Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast.
Speaker 1: I'm Tracy Alloway and I'm Joe. Wisn't thal Joe. I
Speaker 1: feel like I'm gonna jinx things by saying this, But
Speaker 1: it feels like inflation is maybe starting to come down
Speaker 1: a little bit at least it's not accelerating. Let's put
Speaker 1: it that way. Well, here's how Here's what I've been
Speaker 1: thinking about, which is that for the last year, the
Speaker 1: last year and a half, we've done all of these episodes.
Speaker 1: I'm like supply chains and disruptions for this so that reason,
Speaker 1: and all of the various times we've used the term
Speaker 1: perfect storm to describe certain things in certain industries, perfect
Speaker 1: storm of perfect storms. My guess right now, you know,
Speaker 1: in January, is that episodes will be a little less
Speaker 1: dominated by these topics. That would be my guest. I'm
Speaker 1: guessing that this year we do a few fewer perfect
Speaker 1: storm episode. I think that's right. But I think, you know,
Speaker 1: we we spoke a lot about what it was that
Speaker 1: people didn't see coming when it comes to inflation. Why
Speaker 1: did a lot of economists get it wrong? Why was
Speaker 1: the inflation that was supposed to be transitory? You know,
Speaker 1: maybe it was transitory in the sense that it was narrow,
Speaker 1: you know, not a big sort of like macro unleashed inflation,
Speaker 1: but it definitely stuck around longer than a lot of
Speaker 1: people expected. And so every time we have these big
Speaker 1: questions like why aren't we better at forecasting inflation, it
Speaker 1: provides an opportunity to maybe learn something and start thinking
Speaker 1: about it in a slightly different way. Well, yeah, absolutely,
Speaker 1: And I would say there's really two things that I
Speaker 1: feel are unanswered by all of the conversations that we've
Speaker 1: had in the last year. So one is still like,
Speaker 1: is inflation like a macro or a micro thing didn't
Speaker 1: happen because a few categories really had some disruptions and
Speaker 1: then spilled elsewhere, And therefore it's not really about fiscal
Speaker 1: or monetary policy specifically. And be okay, we do have
Speaker 1: very high inflation right now, even if there's evidence coming down,
Speaker 1: what tools, like, if it is the case that a
Speaker 1: lot of it is related to disruptions and chip shortages
Speaker 1: and freezes in Texas, etcetera, what are the tools that
Speaker 1: are best to address that, because it is important to
Speaker 1: get inflation down. But on the other hand, there's a
Speaker 1: pretty good argument that if the issue is some sort
Speaker 1: of disruption at the ports or whatever, that sort of
Speaker 1: like strict blunt instruments like raising rates rates aren't necessarily
Speaker 1: the best approach to dealing with that kind of where
Speaker 1: raising rates won't grow more trees to turn into lumber
Speaker 1: and like that, or more births at the ports or
Speaker 1: anything like that. So I'm so glad you said that
Speaker 1: because today we are going to be speaking with one
Speaker 1: of our Odd Lots favorites, and she has just written
Speaker 1: a new paper which she says is inspired by some
Speaker 1: of the conversations that we've had on Odd Lots, but
Speaker 1: it's also just really interesting because it presents a new
Speaker 1: sort of third way potentially of thinking about inflation, not transitory,
Speaker 1: not persistent, a new more interesting third option, and that
Speaker 1: maybe could help us think about ways of accepting, Yes,
Speaker 1: inflation is real, it is a problem, but that some
Speaker 1: of these blunt instruments that just treat inflation as a
Speaker 1: function of there's too much money in the economy, we
Speaker 1: need there to be less. Maybe there are better approaches
Speaker 1: than just this sort of like blunt monetary approaches to
Speaker 1: addressing them. Absolutely, So without further ado, we are going
Speaker 1: to be speaking today to Isabella Vabor. She has, of
Speaker 1: course a economics professor over at the University of Massachusetts Amherst,
Speaker 1: and you might remember her from from some previous episodes.
