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Speaker 1: Bloomberg Audio Studios, Podcasts, Radio News.

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Speaker 2: Hello and welcome to another episode of The Odd Lots Podcast.

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Speaker 2: I'm joll Wisenthal and.

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Speaker 3: I'm Tracy Alloway.

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Speaker 2: Tracy, you know, it's funny there's all this talk about, Okay,

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Speaker 2: when when is inflation going to get back down to

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Speaker 2: two percent? When is the Fed going to hit it

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Speaker 2: to goals? But when we talk about inflation, there's a

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Speaker 2: million ways to measurement or at least two or three

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Speaker 2: big ones.

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Speaker 3: Yeah, this is one of the things that I've really

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Speaker 3: come to appreciate over time. There are so many different

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Speaker 3: flavors of inflation, so many different ways of measuring it.

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Speaker 3: My understanding is that there's basically, if you're going to

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Speaker 3: break it down, there's CPI, there's PCE, there's core and

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Speaker 3: supercore of each of them. And the way to do

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Speaker 3: it is just choose whichever one of those confirms your

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Speaker 3: priors and then focus on that.

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Speaker 2: That's what I do.

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Speaker 3: That's the secret.

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Speaker 2: That's what I do. Whether it's PCE, whether it's CPI,

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Speaker 2: look for the one that's closest to two percent, and

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Speaker 2: if neither are that closed, then I then I lop

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Speaker 2: out some things. It's like oh, if you exclude rent

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Speaker 2: and use cars.

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Speaker 3: And food everything you need to survive.

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Speaker 2: That we're two percent, so it's time to cut rates.

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Speaker 2: That's basically by my approaches. But I'm glad to hear

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Speaker 2: that validate.

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Speaker 3: I mean, that is the running joke, isn't it. If

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Speaker 3: you exclude everything that you need to live, then inflation

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Speaker 3: is coming down. But I think the important thing, the

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Speaker 3: really important distinction, is CPI versus PCE. CPI is probably

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Speaker 3: the one that people have in their heads when they

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Speaker 3: think about inflation. But PCE, of course is the Fed's

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Speaker 3: preferred measure and the thing that the Central Bank is

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Speaker 3: actually focusing on.

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Speaker 2: And I don't know why that is. Actually, yeah, like

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Speaker 2: I know this that most of the time when people

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Speaker 2: tell what's inflation rate right now, they'll look at CPI

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Speaker 2: or maybe core CPI. But then where I was like,

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Speaker 2: but you know, the FED looks at pc and I

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Speaker 2: guess and I believe that to be true. But I

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Speaker 2: actually don't know what it is about PCE that the

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Speaker 2: FED prefers. I don't I know there's some different weights

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Speaker 2: related to rent, and there's a few things there that

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Speaker 2: cause them to change trajectory.

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Speaker 3: Smooth some stuff is that right? It's supposed to be

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Speaker 3: less volatile. But I one thing I do know, and

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Speaker 3: I have to admit something here, and it's kind of

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Speaker 3: embarrassing at this point in my career as a financial journalist,

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Speaker 3: But CPI includes something called owner's equivalent rent, which is

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Speaker 3: basically a measure of the cost of home ownership, and

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Speaker 3: it comes up all the time as like a key

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Speaker 3: difference between CPI and PCE, and I, for the world,

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Speaker 3: do not understand what well. I kind of get what

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Speaker 3: it's supposed to be, but I don't get how it's

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Speaker 3: measured at all.

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Speaker 2: Well, you know what I've been thinking, generally, I think

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Speaker 2: it would be good to do more episodes about how

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Speaker 2: do we actually get the data that we get, Like

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Speaker 2: how do they do the jobs report survey? I actually

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Speaker 2: don't really know much about that. How do they do

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Speaker 2: all these different surveys. All the smartest people we talk

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Speaker 2: to tend to know this stuff really well. Anyway, this

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Speaker 2: episode that we're recording right now, when you're listening to it,

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Speaker 2: it happens to be pc day, the day that the

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Speaker 2: FEDS preferred inflation measure comes out, and so we should

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Speaker 2: understand what's in the Fed's preferred inflation measure and how

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Speaker 2: it differs from other measures of inflation.

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Speaker 3: I am really into this topic. I feel like this

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Speaker 3: is going to be an episode that I like bookmark

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Speaker 3: the transcript of and then go back and look at

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Speaker 3: it over and over again. So I'm looking forward to it.

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Speaker 1: Well.

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Speaker 2: I'm excited to say we do literally have the two

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Speaker 2: perfect guests to talk about this, two people who really

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Speaker 2: have a deep understanding and appreciation for how these numbers

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Speaker 2: that appear on the screen. PCE for me, is just

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Speaker 2: a number that appears at eight thirty am on my

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Speaker 2: Bloomberg terminal. But the reality is there are all these

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Speaker 2: surveys and calculations and then tabulations, and so there's a

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Speaker 2: lot of hard work that goes into producing this number.

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Speaker 2: We're gonna be talking to two people that have a

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Speaker 2: deep understanding and appreciation for what goes in from a

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Speaker 2: real bottoms up perspective, how these numbers appear on our screens.

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Speaker 2: We're gonna be speaking to multiple time guests, both of

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Speaker 2: them Omir Sharif he's the founder and president of Inflation Insights,

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Speaker 2: as well as Skanda Emernath, executive director at Employee America,

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Speaker 2: so Amair and Skanda, Thank you both for coming back

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Speaker 2: on the show.

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Speaker 4: Thanks for having us, Thanks omayor or.

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Speaker 2: You know, what do we start with you like, why

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Speaker 2: do you answer the sort of basic question for us

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Speaker 2: of what is the difference between PCE and CPI. Why

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Speaker 2: do they even why do we even have two separate

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Speaker 2: measures of this?

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Speaker 5: Yeah, I think the simplest way to think about it

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Speaker 5: is just that they're intended to measure somewhat different things,

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Speaker 5: so they're designed to sort of do different things. The

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Speaker 5: pce is a much broader index. It captures especially more

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Speaker 5: of the economy, if you will, than with the CPA does.

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Speaker 5: The CPI focuses a bit more on consumers out of

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Speaker 5: pocket expenditures, whereas the PCEE covers not just that, but

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Speaker 5: also what is sort of paid on your behalf by

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Speaker 5: third parties or the government. And a good way to

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Speaker 5: think about this is healthcare. In the CPI, largely it's

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Speaker 5: measured as you know, your out of pocket payment, let's say,

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Speaker 5: for your copay if you go to visit the doctor,

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Speaker 5: and there are some other additional measurements there as well.

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Speaker 5: But in the PCE it includes things like you know, Medicaid,

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Speaker 5: which is paid for by through taxes by the government

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Speaker 5: that's out of the scope of the CPI. So scope

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Speaker 5: is really kind of the thing that differentiates these two

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Speaker 5: indexes because one has a certain scope really consumers out

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Speaker 5: of pocket payments, which is a CPI, and the other

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Speaker 5: has just a much broader scope, and it's really able

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Speaker 5: to capture more of what's happening in the economy and

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Speaker 5: more of the inflation you see through the broader economy.

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Speaker 5: And that's probably I think why you hear the beneficial

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Speaker 5: say that, you know, their preferences for the PCE versus

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Speaker 5: the CPI.

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Speaker 3: Can you talk a little bit more about that. So

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Speaker 3: how did it come to be that the Fed is

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Speaker 3: focused more on PCE going back in history? Was there

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Speaker 3: like an announcement or a trigger for them to focus

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Speaker 3: on that measure versus something like CPI.

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Speaker 5: Yeah, I don't know that there's necessarily any historical basis

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Speaker 5: for it. I think it's just more that the PCE

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Speaker 5: is more representative of the broader economy. You know, it

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Speaker 5: just captures more of what the types of inflation that

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Speaker 5: people tend to see across the economy, but it also

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Speaker 5: captures with some of the inflation that you know, businesses

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Speaker 5: are seeing as well across the economy.

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Speaker 4: So if you don't let me jumping out, there actually

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Speaker 4: is a history to this. It's actually o great, why

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Speaker 4: don't you take that on? Yeah, So the FED for

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Speaker 4: the longest time actually did sort of focus more on CPI.

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Speaker 4: They never have like a formal inflation target until twenty twelve,

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Speaker 4: but if you ask the FED how they're tracking inflationary pressures,

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Speaker 4: they probably point to CPI first until the year two

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Speaker 4: thousand and so. Around that time time, especially green Span

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Speaker 4: was focused on so the notion of quality change and

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Speaker 4: how substitution bias might be at work, where the composition

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Speaker 4: of what consumers consume changes. But CPI is conceptually more

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Speaker 4: of a fixed basket relative to PCE, which is trying

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Speaker 4: to dynamically change the weighting on the price index to

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Speaker 4: match what people are consuming and put a little bit

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Speaker 4: more emphasis on how consumer spending patterns change. And so

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Speaker 4: around two thousand the shift was from CPI to PCE

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Speaker 4: within the FED. If I didn't really say what kind

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Speaker 4: of target was going to be, the place on it

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Speaker 4: would think it was implicitly assumed to be around one

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Speaker 4: to two one to two and a half percent, sort

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Speaker 4: of where core inflation was, But actually there was a

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Speaker 4: very big difference in terms of well you q CPI

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Speaker 4: or PCE. There's obviously just an inherent bias and what

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Speaker 4: CPI readings tend to be a little bit higher than PCE,

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Speaker 4: and so that itself kind of changes sort of if

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Speaker 4: you thought two percent with some magic number, it actually

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Speaker 4: means different things if it's tracked in terms of CPI

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Speaker 4: or PCE.

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Speaker 2: What's happening, First of all, that's really interesting and I

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Speaker 2: didn't know that that that history. What's happening right now?

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Speaker 2: Just to get up to speed, we're going to dive

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Speaker 2: into the guts of some of these, but right now

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Speaker 2: there is a gap between pc and CPI or the course,

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Speaker 2: what are we seeing in the trajectory of this sort

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Speaker 2: of I guess you call it the wedge of the

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Speaker 2: jaws between these two lines.

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Speaker 4: So typically the wedge between core CPI and core PCE.

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Speaker 4: To a first approximation, especially pre pandemic, you would have

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Speaker 4: said it was roughly thirty to fifty basis points and

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Speaker 4: the year of a year readings so point three to

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Speaker 4: point five percent. If you know what core CPI is,

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Speaker 4: you should be able to know what core.

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Speaker 2: Pc is with CPI being right right now, with CPR

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Speaker 2: being hired.

