Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast.
Speaker 1: I'm Joe Wisenthal and I'm Tracy Halloway. Tracy, do you
Speaker 1: remember I think it was probably like last June or
Speaker 1: last July, like over a year ago. Now, I think
Speaker 1: we're talking to Vitour Constantio, and I think you asked
Speaker 1: like one of the most important questions, like at the
Speaker 1: time and maybe still like that we've had on this podcast.
Speaker 1: I struggle to remember things that happened a month ago,
Speaker 1: um let alone twelve months ago. Everything is sort of
Speaker 1: blurring into this one long stretch. But um, yeah, that's fair.
Speaker 1: What did I ask, Well, you asked him whether economists
Speaker 1: or anyone these days had a cogent theory of inflation.
Speaker 1: Do you remember that? And at the time, like you know,
Speaker 1: there wasn't much inflation going on. I think we're probably
Speaker 1: still in something resembling deflation or disinflation not long after
Speaker 1: the initial shock. But now, you know, fast forward to
Speaker 1: August and official inflation measurements are pretty elevated relative to
Speaker 1: recent history. And I think that question and I think
Speaker 1: it's basic into us. No, although I don't want to
Speaker 1: quote him on that, that question of like whether economists
Speaker 1: understand inflation has probably never been is extremely top of
Speaker 1: mind these days totally, And I mean, I think I
Speaker 1: would agree with you on the no part. But of
Speaker 1: course there's a really big irony right now, which is
Speaker 1: right when the FED changed to the flexible average inflation
Speaker 1: targeting regime, after you know, more than a decade of
Speaker 1: undershooting the two percent inflation target. As soon as they
Speaker 1: did that, now we seem to have possibly um transitory inflation,
Speaker 1: but like certainly more than they would have expected a
Speaker 1: year ago. And and yeah, like it just illustrates that
Speaker 1: no one seems to have a very good handle on
Speaker 1: what exactly causes price increases or decreases. Right, So, even
Speaker 1: prior to the new framework, there's always been this idea that, okay,
Speaker 1: we'll use and this came up in our recent episode
Speaker 1: of Neil Cary of the Minneapolis Fed, that okay, we'll
Speaker 1: use inflation as our gauge, as our speed limit to
Speaker 1: know when we say hit maximum employment or full employment.
Speaker 1: That's true under the old FED, that's true under the
Speaker 1: current Fed. Now we have elevated inflation, but it's like, oh,
Speaker 1: this doesn't really count because it's transitory and it's related
Speaker 1: to shipping, and we know that doesn't have anything to
Speaker 1: do with employment, but there's always probably gonna be a
Speaker 1: story to tell which sort of calls to mind whether
Speaker 1: these are sort of like useful things. Of course, no
Speaker 1: one predicted this sort of like very few people accurately
Speaker 1: predicted the timing and the degree of elevation of the
Speaker 1: current inflation. So I think we're still sort of like
Speaker 1: back to square one. We don't know how long this
Speaker 1: will last. I don't even think there's a agreement of
Speaker 1: like what really would be transitory, of what would be worrisome,
Speaker 1: of what would spur the FED to act sooner than
Speaker 1: maybe markets effect, And so I think, um, that question
Speaker 1: that you asked Constancio several months ago remains really the
Speaker 1: sort of the key thing right now. Yeah, alright, So
Speaker 1: today we're going to be talking about inflation and really
Speaker 1: what it is and how it's measured, and whether it's
Speaker 1: even possible to forecast it accurately or how we should
Speaker 1: be thinking about it right now, And we have literally
Speaker 1: the perfect guest. We're gonna be speaking with Omar Sharif.
Speaker 1: He's currently uh the founder and president of a new
Speaker 1: shop that he's set up called appropriately enough for this
Speaker 1: episode Inflation Insights, but he has a long track record.
Speaker 1: He's prior to that a by side strategist at the
Speaker 1: asset management for Millennium. He's been an economist at various
Speaker 1: shops including a Soak, Gen, RBS, and so forth. So
Speaker 1: we're going to talk about whether there is a a
Speaker 1: cogent theory of ation and how to think about it
Speaker 1: right now. So Amara, thank you so much for joining us.
Speaker 1: Thank you having me. Well, what's your answer to Tracy's question?
Speaker 1: Do do economists have a useful or cogent theory of
Speaker 1: inflation that that works in practice? I think the short
Speaker 1: answer to that is, now, you know, all you have
Speaker 1: to do is sort of look at the fact that
Speaker 1: there's a massive academic literature that's basically just devoted to
Speaker 1: forecasting inflation and you know, coming up with variou types
Speaker 1: of models to figure out what the inflation process is.
Speaker 1: And there's an equally large literature talking about why we're
Speaker 1: so bad and forecasting inflation. So I don't know that
Speaker 1: there's a coaching theory. It seems to sort of change
Speaker 1: based on where we are kind of in the cycle,
Speaker 1: and there's different ways of approaching you know, how you
Speaker 1: want to forecast inflation. They're sort of the top down
Speaker 1: modeling approach that a lot of academics use. And I
Speaker 1: think sort of what's more kind of in favor and
Speaker 1: out something that I started doing, you know, well over
Speaker 1: ten years ago, which was kind of more of the
Speaker 1: bottom up approach UM to forecasting inflation. But ultimately, I
Speaker 1: don't know that there's a coaching theory that really can
Speaker 1: explain the inflation process over you know, let's say the
Speaker 1: last several decades. UM. You sort of try to understand
Speaker 1: it based on where you are, I think in the cycle.
Speaker 1: So what is it that makes inflation UM so difficult
Speaker 1: to grasp? Is it the idea of UM that you
Speaker 1: just pointed out that it basically depends on where you
Speaker 1: are in the cycle, and so your framework or the
Speaker 1: dynamics that are underpinning prices are are kind of changing constantly. Yeah,
Speaker 1: I think that's that's exactly what it is. It's just
Speaker 1: it's a constantly evolving process UM. And you know, one
Speaker 1: way to think about it is that if we're trying
Speaker 1: to forecast it, and let's say we just want to
Speaker 1: think about where it's going to go over the course
Speaker 1: of the next year. You know, there are all sorts
Speaker 1: of approaches you can take in terms of modeling, but
Speaker 1: some of the simplest approaches actually worked the which is
Speaker 1: simply to say that, you know, if I want to
Speaker 1: forecast inflation over the course of the next four quarters,
Speaker 1: I might just use the average of the last four quarters,
Speaker 1: and most often than not, that will actually perform better
Speaker 1: than trying to come up with some models that you know,
Speaker 1: Phillips curve type models for example, because inflation persistence is
Speaker 1: actually a pretty big key I think in trying to
Speaker 1: understand the dynamics with an inflation um and that persistence
Speaker 1: is is it varies across time and and that is
Speaker 1: one of the keys really and trying to think about
Speaker 1: it is you know, if I if I were to
Speaker 1: tell you that the core CPI has been between one
Speaker 1: and a half to two and a half percent for
Speaker 1: the last twenty years, those types of models that are
Speaker 1: what we call nightive models work quite well because if
Speaker 1: inflation has been around that for the last twenty years,
Speaker 1: pretty good odds that you know for the next year
Speaker 1: will be somewhere in that range. Uh. But that persistence
Speaker 1: varies in the short run. It varies, you know, even
Speaker 1: within a decade, and so trying to capture that kind
Speaker 1: of time varying nature of inflation for sistance is really
Speaker 1: what everyone's striving to do. And that's why certain models perform,
Speaker 1: you know, really well in certain decades and they completely
Speaker 1: collapse in the next decade. Well, so this gets to
Speaker 1: something that we um talked about in the beginning that
Speaker 1: whether we're talking about the FEDS new framework, and we
Speaker 1: should point out recording this auguste by the time people
Speaker 1: listen to this, it will have been the one year
