I think overall speaking,
Speaker 1: I think there is an aspect of mismatch going on
Speaker 1: that we don't quite fully understand yet, which is connected
Speaker 1: to this this NEXUSUS Tracy mentioned of workers being reluctant
Speaker 1: to return to work, childcare issues, COVID is still still around,
Speaker 1: and also potentially skills changing skills requirement. So but in
Speaker 1: that sense, I think I would argue that what we've
Speaker 1: seen in the second half of the last decades, so
Speaker 1: between two thousand and fifteen two thousand and twenty, that
Speaker 1: this may have been more of an outlier than was
Speaker 1: acknowledged at that time. So we saw the labor force
Speaker 1: participation going up despite all these demographic changes, so it
Speaker 1: brought in a lot of people into the labor force,
Speaker 1: and this has disappeared through COVID. So in terms of
Speaker 1: labor force participation, I would argue that we are now
Speaker 1: almost back to the pre two thousand fifteen trend based
Speaker 1: on cham with demographics. So long story short, I think
Speaker 1: there's a lot going on in the labor market that
Speaker 1: we don't quite fully understand yet, um simply because we
Speaker 1: are lacking the micro data as of this point. And
Speaker 1: the beverage curve just gives this overall snapshot that something
Speaker 1: is going on in the labor market, a structural change.
Speaker 1: So as you mentioned, I mean, if you look and
Speaker 1: I'm looking right now at b LS dot gov their
Speaker 1: beverage curve, they have a nice chart of it over
Speaker 1: a different time period. And as you mentioned, we did
Speaker 1: see a shift outwards in the beverage curve after the
Speaker 1: Great Financial Crisis, so that was already a bit of
Speaker 1: a change. And then of course this current shape of
Speaker 1: the beverage curve, it's blown out way past that. So
Speaker 1: it's clearly to a very uh high degree. And one
Speaker 1: of the possibilities is the so called mismatch and maybe
Speaker 1: that's geographical. Some people think, uh, this is a very
Speaker 1: popular theory after the GFC that it had to do
Speaker 1: with skills or the lack of skills or mismatch. But
Speaker 1: you know, you mentioned construction and so forth. But on
Speaker 1: the other hand, you know that led to people arguably
Speaker 1: prematurely thinking that we had hit maximum employment or that
Speaker 1: you know, at this point there's nothing more that monetary
Speaker 1: policy can do or fiscal policy because at this point
Speaker 1: we just need to upskill workers, etcetera. Instead, what we
Speaker 1: saw is that the unemployment rate just kept going down.
Speaker 1: It was slow, but I think we got down like
Speaker 1: three point four percent prior to COVID. So what is
Speaker 1: in your view what are in your views some of
Speaker 1: the policy up shots from this s idea of mismarriach
Speaker 1: What what is? What is mismartrich define however you want
Speaker 1: to define it? Tell policymakers. So I think my preferred
Speaker 1: angle in terms of thinking about mismatches is really a
Speaker 1: skill story. So does the workforce has the right scat
Speaker 1: of set sort of skills for the requirements that firms
Speaker 1: in the changing economic environment want to have? And of
Speaker 1: course there's a lot of research shots of policy discussions
Speaker 1: about it, but I think the overall sense is that
Speaker 1: the labor force is lagging behind this in terms of
Speaker 1: um stem skills. Um if you will, no, but do
Speaker 1: your to your point. I think it is also fair
Speaker 1: to say that we work caught by surprise how well
Speaker 1: the labor market performed UM in the second half of
Speaker 1: the last last decade, which brought in a lot of
Speaker 1: people from the from the sidelines. So and in that sense, yes,
Speaker 1: growing economy UM growing. I don't above trend can bring
Speaker 1: in additional workers from the sidelines. But much of this UM,
Speaker 1: I think was driven by an expansion in services, a
Speaker 1: shift away from manufacturing to some extent, healthcare sector expanded.
Speaker 1: So I think there is a structural reason for this.