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Speaker 4: Course CPI being higher, Okay, okay, And yeah, if you

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Speaker 4: look right now, course CPI year over year is something

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Speaker 4: like three point nine percent on a year of a

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Speaker 4: year basis and core PCE is going to track something

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Speaker 4: on two point nine percent, maybe two point eight some

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Speaker 4: around there. Those readings are quite different, right. That's about

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Speaker 4: one hundred basis point spread when the typical spread was

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Speaker 4: point three to point five percent. And yeah, there's obviously

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Speaker 4: a lot of variety of factors that have led to that.

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Speaker 4: I'll kind of let Omeric kind of jump in to

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Speaker 4: sort of like, how if you were trying to explain

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Speaker 4: this on a the first major reason kind of that

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Speaker 4: sticks out to him?

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Speaker 5: Sure, yeah, So you know, I think everyone note normally

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Speaker 5: focuses on the weights, right, and I think Joe you

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Speaker 5: mentioned that earlier, and so they tend to focus on

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Speaker 5: things like shelter inflation, right, I know we are, and

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Speaker 5: the weight of that in the PCE is only about

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Speaker 5: you know, fifteen sixteen percent, but of course in the

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Speaker 5: CPI it's about forty three percent, and so people tend

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Speaker 5: to focus on that difference and say, well, you know

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Speaker 5: that tends to cause a big part of the wedge,

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Speaker 5: and that's true in a very sort of static sense,

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Speaker 5: and that what I mean by that is that over

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Speaker 5: a short term horizon, let's say, you know, six months,

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Speaker 5: seven months, eight months, those weights are just not going

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Speaker 5: to change materially, right, difference is just going to be

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Speaker 5: roughly about the same over a short term time period.

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Speaker 5: And then the year year rates obviously for o were

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Speaker 5: are don't move too dramatically either, So whatever that wedge

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Speaker 5: is coming from shelter inflation in one month will be

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Speaker 5: roughly the same you know, wedge in six months. What's

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Speaker 5: been going on more recently really the last six months

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Speaker 5: is that you know, Scotta talked about the spread historically

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Speaker 5: being thirty to fifty. We'd gotten down to about forty

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Speaker 5: five BIPs in July, so we were very close to

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Speaker 5: kind of a historical norm between pc and CPI. In

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Speaker 5: the last six months, it's blown back out to one percent.

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Speaker 5: And that's largely because the PCEE has been slowing much

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Speaker 5: much faster than the CPI, and that's typically something you know,

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Speaker 5: people tenerally focus on the CPI as being the one

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Speaker 5: that kind of causes the movements. But right now what

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Speaker 5: we're seeing is actually it's the core PCE that is

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Speaker 5: just slowing much much faster than the core CPI, and

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Speaker 5: that's blown the spread back out from about forty five

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Speaker 5: BIPs or so lie to about the one percentage point.

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Speaker 5: And there's more new. Well, you know, this isn't really

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Speaker 5: about shelter. This is about some stuff happening in medical care,

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Speaker 5: and really much more than that. It is really about

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Speaker 5: the core services part of the story. And those are

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Speaker 5: very very different animals in the PCE versus the CPI.

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Speaker 5: They're just not constructed the same in terms of the

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Speaker 5: core services. And so that's really what we're seeing is

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Speaker 5: core services is slowing really fast in the PCE, and

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Speaker 5: in fact has kind of gone up a little bit

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Speaker 5: in the CPI.

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Speaker 4: And just for your listeners to kind of get a

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Speaker 4: sense that CPI is source data, which is to say

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Speaker 4: it actually is a measure of they're doing the direct measurement,

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Speaker 4: the direct surveys of prices. Better to think about pc

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Speaker 4: as a composite of different sources, including CPI, but not

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Speaker 4: limited to just CPI. We also learn a lot about

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Speaker 4: PCE from PPI input data, not the PPI aggregates themselves,

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Speaker 4: but specific inputs, as americad have alluded to in healthcare,

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Speaker 4: there there are inputs there from PPI that matter, from PCE,

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Speaker 4: and then there are things that are that just outside

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Speaker 4: of CPI and BPI that also matter. And it's that

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Speaker 4: PPI and that other stuff that really feeds into core

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Speaker 4: PC in a pretty meaningful sense and has driven more

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Speaker 4: of this short run divergence even beyond what you might

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Speaker 4: explain from kind of changes and weights rent owners equivalent rent.

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Speaker 3: So I definitely want to dig into what's driving these

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Speaker 3: various inflation numbers at the moment even more. But before

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Speaker 3: we do, I have a sort of existential question, which

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Speaker 3: is I'm always kind of amazed at how much mental

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Speaker 3: energy we expend on the question of what prices are

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Speaker 3: doing at the moment. And it seems like one of

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Speaker 3: those things that like, all right, there's observable prices for everything,

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Speaker 3: So like, why is it so difficult? And obviously the

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Speaker 3: weightings come into play here and what you choose to

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Speaker 3: focus on, et cetera, et cetera, But does it matter

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Speaker 3: if PCE is different to CPI. I mean, if we

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Speaker 3: understand the difference in methodology, why should we care about

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Speaker 3: this divergence.

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Speaker 4: I guess I think it matters to the extent that

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Speaker 4: you are trying to anticipate let's say a CPI index,

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Speaker 4: if you're someone who's let's say investing in inflation products

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Speaker 4: inflation link financial products, or if you're somebody trying to

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Speaker 4: focus on how the FED is supposed to react. When

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Speaker 4: the FED is kind of laid out an inflation target

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Speaker 4: that's anchored to two percent on PCE and proxied by

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Speaker 4: core PCE over time, you'll get all of different answers.

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Speaker 4: That's kind of the technical, sort of markets oriented answer.

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Speaker 4: The bigger thing is actually, I think if you ask

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Speaker 4: maybe some economists, they'll probably tell you, well, if you

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Speaker 4: as like CPI, PCE, PPI, what all doesn't really matter.

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Speaker 4: It should average out there is some underlying price level

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Speaker 4: that is all just these are all just like imperfect

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Speaker 4: approximations of the price level. But in practice you get

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Speaker 4: some pretty big divergences, especially in real time, because of

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Speaker 4: choices and weights, choices and methodology choices in what scope

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Speaker 4: of goods and services you're going to put more emphasis

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Speaker 4: on or less emphasis on, and you'll get different answers.

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Speaker 4: And this is kind of how like that cottage industry

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Speaker 4: of different private sector measures of inflation or true inflation

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Speaker 4: or whatever it is shadow stats. These are all various

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Speaker 4: spectrum of crankery to less crank measures of inflation. But

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Speaker 4: I think that that's kind of the byproduct of the

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Speaker 4: fact that all these choices do matter, right, And that's

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Speaker 4: like there is some level of faith to saying there's

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Speaker 4: some underlying true inflation and that's actually here, and it's

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Speaker 4: not there. It just really depends on the choices you make.

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Speaker 5: Just had two other things quickly. One is just simply

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Speaker 5: that I didn't care about the CPI for two reasons,

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Speaker 5: also a relative to the PCE. One is that you know,

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Speaker 5: simply put, it comes out first and it shapes expectations

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Speaker 5: for where inflation's going. So you know, we get that

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Speaker 5: number typically by the twelve thirteenth of the month, whereas

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Speaker 5: PCs the end of the month. So I think for

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Speaker 5: a couple of weeks people are digesting, you know, what

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Speaker 5: is the fad going to do based off of this

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Speaker 5: inflation number, Even if we know their preference really is

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Speaker 5: for the PCE, it just really starts to shape expectations

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Speaker 5: very early on before we get the PCE, and I

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Speaker 5: think the second thing is that it's tied to real

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Speaker 5: life in the sense that you know, all the COLA

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Speaker 5: adjustments made in social security, for example, are derived from

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Speaker 5: the CPI. A lot of rent contracts are based on

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Speaker 5: the CPI, So it does affect consumers in a variety

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Speaker 5: of ways. And so I think that's why there's also still,

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Speaker 5: you know, relative importance in terms of thinking about what

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Speaker 5: the CPI is doing, in addition to what's gonna mentioned,

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Speaker 5: which is that a lot of the PCE is built

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Speaker 5: off of what the CPI is doing.

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Speaker 2: Anyway, I want to get into and we're going to

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Speaker 2: get into the sort of like deep methodological questions and

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Speaker 2: where these numbers actually come from, et cetera. But before

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Speaker 2: we get into sort of complicated methodological questions, I want

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Speaker 2: to ask a sort of simple methodological question, which is like,

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Speaker 2: how does the government, say in the CPI track the

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Speaker 2: price of a tomato or something. I don't know, maybe

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Speaker 2: I don't know if tomatoes a category, but something like that.

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Speaker 2: Let's start with something simple, because I get why measuring

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Speaker 2: insurance is super complicated. Measuring various things like that really difficult.

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Speaker 2: But let's take something simple every month the government wants

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Speaker 2: to know, like how much tomatoes and apples and pairs cost.

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Speaker 2: What is the basic process of collecting that information.

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Speaker 5: Well, so there's the consumer Expenditure Survey conducted now well

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Speaker 5: now every year, used to be every two years. Basically,

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Speaker 5: we're you know, asking people to track their spending and

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Speaker 5: what they're spending on and how much they're spending on

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Speaker 5: these items. And there's you know, thousands of these surveys

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Speaker 5: conducted annually, and so from those surveys, we're collecting data

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Speaker 5: on what exactly not just what you know, kind of

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Speaker 5: apple or whether or not they're personing apples, but what

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Speaker 5: specific kinds of apples they're purchasing. And so based on

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Speaker 5: all of this collected information, you are then figuring out

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Speaker 5: exactly what you want to price and what the share

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Speaker 5: of spending is for each item in the basket. So

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Speaker 5: you know, Fuji apples versus Granny Smith apples, whatever it

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Speaker 5: may be. And these are done at you know, the

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Speaker 5: metro level. So what's there The diary might be a

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Speaker 5: little bit different, Let's say in Chicago versus you know,

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Speaker 5: Miami versus New York in terms of some of these

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Speaker 5: granular items. So ultimate least, a consumer expenditure survey that's

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Speaker 5: sort of dictating everything from what it is that you

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Speaker 5: want to collect prices for where you want to collect

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Speaker 5: those prices as well, because you're also figuring out where

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Speaker 5: it is that people are shopping, and then you know

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Speaker 5: how much weight to put on an item within the basket,

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Speaker 5: so apples within the you know, food at home grocery

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Speaker 5: store index, use cars with the transportation index, and so on.

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Speaker 5: So that really dictates everything in terms of the CPI

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Speaker 5: and how it's it's sort of being constructed and what's

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Speaker 5: being you know, picked to be priced.