Speaker 1: So Isabella, thank you so much for coming back on
Speaker 1: odd Lots. Thank you so much for having me. It's
Speaker 1: a pleasure. Thank you. So the paper is called Inflation
Speaker 1: in Times of overlapping emergencies systemically significant prices from an
Speaker 1: input output perspective. But I just want to get you
Speaker 1: to say on camera that this is inspired by all
Speaker 1: it is. I mean, I have been listening to your
Speaker 1: podcast or through the pandemic um and as you were
Speaker 1: just saying, obviously you have been tracing all these price
Speaker 1: shocks that have been rippling through the economy. So um,
Speaker 1: this paper is trying to come up with the framework
Speaker 1: to trace these shocks and ripple effects in a somewhat
Speaker 1: more aggregate and possibly less fine print, but maybe a
Speaker 1: little bit more like formal kind of fashion. I love
Speaker 1: that the most self serving first question we've ever asked
Speaker 1: on an interview, What is you know, what what is
Speaker 1: an input output approach mean? Because my understanding is that
Speaker 1: this is actually like a very old idea in economics.
Speaker 1: But that is some kind of has actually been forgotten,
Speaker 1: is my understanding, And that the sort of like various
Speaker 1: versions of monitorist thinking which sort of treat if prices
Speaker 1: are hive, we want to understand prices, well, just look
Speaker 1: at how much money or how much credit is in
Speaker 1: the economy. Rein that in and you've seen this paper
Speaker 1: seems to be like going back to like an older
Speaker 1: tradition in economics. Can you talk a little bit about
Speaker 1: what this is. Yeah, So, as we said, we tend
Speaker 1: to think about inflation as a micro phenomenon, right, where
Speaker 1: it's basically just about the movement of aggregate measures. Whereas
Speaker 1: what we're trying to do here is to think of
Speaker 1: prices as kind of an interconnected network where since one
Speaker 1: sector's output is another sector's input um, and therefore one
Speaker 1: sector's output prices at the cost of another sector UM,
Speaker 1: you can't kind of trace um the price movements across
Speaker 1: the whole production network, which input out put tables allow
Speaker 1: you to do. So. These tables basically like Rchester the
Speaker 1: relationships of input and outputs across the whole economy. Historically,
Speaker 1: UM input output tables really had a breakthrough during the
Speaker 1: War time UM. Where the question was, how can we
Speaker 1: hit the enemy's UM economy in ways that we kind
Speaker 1: of like, with the minimum number of bombs UM, create
Speaker 1: the maximal damage to really UM, I mean undermine UM
Speaker 1: the enemy economy's ability to even fight a war. I
Speaker 1: mean concretely. Of course, this is mainly about the German
Speaker 1: economy UM, and so therefore it really is a method
Speaker 1: of identifying points UM that are of particular systemic significance
Speaker 1: for the economy as a whole. Back then, the idea
Speaker 1: was to identify these points of vulnerability to UM, I mean,
Speaker 1: as I said, create destruction UM. The idea of our
Speaker 1: papers to say, if we can identify these points of vulnerabilities,
Speaker 1: then we can actually UM kind of UM know what
Speaker 1: what the potential sources of UM of these report effects
Speaker 1: that can create UM macro outcomes UM could be so
Speaker 1: if some prices matter more than others, we want to
Speaker 1: know what these prices are, and input output is one
Speaker 1: method of trying to identify these systemically significant sectors. So
Speaker 1: Tracy might take away from that is that in a
Speaker 1: war it makes more sense to say bomb and oil refinery,
Speaker 1: even a candy factory like it, right, Like if you're
Speaker 1: thinking about, well, what are these sectors that will have
Speaker 1: the biggest ripple effects across the economy, Then that would
Speaker 1: be the implication, Well, maybe we should talk about morale
Speaker 1: in that context. But no, okay, there's another there's another
Speaker 1: analogy um that you use in the paper, which is,
Speaker 1: you know, if you're trying to identify systemically important sources
Speaker 1: of inflation and maybe address them before they start actually
Speaker 1: contributing to price increases, it's kind of like trying to
Speaker 1: identify systemically important banks and then making sure that they,
Speaker 1: you know, hold more regulatory capital or maybe go under
Speaker 1: preempt of stress tests or things like that. Can you
Speaker 1: talk about, maybe, you know, before we get into policy solutions,
Speaker 1: can you talk about how that approach maybe differs to
Speaker 1: traditional ways of thinking about inflation, because you know, in
Speaker 1: my mind, there's really there's the money terrorist view it's
Speaker 1: all about the money supply, and then there's a sort
Speaker 1: of new Canesian view where it's more about you know,
Speaker 1: supply side and capacity and demand and things like that.