Speaker 1: Just to play devil's advocate for a second, could you
Speaker 1: flip that slightly and argue that maybe the labor market
Speaker 1: or the economy isn't offering up the type of jobs
Speaker 1: that people want. And you know, I say this after
Speaker 1: the experience of the pandemic, when we had a lot
Speaker 1: of anecdotes about people who simply didn't want to go
Speaker 1: back to their service jobs and maybe didn't have to
Speaker 1: because they had higher, you know, unemployment payouts and maybe
Speaker 1: they were day trading game stop stock in their basements
Speaker 1: or cryptocurrency or whatever and didn't feel as much pressure
Speaker 1: to go back to a job that they didn't like
Speaker 1: or value. Is that something that's potentially on your radar
Speaker 1: here it is because it is connected to UM well,
Speaker 1: the outside option of the workers, if you will to
Speaker 1: use the technical term, or the willingness of workers to
Speaker 1: work in low wage shops, if if you will so,
Speaker 1: and yes, I mean this is definitely something that we
Speaker 1: see in the data already that particularly employment in Lesion
Speaker 1: hospitality in the service sector is lagging much behind the
Speaker 1: financial services UM sector, for for instance, And there there
Speaker 1: are good reasons for this. So all the support programs
Speaker 1: UM during the COVID shock and the recovery UM certainly
Speaker 1: changed the financial position of workers. There was no need
Speaker 1: to look for a shop that may not offer the
Speaker 1: same benefits in the same wage that one could get
Speaker 1: through the government support program. So now this is starting
Speaker 1: to disappear. So to take you up on the devil's
Speaker 1: advocate question, so I think if we want to rest
Speaker 1: out the remainder of the slack and the labor market,
Speaker 1: if you will, so, from the gap between four and
Speaker 1: a half percent where we are now to below four percent,
Speaker 1: I think this is probably where it is coming from.
Speaker 1: But to your point, I think this is certainly an
Speaker 1: issue that is on the radar, namely in terms of
Speaker 1: what is maximum employment in this economy. This seems to
Speaker 1: be the question that the FED. And by the way,
Speaker 1: I think it's interesting people should know. We are recording
Speaker 1: this Monday in November twenty two, and we started recording
Speaker 1: at nine am, right at the moment literally we started
Speaker 1: recording right at the moment that it got officially announced
Speaker 1: that President Biden would be renominating Powell. So, assuming he
Speaker 1: gets confirmed, this is the question that Powell will have
Speaker 1: have to answer. How do you think about this question
Speaker 1: of maximum employment and this idea of we wanted you know,
Speaker 1: as you mentioned in the second half of the tens,
Speaker 1: economists were taken by a surprise by how far how
Speaker 1: strong the labor market could get, how many people it
Speaker 1: could bring in, what it could do for labor force participation,
Speaker 1: how low the unemployment rate could get without triggering meaningful
Speaker 1: increase in inflation, and so forth. So on this question
Speaker 1: of you know, obviously there's some head scratching that's going
Speaker 1: to happen. The FET is obviously reluctant to put any
Speaker 1: sort of number on maximum employment. It kind of feels
Speaker 1: like we'll know when we see a type of thing
Speaker 1: inherently subjective, but from your perspective, and from your research,
Speaker 1: how should the FED be thinking about answering that question
Speaker 1: of what what success on the employment front looks like.
Speaker 1: So the Federati surfact stipulates maximum employment UM as the
Speaker 1: first mend that into FAT has always interpreted this well,
Speaker 1: first a little bit more narrower and then a broader
Speaker 1: goal in terms of an unemployment rate that is sustainable
Speaker 1: without generating additional inflation, and where the labor market and
Speaker 1: the turn the labor market, very loosely speaking, are in equilibrium.
Speaker 1: So when I went to college then graduate school, so
Speaker 1: we were thinking of maximum employment as an unemployment rate
Speaker 1: of five percent, which we dropped to four and a
Speaker 1: half percent in the two thousands. So this unemployment rate
Speaker 1: tied to maximum employment can change, of course, and in
Speaker 1: a sense, this is where where we were surprised that
Speaker 1: the unemployment rate could sustain low inflation rates below four
Speaker 1: percent for a very very long time. And I think
Speaker 1: it's fair to say that this experience of below four
Speaker 1: percent and employment really informs the current discussion right now.