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Speaker 3: Maybe this is a good point to talk a little

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Speaker 3: bit about a deterioration in some of the survey responses

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Speaker 3: that people have been discussing recently. So the idea that

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Speaker 3: a lot of this is based on the proportion of

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Speaker 3: survey respondents who actually get back to you and say,

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Speaker 3: this is how much we're spending on Fuji apples per

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Speaker 3: month or whatever, and that percentage seems to be declining

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Speaker 3: over time. I think I've written about this before, but

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Speaker 3: I don't have the numbers in front of me, but

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Speaker 3: it seems like that could be a pretty big deal

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Speaker 3: for the accuracy of some of these figures, or maybe

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Speaker 3: just have some sort of influence on them.

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Speaker 4: Yeah, I mean, I think it seems to be an

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Speaker 4: issue of because so many of these surveys are conducted

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Speaker 4: over the phone. Not everything in CPI is that way.

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Speaker 3: And no one answers their phone anymore. If someone calls me,

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Speaker 3: I don't pick up.

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Speaker 4: I mean, this is the same problem with election polling,

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Speaker 4: right where we have a lot of non response going

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Speaker 4: up and you don't know if that skews a certain way,

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Speaker 4: and if you're kind of calling particular businesses. I don't

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Speaker 4: think it's there's a more structured process there relative to

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Speaker 4: say election polling, but there is still an issue I

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Speaker 4: think of a non response that kind of permeates a

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Speaker 4: lot of data. This is not just about inflation data now.

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Speaker 4: It's obviously like labor market data has the same problem

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Speaker 4: where response rates are going down, it's taking more calls

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Speaker 4: to be able to kind of fill out the survey.

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Speaker 4: The relative to other data points, I'm not sure inflation

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Speaker 4: data is actually as vulnerable, but it is still this

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Speaker 4: is a structural trend that, look, the data is only

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Speaker 4: as good as you measure it, right, So this is

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Speaker 4: actually going to be an ongoing challenge for the BLSS suspect.

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Speaker 2: So let's talk about some of these idiosyncrasies, particularly within

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Speaker 2: core PCE, because there are some things where you can

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Speaker 2: just go to the grocery store. You can go to

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Speaker 2: Whole Foods, and you can go to Trigger Joe's, and

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Speaker 2: you can go to Associated and Wegmans and look at

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Speaker 2: the price of Fuji apples or Red Delicious or God

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Speaker 2: forbid Red Delicious. Hopefully those are getting a smaller and

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Speaker 2: smaller weight in the basket because they're the worst apple.

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Speaker 2: But then there are other things where you you cannot

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Speaker 2: do that. There is not just a price tag, and

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Speaker 2: things have to be imputed in some way, and so

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Speaker 2: you have to sort of derive a price for things

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Speaker 2: where there is just not a public price. Let's talk

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Speaker 2: about some of these imputations and where they get weird,

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Speaker 2: because I think this is where it gets like really interesting.

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Speaker 2: Like you know, when it comes to like we pay

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Speaker 2: people pay financial services, they pay for a financial advisor,

404
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Speaker 2: et cetera. I don't know that there's like a simple

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Speaker 2: price tag that that can be established. Talk about some

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Speaker 2: of these more interesting or complicated or ethereal categories yeah.

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Speaker 4: There are a set of transactions, especially now as you

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Speaker 4: get into PCE where we have no real transactions are observing, right,

409
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Speaker 4: there's probably the more common one would be sort of

410
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Speaker 4: your owner's equivalent rent is very commonly cited because that

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Speaker 4: is effectively trying to approximate effect to the cost of

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Speaker 4: rent for someone who owns their house, and that is

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Speaker 4: something that is not really a transaction there. But the

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Speaker 4: BLS is and the BA BA obviously compiling or PCE,

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Speaker 4: they are basically using rent data to do that, so

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Speaker 4: they from the CPI Housing survey comes to rent data.

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Speaker 4: That rent data is also then used for estimating owners

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Speaker 4: equivalent rent. There's no transaction behind it, right, but it

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Speaker 4: is basically saying we're going to assume this price represents

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Speaker 4: what owner's equivalent revent looks like. It gets trickier when

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Speaker 4: you get into some other things in PCE, the relative

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Speaker 4: CPI something like imputed financial services, where there's no transaction

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Speaker 4: taking place. It's specifically the value you the consumer derived

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Speaker 4: from your financial institution and your bank. When you are

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Speaker 4: getting all these various services, free checking, all sorts of

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Speaker 4: other things, you're getting some value from whatever it is.

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Speaker 4: Chase Bank in America. I'm just giving examples. You're getting

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Speaker 4: some some services, and yet you're also not being charged necessarily, No,

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Speaker 4: you're not getting sort of the deposit rate that reflects

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Speaker 4: what like the bank itself.

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Speaker 2: Earns spread between the bank deposit.

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Speaker 4: And precisely precisely that that spread is a big part

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Speaker 4: of how of the implicit price. And so the BA

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Speaker 4: is simultaneously trying to measure what's that volume of value

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00:22:05,680 --> 00:22:08,639
Speaker 4: that the consumer's driving and also the way of like

436
00:22:08,680 --> 00:22:11,960
Speaker 4: proxying what's the price associated with that value. And these

437
00:22:11,960 --> 00:22:14,200
Speaker 4: are two things that are basically like dark arts, right

438
00:22:14,280 --> 00:22:16,719
Speaker 4: Like it's kind of a not not like something that

439
00:22:16,760 --> 00:22:20,720
Speaker 4: follows an obvious and verifiable method for being able to

440
00:22:20,760 --> 00:22:23,159
Speaker 4: say this is how much value you're driving. There's just

441
00:22:23,160 --> 00:22:26,320
Speaker 4: a lot of rough approximations. It's probably the funniest bit

442
00:22:26,359 --> 00:22:28,680
Speaker 4: of core VC for my money, because it is a

443
00:22:29,200 --> 00:22:33,199
Speaker 4: function of two factors. Which is the value you can

444
00:22:33,240 --> 00:22:35,239
Speaker 4: think of as that spread between deposit rates and call

445
00:22:35,280 --> 00:22:38,560
Speaker 4: it benchmark money market rates. And so if the FED

446
00:22:38,720 --> 00:22:41,720
Speaker 4: is raising rates faster than deposit rates are moving, that's

447
00:22:41,760 --> 00:22:45,000
Speaker 4: going to show up is more inflation. And if deposit

448
00:22:45,160 --> 00:22:48,040
Speaker 4: and so and then we and we saw relatively high

449
00:22:48,080 --> 00:22:51,119
Speaker 4: inflation from this category in twenty twenty two, and it

450
00:22:51,160 --> 00:22:53,719
Speaker 4: really moved the needle on core PCEE even and then

451
00:22:53,760 --> 00:22:55,480
Speaker 4: on the other side of it, when SBB hit, you

452
00:22:55,520 --> 00:22:57,800
Speaker 4: obviously start to see banks start to raise their deposit

453
00:22:57,880 --> 00:23:00,719
Speaker 4: rates more aggressively and the FED slow down on and

454
00:23:00,760 --> 00:23:03,720
Speaker 4: so kind of weirdly, because of both of those factors,

455
00:23:04,000 --> 00:23:07,840
Speaker 4: you've seen that part of VCE really ratchet down in

456
00:23:07,880 --> 00:23:11,800
Speaker 4: the last six to nine months. And this is all

457
00:23:11,960 --> 00:23:14,200
Speaker 4: very weird stuff where it's basically a function of well

458
00:23:14,200 --> 00:23:17,560
Speaker 4: fed hikes are kind of inflationary through this category, and

459
00:23:17,600 --> 00:23:20,199
Speaker 4: then slowing down on fed hikes and getting some deposit

460
00:23:20,240 --> 00:23:22,760
Speaker 4: recatchup ends up being the opposite. It's kind of very

461
00:23:22,760 --> 00:23:24,760
Speaker 4: bizarro stuff. There's some other things that matter, but it

462
00:23:24,840 --> 00:23:26,280
Speaker 4: just kind of goes to show you like there's a

463
00:23:26,320 --> 00:23:28,920
Speaker 4: lot of silly parts of this core pc I didn't

464
00:23:28,920 --> 00:23:32,040
Speaker 4: say courts CPI, but it is. People tend to think

465
00:23:32,080 --> 00:23:36,239
Speaker 4: this stuff is all very fundamental and mechanical, and I

466
00:23:36,320 --> 00:23:39,080
Speaker 4: just would caution that there's a lot of weird methodology

467
00:23:39,119 --> 00:23:41,760
Speaker 4: and imputations that kind of go into various parts of

468
00:23:41,760 --> 00:23:42,360
Speaker 4: that complex.

469
00:23:43,359 --> 00:23:46,480
Speaker 3: This is an interesting wrinkle to my campaign to improve

470
00:23:46,520 --> 00:23:49,520
Speaker 3: the transmission of monetary policy by making everyone switch to

471
00:23:49,720 --> 00:23:53,280
Speaker 3: higher interest bank accounts. But okay, I'm going to ask

472
00:23:53,320 --> 00:23:57,760
Speaker 3: a slightly or a very provocative question, but just on

473
00:23:57,800 --> 00:24:01,320
Speaker 3: the question of how we measure shelter, can both of

474
00:24:01,359 --> 00:24:05,040
Speaker 3: you choose, like if you had to pick a preferred measure,

475
00:24:05,119 --> 00:24:09,199
Speaker 3: would you be team CPI slash BLS or would you

476
00:24:09,240 --> 00:24:14,359
Speaker 3: be team you know, PCE and BA Omeryl.

477
00:24:14,800 --> 00:24:20,440
Speaker 2: I would probably say.

478
00:24:20,560 --> 00:24:22,160
Speaker 5: This is tough, actually, now that I think.

479
00:24:22,080 --> 00:24:24,879
Speaker 4: About it, On some level, the BA is using the

480
00:24:24,880 --> 00:24:28,399
Speaker 4: BLS data, and so this is the data itself about

481
00:24:28,400 --> 00:24:32,240
Speaker 4: rent and owner's equivalent rent are coming from the BLS

482
00:24:32,280 --> 00:24:34,679
Speaker 4: and the CPI having survey in all of its perfections

483
00:24:34,680 --> 00:24:37,320
Speaker 4: and imperfections. I think the better question asked is sort

484
00:24:37,320 --> 00:24:40,399
Speaker 4: of like whether market rents are or contracted rents. What

485
00:24:40,440 --> 00:24:43,560
Speaker 4: we're basically measuring in CPI, what the BLS is measuring

486
00:24:43,680 --> 00:24:46,520
Speaker 4: is a is contracted rents. So they tend to lag.

487
00:24:46,680 --> 00:24:47,400
Speaker 2: They tend to lag.