Speaker 1: Can you place this new approach in the context of
Speaker 1: those two older um ways of thinking about it so
Speaker 1: as different as like kind of monetarism and new caneskiness
Speaker 1: can be. They share the understanding that inflation is always
Speaker 1: driven by macroeconomic factors. Right now, what we are doing here,
Speaker 1: I mean bond case, it's the distance from from aggregate
Speaker 1: capacity utilization. In the other case, it's more that like
Speaker 1: classic story of too much money chasing too few goods.
Speaker 1: But still it's like trying to locate the the origins
Speaker 1: of inflation on the aggregate level. What we're trying to
Speaker 1: do here is to say, well, if there are micro
Speaker 1: origins of inflation, if shocks to specific sectors can matter
Speaker 1: in ways that they can unleash processes that actually unsettled
Speaker 1: the stability of prices overall, that we want to understand
Speaker 1: what these sectors are. We want to know where these
Speaker 1: points of vulnerability are so that we can react to
Speaker 1: these shocks before they kind of ripple throughout the whole system.
Speaker 1: And as you said, um interest rates are already being
Speaker 1: recognized as a systemically significant kind of price, right That's
Speaker 1: why we have central banks, which of course historically at
Speaker 1: some point was also not the case. So it was
Speaker 1: a historical evolution to recognize the systemic significance of interest rates.
Speaker 1: In some sense, what we are arguing here is to
Speaker 1: um is to say that there are more prices than
Speaker 1: the price of boring money that can acquire systemic significance
Speaker 1: in bays, that can have a very large implications for
Speaker 1: monitor stability. Just a shout, I'll be drawn here on
Speaker 1: the workous of salad Amarova, who has been working on
Speaker 1: systemically significant price what someone else We definitely have to
Speaker 1: have on the podcast at some point. It's so funny
Speaker 1: because you know, of course, and we talked about this
Speaker 1: the last time you're on late last year. You took
Speaker 1: a lot of heat for saying, well, maybe there's a
Speaker 1: time for having some discussion about price controls, and everyone
Speaker 1: freaked out about that. And yet they're like, Okay, now
Speaker 1: let's control the price of money, as if that isn't
Speaker 1: a form of price control. And yet of course central
Speaker 1: banking ultimate price control, the ultimate price control. But you know,
Speaker 1: so I joked, but I guess it's not really joked that, Like,
Speaker 1: there are some areas where it's kind of obvious that
Speaker 1: some sort of some functions in the economy are more
Speaker 1: crucial to other industries than others. So an oil refinery
Speaker 1: is going to be more crucial to other industries than
Speaker 1: a candy factory. But that's obvious. How do you go
Speaker 1: about systematically identifying beyond the sort of really crude examples.
Speaker 1: What is this? This sort of like a rigorous or
Speaker 1: empirical approach to actually identifying what parts of the economy
Speaker 1: are in fact the most likely to have ripple effects elsewhere. So,
Speaker 1: but what we have done in this paper is that
Speaker 1: we have simulated shocks to every industry in the input
Speaker 1: out the table, and just for orientation, seventy one industry.
Speaker 1: So it's not super disaggregated, I mean also not super
Speaker 1: aggregate compared to microeconomic variables, but it's the fairly broad right.