Speaker 1: But I think we've the experience of firm the two
Speaker 1: thousand tents and the recovery from the global financial crisis
Speaker 1: also taught us that the unemployment rate, the headline unemployment rate,
Speaker 1: may not be the single best gauge for what maximum unemployment.
Speaker 1: Maximum employment means. So for one, I mean it is
Speaker 1: a survey based measure, so it is measured reliably as
Speaker 1: much as it can reliably be measured, but it does
Speaker 1: not fully encompass all of the chop search that is
Speaker 1: going on. So, and this is why policymakers in my
Speaker 1: in my reading, have shifted to looking at additional metrics,
Speaker 1: so the employment population ratio, which may be just as
Speaker 1: good on a measure of full employment, then the labor
Speaker 1: force participation rate, as well as O based measures such
Speaker 1: as the drop openings in labor turnover survey. So I
Speaker 1: am inclined to agree with you that we know it
Speaker 1: when we see it when we have maximum employment. So
Speaker 1: at this point I think there's still room to go
Speaker 1: until we hit four pc. No. The flip side of
Speaker 1: this is, of course, our view of maximum employment was
Speaker 1: informed by the fact that the inflation rate um stayed
Speaker 1: well contained above two percent for a long time in
Speaker 1: the two thousand tents. So much of the thinking that
Speaker 1: goes into what is maximum employment is actually related to
Speaker 1: the inflation rate, because we did see historical episodes where um,
Speaker 1: when unemployment was below it's its natural rate, if you will,
Speaker 1: inflation would go up. This didn't happen in the two
Speaker 1: thousand tents. This kind of leads into something that I
Speaker 1: wanted to ask, which is, when would you expect to
Speaker 1: see this competence shan for workers or the sort of
Speaker 1: inefficiency in matching. When would you expect to see that
Speaker 1: feed into wage increases? And is it possible that if
Speaker 1: we've seen a historic break in the beverage curve, you know,
Speaker 1: the relationship between the unemployment rate and the job opening rate,
Speaker 1: then is it possible that maybe we're going to see
Speaker 1: something vastly, wildly different when it comes to wages. So
Speaker 1: at this point, we haven't seen much of wage inflation
Speaker 1: at a level where I think policymakers and economists would
Speaker 1: become uncomfortable. So nominal wages have been going up, but
Speaker 1: not excessively so, and actually to the point that real
Speaker 1: wages have been falling because of the inflation numbers that
Speaker 1: we have been seeing. What we do see is some
Speaker 1: higher wage increases in some sectors um so lesion, hospitality.
Speaker 1: There we do see higher wage growth, higher nominal wage growth,
Speaker 1: And we also see the chop switchers, which brings me
Speaker 1: back to UM the quid rate and the historically elevated
Speaker 1: level of quid rate. So chop switchers have seen high
Speaker 1: wage increases, which presumably is one of the reasons why
Speaker 1: they switch shops. So but at the same time, we
Speaker 1: know that the wage data are um lagging behind in
Speaker 1: the sense that so many wages are determined one year ahead,
Speaker 1: and now many companies are having wage discussions at the
Speaker 1: end of the year. So what is the compensation picture
Speaker 1: going to look like for two thousand twenty two given
Speaker 1: the high levels of inflation we have had. So I
Speaker 1: think going into the next year, UM, I am starting
Speaker 1: to become a list little bit more nervous that we
Speaker 1: may see much higher nominal wage inflation numbers. Let me
Speaker 1: I want to go back to something important and again, uh,
Speaker 1: this mismatch idea, because ultimately that really is what the
Speaker 1: chart is showing us. On some level, the things are
Speaker 1: very there is some uh, some big change to what
Speaker 1: extent is these things you know you mentioned for example,
Speaker 1: and you know numerous policy makers talk about say skills
Speaker 1: and stem skills and tech skills and coding skills in
Speaker 1: particular is always being in short supply, and there's probably
Speaker 1: not a major business in the entire country that doesn't