488
00:24:47,640 --> 00:24:49,720
Speaker 4: They also tend to be a little bit smoother, a

489
00:24:49,720 --> 00:24:53,080
Speaker 4: little bit more autocorrelated, a little bit more obviously cyclical

490
00:24:53,520 --> 00:24:56,239
Speaker 4: in a way that let's say we had you been

491
00:24:56,320 --> 00:24:59,440
Speaker 4: using market rents this entire time, we probably have much

492
00:24:59,440 --> 00:25:02,120
Speaker 4: lower inflace and ratings now, or whether we probably see

493
00:25:02,160 --> 00:25:04,440
Speaker 4: something close to two percent on the fence key gages,

494
00:25:05,080 --> 00:25:07,760
Speaker 4: and yet we would have had very very high inflation

495
00:25:07,920 --> 00:25:10,680
Speaker 4: observed in twenty twenty one. Maybe that's actually the true

496
00:25:10,760 --> 00:25:14,000
Speaker 4: version of what was going on, but you also get

497
00:25:14,040 --> 00:25:16,600
Speaker 4: more there's a bit of a trade off between getting

498
00:25:16,600 --> 00:25:21,359
Speaker 4: smooth and cyclical versus something very volatile and jumpy and

499
00:25:21,920 --> 00:25:24,440
Speaker 4: maybe not as reliable in terms of how to set

500
00:25:24,480 --> 00:25:27,080
Speaker 4: monetary policy if you think that operates with some lag,

501
00:25:27,200 --> 00:25:29,560
Speaker 4: which and so you would have either like a super

502
00:25:29,600 --> 00:25:32,120
Speaker 4: super high inflation bulge in twenty twenty one or something

503
00:25:32,160 --> 00:25:34,000
Speaker 4: a little bit more smoothed out over twenty twenty one

504
00:25:34,000 --> 00:25:36,520
Speaker 4: to twenty twenty three. These debates kind of can cut

505
00:25:36,600 --> 00:25:38,800
Speaker 4: up either way, and I'm not sure which is actually

506
00:25:39,119 --> 00:25:41,680
Speaker 4: necessarily better, But it's better to just appreciate the fact

507
00:25:41,720 --> 00:25:42,400
Speaker 4: that there's a lag.

508
00:25:43,720 --> 00:25:44,959
Speaker 5: Yeah, I'm gonna come back and I'm going to say

509
00:25:45,000 --> 00:25:50,600
Speaker 5: CPI and this is just Yeah. The simple reason for that,

510
00:25:50,640 --> 00:25:54,199
Speaker 5: I think, in my mind at least, is the stuff

511
00:25:54,240 --> 00:25:56,520
Speaker 5: that is quirky in the CPI. Like we've talked about

512
00:25:56,520 --> 00:25:59,080
Speaker 5: health insurance on the show before the stuff that is

513
00:25:59,119 --> 00:26:02,800
Speaker 5: quirky in the CPI, the PCE essentially just magnifies that

514
00:26:02,920 --> 00:26:05,720
Speaker 5: even more by some of the items that are in

515
00:26:05,800 --> 00:26:08,800
Speaker 5: that index, like the financial services furnished without payment index

516
00:26:08,840 --> 00:26:11,320
Speaker 5: that you know Skanna talked about. I think there's even

517
00:26:11,359 --> 00:26:16,520
Speaker 5: more stuff in that index that is sort of you know,

518
00:26:16,960 --> 00:26:20,080
Speaker 5: conceptual and imputed. I mean, roughly thirteen percent of the

519
00:26:20,200 --> 00:26:24,159
Speaker 5: entire core PCE is just these imputed prices that no

520
00:26:24,200 --> 00:26:26,200
Speaker 5: one sees, which is why, by the way, we also

521
00:26:26,240 --> 00:26:29,960
Speaker 5: have a market based core PCE to get rid of

522
00:26:29,960 --> 00:26:32,159
Speaker 5: that and just look at actual prices that people do

523
00:26:32,280 --> 00:26:35,040
Speaker 5: pay and people do see. So the CPI does, of

524
00:26:35,080 --> 00:26:36,880
Speaker 5: course have some of that, but I think there's less

525
00:26:36,920 --> 00:26:39,720
Speaker 5: of that influence in the CPI than in the pc

526
00:26:39,880 --> 00:26:42,200
Speaker 5: And yes, we can talk about oere being heavier weight,

527
00:26:42,480 --> 00:26:43,720
Speaker 5: but at the end of the day, it is that's

528
00:26:43,760 --> 00:26:46,919
Speaker 5: in both indexes as well. So I would probably prefer

529
00:26:47,600 --> 00:26:50,040
Speaker 5: the CPI over the pc.

530
00:27:06,920 --> 00:27:10,000
Speaker 2: Let's talk about more of these interesting categories. So one

531
00:27:10,040 --> 00:27:14,480
Speaker 2: of the things that we saw, especially in the sort

532
00:27:14,520 --> 00:27:17,320
Speaker 2: of you know, the twenty twenty one twenty twenty two,

533
00:27:17,400 --> 00:27:20,280
Speaker 2: the sort of big shift and consumption patterns between goods

534
00:27:20,280 --> 00:27:23,080
Speaker 2: and services, And we talked a lot about Okay, goods

535
00:27:23,080 --> 00:27:25,399
Speaker 2: are doing this and services are doing that, and goods

536
00:27:25,400 --> 00:27:28,399
Speaker 2: prices through the roof, et cetera. But one of the

537
00:27:28,400 --> 00:27:32,160
Speaker 2: things that you both pointed out over time, and I've

538
00:27:32,160 --> 00:27:34,560
Speaker 2: heard you talk about this a fair amount, Skanda, is

539
00:27:34,600 --> 00:27:37,560
Speaker 2: that this idea of drawing a bright line in many

540
00:27:37,680 --> 00:27:42,080
Speaker 2: instances between a good and a service, it, particularly when

541
00:27:42,080 --> 00:27:44,760
Speaker 2: it comes to measuring costs, is sort of impossible or

542
00:27:44,800 --> 00:27:48,159
Speaker 2: fallacious in some way. And so auto insurance seems to

543
00:27:48,200 --> 00:27:51,000
Speaker 2: be a big area in which we call it a

544
00:27:51,040 --> 00:27:54,080
Speaker 2: service for measurement purposes, but it has connection to the

545
00:27:54,080 --> 00:27:56,040
Speaker 2: goods aspect. Could you explain that a little bit further?

546
00:27:56,800 --> 00:27:59,040
Speaker 4: Sure, I think the conventional wisdom and the FED is

547
00:27:59,119 --> 00:28:01,520
Speaker 4: obviously done his job trying to propagate this, which is

548
00:28:01,560 --> 00:28:04,440
Speaker 4: to say that, okay, the goods side of the economy

549
00:28:04,440 --> 00:28:06,879
Speaker 4: that supply chains, that's like maybe a commodity short as

550
00:28:06,880 --> 00:28:10,960
Speaker 4: you're there, services services sounds like labor, services, sounds like wages.

551
00:28:11,280 --> 00:28:14,000
Speaker 4: Service prices are obviously a function of what people are

552
00:28:14,080 --> 00:28:15,840
Speaker 4: who are working, how much are they paid, and then

553
00:28:15,840 --> 00:28:18,480
Speaker 4: it's just some spread on that. So wage growth should

554
00:28:18,480 --> 00:28:21,800
Speaker 4: be dictating services. They're like an okay guide for maybe

555
00:28:21,920 --> 00:28:23,359
Speaker 4: understanding even housing costs.

556
00:28:23,480 --> 00:28:25,960
Speaker 2: Like we think of like services as like some a

557
00:28:26,000 --> 00:28:29,440
Speaker 2: restaurant worker or a massuse or someone painting your house

558
00:28:29,520 --> 00:28:31,920
Speaker 2: or something like that, and so it's very much like correct,

559
00:28:32,080 --> 00:28:33,600
Speaker 2: very linear to labor costs.

560
00:28:34,680 --> 00:28:36,400
Speaker 4: Yes, And so you think of someone who's new cutting

561
00:28:36,400 --> 00:28:39,160
Speaker 4: your hair, right, it's like that probably is more directly

562
00:28:39,200 --> 00:28:41,240
Speaker 4: tied to one another. Right. But at the same time,

563
00:28:41,800 --> 00:28:43,960
Speaker 4: I think like even like say housing, which I think

564
00:28:43,960 --> 00:28:46,840
Speaker 4: of housing and rent as actually being related to labor market.

565
00:28:46,920 --> 00:28:49,560
Speaker 4: But it's not the cost of like construction or maintenance

566
00:28:49,600 --> 00:28:51,800
Speaker 4: that's really dictating the cost of rent. It's the marginal

567
00:28:51,880 --> 00:28:55,360
Speaker 4: supply and demand for housing, and that's something that's not

568
00:28:55,400 --> 00:28:58,520
Speaker 4: really driven by labor in any sort of proximate direct sense.

569
00:28:58,880 --> 00:29:01,600
Speaker 4: But then we get to a lot of like vehicle insurance,

570
00:29:01,840 --> 00:29:05,280
Speaker 4: when we get to airfares, those are areas where you

571
00:29:05,280 --> 00:29:08,320
Speaker 4: can definitely point to specific things where goods and good

572
00:29:08,400 --> 00:29:11,920
Speaker 4: supply chains really matter. So jet fuel costs are very

573
00:29:11,960 --> 00:29:14,520
Speaker 4: important because they're the most variable cost in like an

574
00:29:14,520 --> 00:29:19,040
Speaker 4: air airline's cost structure. Quite reliably, jet fuel costs feed

575
00:29:19,080 --> 00:29:22,320
Speaker 4: into what airfares look like. So when jet fuel spiked

576
00:29:22,360 --> 00:29:26,440
Speaker 4: in twenty twenty two due to the invasion of Ukraine.