Speaker 1: So we run a shock on each of these sectors,
Speaker 1: and then we simulate how this shock runs through the
Speaker 1: whole economy, reciting in an indirect impact on on on
Speaker 1: the CPI, right, Because if the price of oil goes up,
Speaker 1: the price of plastic goes up, the price of plastic
Speaker 1: toys goes up. So therefore in the CPI you do
Speaker 1: not only have the direct effect of people of people
Speaker 1: consuming fewer or gas, but you also have indirect effects
Speaker 1: of plastic and plastic toys. And then in all sorts
Speaker 1: of packaging and so on. Right, So we are tracing
Speaker 1: this direct and indirect effect that results from a price
Speaker 1: shock in any one individual sector, and we run this
Speaker 1: UM this simulation UM for for every separate sector, so
Speaker 1: that we then get distinct magnitudes that show us whether
Speaker 1: as shocked to UM to to one sector matters more
Speaker 1: in comparison to another sector. In other words, we can
Speaker 1: create a ranking of what we called the total inflation
Speaker 1: impact from a shock in these sectors. Now, UM, with
Speaker 1: the simulation, we basically have three determinants that can render
Speaker 1: a sector systemically significant. The first determinant is the bait
Speaker 1: in the CPI UM, and housing is a great example here.
Speaker 1: Housing is not something that is very upstream and that
Speaker 1: creates a lot of propert effects in other industries, but
Speaker 1: it has a very large bay in the CPI right.
Speaker 1: So therefore UM, if there is a price change in housing,
Speaker 1: it has a pretty large impact on on the CPI UM.
Speaker 1: Something like UM like oil and gas is actually pretty upstream,
Speaker 1: but not as upstream as something like wholesale trade because
Speaker 1: of the ways in which the upstreamness measures are constructed.
Speaker 1: But for oil and gas UM you have very large
Speaker 1: price movements. So the magnitude of the shocks that we
Speaker 1: use UM are either using average volatilities UM in the
Speaker 1: in the two decades before the pandemic, or using the
Speaker 1: actual price change in the pandemic and in the context
Speaker 1: of the Ukraine War. So in oil and gas we
Speaker 1: actually had very large price movements already before the pandemic
Speaker 1: and then again during the pandemic UM and in the
Speaker 1: context of the war. So here the drivers would be
Speaker 1: kind of all three components the importance UM in terms
Speaker 1: of indirect effects, creating a relatively large total the eight
Speaker 1: in the CPI UM the large price movements and relatively
Speaker 1: upstream even though not as upstream as hole sate trade,
Speaker 1: where it's for holes trade, it's really basically because of
Speaker 1: the upstream nous of that sector. And then in the pandemic,
Speaker 1: of course we also had fairly large price movements there.
Speaker 1: But before the pandemic the price movements in hole say
Speaker 1: trade would have been much smaller than in in something
Speaker 1: like oil and gas extraction. Right, So it's it's these
Speaker 1: three dimensions that we are capturing in in UM in
Speaker 1: creating this ranking. So just on this point, can I
Speaker 1: just press you when it comes to identifying the systemically
Speaker 1: important industries or I think you call them ubiquitous industries. Like,
Speaker 1: how do you just just aggregate their weight in the
Speaker 1: inflation indusseries versus the extent to which they matter for
Speaker 1: other prices, Because I'm sure there will be some people
Speaker 1: who listen to this and say, like, well, obviously, energy
Speaker 1: and you know, maybe some consumer goods and things like
Speaker 1: that have a higher weight in the c p I.
Speaker 1: And so that's why you're getting these results. If you
Speaker 1: look at the paper, which I'm not expecting anyone to do,
Speaker 1: we can we can distinguish between a direct and an
Speaker 1: indirect effect. Right, So what our direct inflation impact is
Speaker 1: is just the weight in the CPI, Right, this is
Speaker 1: just giving you this is what the CPI shows us
Speaker 1: UM is the weight of UM of the change in
Speaker 1: save petroleum in core products UM for the change in
Speaker 1: the CPI UM. But then there's this addition is share,
Speaker 1: which we call the indirect effect, which comes from tracing
Speaker 1: the indirect price UM movements that reside from this initiative
Speaker 1: shock in say petroleum in core products. Now, of course
Speaker 1: we have to make assumptions on how industries UM hand
Speaker 1: over um UH cost increases, right, and be in the paper,
Speaker 1: we make two distinct assumptions. One is that it's just
Speaker 1: a pastor of one, so firms just have a cost
Speaker 1: increase and just passed us on to their customers. The
Speaker 1: second assumption that we make is to say, um, what
Speaker 1: if firms actually don't just pass on the cost, but
Speaker 1: they actually want to protect their profit margins. Now, if
Speaker 1: their cost goes up, go up, and they were to
Speaker 1: increase prices by just the amount of the increasing costs,
Speaker 1: their profit margin would go down, right, So what if
Speaker 1: what if they actually protect their profit margins are therefore
Speaker 1: increase prices by more than the increase in costs um.