Speaker 1: have numerous job openings for technical skills. But one thing
Speaker 1: that we did see at the end of the tens
Speaker 1: in addition to bring some people back into the labor forces,
Speaker 1: more anecdotal stories about skills training where the company itself
Speaker 1: would pay for skills training or fund skills training, or
Speaker 1: also where the companies would hire people who are previously
Speaker 1: incarcerated and so looking beyond the normal pool of applicants
Speaker 1: to bring in people back into the workforce. Should theory
Speaker 1: has a very sort of positive long term effect to
Speaker 1: what extent should these mismatches essentially be or can they
Speaker 1: essentially be dealt with by the market that if you know,
Speaker 1: FED recognized can recognize the persistence of mismatches, but ultimately,
Speaker 1: if there are whether it's skills or geography, these are
Speaker 1: things that employers and employees will ultimately solve if there
Speaker 1: is a price opportunity there. Yeah, I mean I very
Speaker 1: much agree with you on this point. I mean, in
Speaker 1: the end, these mismatches will be dealt with by um
Speaker 1: changes and employment relationships and how workers and their employers
Speaker 1: reorient their relationship. I mean, I think the prime example
Speaker 1: for this is um working from home on a hybrid
Speaker 1: working environment, which decouples the location of the business from
Speaker 1: the location of the workers. So so the geographic mismatch
Speaker 1: part of the mismach story I think would probably largely
Speaker 1: go where because I could, you know, as we're having
Speaker 1: this interview right now, I mean, I'm sitting here in Richmond,
Speaker 1: UM and you're in other locations all over the world,
Speaker 1: So that part, I think can be mitigated. So one thing,
Speaker 1: so with respect to the US labor markets, So one
Speaker 1: thing that struck me and my background is in Germany
Speaker 1: and growing up in Germany, is the is the lack
Speaker 1: of apprenticeship programs and on the job training programs, which
Speaker 1: is very formalized UM and very institutional liced in in
Speaker 1: in Germany. And you don't see this to the same extent,
Speaker 1: actually to a much lower extent here in the United States.
Speaker 1: So and I think this is one of those labor
Speaker 1: market policies that UM I think policymakers should try to
Speaker 1: pay more attention too. I'm under drop training, um upskilling
Speaker 1: of the worker force and essentially worker training. But I
Speaker 1: think the broader issue is can we already discern structural
Speaker 1: changes in the labor market that would completely decouple us
Speaker 1: from you know, previous working arrangements. And I think the
Speaker 1: first signs are there. Um. So, I think the COVID
Speaker 1: um shock has accelerated this work towards more of the
Speaker 1: worker as an entrepreneur rather than as a salaried wage employee. So, Thomas,
Speaker 1: I'm I'm aware that you've been publishing quite a lot
Speaker 1: at the Richmond FED and I mean you've sort of
Speaker 1: taken on the very very big questions of the economic
Speaker 1: experience of the pandemic, including how to actually model um
Speaker 1: COVID nineteen and things like that. But what's been the
Speaker 1: most interesting work that you've undertaken over the past year
Speaker 1: or two, or perhaps the most surprising thing that you've
Speaker 1: seen other than the beverage curve of course, Um, yeah,
Speaker 1: thanks for your kind words. I mean I would have
Speaker 1: answered the beverage curve because because this is this is
Speaker 1: truly striking. I mean I started working on this during
Speaker 1: the financial crisis, and at that time, the shifts in
Speaker 1: the beverage curve seemed completely out of this, out of
Speaker 1: line with historical record and then I just plotted late
Speaker 1: last year the beverage curve and whoa, suddenly that the
Speaker 1: change in the beverage curve was even much more dramatic.
Speaker 1: But in terms of other other wor work. UM. So
Speaker 1: one aspect that that occupies my thinking a lot is UM. Well,
Speaker 1: what we call our star or the natural real rate
Speaker 1: of interest, which basically anchors almost all of our policy discussions.