577
00:29:26,520 --> 00:29:29,920
Speaker 4: You saw lobsly crackspreads blue out, oil prices blow out,

578
00:29:29,920 --> 00:29:32,320
Speaker 4: and therefore jet fuel prices blew out, and that had

579
00:29:32,320 --> 00:29:36,000
Speaker 4: a pretty reliable and predictable pass through into airfares, and

580
00:29:36,040 --> 00:29:38,680
Speaker 4: they even showed up in previous instances like the two

581
00:29:38,680 --> 00:29:41,040
Speaker 4: thousand and eight oil price spike having a pass through

582
00:29:41,040 --> 00:29:45,120
Speaker 4: effect into airfares. In the case of vehicle insurance, right,

583
00:29:45,200 --> 00:29:46,960
Speaker 4: and it's not just vehicle insurance, we can think about

584
00:29:47,000 --> 00:29:52,760
Speaker 4: motor vehicle leasing, repair, maintenance, rental. These are all i'd

585
00:29:52,800 --> 00:29:56,320
Speaker 4: call value sensitive services. So the value of an automobile

586
00:29:56,600 --> 00:29:59,320
Speaker 4: will shape the cost of being like that also affects

587
00:29:59,640 --> 00:30:02,800
Speaker 4: the price of parts, right because let's say autobiles are

588
00:30:02,840 --> 00:30:05,200
Speaker 4: in shortage, then the value of repair goes up because

589
00:30:05,200 --> 00:30:07,640
Speaker 4: of it, the value of spare parts goes up. I

590
00:30:07,640 --> 00:30:10,320
Speaker 4: mean've basically seen that, and that's obviously affected the cost

591
00:30:10,320 --> 00:30:14,160
Speaker 4: structure for insurers. There are some other regulatory thing dynamics

592
00:30:14,200 --> 00:30:17,080
Speaker 4: going on with respective vehicle insurance, and that also has

593
00:30:17,080 --> 00:30:21,240
Speaker 4: an implication for CPI that's different from PCEE. But the

594
00:30:21,400 --> 00:30:24,600
Speaker 4: connection between goods to services itself like kind of important

595
00:30:24,600 --> 00:30:27,360
Speaker 4: to appreciate. Yes, services tends to move more slowly, with

596
00:30:27,400 --> 00:30:29,959
Speaker 4: more of a lag, but it is kind of fundamentally

597
00:30:30,000 --> 00:30:32,640
Speaker 4: moving with respect to a lot of these dislocated supply

598
00:30:32,760 --> 00:30:36,240
Speaker 4: chain and commodity supply issues in ways that I think

599
00:30:36,320 --> 00:30:39,560
Speaker 4: are in some ways it just removed from the labor

600
00:30:39,720 --> 00:30:42,040
Speaker 4: market itself. I think that is something the FED has

601
00:30:42,080 --> 00:30:43,760
Speaker 4: been kind of keen to say, Well, labor market must

602
00:30:43,840 --> 00:30:46,640
Speaker 4: matter somewhere, so let me jam it into all these

603
00:30:46,680 --> 00:30:50,840
Speaker 4: other services aside from housing. In practice, though, there's just

604
00:30:50,880 --> 00:30:52,840
Speaker 4: a lot of stuff, even in supply chains and commodity

605
00:30:52,840 --> 00:30:55,720
Speaker 4: price swings that actually have a lot of relevance beyond

606
00:30:56,440 --> 00:30:59,280
Speaker 4: what we could strictly classify as a good and has

607
00:30:59,320 --> 00:31:01,920
Speaker 4: a lot of impact on the services side of the economy,

608
00:31:01,960 --> 00:31:06,520
Speaker 4: and services that are consumed but maybe actually pretty capital

609
00:31:06,560 --> 00:31:10,120
Speaker 4: intensive or not necessarily tied to the direct price of labor.

610
00:31:10,520 --> 00:31:12,600
Speaker 3: That reminds me, actually, can you talk a little bit

611
00:31:12,640 --> 00:31:16,640
Speaker 3: about the timing of some of these pricing decisions? And

612
00:31:16,760 --> 00:31:19,640
Speaker 3: what I mean by that is I remember talking to

613
00:31:19,920 --> 00:31:24,160
Speaker 3: Omare about producer prices for mayonnaise. I guess this would

614
00:31:24,200 --> 00:31:26,640
Speaker 3: have been over like two years ago, and there was

615
00:31:26,800 --> 00:31:31,800
Speaker 3: an idea there that companies often revise their prices around

616
00:31:32,120 --> 00:31:36,200
Speaker 3: quarter ends. There's also a more recent phenomenon that I

617
00:31:36,240 --> 00:31:40,120
Speaker 3: think the Goldman Sachs analysts are calling the January effect.

618
00:31:40,160 --> 00:31:42,240
Speaker 3: This idea that well, in a new year, lots of

619
00:31:42,240 --> 00:31:45,960
Speaker 3: people revisit how much they're charging and unveil all their

620
00:31:46,040 --> 00:31:49,239
Speaker 3: new prices around the new year. But talk to us

621
00:31:49,240 --> 00:31:52,760
Speaker 3: about like the actual timing and mechanics of how prices

622
00:31:52,800 --> 00:31:53,400
Speaker 3: get changed.

623
00:31:54,160 --> 00:31:55,840
Speaker 5: So I will say that, you know, there is this

624
00:31:56,000 --> 00:31:58,040
Speaker 5: you know, so called channery effect, which the rest of

625
00:31:58,120 --> 00:32:01,200
Speaker 5: us just call residualciesonality in the data. That's been something

626
00:32:01,480 --> 00:32:04,719
Speaker 5: that's been prevalent in you know, the start of your

627
00:32:04,760 --> 00:32:07,400
Speaker 5: price increase is something that's been prevalent in the CPI

628
00:32:07,520 --> 00:32:10,280
Speaker 5: data really for probably the last twenty years or so,

629
00:32:10,840 --> 00:32:14,040
Speaker 5: and you tend to see it much much more in goods,

630
00:32:14,520 --> 00:32:18,040
Speaker 5: where we're talking more about you know, furniture, apparel, things

631
00:32:18,040 --> 00:32:21,160
Speaker 5: of that nature, where contracts for delivery tend to get

632
00:32:21,160 --> 00:32:23,360
Speaker 5: reset for the start of the year. And so what

633
00:32:23,400 --> 00:32:26,560
Speaker 5: you'll typically find is that, yes, at the very start

634
00:32:26,560 --> 00:32:29,400
Speaker 5: of January and February, you tend to see prices on

635
00:32:29,440 --> 00:32:33,280
Speaker 5: an unadjusted basis increase by more than what you'll see

636
00:32:33,280 --> 00:32:35,600
Speaker 5: them do over the balance of the rest of the year.

637
00:32:36,080 --> 00:32:38,560
Speaker 5: And that's something that's been pretty well known in the

638
00:32:38,600 --> 00:32:42,440
Speaker 5: CPI data, and the idea is of seasonal adjustments should

639
00:32:42,440 --> 00:32:45,680
Speaker 5: be able to sort of offset that seasonal move every year.

640
00:32:46,240 --> 00:32:48,320
Speaker 5: But of course the problem is that, you know, those

641
00:32:48,360 --> 00:32:51,440
Speaker 5: price increases aren't sort of a static thing. They tend

642
00:32:51,440 --> 00:32:54,840
Speaker 5: to move around quite a lot, and so it's seasons

643
00:32:54,920 --> 00:32:58,280
Speaker 5: never quite are able to capture it in that first go.

644
00:32:58,800 --> 00:33:01,560
Speaker 5: It's only sort of several years later when the seasonals

645
00:33:01,600 --> 00:33:04,120
Speaker 5: are kind of redone on those particular years where that

646
00:33:04,560 --> 00:33:07,920
Speaker 5: effect kind of compresses in January. But we saw it,

647
00:33:08,040 --> 00:33:10,160
Speaker 5: you know, this year for sure, where we had some

648
00:33:10,240 --> 00:33:13,840
Speaker 5: big moves. What was really interesting though, so typically residual seasonality.

649
00:33:13,880 --> 00:33:17,400
Speaker 5: The way it works is that first quarter the Q

650
00:33:17,520 --> 00:33:20,400
Speaker 5: one data is typically stronger than the rest of the year.

651
00:33:21,480 --> 00:33:25,160
Speaker 5: Two thirds of that strength is in core goods and

652
00:33:25,280 --> 00:33:27,000
Speaker 5: only about a third of it is coming from the

653
00:33:27,040 --> 00:33:29,560
Speaker 5: services categories, which makes a bit of sense when you

654
00:33:29,600 --> 00:33:33,120
Speaker 5: think about you know, delivery cost changing for shipping goods

655
00:33:33,200 --> 00:33:36,960
Speaker 5: items across the country and from overseas. That gets worked

656
00:33:36,960 --> 00:33:39,040
Speaker 5: into new contracts at the start of the year for goods.

657
00:33:39,280 --> 00:33:42,600
Speaker 5: What was really peculiar this year though, is that goods

658
00:33:42,640 --> 00:33:45,720
Speaker 5: really didn't do much, you know, core goods, even excluding autos.

659
00:33:46,320 --> 00:33:49,640
Speaker 5: All the strength was really in the services categories. And

660
00:33:50,320 --> 00:33:52,640
Speaker 5: that's what really kind of stood out this January was

661
00:33:53,040 --> 00:33:55,680
Speaker 5: it wasn't the traditional you know, it wasn't your your

662
00:33:55,680 --> 00:33:58,719
Speaker 5: father's residual seasonality. This was something a little bit different

663
00:33:59,080 --> 00:34:02,040
Speaker 5: because it was so heavily focused on the services side.

664
00:34:02,160 --> 00:34:03,600
Speaker 5: And so that's something I think we just need to

665
00:34:03,600 --> 00:34:06,320
Speaker 5: be careful of going forward. Is normally, when you think

666
00:34:06,360 --> 00:34:08,920
Speaker 5: about residual seasonality, you say, okay, you know, so January

667
00:34:08,920 --> 00:34:11,839
Speaker 5: Febry effect, once we get into the second quarter, it'll

668
00:34:11,880 --> 00:34:13,919
Speaker 5: go way. And if it was in core goods again

669
00:34:13,960 --> 00:34:15,680
Speaker 5: this January, I would have said, yes, that's probably the

670
00:34:15,760 --> 00:34:18,040
Speaker 5: right take, but I would just say there's maybe a

671
00:34:18,080 --> 00:34:20,759
Speaker 5: little bit more caution here needed because it wasn't in

672
00:34:20,840 --> 00:34:23,279
Speaker 5: core goods, it was in core services. So I think

673
00:34:23,280 --> 00:34:24,680
Speaker 5: that's just something we need to be a little bit

674
00:34:24,719 --> 00:34:27,440
Speaker 5: careful of, you know, thinking about the data going forward.