Speaker 1: So this then gives us different magnitudes of the total effect,
Speaker 1: but we find that the rankings are relatively stable independent
Speaker 1: of these different assumptions that we are making. And the
Speaker 1: CPI that we are using here is a synthactic CPI,
Speaker 1: because of course we have to break it down to
Speaker 1: UM these seventy one industries that we half UM. So
Speaker 1: it's it's it's it's not the CPI that you're downard
Speaker 1: from the b A UM if you just look for CPI,
Speaker 1: but it's a CPI that you get from the b
Speaker 1: A if you look into it put out for Tavist.
Speaker 1: You know, something I'm interested in, and I don't know
Speaker 1: if it's something you've specifically looked at, but it sort
Speaker 1: of reminds me of this, Like, you know, we talked
Speaker 1: a lot about or economists have talked a lot in
Speaker 1: the last year about goods versus services. Inflation is if
Speaker 1: these are like two distinct categories of types of things
Speaker 1: that people buy, that you can draw a bright line
Speaker 1: and say, Okay, goods have gone down, but service is
Speaker 1: still up. But it seems to me that any good
Speaker 1: that we buy is also implicitly a bundle of services
Speaker 1: that need to go into the You know, if I
Speaker 1: buy a refrigerator, well, there's some sort of service person
Speaker 1: who helped delivery deliver the furniture. Um, and there are
Speaker 1: services for you know, the truck driver whatever it is.
Speaker 1: Does your approach the sort of input output approach sort
Speaker 1: of Um, I'm trying to think exactly the way to
Speaker 1: phrase it, But in your view, does it offer a
Speaker 1: more useful way of thinking about categories of goods beyond
Speaker 1: just or sort of would seem to me like these
Speaker 1: arbitrary distinctions between between the types of things that get
Speaker 1: bought in the economy. Good question, Yeah, great question. UM.
Speaker 1: I mean I would of course say yes, thank you,
Speaker 1: thank you for saying that. A great ka. Sorry, keep going, UM.
Speaker 1: To be sure, services are part of the input out
Speaker 1: put tables, and we actually find that they are pretty
Speaker 1: upstream because of the fact that you just described, right,
Speaker 1: because it's like some form of even like small administrative
Speaker 1: service UM involved in pretty much everything. So if we
Speaker 1: talk about it administ sorry, if we talk about upstream sectors,
Speaker 1: we tend to think about physical stuff like oil and
Speaker 1: gas or matters or candicurstans on, right. But what we
Speaker 1: actually see when we do the analysis that is that
Speaker 1: some that some services are very upstream. Now, the price
Speaker 1: movements in services are relatively small on average over time
Speaker 1: because they are very much UM tied to wages, right,
Speaker 1: and wages tend to move much less than let's say,
Speaker 1: commodity prices. Right. So therefore, when we run these shocks,
Speaker 1: the service sectoris even though um they are pretty upstream,
Speaker 1: end up not being very important for the general movement
Speaker 1: of prices in in this model because just the initial
Speaker 1: shock um is so small. If we model the shock
Speaker 1: um based on magnitudes of past price movements and price
Speaker 1: movements in the in the in the the COVID nineteen inflation. Now,
Speaker 1: I do think that this kind of dust give us
Speaker 1: a different way of distinguishing um categories of of of
Speaker 1: of sectors if you want so, because the idea here
Speaker 1: really is to say, Okay, we don't care if it's services,
Speaker 1: or if it's commodities, or if it's processed goods, or
Speaker 1: if it's manufacturing of whatever it might be. But all
Speaker 1: that we care about is um the importance of this sector.