Speaker 1: anniversary of Jackson Hole where they laid out and so
Speaker 1: we make it some new speeches on this, but where
Speaker 1: they laid out the new framework last year. So whether
Speaker 1: it's the new framework, the Flexible Average Inflation Targeting Framework,
Speaker 1: or the old framework, I'm not even sure what that was,
Speaker 1: both are premised on this sort of like Phillips curve,
Speaker 1: thinking that there is some inherent trade off, that there
Speaker 1: is some inherent speed limit or maximum employment, and we'll
Speaker 1: know we'll get there not by some number of employment level,
Speaker 1: but by inflation readings. And if the nature of inflation
Speaker 1: sort of changes all the time, maybe decade by decade
Speaker 1: or some other time interval. Is that going to be
Speaker 1: a folly for the FED to think that inflation or like,
Speaker 1: is there any reason to think that Philip's curve thinking
Speaker 1: or Philips curve framework will be a useful guide post
Speaker 1: for the FED? It's hard to say. I think that
Speaker 1: the thing is that the Feds, you know, their time
Speaker 1: horizons really if you think about it is essentially about
Speaker 1: three years, right. We we get about three years of
Speaker 1: forecast from the FRET FED within the SCP, and so
Speaker 1: you know, if you're thinking about inflation changing over ten
Speaker 1: years or fifteen years, that's less of an issue for
Speaker 1: the FED. So that can the Phillips curve work accurately
Speaker 1: for them? And then a three to five year horizon sure,
Speaker 1: And and so you know there are times that it
Speaker 1: has actually performed relatively well. So for example, kind of
Speaker 1: the late seventies when you ran aggressions sort of these
Speaker 1: you know, using output on employment gaps, Phillips curves actually
Speaker 1: turned out to to be kind of useful. But you know,
Speaker 1: the FED will always tell you that they have a
Speaker 1: suite of models that they look at. They will look
Speaker 1: at everything from core inflation to you know, trim means
Speaker 1: and medium c P I S. So I don't know
Speaker 1: that they're as reliant on the Phillips curve as they
Speaker 1: used to be, and I think they've kind of spelled
Speaker 1: that out for us over the course of you know,
Speaker 1: the last year. It's not clear that the Philip's curve
Speaker 1: really works, and I think Powell's kind of ditched that approach,
Speaker 1: and it's you know, it's kind of back to the
Speaker 1: old adage of saying, you know, we'll we'll know it
Speaker 1: when we see it, and we'll kind of wait for
Speaker 1: the whites of the eyes of inflation before we decide
Speaker 1: to move on on policy. MHM. So you mentioned all
Speaker 1: the different inflation stats or figures that the FED can
Speaker 1: look at, and of course there are, I mean, there's
Speaker 1: probably dozens of different measures of inflation um that are
Speaker 1: based on hundreds, if not thousands, of different baskets. I
Speaker 1: guess my question is how much does your interpretation or
Speaker 1: does one's interpretation or thinking around inflation actually depend on
Speaker 1: the measure that they're looking at, And how do people
Speaker 1: go about choosing which measure is most relevant m in
Speaker 1: a particular time. Well, I think, you know, we there's
Speaker 1: basically two main measures. Is the way that I really
Speaker 1: look at it. You know, there's obviously the c p
Speaker 1: I and then there's the there's the Feens preferred measure
Speaker 1: that the core PC. Are there other measures that you
Speaker 1: can look at, absolutely, but typically they tend to be
Speaker 1: kind of variations on those two. So you know, the
Speaker 1: trim mean and and the median c p I and
Speaker 1: the median PC are just variations and different ways to
Speaker 1: kind of approach those same baskets. And you know, maybe
Speaker 1: you're taking some of the volatility out from the top
Speaker 1: and the bottom, but you're really sticking with those two
Speaker 1: main baskets, which one you want to really focus on?
Speaker 1: You know, I think it depends. Um, if you're the Fed,
Speaker 1: they've already made that decision for us. You know, it
Speaker 1: kind of makes it easy. Um, we're gonna be focusing
Speaker 1: on the core PC if you're thinking about monetary policy.
Speaker 1: But obviously for the markets, what matters is the c
Speaker 1: p I and what matters is the CPI because that's
Speaker 1: what it goes into pricing tips. So it sort of
Speaker 1: depends on who you are. You know, if you're the A,
Speaker 1: obviously you're going to be concerned and obviously the two
Speaker 1: are related about you know, roughly something like seventies seventy
Speaker 1: of the core PC is actually just passed through from
Speaker 1: the course cp I. So those to me are really
Speaker 1: the at least in the US, are the two main
Speaker 1: metrics that you want to focus on. Well, let me
Speaker 1: ask you. You know, if economists, you know, don't have
Speaker 1: a great track record of forecasting inflation, they don't have
Speaker 1: great models um for it. So we have these things
Speaker 1: that Okay, if I talked to Tracy, I say, let's
Speaker 1: talk about inflation, and we want to know where inflation is.
Speaker 1: We'll look up some indicries on the terminal, might look
Speaker 1: up to c p I, course, CPI, core PC, etcetera.
Speaker 1: Are the concepts of inflation indices themselves cogent? In other words,
Speaker 1: we're put we're aggregating all these different prices and trying
Speaker 1: to arrive at one number. And right now I think
Speaker 1: the number, you know, cp I, it's a little bit
Speaker 1: over five percent, maybe five point four percent, I don't
Speaker 1: remember exactly. That's down from a recent high. But is
Speaker 1: there some true information contained in that headline number or
Speaker 1: is it just a number that gets spit out when
Speaker 1: you go through the work of adding up all of
Speaker 1: the thousands of prices that go into it. Yeah. Look,
Speaker 1: I mean at the end of the day, Um, all
Speaker 1: of this stuff is is a construct, right, and and
Speaker 1: there's certain things in there which I think do a
Speaker 1: great job of reflecting reality. And if we think about energy,
Speaker 1: that's a very simple one. You know, everybody knows what
Speaker 1: they're paying at the pumper for gasoline, and within the
Speaker 1: c p I, you know you're you're capturing these movements
Speaker 1: and energy prices, those are pretty straightforward. The same thing
Speaker 1: is true when you think about you know, car prices.
Speaker 1: These are items that are pretty easy, easy to capture,
Speaker 1: and you know they do a pretty good job sort
Speaker 1: of representing reality. Where you start to get we start
Speaker 1: to lose people, frankly, is when you kind of get
Speaker 1: into some of the sort of the price index theory
Speaker 1: and sort of the number theory where you start to
Speaker 1: talk about imputations and you know how to handle missing
Speaker 1: prices and you know, owner's equivalent RAN is a great example.
Speaker 1: There's been a debate about this for you know, pretty
Speaker 1: much the last forty fifty years about how should we
Speaker 1: really capture house prices? What is the role in an index?
Speaker 1: And the CPI is very clear, we don't want to
Speaker 1: We don't want anything to do with house prices. Why,
Speaker 1: because we consider it to be an asset. We're trying
Speaker 1: to measure what you pay out of pocket as a consumer,
Speaker 1: And so these are the kinds of debates that I think,
Speaker 1: you know, when you're paying, when you're seeing you know,
Speaker 1: home prices go up, you care less about what satistations
Speaker 1: are arguing about when it comes to you know, imputation
Speaker 1: and so on. You just know that if you want
Speaker 1: to buy a house, you've got to pay more than
Speaker 1: maybe you did last year. And so you tend to
Speaker 1: kind of lose the public when you're getting into those
Speaker 1: sorts of weeds in the inflation data. But I think
Speaker 1: for the most part, these indexes do a pretty good
Speaker 1: job of capturing what's going on in terms of the
Speaker 1: pricing environment around US. UM. Can we spend a little
Speaker 1: bit of time on owners equivalent rent or o E ER,
Speaker 1: because as you mentioned, this is a source of big controversy.
Speaker 1: Anyone looking at the housing market, you know, over the
Speaker 1: past few decades will say that house prices have gone up,
Speaker 1: rents have gone up, um, certainly relative to one's income.