675
00:34:27,480 --> 00:34:30,600
Speaker 4: And something that may be an extension of Omer's point here. Right,

676
00:34:30,640 --> 00:34:33,799
Speaker 4: So in Omere's time about course services and CPI, this

677
00:34:33,920 --> 00:34:37,520
Speaker 4: is exactly where thinking about the wedge is especially important

678
00:34:37,600 --> 00:34:40,839
Speaker 4: because when you think about the particular prices that are

679
00:34:40,880 --> 00:34:44,920
Speaker 4: of relevance for PCE, once you get outside of goods

680
00:34:45,040 --> 00:34:48,040
Speaker 4: and housing and goods and called rent and owners equivalent

681
00:34:48,080 --> 00:34:51,799
Speaker 4: front specifically, there's a pretty big divergence between what you

682
00:34:51,880 --> 00:34:55,799
Speaker 4: learn from CPI, especially in that kind of supercre core

683
00:34:55,920 --> 00:35:00,960
Speaker 4: non housing services CPI is very different from core non

684
00:35:01,000 --> 00:35:04,759
Speaker 4: housing services pc and they're just like where you talked

685
00:35:04,760 --> 00:35:08,280
Speaker 4: about any impeded financial services as being one goofy example,

686
00:35:08,440 --> 00:35:11,600
Speaker 4: but there are other examples, including vehicle insurance and airfares,

687
00:35:11,800 --> 00:35:14,719
Speaker 4: where they're just measured in different ways, and so the

688
00:35:14,840 --> 00:35:17,840
Speaker 4: residual seasonality that shows up in one part of service

689
00:35:17,920 --> 00:35:22,240
Speaker 4: a core service CPI segment doesn't necessarily have a neat cognate,

690
00:35:22,920 --> 00:35:23,600
Speaker 4: but how are they.

691
00:35:23,560 --> 00:35:29,600
Speaker 2: Measured differently those categories in the two indices, which categories

692
00:35:29,600 --> 00:35:31,719
Speaker 2: well you said, I think you said, airferers and motor

693
00:35:31,760 --> 00:35:34,720
Speaker 2: vehicle insurance are measured differently.

694
00:35:34,640 --> 00:35:39,320
Speaker 4: So more vehicle insurance, for example, is more directly to

695
00:35:39,560 --> 00:35:42,000
Speaker 4: insurance products in general. And CPI is really about a

696
00:35:42,000 --> 00:35:44,760
Speaker 4: function of payment and what's really the out of pocket

697
00:35:44,800 --> 00:35:47,919
Speaker 4: costs to the consumer conceptually, so it's really tracking that

698
00:35:48,440 --> 00:35:50,920
Speaker 4: in real time. And obviously right now you have a

699
00:35:50,920 --> 00:35:55,000
Speaker 4: lot of state by state insurance companies are pushing for

700
00:35:55,400 --> 00:35:58,319
Speaker 4: regulators to allow them to charge higher premiums for auto

701
00:35:58,320 --> 00:36:00,799
Speaker 4: insurance after a sort of a psychal of I think,

702
00:36:00,880 --> 00:36:03,800
Speaker 4: a lack of profitability relative to the cost and expenses

703
00:36:03,880 --> 00:36:07,840
Speaker 4: of for insure, whereas for vehicle and for insurance products

704
00:36:07,840 --> 00:36:10,439
Speaker 4: and PCE, it's really about the value that is trying

705
00:36:10,480 --> 00:36:13,160
Speaker 4: to proxy or capture, right, So the value to the

706
00:36:13,160 --> 00:36:15,520
Speaker 4: consumer is a function of not just what you pay,

707
00:36:15,560 --> 00:36:17,520
Speaker 4: but also what third parties are paying and what you're

708
00:36:17,520 --> 00:36:19,200
Speaker 4: getting back in terms of the expenses that have to

709
00:36:19,239 --> 00:36:21,200
Speaker 4: be covered. So they do tell you different things there.

710
00:36:21,719 --> 00:36:24,560
Speaker 4: Vehicle insurance in PCE has been much more benign. It

711
00:36:24,560 --> 00:36:28,640
Speaker 4: comes from a PPI segment, whereas vehicle insurance in CPI

712
00:36:28,760 --> 00:36:31,000
Speaker 4: has been very strong, and so that's like one part

713
00:36:31,000 --> 00:36:34,239
Speaker 4: of the divergence. Then there's another one. Airfares is actually

714
00:36:34,280 --> 00:36:36,120
Speaker 4: a function of I think American really speak to this

715
00:36:36,200 --> 00:36:40,239
Speaker 4: with high expertise here, but the CPI is tracking very

716
00:36:40,239 --> 00:36:43,479
Speaker 4: specific routes and trying to track them systematically over time

717
00:36:43,640 --> 00:36:45,200
Speaker 4: in terms of how much cost to be able to

718
00:36:45,239 --> 00:36:49,160
Speaker 4: fly from one place another different categories of seats on airplanes,

719
00:36:49,560 --> 00:36:54,719
Speaker 4: but in PPI it's meant to reflect sort of the

720
00:36:54,800 --> 00:36:58,279
Speaker 4: revenue for passenger mile and it tends to have a

721
00:36:58,320 --> 00:37:00,760
Speaker 4: little more of an upward bias actually electric to CPI.

722
00:37:00,920 --> 00:37:05,000
Speaker 4: So PPI and PPI for airfares has gaily run stronger

723
00:37:05,040 --> 00:37:08,439
Speaker 4: than CPI and especially so so despite the wedge blowing out,

724
00:37:08,480 --> 00:37:11,200
Speaker 4: it hasn't been a function of airfares as much as

725
00:37:11,239 --> 00:37:12,040
Speaker 4: other categories.

726
00:37:12,440 --> 00:37:13,879
Speaker 6: But I'll let when expand.

727
00:37:13,600 --> 00:37:15,879
Speaker 5: Further here, well, I'm just going to actually quickly put

728
00:37:15,880 --> 00:37:18,920
Speaker 5: some numbers on the auto insurance thing, because yes, the

729
00:37:18,960 --> 00:37:21,160
Speaker 5: methodologies are different, but to give you some sense of it,

730
00:37:21,600 --> 00:37:24,040
Speaker 5: auto insurance and the CPI right now year of year

731
00:37:24,080 --> 00:37:27,000
Speaker 5: is running at about twenty one percent in the pc

732
00:37:27,160 --> 00:37:31,120
Speaker 5: is running at about eight point seven. So you know,

733
00:37:31,200 --> 00:37:34,560
Speaker 5: methodologies are different. They produce vastly different numbers and growth

734
00:37:34,640 --> 00:37:37,719
Speaker 5: rates for these two indexes. So given their weightings, you're

735
00:37:37,719 --> 00:37:40,360
Speaker 5: going to have just, you know, a very different influence

736
00:37:40,960 --> 00:37:43,759
Speaker 5: of what is a Sensibly, it seems like on the

737
00:37:43,760 --> 00:37:47,120
Speaker 5: surface the same thing auto insurance, but the different measurement

738
00:37:47,480 --> 00:37:50,479
Speaker 5: is resulting in just vastly different growth rates, which means

739
00:37:50,520 --> 00:37:53,680
Speaker 5: its impact on the core and core services overall is

740
00:37:53,680 --> 00:37:56,360
Speaker 5: also just going to be hugely different. So that hopefully,

741
00:37:56,400 --> 00:37:58,880
Speaker 5: you know, kind of gives some context around what the

742
00:37:58,920 --> 00:38:02,480
Speaker 5: difference in methodology can mean for the growth rates around

743
00:38:02,520 --> 00:38:05,160
Speaker 5: these these particular items. On airfares, Yeah, you know, it's

744
00:38:05,160 --> 00:38:08,120
Speaker 5: gonna mention it's the CPI is basically very much just

745
00:38:08,800 --> 00:38:12,440
Speaker 5: a weighted average of routes you know, Chicago, La, La,

746
00:38:12,560 --> 00:38:15,520
Speaker 5: to Vegas, what have you, and is very much just

747
00:38:15,560 --> 00:38:18,719
Speaker 5: capturing directly from the carrier's website what it is that

748
00:38:18,760 --> 00:38:22,840
Speaker 5: you're paying for that flight and also the cost of

749
00:38:22,920 --> 00:38:27,480
Speaker 5: the first checkback, and the ppi's you know, is also

750
00:38:27,560 --> 00:38:30,880
Speaker 5: looking at these routes, but looking at the overall revenue

751
00:38:30,880 --> 00:38:34,560
Speaker 5: for passenger mile ascutamension, so month to month they can

752
00:38:34,600 --> 00:38:37,640
Speaker 5: actually differ quite a bit. Over the longer term, the

753
00:38:37,760 --> 00:38:40,360
Speaker 5: trends directionally, they tend to be in the same direction,

754
00:38:40,920 --> 00:38:44,480
Speaker 5: but it can cause you know, variability on a month

755
00:38:44,480 --> 00:38:46,600
Speaker 5: to month basis, where you could have the CPI, for example,

756
00:38:46,680 --> 00:38:49,719
Speaker 5: up three four percent and the PPI actually down a

757
00:38:49,719 --> 00:38:52,320
Speaker 5: couple of percentage points. So on a month to month basis,

758
00:38:52,360 --> 00:38:53,680
Speaker 5: you do have to be sort of be aware of

759
00:38:53,680 --> 00:38:56,759
Speaker 5: what these differences are because they can produce you know,

760
00:38:57,200 --> 00:39:00,960
Speaker 5: pretty different results and pretty different impacts on the relative course.

761
00:39:02,000 --> 00:39:04,520
Speaker 4: Yeah, airfares is a really big one from the CPI,

762
00:39:04,680 --> 00:39:08,680
Speaker 4: just because it's so volatile in the CPI and you'll

763
00:39:08,680 --> 00:39:12,400
Speaker 4: typically hear right afterwards, well, core services X housing CPI

764
00:39:12,719 --> 00:39:15,839
Speaker 4: was really strong or really soft, and it's driven by

765
00:39:15,840 --> 00:39:18,560
Speaker 4: airfares and that just doesn't have the sort of bearing

766
00:39:18,600 --> 00:39:22,399
Speaker 4: on that sort of supercre pcee component because that's coming

767
00:39:22,400 --> 00:39:24,480
Speaker 4: from BPI and you learned that usually only a day

768
00:39:24,520 --> 00:39:24,920
Speaker 4: OFCU latter.

769
00:39:25,520 --> 00:39:27,239
Speaker 5: I can't tell you over the years the amount of

770
00:39:28,000 --> 00:39:30,319
Speaker 5: time and money I've spent trying to get airfares right.

771
00:39:30,360 --> 00:39:31,960
Speaker 5: And it's worth like less than one percent of the

772
00:39:32,000 --> 00:39:35,120
Speaker 5: core CPI because you know, again the volatility, it could

773
00:39:35,120 --> 00:39:38,080
Speaker 5: be up eight percent, down eight percent, and so it

774
00:39:38,120 --> 00:39:40,480
Speaker 5: can add or subtract you know, five to ten basis

775
00:39:40,480 --> 00:39:43,719
Speaker 5: points each month from the core and so getting that,

776
00:39:43,880 --> 00:39:45,759
Speaker 5: you know, it's just one of these high volatility ones

777
00:39:45,800 --> 00:39:48,080
Speaker 5: where yes, it's not worth a lot, but the magnitude

778
00:39:48,080 --> 00:39:51,080
Speaker 5: of the moves is so great that it just demands

779
00:39:51,120 --> 00:39:53,440
Speaker 5: a lot of attention, you know, like hotel rates as well,

780
00:39:53,520 --> 00:39:53,920
Speaker 5: same thing.