Speaker 1: It's if you want so, it's centrality in relation to
Speaker 1: all other sectors, and in relation to people, it's um
Speaker 1: um uh consumption patterns. Right. So what we find then
Speaker 1: is that the sectors that we identify systemically significant basically
Speaker 1: in three groups. So it's like basic necessities stuff like housing,
Speaker 1: food forms that of course produce a lot of food
Speaker 1: utilities um, and of course also energy. And then basic
Speaker 1: production inputs stuff like the fosil fields that we haven't
Speaker 1: really talked about but also can a good products um.
Speaker 1: And then kind of like basic circulation infrastructure, so things
Speaker 1: like always say trade right, which is critical for commerce.
Speaker 1: It's a kind of a basic commercial infrastructure. So I
Speaker 1: do think that this does give us a different way
Speaker 1: of kind of UM distinguishing the nature of different sectors.
Speaker 1: So once you've identified these systemically important industries, you know,
Speaker 1: these ubiquitous industries for inflation, things like basic necessities housing, farms,
Speaker 1: food and utilities, and energy, how does that inform the
Speaker 1: policy response. So the idea here is that because these
Speaker 1: UM centers are so important that if there are large
Speaker 1: price movements in these sectors that have this has implications
Speaker 1: way beyond these specific sectors. We should be paying more
Speaker 1: attention to what is happening in these sectors. So the
Speaker 1: first occasion is to say we need more monitoring capacity.
Speaker 1: Why do we need more monitoring capacity? Because we are
Speaker 1: living in some sort of a age of overlapping emergencies
Speaker 1: right where UM we have, of course a pandemic that
Speaker 1: is not over looking for example, at what's happening in
Speaker 1: China and how this UM impact global production networks, but
Speaker 1: also looking at climate change and you're a great episode
Speaker 1: on the Mississippi River and how this is a kind
Speaker 1: of just making a whole UM sector. In this case,
Speaker 1: of course grain UM and other commodities m gryan to
Speaker 1: a hold UM. But we also have these massive geopolitical
Speaker 1: tensions that can have huge implications for the ways in
Speaker 1: which production is organized globally. So in other words, it
Speaker 1: seems very likely from my perspective that more shocks maybe
Speaker 1: in the pipeline. Of course, no one wants these shocks,
Speaker 1: and everybody is hoping that things will be calm and stable. UM.
Speaker 1: But um. But like from the perspective of the dynamics
Speaker 1: of overlapping emergencies, even if inflation is now easing and
Speaker 1: it seems like in the next couple of years these
Speaker 1: kind of shocks UM are likely to keep coming. So
Speaker 1: if that is the case, you kin't want to have
Speaker 1: capacity on the side of the state to be able
Speaker 1: to monitor these sectors that are so important in UM
Speaker 1: in in ways that allow you to react to these
Speaker 1: shocks before they kind of create these huge cascading effects
Speaker 1: throughout the whole economy, and you then actually get some
Speaker 1: sort of potentially more generalized kind of inflation UM. Beyond
Speaker 1: monitoring capacity, of course, not enough to watch. You want
Speaker 1: to be able to kind of step in and stabilize,
Speaker 1: right and UM here then UM, I think the big
Speaker 1: shift in in policy think that emergence from this paper
Speaker 1: is that once we go on the sector level, we
Speaker 1: kind of leave the world of more or less homogeneous
Speaker 1: aggregates where we can talk about interest rates up at
Speaker 1: one percent or down by one percent or point five
Speaker 1: or point seven five or whatever. But it's like pretty
Speaker 1: one dimension, right, and pretty clear that there's a one
Speaker 1: dimension that we can measure in very clear ways quantitatively
Speaker 1: in percentage points, very straightforward. If we now think about
Speaker 1: the prices of chemicals or um the stability of the
Speaker 1: flow of goods and holes trade and therefore the prices
Speaker 1: attached to hols trade or the prices of commodities, we
Speaker 1: enter the word of qualitative differences. Right, we enter the
Speaker 1: word of the last uh two years of odd lots
Speaker 1: episodes right where you have been unpacking this incredible amount
Speaker 1: of detail on the qualitative differences that have huge quantitative
Speaker 1: implications for pricing. But that required quiet um an extraordinary
Speaker 1: extent of understanding of the specific specifics of these sectors.