Speaker 1: So why is it that it seems difficult for the
Speaker 1: inflation indices to capture that, is it just is it
Speaker 1: just that they've made a conscious decision not to include
Speaker 1: it or to include it in this very specific way,
Speaker 1: or is it something else? So we actually used to
Speaker 1: include it, um so so prior to the CPI, for example,
Speaker 1: um they took what was called the asset approach, and
Speaker 1: so that included, uh, you know, the price of a house,
Speaker 1: included everything related to your mortgage, interest costs, your property taxes,
Speaker 1: and so on. And even though from about the late
Speaker 1: fifties to about three they they did it in this manner,
Speaker 1: they knew from really the early sixties that this was
Speaker 1: not the right approach and this was just a conceptual
Speaker 1: issue with the cp I. All this had to do
Speaker 1: was was to say, what we're really doing here is
Speaker 1: we're capturing an investment piece of the house, and we're
Speaker 1: also we really want to capture is just the consumption
Speaker 1: aspect of it. And so they knew for you know,
Speaker 1: twenty plus years um that even though they were doing
Speaker 1: in this manner, this was not what they wanted to
Speaker 1: actually be doing in terms of the CPI. And finally
Speaker 1: around the late seventies they started doing more detailed work
Speaker 1: on how to get around, you know, eliminating the investment
Speaker 1: piece of it and focusing just on sort of the
Speaker 1: shelter part of it UM. And they made that change
Speaker 1: in three and you know, another part of the reason
Speaker 1: for making that change was, you know, as you recall,
Speaker 1: interest rates were kind of all over the map in
Speaker 1: the late seventies and the early eighties, and that introduced
Speaker 1: a tremendous amount of volatility in the CPI to the
Speaker 1: point where it sort of became, I don't want to
Speaker 1: say useless, but so volatile that it was really hard
Speaker 1: to get any kind of sense of what was going
Speaker 1: on with underlying inflation. And you had everything tied to it,
Speaker 1: you know, cost of living adjustments UM, wage negotiations were
Speaker 1: tied to it. And one year it was up you know,
Speaker 1: ten eleven, the next year might be back down to three.
Speaker 1: So it was sort of losing its significance, and so
Speaker 1: this decision was made to work on trying to implement
Speaker 1: this owner's equivalent rent index, which finally came into playe UM.
Speaker 1: So that is a consensual issue. It's it's just underlies
Speaker 1: sort of what the CPI is really meant to do.
Speaker 1: The second part of this, I think, is that you know,
Speaker 1: when you look at for example, Zello core logic and
Speaker 1: you're seeing rents up, where you're seeing case Shiller saying
Speaker 1: house prices are one of the you don't see it
Speaker 1: in the CPI indexes. To that magnitude is because it
Speaker 1: is there's just very little turnover in the CPI sample.
Speaker 1: So every month, only about ten to fift pent the
Speaker 1: sample actually represents new renters, and so what you see
Speaker 1: in list prices um you know that might be moving
Speaker 1: very quickly when market conditions are changing, that shows up
Speaker 1: over the course of about twelve to eighteen months in
Speaker 1: the CPI because you just don't have that same kind
Speaker 1: of turnover that you see in these indexes that look
Speaker 1: at just for example, listed rents. So part of its
Speaker 1: conceptual issue, but the other part is just the methodology
Speaker 1: and the way that the sample works. You're just never
Speaker 1: going to have the magnitude of the changes that you
Speaker 1: see in all these sort of you know, private private
Speaker 1: sector indexes. So like if we're talking about something like
Speaker 1: buying apples or buying milk or buying gasoline, everybody buys
Speaker 1: those things every day or every week all the time
Speaker 1: with rant, not only do very few people actually signed
Speaker 1: a new lease every every month, but also many of
Speaker 1: the new leases that people actually sign or with their
Speaker 1: current landlord, and so they probably uh don't get the
Speaker 1: full market rent because those are those don't adjust as fast.
Speaker 1: And so you know, looking at this, Okay, this is
Speaker 1: one of the big questions right now. We know that
Speaker 1: headline inflation has come down a little bit. Used cars
Speaker 1: seem to have stopped going up. That's a big factor.
Speaker 1: But everyone's like, okay, ore is coming, ohr is coming.
Speaker 1: We see the market rent some places like Zillo and
Speaker 1: so forth, those are shooting up. Why don't you give
Speaker 1: us what you know? Sort of you just explained the theory.
Speaker 1: What are you actually seeing in practice when you look
Speaker 1: at the data and how much is rent and other
Speaker 1: attempts that the CPI or that these in disease used
Speaker 1: to capture shelter. How much upward pressure are they going
Speaker 1: to put on the measures in the months and years ahead. Yeah,
Speaker 1: so we you know, we have seen both of these measures,
Speaker 1: both rent and now we are actually bottom out over
Speaker 1: the course of the last several months, and you're starting
Speaker 1: to see price increases. Is in the major metro areas,
Speaker 1: and so even you know, places like New York, Los Angeles, Chicago,
Speaker 1: San Francisco, which are still down pretty sharply year over year,
Speaker 1: it looks like on a monthly basis they've they've finally
Speaker 1: kind of begun to stabilize a little bit. And you know,
Speaker 1: it's important to kind of understand when you talk about
Speaker 1: the c p I that a lot of these rent indicries,
Speaker 1: what really matters is where these you know, so called
Speaker 1: Class A cities, which are you know, the big ones
Speaker 1: with populations over two and a half million, what they're
Speaker 1: doing because the weights on these cities um is incredibly large.
Speaker 1: So if you looked at just three of them, New York,
Speaker 1: Los Angeles, Chicago, that is of the entire rent inducts
Speaker 1: from just those three metro areas. So where they go
Speaker 1: matters quite a lot for the overall index. But we
Speaker 1: are starting to see these places stabilize and move up.
Speaker 1: But I think there's something to keep in mind here
Speaker 1: about you know, this whole story about shelters commenting and
Speaker 1: O we are is going to go up and so on.
Speaker 1: Number One, people again are looking at these private market
Speaker 1: rent data and they're seeing seven percent eight percent growth.
Speaker 1: We've never seen anything like that in the c p I.
Speaker 1: I'm hard pressed to think, you know, we'll see anything
Speaker 1: like that over Let's say that the course of the
Speaker 1: next year, um will rent go up, yes, but you know,
Speaker 1: don't forget before the pandemic we were running around three
Speaker 1: and a half percent. We're about two and a half
Speaker 1: percent right now, and rent and we are combined. So
Speaker 1: you know, even if you move up a full percentage
Speaker 1: point over the course of the next year, you'll be
Speaker 1: kind of right back where you started in early two
Speaker 1: thousand and twenty. But let's assume for a moment that
Speaker 1: you know, we move up to four and a half percent,
Speaker 1: so another two percentage points from where we are today.
Speaker 1: What that basically means is you're looking at overall core
Speaker 1: inflation rising by roughly about another eighty basis points. You know,
Speaker 1: rents got about a weight, you go up two percentage points.
Speaker 1: That's about eighty bits on on the core cp I.
Speaker 1: Now that sounds like a lot, but you mentioned used
Speaker 1: cars earlier. They're adding over a hundred and thirty basis
Speaker 1: points to the core CPI right now in the year.
Speaker 1: Your basis that it's almost certainly going to come off.
Speaker 1: So even if we are goes up and rent goes up,
Speaker 1: you know, a couple of percentage points over the course
Speaker 1: of let's say, the next year eighteen months, that's almost
Speaker 1: certainly going to be offset to a great extent by
Speaker 1: you know, a lot of these things that we're seeing
Speaker 1: now that we you know, continue to think of transitory.
Speaker 1: That's going to upset a lot of the upward pressure
Speaker 1: you're gonna get from from shelter, I think, over the
Speaker 1: course of the next eighteen months. So it's kind of
Speaker 1: important to keep that in perspective because again, four and
Speaker 1: a half percent is really where we've peaked in the past,
Speaker 1: and even if we get a bit higher than that,
Speaker 1: you know, year a year on use cars is not
Speaker 1: going to stick. You know, that's going to potentially more
Speaker 1: than offset what we see out of shelter. So since
Speaker 1: we're talking about the current environment in terms of inflation,
Speaker 1: maybe it's worth asking, you know, when you hear the
Speaker 1: term transitory inflation, what does it actually mean to you?