Speaker 1: And what we can say is that the natural real
Speaker 1: rate of interest, So when all is said and done,
Speaker 1: the level of the real interest rate that the economy
Speaker 1: would naturally gravitate towards has declined over the last twenty
Speaker 1: thirty forty years. The precise level of where our star
Speaker 1: is UM, Yeah, there's much uncertainty about this, and this
Speaker 1: fundamentally informs the policy question. So in the long run,
Speaker 1: where should a natural normal level of UM policy accommodation
Speaker 1: or the federal funds rate? But I think we're far
Speaker 1: away from UM having a good answer to this at
Speaker 1: this point. What about just this sort of you you know,
Speaker 1: usefulness of these indicators are star neutral rate, real rate?
Speaker 1: You know this is prior to COVID and I always
Speaker 1: forget which hero was either I want to say chair.
Speaker 1: Powell gave a speech sort of questioning whether any of this,
Speaker 1: any of these numbers, what the neutral rate is, that
Speaker 1: this is really knowable in real time? And I took
Speaker 1: it to me and that maybe there's just some question
Speaker 1: about like to what degree should we be using these
Speaker 1: to build models that inform policy in real time? How
Speaker 1: do you feel about the confidence that economists should have
Speaker 1: in being able to derive a number like our star
Speaker 1: and actually use it to make a decision from one
Speaker 1: meeting to the next. Um, Yeah, thanks for the questions.
Speaker 1: So I mean, as I said, I mean there's much
Speaker 1: uncertainty about um, the levels of these natural rates, be
Speaker 1: it you still in a sort of unemployment bepat our star. Ultimately,
Speaker 1: think all of the models that we have in mind,
Speaker 1: and I'm not just thinking about, you know, the academic
Speaker 1: models that academic economists built, but also the implicit models
Speaker 1: that policymakers have in their mind. They ultimately come down
Speaker 1: to the question, what is the long run equilibrium outcome
Speaker 1: in the economy where we are at maximum employment, where
Speaker 1: we fit our inflation target, and what the long run
Speaker 1: interest rate should be. So and and once you take
Speaker 1: this issue on board, this immediately leads you to the question,
Speaker 1: what can we figure out what our star or you
Speaker 1: star UM is so and and and to be fair,
Speaker 1: these are fundamentally unobservable, so we have to use some
Speaker 1: statistical methods technical tricks to tease them out from the data.
Speaker 1: But I think that they are informative. Nevertheless, so even
Speaker 1: if it is just that the level that our star
Speaker 1: is much lower than it was in the ninety eighties,
Speaker 1: which puts us into a different policy environment. So just
Speaker 1: on that note, I have a slightly I guess, strange question.
Speaker 1: But you know, one of the things that has been
Speaker 1: repeated in many of our conversations on all lots over
Speaker 1: the past year or so is the idea that a
Speaker 1: lot of economic principles that we seem to have taken
Speaker 1: for granted, actually no one seems to know how they
Speaker 1: really work. So, you know, something weird is going on
Speaker 1: with the labor market, something weird is going on with inflation.
Speaker 1: I think our star. You know, people have been questioning
Speaker 1: UM the natural rate of interest idea for a while now.
Speaker 1: I know you've done some academic work on the output gap,
Speaker 1: UM not being particularly useful for monetary policy. Is this
Speaker 1: sort of a moment of doubt for economic researchers, or
Speaker 1: does it encourage you to, you know, examine these issues
Speaker 1: even more and seek out answers. It feels almost like
Speaker 1: a sort of existential crisis, or at least if you
Speaker 1: read some of the commentary around higher than expected c
Speaker 1: p i UM from a week or two ago, it
Speaker 1: feels like existential crisis for the FAT at least. Yeah,
Speaker 1: I would not put it in such standard terms. That's fair.
Speaker 1: I just I gotta ask. Yeah, so in the sense
Speaker 1: that I think we do have a much better understanding
Speaker 1: of how the economy works UM compared to forty years ago.
Speaker 1: But I think what we've become more aware is that
Speaker 1: there's much more uncertainty about these unobservable variables. And and
Speaker 1: and again, going back to the COVID shock, we were
Speaker 1: hit by an completely unprecedented UM shocked that shut down
Speaker 1: the economy the economy is worldwide to an unprecedented level.