781
00:39:54,280 --> 00:39:58,040
Speaker 3: Gosh, darn airlines and their dynamic pricing. So we mentioned

782
00:39:58,080 --> 00:40:01,879
Speaker 3: earlier that we're recording this episode right before PCE comes out.

783
00:40:01,880 --> 00:40:04,000
Speaker 3: Can I put you both on the spot and ask

784
00:40:04,080 --> 00:40:06,120
Speaker 3: you for PCE guesses.

785
00:40:06,840 --> 00:40:09,919
Speaker 5: I am probably I think a little bit below some

786
00:40:09,960 --> 00:40:13,400
Speaker 5: of those, so most most of I guess the forecasters

787
00:40:13,400 --> 00:40:16,160
Speaker 5: I would want to follow, or right around point four zero.

788
00:40:16,480 --> 00:40:19,600
Speaker 5: I'm a touch lower at point three six. I think

789
00:40:19,440 --> 00:40:23,359
Speaker 5: the difference is just assumptions about imputed prices that people

790
00:40:23,400 --> 00:40:27,040
Speaker 5: are making. But on the super Core PCEE, I'm expecting

791
00:40:27,080 --> 00:40:29,600
Speaker 5: a point five so that is going to be, you know,

792
00:40:29,760 --> 00:40:32,960
Speaker 5: pretty strong print. I think obviously in the core CPI

793
00:40:33,080 --> 00:40:35,600
Speaker 5: we had about a point eighty five. But yeah, I

794
00:40:35,600 --> 00:40:37,360
Speaker 5: think it's going to be a relatively firm print. The

795
00:40:37,360 --> 00:40:40,400
Speaker 5: PPI data was strong, the CPI data was strong, so

796
00:40:40,400 --> 00:40:42,120
Speaker 5: at least for January, it looks like we're going to

797
00:40:42,120 --> 00:40:45,160
Speaker 5: get a pretty robust move in the PC data.

798
00:40:45,320 --> 00:40:45,560
Speaker 6: Yeah.

799
00:40:45,640 --> 00:40:48,600
Speaker 4: This is actually coincidental because I'm not sharing my work

800
00:40:48,640 --> 00:40:50,759
Speaker 4: at OMERE on these things. But we end up in

801
00:40:50,800 --> 00:40:53,239
Speaker 4: the same place on both core PC being point three

802
00:40:53,280 --> 00:40:56,200
Speaker 4: six percent and super core for myself point five zero percent.

803
00:40:56,400 --> 00:40:58,120
Speaker 4: But I also will not like for at least on

804
00:40:58,200 --> 00:41:01,520
Speaker 4: the year reading. Something to be pre is there's also revisions,

805
00:41:01,840 --> 00:41:04,760
Speaker 4: So while some people might have higher month over month readings,

806
00:41:04,760 --> 00:41:06,440
Speaker 4: they may not also reflect the fact that there are

807
00:41:06,920 --> 00:41:10,319
Speaker 4: reasons for revisions to prior months. So for example, and

808
00:41:10,320 --> 00:41:12,040
Speaker 4: it's something I think also om er Vi here to

809
00:41:12,080 --> 00:41:15,400
Speaker 4: talk about too, which is financial services prices now not

810
00:41:15,440 --> 00:41:17,640
Speaker 4: the imputed ones, but the ones that we that are

811
00:41:17,920 --> 00:41:21,840
Speaker 4: more measureable. Those prices also kind of factor into revisions,

812
00:41:21,880 --> 00:41:24,480
Speaker 4: and those are why I suspect that we're probably going

813
00:41:24,560 --> 00:41:27,080
Speaker 4: to see more shallow inflation progress. So if we kind

814
00:41:27,080 --> 00:41:30,040
Speaker 4: of were around high two point nine percent, low three

815
00:41:30,080 --> 00:41:32,760
Speaker 4: percent last month, that's actually going to bump.

816
00:41:32,600 --> 00:41:34,920
Speaker 2: Up a bit. And yeah, real quickly.

817
00:41:35,000 --> 00:41:36,359
Speaker 4: The same time we're going to see two point eight

818
00:41:36,360 --> 00:41:38,480
Speaker 4: eight percent for COREBC.

819
00:41:38,280 --> 00:41:39,840
Speaker 2: Real quickly. I'm glad you said this is going to

820
00:41:39,840 --> 00:41:43,439
Speaker 2: be my last question. Explain measured financial services. So when

821
00:41:43,520 --> 00:41:46,760
Speaker 2: stocks go up, measures of inflation go up. Correct.

822
00:41:46,840 --> 00:41:50,719
Speaker 4: So first approximation, measured measured financial services are a lot

823
00:41:50,719 --> 00:41:55,520
Speaker 4: of the portfolio management services that consumers are effectively consuming,

824
00:41:55,920 --> 00:41:59,200
Speaker 4: and those the way they're measured, tend to in the

825
00:41:59,280 --> 00:42:02,399
Speaker 4: aggregate kind of proxy what the equity market's doing how much,

826
00:42:02,400 --> 00:42:04,080
Speaker 4: So can vary a little bit over time, but the

827
00:42:04,120 --> 00:42:06,120
Speaker 4: equity market doesn' matter. So the equity market's been up

828
00:42:06,280 --> 00:42:09,399
Speaker 4: a bunch over the last few months, and that has

829
00:42:09,480 --> 00:42:12,360
Speaker 4: taken time to really show open the PPI data, but

830
00:42:12,480 --> 00:42:15,160
Speaker 4: it has, and that PPI data kind of is relevant

831
00:42:15,200 --> 00:42:16,960
Speaker 4: for sort of PC purposes.

832
00:42:17,200 --> 00:42:21,000
Speaker 5: Yeah, and in the PC, that Portfolio Management index is

833
00:42:21,360 --> 00:42:24,400
Speaker 5: you know, it added quite a bit to the generary

834
00:42:24,520 --> 00:42:27,680
Speaker 5: core PCE number. I think it's going to add something

835
00:42:27,680 --> 00:42:30,160
Speaker 5: like eight basis points to that number alone, and that

836
00:42:30,280 --> 00:42:32,880
Speaker 5: is mostly a reflection of how the equity market did

837
00:42:33,320 --> 00:42:35,680
Speaker 5: in Q four, so up around I think SMP was

838
00:42:35,719 --> 00:42:39,399
Speaker 5: something like twelve thirteen percent higher. That pretty much goes

839
00:42:39,440 --> 00:42:45,720
Speaker 5: into you know, the returns that are reported to the BLS.

840
00:42:46,000 --> 00:42:48,600
Speaker 5: So these equity returns from you know, mutual funds and

841
00:42:48,640 --> 00:42:51,879
Speaker 5: ETFs and private portfolio managers. They come back and say, hey,

842
00:42:51,920 --> 00:42:54,440
Speaker 5: we did great in Q four. Here are numbers that

843
00:42:54,480 --> 00:42:57,160
Speaker 5: gets built into the PPI data, which then flows into

844
00:42:57,200 --> 00:42:59,879
Speaker 5: the PCE. And so you know, the index is worth

845
00:43:00,120 --> 00:43:02,359
Speaker 5: one and a half percent. But when you're up five

846
00:43:02,360 --> 00:43:05,040
Speaker 5: percent or so roughly as it was last month, you're

847
00:43:05,040 --> 00:43:07,239
Speaker 5: gonna get a big pop in the core PCE. So

848
00:43:07,719 --> 00:43:09,960
Speaker 5: that's that's likely what you know we already saw into

849
00:43:09,960 --> 00:43:11,719
Speaker 5: PPI and that's what's going to feed into the pce

850
00:43:12,040 --> 00:43:14,280
Speaker 5: SO equities. You matter quite a bit for that number.

851
00:43:14,840 --> 00:43:17,759
Speaker 2: All right, Well, this episode comes out at four a m.

852
00:43:18,040 --> 00:43:20,239
Speaker 2: Eastern on the twenty nine, so people have four and

853
00:43:20,280 --> 00:43:23,360
Speaker 2: a half hours to listen to it and then you know,

854
00:43:23,600 --> 00:43:27,320
Speaker 2: understand what's gonna come out at eight thirty a m. Eastern.

855
00:43:27,560 --> 00:43:30,080
Speaker 2: Omeer and Sconda, thank you so much for coming on.

856
00:43:30,160 --> 00:43:32,520
Speaker 2: That was fascinating. We want to do more of these

857
00:43:32,560 --> 00:43:35,440
Speaker 2: episodes where we actually learn about the data that we

858
00:43:35,480 --> 00:43:37,520
Speaker 2: talk about all the time. But appreciate you both for

859
00:43:37,600 --> 00:43:39,319
Speaker 2: coming back on the oblawnch thank you.

860
00:43:39,440 --> 00:43:51,960
Speaker 6: Thanks for having us.

861
00:43:52,920 --> 00:43:56,560
Speaker 2: Tracy, I phound that to be a really interesting conversation.

862
00:43:56,640 --> 00:43:59,759
Speaker 2: I have to say, you know, the cranks will hate

863
00:43:59,760 --> 00:44:02,919
Speaker 2: me for this. I have a lot of admiration for

864
00:44:03,000 --> 00:44:06,040
Speaker 2: the public officials, the bureaucrats, the economists is at the

865
00:44:06,080 --> 00:44:08,839
Speaker 2: BLS and BEE who have BA who have to like

866
00:44:08,920 --> 00:44:11,680
Speaker 2: assemble all this stuff and figure out, like you know,

867
00:44:12,120 --> 00:44:16,920
Speaker 2: the different ways of measuring airline costs and portfolio management costs.

868
00:44:16,920 --> 00:44:17,880
Speaker 2: It doesn't seem easy.

869
00:44:18,000 --> 00:44:20,040
Speaker 3: I think that's a totally fair thing.

870
00:44:20,120 --> 00:44:20,479
Speaker 2: To say.

871
00:44:20,520 --> 00:44:22,920
Speaker 3: The other thing I would say is like the people

872
00:44:23,040 --> 00:44:26,760
Speaker 3: doing this, at least at the BLS are really responsive

873
00:44:27,040 --> 00:44:30,680
Speaker 3: to inquiries and omayor would be able to talk about

874
00:44:30,680 --> 00:44:32,239
Speaker 3: this and maybe we should have asked him. But if

875
00:44:32,280 --> 00:44:35,520
Speaker 3: you send them a question and ask I did this

876
00:44:35,560 --> 00:44:37,799
Speaker 3: for that mayonnaise story and ask them like, how are

877
00:44:37,800 --> 00:44:41,160
Speaker 3: you calculating this particular line item, they won't get back

878
00:44:41,200 --> 00:44:42,600
Speaker 3: to you and they'll get on the phone with you

879
00:44:42,640 --> 00:44:44,280
Speaker 3: and explain it for like twenty minutes.