Speaker 1: Because we've had um at least one feed official come
Speaker 1: on and talk about how they sort of regret using
Speaker 1: the term transitory inflation, and other people have said you know,
Speaker 1: maybe it would have been better if the FED was
Speaker 1: talking about narrow inflation versus more broader inflation, or um
Speaker 1: manageable inflation versus unmanageable inflation. So what does that term
Speaker 1: actually mean to you? Transitory inflation? So to me, it's
Speaker 1: just about, you know, how long that rate of change
Speaker 1: continues to sort of accelerate. So you know, use cards
Speaker 1: going up yar over a year from zero basically, which
Speaker 1: is where they were pre pandemic too. Now the question
Speaker 1: is how long can we sort of not just how
Speaker 1: long will that persists, but can it continually go up
Speaker 1: at sort of the rates we've seen over over the
Speaker 1: last six months. That's kind of the way I think
Speaker 1: about it. That's I think the way that share Powell
Speaker 1: has sort of explained inflation as well, is it's this
Speaker 1: process of can we see continually this rate of growth
Speaker 1: sort of accelerate year after year after year, And that's
Speaker 1: what we're sort of looking at for these components, but
Speaker 1: obviously much more sort of in the short term. But
Speaker 1: I do think there's a couple of ways to think
Speaker 1: about this transitory question. And if you're trying to figure
Speaker 1: out is is the inflation I'm saying that transitory or
Speaker 1: is it gonna continue will spread out to other components.
Speaker 1: There's I think a few ways to kind of think
Speaker 1: about that um. One, for example, is just simply look
Speaker 1: at the dispersion within the cp I, so you know
Speaker 1: what share of components are seeing price increases today versus
Speaker 1: price decreases, And also you know what does that look
Speaker 1: like on a weighted average basis versus history. So you
Speaker 1: could have a lot of components, for example, rising, but
Speaker 1: if combined the weight of those components is not that
Speaker 1: that high, it really may not matter for kind of
Speaker 1: the longer term inflation picture. Another thing that I like
Speaker 1: to look at is momentum within the core cp I.
Speaker 1: So here what I want to look at is, you know,
Speaker 1: what is the share of components that are either accelerating
Speaker 1: or de cel a rating within the corese c p I.
Speaker 1: And here you can sort of you know, normally you
Speaker 1: would look at, for example, the twelve month change in
Speaker 1: the year of a year rate of specific components and
Speaker 1: see if that's picking up steam or losing steam, and
Speaker 1: that once you wait those those sort of changes gives
Speaker 1: you a sense of kind of the underlying momentum that's
Speaker 1: really sort of driving the you know, the aggregate core number.
Speaker 1: And then one final thing, which I think is pretty
Speaker 1: important right now, especially since we're sort of comparing everything
Speaker 1: to kind of the pre pandemic time, is you've got
Speaker 1: to kind of keep a close eye on where the
Speaker 1: price level is today for certain components versus not just
Speaker 1: where it was let's say in but where would you
Speaker 1: expect it to be today, you know, given the pre
Speaker 1: pandemic trend. So are we overshooting that or are we
Speaker 1: undershooting that? And I think a good example here is
Speaker 1: something like air fares. Right there's still about ten percent
Speaker 1: above excuse me below their fable, but they're more like
Speaker 1: pent below where you would expect them to be if
Speaker 1: they had just continued on their pre pandemic trend. So
Speaker 1: that kind of tells you, you know, things normalize. That's
Speaker 1: an area where you might start to see some upward
Speaker 1: pressure come, as in airfares. And on the flip side,
Speaker 1: hotel rates are running about eight percent above where you'd
Speaker 1: expect them to be right now, and so that's the
Speaker 1: place where you might get a little bit of get back.
Speaker 1: And if you don't, then then you you know, potentially
Speaker 1: start to get a little bit concerned that this might
Speaker 1: stick a bit longer than you would have expected. Big picture,
Speaker 1: I mean, we you know, we we fixate on a
Speaker 1: few of these so called reopening categories, and used cars
Speaker 1: we know the story there, and rental cars we know
Speaker 1: the story there. And with airplanes and hotels we understand
Speaker 1: some of this also. You know, we talk a lot
Speaker 1: about certain goods related that relate to shipping and logistics,
Speaker 1: which we know is supply chains jammed. When you look
Speaker 1: at some of these measures, like you do the breadth
Speaker 1: of the inflation, general inflation momentum and so forth, what
Speaker 1: are you seeing right now? Is their process happening. It
Speaker 1: appears to be broadening out, and momentum is gathering steam
Speaker 1: or or is it something else? You know, let's let's
Speaker 1: we go back to its kind of the FATS preferred
Speaker 1: measure of the PC. The San Francisco FAT actually does
Speaker 1: a nice job keeping track of some of these dispersion
Speaker 1: measures and so on. And what you look at now
Speaker 1: is that about roughly, you know, if you sort of
Speaker 1: look at all the components in the PC, about eight
Speaker 1: percent of them currently are showing price games. And you
Speaker 1: know that sounds like a pretty big number. That most
Speaker 1: of the most of you know, the components arising, but
Speaker 1: in fact it's it's only a couple of percentage points
Speaker 1: more than what we were seeing sort of you know,
Speaker 1: pre pandemic. So it doesn't it's not clear to me
Speaker 1: that we've seen a big broadening out of of price pressures.
Speaker 1: We've seen, as you mentioned, just really concentrated increases in
Speaker 1: pressures in some components. So I'm still very much in
Speaker 1: the camp that you know, as we sort of get
Speaker 1: through the spring of two, we're essentially going to see
Speaker 1: a lot of slow down I think in the core
Speaker 1: and much more I think in the core PC for example.
Speaker 1: Like I wouldn't be surprised if by the middle of
Speaker 1: twenty two we're talking about core PC being closer to
Speaker 1: around two whereas the core CPI potentially is is still
Speaker 1: you know, punching along and around two and a half percent.
Speaker 1: And one thing I just want to mention is, you know,
Speaker 1: you talked a little bit about some of these macro
Speaker 1: stories with you know, chip shortages and so on. You know,
Speaker 1: these are important, right we we we we like to
Speaker 1: have narratives to try to explain something. But one of
Speaker 1: the things with when you are really in the weeds
Speaker 1: of this inflation data. Is that as important as those
Speaker 1: narratives are to kind of understand the picture, most people
Speaker 1: don't really pay attention to the fact that a lot
Speaker 1: of price movements that you tend to see have nothing
Speaker 1: to do with the macro story or a micro story.
Speaker 1: It's literally just about the way the methodology works in
Speaker 1: the index. It's about the seasonality of the index. You know,
Speaker 1: it's about changes in the way we actually compute and
Speaker 1: construct the data, and it has less to do with
Speaker 1: you know, these broader stories that we're trying to explain.
Speaker 1: We're trying to use explain the inflation number. Sometimes it's
Speaker 1: just about understanding how this thing is built and sort
Speaker 1: of really getting into the weeds of, you know, understanding
Speaker 1: the parts that sort of make up the sum. And
Speaker 1: that good example is motor vehicle insurance. This is an
Speaker 1: index that you know a lot of people don't pay
Speaker 1: attention to. Last month was down about two and a
Speaker 1: half percent, you know, a little bit less than a
Speaker 1: full tenth off the core CPI, which is a lot
Speaker 1: when the core is around point three only and it
Speaker 1: has nothing to do with a big story. You know,
Speaker 1: UM insurers are not cutting your your rates. It just
Speaker 1: has to do with the way the seasonality is working
Speaker 1: out this year for this particular index, and it's going
Speaker 1: to be a very similar story when the next point
Speaker 1: comes out insurance motor vehicle insurance should be down around
Speaker 1: two and a half three percent. Again, do you just
Speaker 1: to the seasonal factor. So, no big story, but if
Speaker 1: you understand the seasonality and understand how this thing is constructed,
Speaker 1: it gives you an edge in terms of forecasting. Uh,
Speaker 1: this number just to play Devil's advocate for a second.
Speaker 1: So um, when it comes to those macro stories that
Speaker 1: you just mentioned, one of the things that Joe and
Speaker 1: I have been discussing a lot over the past year
Speaker 1: or so is this idea of the bullwidth effect and
Speaker 1: that you end up seeing a massive amount of volatility
Speaker 1: in orders and stockpiling because of the uncertain environment. So
Speaker 1: you know, you get a shortage one month and then
Speaker 1: everyone ramps up their orders because they don't want to
Speaker 1: be caught short again, and suddenly they're oversupplied and you
Speaker 1: get these sort of intense um price increases and decreases.