Speaker 1: And we've recovered from this incredibly quickly in terms of
Speaker 1: the macroeconomic data. And yes, while the beverage curve may
Speaker 1: look different from what we would have expected had had
Speaker 1: COVID not happened, UM, it still follows the same underlying principles.
Speaker 1: So when times are good or improving, the unemployment rate falls,
Speaker 1: chop openings go up. But what the beverage curve tells
Speaker 1: us in that sense it is it is you know,
Speaker 1: a visualization device of the state of the economy. Is yes,
Speaker 1: but there's something else going on now. We don't know
Speaker 1: exactly what is going on, so more research will be
Speaker 1: poured into it. So when I presented the beverage curve
Speaker 1: to our internal audience and outside audiences, I introduced it
Speaker 1: as um chop security for labor economists. So more research
Speaker 1: needs to be done. But I think overall, our economic
Speaker 1: models and our economic thinking actually had held up pretty well,
Speaker 1: um during the COVID shock. Thomas, it's been great speaking
Speaker 1: with you, and uh again plug to the beverage curve paper,
Speaker 1: which you can find on the Richmond Fed website. Thank
Speaker 1: you so much. Okay, thank you so much. It's a
Speaker 1: pleasure talking to you. Thanks Thomas. That was great, So Joe,
Speaker 1: I thought that was really interesting, and again I think, um,
Speaker 1: you know all of well, the two major issues inflation
Speaker 1: and the labor market are of course tied together, but
Speaker 1: it does feel like the focus of the majority of
Speaker 1: attention has been on the inflation question, um, and people
Speaker 1: are only really talking about the labor market insofar as
Speaker 1: it might lead to wage increases. So I thought it
Speaker 1: was quite um, it was quite good to dig into,
Speaker 1: you know, the beverage curve and a particularly wonky corner
Speaker 1: of economic research. Yeah, it really is. If anyone who
Speaker 1: just pulls it up and goes to the BLS beverage
Speaker 1: curved chart, you just instantly see how wild. I mean,
Speaker 1: look like COVID data is going to leave this imprint
Speaker 1: on all the church that we look at for like
Speaker 1: decades because it's just so weird, whether it's the surge,
Speaker 1: the raw surge in the unemployment rate, the pure speed
Speaker 1: of the bounce back, the collapse, everything is just so weird.
Speaker 1: But you look at this and it's obviously very different.
Speaker 1: And I do think that, like, I don't think there's
Speaker 1: a totally satisfactory answer yet to why do we seem
Speaker 1: to have this very robust demand for labor and yet
Speaker 1: we continue to have, um, this big whole you know,
Speaker 1: at least five or six million people if you were
Speaker 1: on the employed than they were a pre crisis. It's
Speaker 1: a pretty it still remains a pretty big puzzle. Yeah,
Speaker 1: and I like to Thomas's description of it as a
Speaker 1: full employment plan for economists, but I mean on that
Speaker 1: on that wider point though, I mean the idea that
Speaker 1: maybe maybe we know more than we did before about
Speaker 1: the way the economy works, but we sort of don't
Speaker 1: have a good way of measuring those unknown economic variables
Speaker 1: like maximum employment and um our star. I think that's
Speaker 1: quite maybe that's the way to think about it, Like
Speaker 1: it's not just that no one knows how anything works anymore,
Speaker 1: which would be quite frightening, but it's becoming increasingly hard
Speaker 1: to um to gauge those particular ideas. Maybe, you know what,
Speaker 1: while we're here, I imagine some people maybe this is
Speaker 1: no while we're here, And I imagine maybe some listeners
Speaker 1: who listen to this episode may work at the FED
Speaker 1: or something like that, because we had a guest at
Speaker 1: the Richmond Fed. So I have a request to those listeners, Tracy,
Speaker 1: you don't like the Beige Book, do you ever? Uh? So,
Speaker 1: they it's like the regional survey and they always and
Speaker 1: um our guests just mentioned it. It's like business leaders said, uh,
Speaker 1: you know, we're seeing labor market Titan is having trouble
Speaker 1: hiring this. I want a Beige Book for workers anecdotes
Speaker 1: of the labor market, but from the from the worker perspective,
Speaker 1: just asking people questions. Okay, we get the actual data,
Speaker 1: but talking about what was your experience? What was your
Speaker 1: experience applying for a job that you're ostensibly qualified for?