880
00:44:44,400 --> 00:44:47,160
Speaker 2: This is true and actually listeners should.

881
00:44:47,239 --> 00:44:49,719
Speaker 3: Know this that if you don't flood the BLS with

882
00:44:49,760 --> 00:44:51,200
Speaker 3: the don'ts.

883
00:44:51,400 --> 00:44:54,319
Speaker 2: But when you see someone and you see something, they're like, oh,

884
00:44:54,360 --> 00:44:56,920
Speaker 2: this is people like this is crazy, look what they

885
00:44:57,000 --> 00:45:00,839
Speaker 2: hid in this area. They're very transparent and this is true.

886
00:45:00,880 --> 00:45:02,840
Speaker 2: They'll call You can call them up and they'll say

887
00:45:03,000 --> 00:45:05,400
Speaker 2: this is what this is how it works. So Tracey

888
00:45:05,440 --> 00:45:08,160
Speaker 2: is making an excellent point. No one's going to take

889
00:45:08,239 --> 00:45:11,640
Speaker 2: us up on that because people prefer to believe conspiracy theories.

890
00:45:11,920 --> 00:45:14,360
Speaker 2: But if you see something that see they will respond.

891
00:45:14,520 --> 00:45:16,600
Speaker 3: If you see something, say something, you.

892
00:45:16,360 --> 00:45:18,839
Speaker 2: See something, if you see a weird number, call them

893
00:45:18,920 --> 00:45:21,359
Speaker 2: up and explain. They will explain how it came there.

894
00:45:21,400 --> 00:45:23,960
Speaker 3: Well, the other thing that comes out of that conversation,

895
00:45:24,080 --> 00:45:26,920
Speaker 3: and again I thought both Scanda and Omer were incredibly

896
00:45:27,120 --> 00:45:30,360
Speaker 3: clear in laying out the difference in methodology. But really

897
00:45:30,440 --> 00:45:33,960
Speaker 3: the overarching theme is the amount of like subjectivity and

898
00:45:34,120 --> 00:45:37,799
Speaker 3: value decisions being made when it comes to how to

899
00:45:38,040 --> 00:45:41,799
Speaker 3: present this overall data. And you can get super granular

900
00:45:42,000 --> 00:45:44,440
Speaker 3: on this and think about all these things that are

901
00:45:44,480 --> 00:45:46,759
Speaker 3: sort of hidden in the background. But I remember there's

902
00:45:46,800 --> 00:45:49,960
Speaker 3: stuff like, you know, the waiting of certain items is

903
00:45:50,080 --> 00:45:53,399
Speaker 3: different depending on where you are in the country. There's

904
00:45:53,400 --> 00:45:57,960
Speaker 3: also qualitative adjustments. So you know, your refrigerator, maybe the

905
00:45:58,000 --> 00:46:01,239
Speaker 3: price is declining, but now how it comes with Wi Fi,

906
00:46:01,480 --> 00:46:04,719
Speaker 3: and so you have to incorporate that qualitative judgment as well.

907
00:46:05,040 --> 00:46:05,200
Speaker 5: Well.

908
00:46:05,239 --> 00:46:06,680
Speaker 2: You know in some of these things that know Mayor

909
00:46:06,719 --> 00:46:08,960
Speaker 2: made this point about, I think in one of the

910
00:46:09,000 --> 00:46:12,200
Speaker 2: insurance categories about how CPI and PC are different. So

911
00:46:12,200 --> 00:46:15,080
Speaker 2: you could imagine, you know, let's say someone pays I

912
00:46:15,080 --> 00:46:18,640
Speaker 2: don't know, one hundred dollars a month for car insurance

913
00:46:18,680 --> 00:46:20,759
Speaker 2: and then the next month, you know, the next year

914
00:46:21,040 --> 00:46:22,799
Speaker 2: it goes up to one hundred and ten, so that's

915
00:46:22,800 --> 00:46:26,400
Speaker 2: a ten percent increase. But you know, let's say that

916
00:46:26,600 --> 00:46:29,280
Speaker 2: in that second year, you know, you're getting one hundred

917
00:46:29,280 --> 00:46:32,440
Speaker 2: and seven dollars back every month equivalently, and repairs for

918
00:46:32,480 --> 00:46:34,879
Speaker 2: your car in the previous year, you're early getting ninety. Well,

919
00:46:34,880 --> 00:46:38,760
Speaker 2: maybe arguably your insurance just got cheaper because the amount

920
00:46:38,800 --> 00:46:41,000
Speaker 2: you're getting back relative to the amount you're paying is

921
00:46:41,080 --> 00:46:44,440
Speaker 2: so much higher. And so you could see immediately how

922
00:46:44,640 --> 00:46:47,520
Speaker 2: something that's very important, insurance, huge parts of the economy,

923
00:46:47,760 --> 00:46:53,680
Speaker 2: becomes incredibly difficult to measure when you're trying to gauge, like, well,

924
00:46:54,080 --> 00:46:55,640
Speaker 2: are you just trying to gauge how much you pay,

925
00:46:55,960 --> 00:46:58,000
Speaker 2: or are you trying to gauge how much you paid

926
00:46:58,040 --> 00:47:01,440
Speaker 2: relative to the value of the service received, which is

927
00:47:01,480 --> 00:47:03,239
Speaker 2: going to be you know, a change based on the

928
00:47:03,320 --> 00:47:06,120
Speaker 2: value of your car and the difficulty of obtaining the

929
00:47:06,160 --> 00:47:08,520
Speaker 2: replacement components. It's really tricky stuff.

930
00:47:08,800 --> 00:47:11,720
Speaker 3: Well, I also like Scanda's point on this note about

931
00:47:11,719 --> 00:47:16,640
Speaker 3: deposit betas, and yeah, I know, I feel like we

932
00:47:16,640 --> 00:47:19,040
Speaker 3: should end this before we start talking about how gas

933
00:47:19,080 --> 00:47:22,239
Speaker 3: prices going down is actually inflationary. I think people spend more.

934
00:47:22,320 --> 00:47:24,040
Speaker 2: I think you're gonna say we should end this before

935
00:47:24,080 --> 00:47:26,120
Speaker 2: I suggest that we should be paying our banks for

936
00:47:26,239 --> 00:47:28,319
Speaker 2: checking well that too, but you know it really clicked

937
00:47:28,320 --> 00:47:30,400
Speaker 2: because you know, we had that episode with Steve Stephen

938
00:47:30,480 --> 00:47:32,120
Speaker 2: Kelly and I was like, well, what is the service

939
00:47:32,160 --> 00:47:33,680
Speaker 2: of a bank? And He's like, the service of a

940
00:47:33,719 --> 00:47:35,879
Speaker 2: bank is deposits. And that's why you get a sub.

941
00:47:36,280 --> 00:47:38,360
Speaker 2: You get that cheap rate because they're providing your service.

942
00:47:38,560 --> 00:47:42,960
Speaker 2: So there is this sort of intellectual logic behind Okay,

943
00:47:43,000 --> 00:47:46,359
Speaker 2: you're getting two percent rates for your checking account, FED

944
00:47:46,360 --> 00:47:50,600
Speaker 2: funds in five percent, therefore implicitly that you're paying you know,

945
00:47:50,719 --> 00:47:53,680
Speaker 2: you're paying three percent for those checking services and all

946
00:47:53,719 --> 00:47:56,120
Speaker 2: those other things. But yeah, these are tricky things to measure,

947
00:47:56,280 --> 00:47:58,600
Speaker 2: but it is funny how mechanically, just like the FED

948
00:47:58,719 --> 00:48:02,759
Speaker 2: raising rates and increasing, uh, that gap between rates and

949
00:48:03,120 --> 00:48:06,640
Speaker 2: deposit rates just sort of mechanically increases measured inflation.

950
00:48:06,880 --> 00:48:09,480
Speaker 3: Joe, you're about one connection away from breaking out the

951
00:48:09,560 --> 00:48:10,800
Speaker 3: yield bug hat again.

952
00:48:11,520 --> 00:48:13,840
Speaker 2: So I'm like, I'm like that, what's that what's that

953
00:48:14,000 --> 00:48:16,680
Speaker 2: meme of the guy? Oh yeah, I think it's it's

954
00:48:16,719 --> 00:48:19,359
Speaker 2: always sunny. Yeah, Philadelphia, That's where I'm right now.

955
00:48:19,719 --> 00:48:20,960
Speaker 3: Okay, shall we leave it there.

956
00:48:21,000 --> 00:48:21,719
Speaker 2: Let's leave it there.

957
00:48:21,840 --> 00:48:24,719
Speaker 3: This has been another episode of the Authoughts podcast. I'm

958
00:48:24,760 --> 00:48:27,960
Speaker 3: Tracy Alloway. You can follow me at Tracy Alloway and I'm.

959
00:48:27,880 --> 00:48:30,320
Speaker 2: Joe Wisen though you could follow me at the Stalwart.

960
00:48:30,560 --> 00:48:33,719
Speaker 2: Follow our guests OMAYR. Sharif he's at f Cast of

961
00:48:33,760 --> 00:48:37,200
Speaker 2: the Month and Sconda Amernath at Irving Swisher. Follow our

962
00:48:37,239 --> 00:48:40,920
Speaker 2: producers Carmen Rodriguez at Carmen Ermann, dash, Ol Bennett at

963
00:48:41,000 --> 00:48:44,080
Speaker 2: Dashbot and kel Brooks at kel Brooks. Thank you to

964
00:48:44,120 --> 00:48:47,040
Speaker 2: our producer Moses on them From our odd Loads content.

965
00:48:47,080 --> 00:48:50,279
Speaker 2: Go to Bloomberg dot com slash odd Lots for transcripts,

966
00:48:50,320 --> 00:48:53,680
Speaker 2: blog and a newsletter, and you can chat with fellow

967
00:48:53,680 --> 00:48:56,680
Speaker 2: listeners twenty four to seven in the discord discord dot

968
00:48:56,719 --> 00:48:58,160
Speaker 2: gg slash offline.

969
00:48:58,640 --> 00:49:00,680
Speaker 3: And if you enjoy ad thloughts, if you like it

970
00:49:00,719 --> 00:49:03,480
Speaker 3: when we discuss the methodology behind some of the big

971
00:49:03,560 --> 00:49:05,839
Speaker 3: numbers that we talk about on a daily basis, then

972
00:49:05,880 --> 00:49:09,600
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973
00:49:10,160 --> 00:49:13,040
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974
00:49:13,080 --> 00:49:16,520
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975
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976
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