Speaker 1: So I guess my question is, like, is that a
Speaker 1: risk to inflation Actually proving transitory. Is that something that
Speaker 1: could start to come into play. Yeah, that's a that's
Speaker 1: a good point. It's it's possible. But I think you know,
Speaker 1: where you would see that obviously would be a ramping
Speaker 1: up in in the inventory numbers for some of the
Speaker 1: you know, the places where we're seeing where we are
Speaker 1: seeing shortages now, where we are seeing orders pick up steam,
Speaker 1: you know, I mean, honestly, to some extent to your point,
Speaker 1: we're kind of seeing this. We use cars now, so
Speaker 1: wholesale prices have been coming off the last couple of months,
Speaker 1: and again where you really want to look as on
Speaker 1: the inventory side, so when you look at use cars,
Speaker 1: when you look at the wholesale piece of that, we're
Speaker 1: only about a couple of days below a normal level
Speaker 1: of inventory for wholesale used vehicles, and on the retail
Speaker 1: side is actually pretty similar as well. So you know,
Speaker 1: we were catching up on the inventory side and getting
Speaker 1: to something that actually really resembles normality in the wholesale
Speaker 1: used vehicle market. And you know, low and Behold you
Speaker 1: were down about three or four and wholesale prices over
Speaker 1: the last couple of months. So I think, sort of
Speaker 1: to your point, I think where we are starting to
Speaker 1: see some of that happen in some of these components.
Speaker 1: So I'm thinking, you know, I kind of want to
Speaker 1: zoom out a little bit and talk about the relationship
Speaker 1: between some of your work and you know, how investors
Speaker 1: use it. You've been on the cell side, You've been
Speaker 1: on the BI side, now you have your own shop.
Speaker 1: As Tracy and I have talked about the past episodes,
Speaker 1: inflation gets people going. It gets consumers going emotionally, but
Speaker 1: it also gets traders and investors going, and people are
Speaker 1: very strong views about the FED and so forth. I'm
Speaker 1: curious about like receptiveness to your way of thinking, because
Speaker 1: you obviously clearly take this bottoms up approach where it
Speaker 1: looked not only at individual categories, but individual category construction.
Speaker 1: How do like, you know, traders investors who want to
Speaker 1: use this, are they receptive to it? Are they do
Speaker 1: they get you know, are they angry at the ideas like, oh,
Speaker 1: you know, this is all the FED money printing, etcetera.
Speaker 1: Which is kind of seems to be the opposite of
Speaker 1: how you think about these questions. What do you talk
Speaker 1: a little bit more about your work and how how
Speaker 1: investors use it? I think, but the most part, people
Speaker 1: are incredibly receptive to it. I mean, when I started
Speaker 1: doing this, um, I don't know of many shops or
Speaker 1: many individuals who were taking this kind of bottom approach
Speaker 1: and sort of doing you know, detailed analysis of the
Speaker 1: components and index construction and so on. And I think
Speaker 1: people are especially periods like this, they want to understand
Speaker 1: what is moving the print, Is it a one off print,
Speaker 1: is there you know, was there something driving it this
Speaker 1: month that could be more persistent? And how do I
Speaker 1: think about that for the following month. Because if you're
Speaker 1: an investor and you're you know, in the tips market,
Speaker 1: or you're you're, you know, interested in the fixings, one
Speaker 1: month obviously influences everything, and so you really want to
Speaker 1: understand what is what's going on kind of beneath the
Speaker 1: hood of the data. So I think people are incredibly receptive.
Speaker 1: And you know, in terms of getting pushed back from
Speaker 1: folks who are like, hey, this is just the FEDS
Speaker 1: money printing, there's there's always element of that, but I
Speaker 1: find that those are the folks who were, you know,
Speaker 1: potentially removed from actually trading or managing money. Um, you know,
Speaker 1: the folks who are managing the money. They are into
Speaker 1: the weeds of it. And you know, it's funny because,
Speaker 1: as I mentioned, when I was on the cell side,
Speaker 1: when I did this, very few people did it. Now,
Speaker 1: being on the buy side of the last two years,
Speaker 1: I was a consumer of all the cell side research,
Speaker 1: so I got all the research from the banks on
Speaker 1: inflation and how they forecast it and so on. And
Speaker 1: it's it's funny to me because now a lot of
Speaker 1: people take this bottom of approach on on the cell
Speaker 1: side as well, some more so than others, but it's
Speaker 1: kind of the way everyone on the cell side is
Speaker 1: doing it now because I think there's a value add
Speaker 1: in understanding the weeds of you know, what's driving shelter
Speaker 1: inflation and what's driving apparel prices and so on, because
Speaker 1: it really does give you a window into where the
Speaker 1: kind of headline numbers going and importantly, is it going
Speaker 1: to stick or is it just you know, kind of
Speaker 1: a one off. So in a bottom up approach like
Speaker 1: the one, you just describe what role, if any, does
Speaker 1: monetary policy actually play. And you know, I'm thinking of
Speaker 1: that famous Milton Friedman quote about inflation is always in
Speaker 1: everywhere a monetary phenomenon like is that incorporated anywhere in
Speaker 1: the type of work that you do, or is it
Speaker 1: irrelevant the way when you're when you're doing the sort
Speaker 1: of approach, it is almost by design, it's a very
Speaker 1: short term approach. You know, I'm not going to sit
Speaker 1: here and say, hey, I'm in a forecast inflation for
Speaker 1: the next five years, um doing this approach because it's
Speaker 1: it's just not designed to do anything like that. When
Speaker 1: you're doing something like this, it's much more looking at
Speaker 1: let's say the twelve next, twelve to eighteen months UM.
Speaker 1: And really, if you think about policy in the lags,
Speaker 1: you know, to some extent, you know, maybe it's impacting, uh,
Speaker 1: some of these components in that time frame, let's say,
Speaker 1: especially housing, but in the twelve eighteen months, it doesn't
Speaker 1: play that big of a role. And honestly, if you
Speaker 1: even think about the way that these indexes work. The
Speaker 1: San Francisco Found a couple of years ago had a
Speaker 1: great paper where they applied kind of the Phillips curve
Speaker 1: methodology to individual components of the PC and what they
Speaker 1: found was a roughly sixty percent of these components or
Speaker 1: what they would term a cyclical and essentially, you know,
Speaker 1: policy can't really impact them. So stuff like medical care,
Speaker 1: for example, whatever you're doing with policy is probably not
Speaker 1: really going to impact physicians prices um or you know,
Speaker 1: hospital prices, and so six the index just doesn't really
Speaker 1: react to policy. And even that does, you know, it's
Speaker 1: going to be a bit of time. That's twelve to
Speaker 1: eighteen months, And this approach is pretty narrowly focused on
Speaker 1: kind of you know, just that kind of window. So
Speaker 1: I would say that if it does, it's kind of
Speaker 1: hard to really it's hard to really incorporated into this
Speaker 1: sort of a framework when you're thinking about forecasting. Should
Speaker 1: we sort of established that there isn't that much of
Speaker 1: a sort of cogent theory of an inflation from sort
Speaker 1: of like pure macro standpoint. What is your pitch then?
Speaker 1: Is it just that you're going to help explain what
Speaker 1: you a little bit more about your pitch to potential
Speaker 1: clients to help them understand what's going on. Like what
Speaker 1: is it that you say it's like, okay, you do
Speaker 1: at your new shop appropriately enough called inflation insights? What
Speaker 1: is like the basic sales pitch of what you can
Speaker 1: bring to the table. Sure, so you know, for for me,
Speaker 1: my target audience, is mostly um, you know institutional clients, right, Um,
Speaker 1: the folks who actually are are trading tips and who
Speaker 1: are trading to fix things. Um, So in that respect
Speaker 1: that the pitch is really sort of uh. I would
Speaker 1: say there's kind of three main elements. One is the
Speaker 1: actual forecast. You know, for me, luckily, I've been doing
Speaker 1: this long enough where I've got a reputation, I've got
Speaker 1: a hit track record in history that I can present
Speaker 1: to clients and say, look what I'm trying to build.