Speaker 1: Did companies actually call you back? Was the description actually
Speaker 1: how it was. I think employers are going to get
Speaker 1: to sort of like give their anecdotal takes that aren't
Speaker 1: really based in data on like oh, you know, like
Speaker 1: we can't find the people or the workers aren't showing
Speaker 1: up after we offer them the job. I think we
Speaker 1: deserve a Beijing Book from the workers perspective, and I
Speaker 1: think that might help us answer some of these questions stuff.
Speaker 1: Anyone who's listening. Maybe we could get some funding for that.
Speaker 1: I think that's a great idea. And I mean I
Speaker 1: want to know whether or not there is a wealth effect, Yeah,
Speaker 1: greater wealth effects going on from like stock trading from crypto. Yeah.
Speaker 1: This would be the kind of thing where like instead
Speaker 1: of just having to speculate, I mean, anecdotes can only
Speaker 1: go if you go so far. And I think we
Speaker 1: have to be careful. And one reason we have to
Speaker 1: be careful about anecdotes is because you know, employers started
Speaker 1: calling the labor market tight like fifteen, then we had
Speaker 1: like five more years of unemployment, right, so you have
Speaker 1: to be careful of anecdotes. But all of these things
Speaker 1: like oh, are you taking the time off from work
Speaker 1: because you want to trade crypto or something like, let's
Speaker 1: ask people in a systematic manner and have it be
Speaker 1: something that we record rather than just sort of like
Speaker 1: speculate on totally. And I also I also want to
Speaker 1: see how people react to or what they say about,
Speaker 1: like the new sort of UM hiring websites and things
Speaker 1: like that, because I gather it's been it's been a
Speaker 1: while since I've applied to a job on on one
Speaker 1: of those um so, thank you Bloomberg. But like my
Speaker 1: impression of them is that you kind of have to
Speaker 1: take all these boxes and it can be really really
Speaker 1: frustrating if like one aspect of your resume is slightly
Speaker 1: out of line with whatever the request is from the
Speaker 1: potential employer or the monster dot conform or whatever. And
Speaker 1: I suspect that's also frustrating some of these matching efforts. Yeah,
Speaker 1: totally that again, and that speaks to Thomas's point, which
Speaker 1: is like, Okay, like these websites have made it a
Speaker 1: lot easier to post job openings, their behavioral effects on
Speaker 1: the employment side where it's like listing is maybe different
Speaker 1: than listings in you know or something like that. And
Speaker 1: so again it feels like there's a lot of ambiguity
Speaker 1: in all of this, and I yes, interviewing someone interviewing
Speaker 1: more people about their experience on these sites. Do they
Speaker 1: actually get callbacks for jobs that they're qualified for that
Speaker 1: they continually see posted? I think would be very useful.
Speaker 1: So hopefully as someone listening, call us up, name it
Speaker 1: the odd odd Survey, great idea, Boka, the Odd Book,
Speaker 1: the Odd Book that is at ring to it all? Right, Um,
Speaker 1: let's leave in there. Let's leave it there. This has
Speaker 1: been another episode of the Odds Podcast. I'm Tracy Alloway.
Speaker 1: You can follow me on Twitter at Tracy Alloway and
Speaker 1: I'm Joe Why Isn't All? You can follow me on
Speaker 1: Twitter at the Stalwart. Follow our producer on Twitter, Laura Carlson.
Speaker 1: She's at Laura M. Carlson. Follow the Bloomberg head of podcast,
Speaker 1: Francesco Levi at Francesca Today and check out all of
Speaker 1: our podcasts on Twitter under the handle at podcasts. Thanks
Speaker 1: for listening.