Speaker 1: So to be able to react to shocks in these sectors,
Speaker 1: I think one would really need quite a bit of
Speaker 1: capacity that is quite tailored to these sectors. So there's
Speaker 1: no like kind of um uh one solution that does
Speaker 1: at all if you think about housing versus um oil refineries,
Speaker 1: you would obviously need a very different kind of policy approach, Right,
Speaker 1: So this then means that kind of these and I mean,
Speaker 1: there is a lot of capacity out there, but it
Speaker 1: needs to be connected back to the question of macroeconomic
Speaker 1: and monetary stability. It's always so funny to me that
Speaker 1: there exists a data point on the terminals that the
Speaker 1: FED monitors called capacity utilization. Is if there's is if
Speaker 1: the concept of industrial capacity could ever be homogenized in
Speaker 1: a single index of like here's your finding capacity, here's
Speaker 1: apartment capacity, here's capacity to make cars. Like it just
Speaker 1: like sort of blows my mind that that's like a
Speaker 1: that that could ever be boiled down to a single number.
Speaker 1: Let me ask you a random question. Is there a
Speaker 1: sector or a part of the economy that in your
Speaker 1: research surprised you as having more ripple effects across other
Speaker 1: prices than you might have expected that maybe people I
Speaker 1: mean oils obvious, right, we all know that everything needs
Speaker 1: energy or whatever, but other sectors that maybe people don't
Speaker 1: think of that have outside effects. Generally speaking, I would
Speaker 1: say that the results are not terribly surprising, which might
Speaker 1: make you say like, Yeah, then why I bothered modeling,
Speaker 1: to which I would answer, well, it is nice to
Speaker 1: kind of be able to capture these aggregate effects and
Speaker 1: trace them in a systematic way throughout the economy. One
Speaker 1: of the sectors that I think is quite interesting is
Speaker 1: chemical products, like, which is just in everything, right, It's
Speaker 1: like as ubiquitous almost as UM as as fossive feuds. UM,
Speaker 1: and UM is incredibly important and apparently it's also important
Speaker 1: not only like from a quantity perspective of composition of production,
Speaker 1: but also from a from a price perspective. So this
Speaker 1: is one that I personally hadn't hadn't thought about as much. UM.
Speaker 1: I think holds trade kind of came very much to
Speaker 1: UM to the top of our minds in the pandemic,
Speaker 1: But our simulations for before the pandemic UM also show
Speaker 1: that holes trade was already pretty important, which again is
Speaker 1: something that I think, like from the pre COVID mindset,
Speaker 1: would not have been something that I would necessarily have
Speaker 1: associated with thinking about inflation. Sorry, really, what do you what?
Speaker 1: Hole shield trade? Man? You said, what do what specifically
Speaker 1: you're talking about? Yeah, so holds the trade again, Like
Speaker 1: this is actually one of the points where probably the
Speaker 1: level of aggregation can become a problem. I mean generally speaking,
Speaker 1: it's stuff like logistics, but also whole say traders, I
Speaker 1: mean any kind of company that that provide that that
Speaker 1: basically does Whoway say merchandising, right, which yeah, so Isabelle
Speaker 1: it can I ask one thing you mentioned in your paper.
Speaker 1: You talk about the possibility of minimum inventory requirements. So
Speaker 1: if you know that a specific industry or thing is
Speaker 1: important from an inflation perspective, maybe we should build in
Speaker 1: additional inventory, some resilience into the system. And this is
Speaker 1: you know, inventories. Um. The idea of business is moving
Speaker 1: to just in time and maybe being a little bit
Speaker 1: more vulnerable to big shocks and demand. This is almost
Speaker 1: classic odd thoughts territory. And it seems like the difficulty
Speaker 1: there is how do you encourage companies to build up
Speaker 1: that extra capacity in their system when maybe their incentives
Speaker 1: are more skewed towards you know, just making money and
Speaker 1: profits and short term things. How do you actually go
Speaker 1: about doing that? How realistic is it? Yeah? Absolutely great question, um?