Speaker 1: Here is the best in class forecasts, Um that you
Speaker 1: will get on the c P I S N s
Speaker 1: A Index, which is what matters for tips, and kind
Speaker 1: of here's my my history of that, and that's you know,
Speaker 1: the goal for is to have that be the best
Speaker 1: in class moving forward. The second is just the detailed
Speaker 1: analysis making sure that everyone understands what's going on. And
Speaker 1: the timeliness I think also matters quite a lot. So
Speaker 1: you know, the stuff that I put out typically will
Speaker 1: be well in advance of anything you're gonna get from
Speaker 1: the south side, and it will give you an opportunity. Um,
Speaker 1: you know, if you agree with my view, for example,
Speaker 1: that it will give you opportunity to actually traded in
Speaker 1: the market before the CPI comes out, whereas right now
Speaker 1: a lot of seal side research, you know, it's coming
Speaker 1: out forty eight hours before the number prints, and that's
Speaker 1: really not much of an edge, but it's the detail analysis,
Speaker 1: the timeliness, and then finally, you know, I would say
Speaker 1: I'm probably on the horn with the BLS, if not daily,
Speaker 1: you know, at least once a week. Even though I've
Speaker 1: been doing this for a long time. It is honestly
Speaker 1: just a constant kind of learning process. I mean, there's
Speaker 1: there's about two eleven indicators that go into the cp I.
Speaker 1: There's over seven thousand basic item in area indexes that
Speaker 1: you could look at, and so it's just kind of
Speaker 1: a constant learning process. And it's you know, for me,
Speaker 1: I've always had this likely good rapport with with the
Speaker 1: folks there, who I think are incredibly helpful in terms
Speaker 1: of learning about the components and so on, And that's
Speaker 1: sort of the kind of I think, you know, the
Speaker 1: kind of knowledge you're not really going to be able
Speaker 1: to get most other places. So now I have to
Speaker 1: ask how specific you can actually get when it comes
Speaker 1: to the inflation baskets. So this is a really weird question.
Speaker 1: But I went on like a massive tangent a couple
Speaker 1: of weeks ago because there was a restaurant in North
Speaker 1: Carolina that that a guy was quoted as saying that
Speaker 1: he was spending two hundred dollars more per week in
Speaker 1: mayonnaise because of inflation, and so of course everyone started
Speaker 1: calculating like, well, how much mayonnaise is this restaurant actually
Speaker 1: buying based on CPI, And then I started going on
Speaker 1: Bloomberg and looking at the components and c p I,
Speaker 1: and it turns out mayonnaise comes under the salad dressing
Speaker 1: um and spreads basket. And so I guess I'm just curious, like,
Speaker 1: how in the weeds do you go? And can you
Speaker 1: give me like a quick, uh quick read on what's
Speaker 1: going on with with salad dressings? Yeah, so I don't
Speaker 1: know if I can pull up the salad dressing forecast
Speaker 1: just now, but you know I would stick. When you
Speaker 1: get to kind of that level, Um, you have to
Speaker 1: make choices, right, I mean, like I said, there's there's
Speaker 1: over seven thousand I had to marry indexes. Uh, there's
Speaker 1: over two sort of broad components in the c p I.
Speaker 1: Most likely when you can kind of get something like food,
Speaker 1: which has dozens of indexes, you kind of have to
Speaker 1: make a choice in terms of how far are you
Speaker 1: going to drill down. So I might follow all of these,
Speaker 1: you know, I've got them in my spreadsheets and so on,
Speaker 1: but when it kind of comes to forecasting, you're probably
Speaker 1: gonna want to stick, for example, with looking at the
Speaker 1: broader too, which is the food at home index, which
Speaker 1: kind of encompasses the entire grocery basket and the food
Speaker 1: away from home with restaurant prices and there with within
Speaker 1: food at home. You know, you would if you want
Speaker 1: to drill down, you would break break it down into
Speaker 1: some of these components, so cereals, you know, the various
Speaker 1: types of meats, eggs, food, vegetables and so on. But
Speaker 1: it doesn't mean that you're necessarily going to go in
Speaker 1: and you know, forecast uncooked beef steaks for example, right,
Speaker 1: I mean you could, you could, but it would take
Speaker 1: you a month or longer to just come up with
Speaker 1: a simple forecast. I mean I used to spend probably
Speaker 1: two days just doing the food forecast. So you have
Speaker 1: to kind of make some choices about the timeliness of
Speaker 1: your forecast and how uh, into the weeds you're going
Speaker 1: to be able to go in order to produce something
Speaker 1: that's actually you know, actionable. So this reminds me of
Speaker 1: something I wanted to ask you. Um So, when I
Speaker 1: was in my Mayo analysis adventure, one of the things
Speaker 1: I was trying to do because I couldn't find an
Speaker 1: inflation pick up in the official CPI basket, but I
Speaker 1: tried to look at um an Amazon tracking website to
Speaker 1: see if prices had gone up on Amazon. So I'm curious,
Speaker 1: do you ever look at alternate data in order to
Speaker 1: make your forecast? Yea, So there's a couple of things,
Speaker 1: UM I do for certain components that where I will
Speaker 1: look at you know, uh, non BLS data sets to
Speaker 1: try to get a sense of what's going on. And
Speaker 1: one of those, for example, is just airfares. Air Fares
Speaker 1: is only worth you know, a little bit less on
Speaker 1: one percent of the core, but it's it's basically been
Speaker 1: the bane of my existence and forecasting for the last
Speaker 1: you know, fifteen years, because it's incredibly convoluted the way
Speaker 1: that it's done. But um, you know, at the end
Speaker 1: of the day, what they're really pricing is you know,
Speaker 1: they're going to the websites of you know, Delta American
Speaker 1: Southwest so on UM, and they're pricing flights out, so
Speaker 1: you can try and come up with an index yourself
Speaker 1: where you just you know, go onto these websites and
Speaker 1: try to say, hey, what's the flight, um, you know,
Speaker 1: from your to l A going to cost me or
Speaker 1: new or to Miami or whatever. And so you can
Speaker 1: sort of look at those sorts of data to try
Speaker 1: to help you forecast, um the airfare sundas. You can
Speaker 1: look at you know, Black Book and JD Power and
Speaker 1: so on to get a sense of what use card
Speaker 1: prices might do. And then there's of course the Billion
Speaker 1: Prices project there. I think you just have to be
Speaker 1: a little bit careful because a lot of what they
Speaker 1: are capturing is much more UM has much more to
Speaker 1: do with goods prices and much less to do with
Speaker 1: services prices. But for goods prices, you know, that does
Speaker 1: a pretty decent job from time to time. So there
Speaker 1: are other things that you can certainly look at gas Buddy,
Speaker 1: which is actually now being used directly in the c
Speaker 1: p I UM. So they've gone from having you know,
Speaker 1: one thousand quotes on gasoline each month to having millions
Speaker 1: of quotes because essentially they've crowdsourced the data is something
Speaker 1: else that you can also look at. So there definitely
Speaker 1: are alternative data sets that you can try to to
Speaker 1: work into into your forecast. I just want to say, Tracy,
Speaker 1: you you stole the question right. That was literally the
Speaker 1: next thing I was gonna ask you. No, no, no,
Speaker 1: that was great, You asked it. Great. But I just
Speaker 1: weirdly continue to be perfect blade length. You know, I'm
Speaker 1: bigger picture, or I guess sort of like medium term.
Speaker 1: You know, you present, as you said a little bit ago,
Speaker 1: when you look at some of the broader metrics, you
Speaker 1: don't necessarily see a sustained upward move in inflation that
Speaker 1: there isn't necessarily this kind of momentum that even if
Speaker 1: rent were to go above um grow at a pace
Speaker 1: that's well above historical averages, they might be offset. What
Speaker 1: would make you worried or what would make you think, Okay,
Speaker 1: this is going to be a type of elevated inflation
Speaker 1: that persists. And maybe monetary policy doesn't really affect inflation
Speaker 1: at least in the medium term, but inflation could certainly
Speaker 1: affect monetary policy if the FED gets spooped or so forth.
Speaker 1: So I assume that's important information for investors. What would
Speaker 1: you be looking for saying through the rest of this
Speaker 1: year or early next year to say, oh, this is
Speaker 1: going to be higher and more persistent than I would
Speaker 1: have gived. Yeah. So one of the things that's you know,
Speaker 1: kind of come up in the last print or two, um,
Speaker 1: that I'm going to be keeping a pretty close eye
Speaker 1: on going forward, is this, you know, idea of whether
Speaker 1: some of the pickup we've seen recently in wages begins
Speaker 1: to pass through more persistently into the inflation data. And
Speaker 1: you know, we saw this actually last month in the
Speaker 1: food away from Home index. Um. You know, there was
Speaker 1: a pretty big increase in what are called you know,
Speaker 1: limited service restaurants so fast food, and it was for
Speaker 1: for that index was was a huge huge jump. And
Speaker 1: we know that wages are going up in lena leisure
Speaker 1: and hospitality for example, and so the idea that some
Speaker 1: of this might be feeding through, for example, into hotel
Speaker 1: rates or limited service restaurants and things like that, those
Speaker 1: are areas where potentially you start to say, okay, you know,
Speaker 1: we've keep seeing wages move up at these sorts of
Speaker 1: rates if this is what, if this really is that
Speaker 1: kind of a path through, then this is potentially something
Speaker 1: that is more persistent that will last into next year.
Speaker 1: And it's not going to be something you know, sort
Speaker 1: of a one off shock like let's say, you know,
Speaker 1: oil price shock or something of that nature. You know,
Speaker 1: this is something that is potentially more persistent. And I
Speaker 1: have to say, I think even with something like use cars,
Speaker 1: we know they're starting to come off, I am a
Speaker 1: little bit wary of just kind of having a repeat
Speaker 1: of what we had, which is, you know, last summer
Speaker 1: we had a huge jumping used car prices, it completely
Speaker 1: tailed off, they declined throughout the fall and winter until
Speaker 1: we had another huge burst over the last several months.
Speaker 1: And whether that's you know, mostly a function of sort
Speaker 1: of the demand side or the supplies I'm definitely more
Speaker 1: on the supply side part of that story. But you know,
Speaker 1: it's we still have kind of to deal with this
Speaker 1: idea of the delta variant and what's what is that
Speaker 1: going to do to activity going forward? What's that going
Speaker 1: to do for the demand for use cars and new
Speaker 1: vehicles you know later into this year and into next year.
Speaker 1: I don't know that anyone's got a good answer for that.
Speaker 1: But that is something that I think kind of remains
Speaker 1: or upward risk on the in the inflation story. Is
Speaker 1: you know, we sort of see a repeat of some
Speaker 1: of these um some of these upward pressures from from
Speaker 1: you know, something like the delta variant going forward, but
Speaker 1: more persistently, it would definitely be some of this wage
Speaker 1: passed through into some of these components that I mentioned earlier.
Speaker 1: So on a related note, is there you know, in
Speaker 1: your very long career analyzing inflation, is there any particular
Speaker 1: component that has just remained an absolute mystery to you?
Speaker 1: And that is sort of like I guess, immune to
Speaker 1: the bottom up analytical approach, like something that really flaw
Speaker 1: makes you Yeah, I think apparel. Apparel is the is
Speaker 1: one where in you know, years of doing this, I've
Speaker 1: literally just never found anything that works at forecasting apparel
Speaker 1: other than you know, one of the approaches I mentioned earlier,
Speaker 1: which is just this naive approach of saying, Okay, you know,
Speaker 1: looking at these things on an unadjusted basis, you get
Speaker 1: a sense for a sort of seasonal patterns, and uh,
Speaker 1: you know, let's say apparel every March tends to decline
Speaker 1: by about two tents. You're going to be probably um,
Speaker 1: doing a decent job if you put in you know,
Speaker 1: a drop of two tents, because there's very little to
Speaker 1: go on when it comes to two apparel prices. You know,
Speaker 1: I've tried using everything from import prices, um two you know,
Speaker 1: different data sets, retail sales and so on, and there's
Speaker 1: just nothing that is gives you a good lead into
Speaker 1: what apparel is doing. And that's been you know, that's
Speaker 1: been another tough one to do. UM, not as difficult
Speaker 1: as as air fares. Air fares at least you know
Speaker 1: what they're doing, UM, you just can't replicate it exactly.
Speaker 1: But Apparel's yeah, apparel is one that has just really
Speaker 1: you sort of just have to lick the patterns and
Speaker 1: and honestly, it's it's it's much more about kind of
Speaker 1: looking at these patterns and thinking about, you know, to
Speaker 1: what extent you're following the same trajectory as you did
Speaker 1: in the past for something like apparel. So one of
Speaker 1: the sources of like constant controversy and you know CPI inflation,
Speaker 1: truth thors and so forth always like to talk about
Speaker 1: it is like the so called hedonic adjustments, and they're
Speaker 1: always like, oh, this is not you know, we all
Speaker 1: we've all heard the conspiracy theories right now. For example, though,
Speaker 1: if if everyone is complaining about the service they get
Speaker 1: at restaurants because of the so called worker shortage, people
Speaker 1: are complaining about the service they get at hotels, and
Speaker 1: we know, for example that hotels in some cases have
Speaker 1: degraded service or not picking up towels is often or
Speaker 1: whatever it is. Are these sorts of things captured to
Speaker 1: the BLS. I mean, as you said, you talk to
Speaker 1: them all the time and you're trying to learn their approach.
Speaker 1: Are they trying to capture these types of things such
Speaker 1: that maybe the experience at a restaurant or a hotel
Speaker 1: isn't what it was in no, so hedonic adjustments are
Speaker 1: just applied um two goods. So yeah, and so you know,
Speaker 1: if if I'm sure you kind of remember this whole
Speaker 1: you know, wireless thing in Martial two seventeen. Yeah, so
Speaker 1: things like that is where you see hedonics. Apparel is
Speaker 1: one where you see hedonics um and it so it
Speaker 1: really is just limited to goods. And also when you
Speaker 1: think about hedonic adjustments, for the most part, I think
Speaker 1: it's about only about four or five percent of the
Speaker 1: c p I is actually subject to those sorts of
Speaker 1: kind of quality adjustments. Um, you know, other indexes are
Speaker 1: subject to other types of adjustments, but they tend to
Speaker 1: be much smaller. So for example, with rent, you know, rent,
Speaker 1: there's something called an age bias adjustment because you're let's say,
Speaker 1: let's say you've got an apartment and you happen to
Speaker 1: make it into the BLS survey and in January they
Speaker 1: come to you and they say, you know, what do
Speaker 1: you pay for rent? You give them a number. They
Speaker 1: come back to you in July six months later, and
Speaker 1: of course you let's say you've got your least your
Speaker 1: rent hasn't changed, but your apartment six months older, and
Speaker 1: so they apply what's called an age bias adjustment to
Speaker 1: to your apartment. It doesn't really change, you know, very much.
Speaker 1: But those are the other sort of types of adjustments
Speaker 1: that the BLS will make. But for hedonics, it's it's
Speaker 1: just not a big fraction of the index that is
Speaker 1: really kind of getting that kind of a treatment. And
Speaker 1: it's really only you know, it only really comes to
Speaker 1: light when you have these huge moves like you did
Speaker 1: with wireless a couple of years ago. Those sorts of
Speaker 1: quality adjustments. UM. You know, they get a lot of press,
Speaker 1: but they don't really remind people what happened. I remember
Speaker 1: the wirelessing happening, but I don't remember what it was.
Speaker 1: Can you just remind me? Yeah, I think we went
Speaker 1: to um, we went to unlimited wireless plans, and I
Speaker 1: think it's February March in two seventeen. So you know,
Speaker 1: when we switched over from let's say you paid however much,
Speaker 1: however much your bill was for a certain amount for
Speaker 1: your phone. When we went to unlimited plans and you had,
Speaker 1: you know, instead of having you know, time gigs and
Speaker 1: you maybe you had thirty or whatever it was, they
Speaker 1: had to find a way to price that out. And
Speaker 1: that's where kind of the hedonic regressions came in, was
Speaker 1: to say, you know, how much is this extra speed worth,
Speaker 1: or how much is this extra memory worth? Um? How
Speaker 1: much is extra data plan worth to the consumer. And
Speaker 1: once they came up with those measurements, they applied them
Speaker 1: and what it ended up leading to was about a
Speaker 1: seven percent decline in the wireless index in a one month,
Speaker 1: which is a record decline. And it's subtracted about almost
Speaker 1: close to a tent just a bit over a tent
Speaker 1: off of the monthly changing the core CPI, and you know,
Speaker 1: that's a huge, huge number, got a lot of attention,
Speaker 1: and so people start talking about hedonics again, and you
Speaker 1: know that's where you know, the so called sort of
Speaker 1: inflation truths come in. It's like, well, this is just
Speaker 1: this arbitrary adjustment that they're making and so on. But
Speaker 1: you know, this is the kind of stuff that goes
Speaker 1: on in a pretty regular basis. Typically you just don't
Speaker 1: see those kinds of moves. But for the most part,
Speaker 1: these things are are pretty standard and not just for
Speaker 1: by the way, not just for the BLS, but almost
Speaker 1: for every statistical agency that does a cp I. At
Speaker 1: the end of the day, the c p I is
Speaker 1: you always want a price between you know, one month
Speaker 1: and the prior month the same good, and if it's
Speaker 1: changing in quality, you have to try to control all
Speaker 1: for that quality. So these adjustments are happening, you know
Speaker 1: Canadian cp I and your status so on. So it's
Speaker 1: a pretty sort of time tested methodology that everyone uses
Speaker 1: in all kinds of m consumer price and nexes. So
Speaker 1: I just have one last question and it's sort of
Speaker 1: big picture. But you know, in the very beginning you
Speaker 1: talked about, Okay, different regimes, different times, different relationships might work.
Speaker 1: Philip's curve thinking sometimes seems to be robust, sometimes not
Speaker 1: so much. One of the things in the post crisis
Speaker 1: period is people are asking, well, is this like a
Speaker 1: new regime, like as this is the economy now just
Speaker 1: going to be fundamentally different, maybe because of some sort
Speaker 1: of change to international trade or something like that. Is
Speaker 1: that something that you're on the lookout for or thinking
Speaker 1: that maybe like even post virus, maybe we'll get something
Speaker 1: resembling normalization, but that's something structurally might be a different
Speaker 1: economy than we had pre crisis, thus forcing you know,
Speaker 1: thus causing a sort of different way to think about
Speaker 1: what might uh manifest inflation. Yes, I think let me
Speaker 1: preface this by saying, you know, for the most part,
Speaker 1: economists are really terrible at picking up like turning points
Speaker 1: and you know, paradigm shifts and things of that nature,
Speaker 1: which is why there's such a large literature on how
Speaker 1: to forecast inflation. But yeah, I think one of the
Speaker 1: things that you know, at least I'm on the lookout
Speaker 1: for it, and I think others are as well. Is
Speaker 1: to think about the idea of how all this sort
Speaker 1: of disturbce and supply chains is potentially going to lead to,
Speaker 1: let's say, on shoring. You know, we're talking about building
Speaker 1: more semiconductor factories here in the US. We're talking about
Speaker 1: having sort of you know, more of you know, manufacturing
Speaker 1: in the US, And you know, what does that mean
Speaker 1: for for inflation going forward? So that's that's potentially a
Speaker 1: big paradigm shift that I think we need to be
Speaker 1: on the lookout for. But is that going to be
Speaker 1: a six, twelve, eighteen month thing. Uh, you know, I'm
Speaker 1: pretty skeptical of that. To meet that is a much broader,
Speaker 1: much sort of you know, longer tenure type of topic
Speaker 1: um to think about, and you know, probably not something
Speaker 1: that you're really going to be able to capture kind
Speaker 1: of doing a bottom up type forecast. Omar Sharif, thank
Speaker 1: you so much for coming on odd lots really appreciate it.
Speaker 1: Thank you appreciate it. Thanks O Mary. That was fantastic.
Speaker 1: Thanks Sorry, I really like that was great. I really
Speaker 1: like talking to Amara. I feel like, at least right now,
Speaker 1: it really feels like if you're not doing some sort
Speaker 1: of bottoms up analysis where you're actually looking at the component.
Speaker 1: There's probably like no hope to understanding what's going on
Speaker 1: with inflation. Yeah, totally, especially since so much of it
Speaker 1: seems to be driven by the reopening like not just
Speaker 1: the reopening categories, but literally one or two or maybe
Speaker 1: three reopening categories like a big chunk down to use
Speaker 1: car prices, air affairs, um and hotels. I think. Yeah. Uh.
Speaker 1: I also thought it was super interesting that, you know,
Speaker 1: it's like that he sort of pushed back a little
Speaker 1: bit about the so called like stories we tell about
Speaker 1: even those categories, and so even though like, okay, we
Speaker 1: can talk about semi conductors are shipping containers, but that actually,
Speaker 1: per his view, you have to go even deeper and
Speaker 1: just like really get to know index construction and really
Speaker 1: no methodology and seasonality and to actually sort of do it.
Speaker 1: Is not enough to just be able to like sort
Speaker 1: of like tell some like bigger stories about the categories
Speaker 1: that are really moving. Yeah. I'm very curious about the
Speaker 1: seasonality portion of it. And I guess, like if everything
Speaker 1: is so seasonal and predictable, why do people still get
Speaker 1: it wrong occasionally? I guess it goes back to what
Speaker 1: we started um the episode talking about, which is this
Speaker 1: idea that you know, despite decades and decades of studying inflation,
Speaker 1: it does feel like economists certainly struggle to look at
Speaker 1: it as a whole. It's also interesting, Uh, by the way,
Speaker 1: I really liked your question about mayonnaise inflation or the
Speaker 1: sailor addressing category. But it is interesting that there were
Speaker 1: like these categories that he like, you know, he he
Speaker 1: expressed sort of like confidence about his ability to make
Speaker 1: a forecast and then other runs. And I think he
Speaker 1: said like air fairs, and you wouldn't necessarily think of
Speaker 1: with air fares, because again, it seems like the numbers
Speaker 1: are kind of transparent or there's like dozens of websites
Speaker 1: that track airfairs. But it's interesting that they're like these
Speaker 1: categories that like, you just can't quite crack. I have
Speaker 1: a great book idea, So what if you, um, what
Speaker 1: if you went through the like two hundred CPI components
Speaker 1: and like for each one kind of told the story
Speaker 1: of the industry and how prices are actually made and
Speaker 1: how the BLS incorporates them. Yeah, best seller New York Times. No,
Speaker 1: I think it's interesting. I've read a book one through
Speaker 1: every ingredient of twinkies, and and that was that was fascinating.
Speaker 1: There's something like a hundred ingredients in there. You could
Speaker 1: do the same for CPI. No, Actually, on ironical, maybe
Speaker 1: what about a a coffee table book like each picture
Speaker 1: is like sort of like a really glossy photo, beautiful
Speaker 1: photo of like mayonnaise picture or something like that, and
Speaker 1: then a page on the left talking about how the
Speaker 1: prices derived. Yeah, okay, literary agents and publishers hit us up,
Speaker 1: We're ready to write it. Reach out. Let's leave it there.
Speaker 1: All right, let's leave it there. This has been another
Speaker 1: episode of the All Thoughts podcast. I'm Tracy Alloway. You
Speaker 1: can follow me on Twitter at Tracy Alloway and I'm
Speaker 1: Joe wisn't thought you could follow me on Twitter at
Speaker 1: the Stalwart. Follow our guest Omar Sharif. His handle is
Speaker 1: at f Cast of the Month. Follow our producer Laura Carlson.
Speaker 1: She's at Laura M. Carlson. Follow the Bloomberg head of
Speaker 1: podcast Francesca Levi at francesco Today, and check out all
Speaker 1: of our podcasts at Bloomberg under the handle at podcasts.
Speaker 1: Thanks for listening to