Speaker 1: And I think that um. I mean, if it is
Speaker 1: about making money and some of the companies that have
Speaker 1: experienced bottomnecks actually have experience that they have managed to
Speaker 1: increase their prices and ways that rendered them even more
Speaker 1: profitive with them before the pandemic. Right, so then your
Speaker 1: incentive of of increasing your inventory it might actually be
Speaker 1: pretty low because you think, like in normal times, UM,
Speaker 1: I don't wanna have inventories because I want to be
Speaker 1: as efficient as I can be. And then if shocks hit,
Speaker 1: if everybody is kind of um running this same model,
Speaker 1: like all competitors in one in one segment running this
Speaker 1: same model, so then they all don't have a lot
Speaker 1: of inventories, then there's this exactor white UM supply change
Speaker 1: shock which all allows them to high prices and base
Speaker 1: in which they could not hide prices at normal times
Speaker 1: because now they kind of had this mutual knowledge of
Speaker 1: UM of of of shortage UM. So and then they
Speaker 1: end up being actually in a pretty good position, which
Speaker 1: we have seen in some of the sectors that have
Speaker 1: experienced extreme UH impacts on their supply change during the pandemic. Right, So, therefore,
Speaker 1: we somehow need a way to get out of this.
Speaker 1: And I think because of what I just laid out,
Speaker 1: it's not clear that companies by themselves would necessarily increase
Speaker 1: the inventories space. Um that that that sufficiently prevent this situation,
Speaker 1: at least not to the extent as it would be
Speaker 1: like kind of um socially desirable or desirable from a
Speaker 1: more like macroeconomic kind of standpoint. How to do it practically? Again, Like,
Speaker 1: I really see this paper as providing a framework and
Speaker 1: kind of starting a conversation, and I think to get
Speaker 1: to the question of how to do it practical, one
Speaker 1: really has to start. I'm talking to people who understand
Speaker 1: inventory management and companies rather than me like kind of
Speaker 1: as the arm to economists coming up with some some
Speaker 1: sort of fix all the inventories of US corporations and
Speaker 1: one type of approach. We're almost out of time. I
Speaker 1: have one very short question, but you know, we did
Speaker 1: an episode recently and it was pointed out by one
Speaker 1: of our guests of the way a lot of economists
Speaker 1: think is that if the price of gas goes down,
Speaker 1: for example, that doesn't improve inflation because the sort of
Speaker 1: general equilibrium, Well, that's more money in people's podcasts, and
Speaker 1: they're just going to spend more on haircuts now, or
Speaker 1: they're just gonna spend more on cars. Why is a
Speaker 1: limit to how many haircuts, yeah, right, or maybe they'll
Speaker 1: spend more on going out to eat, okay, so uh
Speaker 1: and then it doesn't really get us anywhere. Like what
Speaker 1: do you say? I'm just curious your response to that.
Speaker 1: That's like, okay, you target a sector, great, you target energy, great,
Speaker 1: But then everything is cheaper, people have more money and
Speaker 1: they spend elsewhere, and you don't get anywhere. Why should
Speaker 1: that not? Is that not a fatal flaw of your approach?
Speaker 1: I mean this is the famous I mean one of
Speaker 1: the famous fretument frequent quotes also where he's saying exactly
Speaker 1: what you just said. We were back to monitor, Yeah, yeah,
Speaker 1: I mean that's the kind of brings you back to
Speaker 1: the question of how firms are setting prices, right, um,
Speaker 1: And if we are in a situation where we have
Speaker 1: very highly concentrated um corporate structures, which I think is
Speaker 1: a fairly fair descriptions of large parts of the American economy,
Speaker 1: then we can actually see that that the demand response, sorry,
Speaker 1: that the price response to demand is surprisingly small. In
Speaker 1: many cases, the prices are actually quite surprisingly stable. I mean,
Speaker 1: if you think back to the two decades decades before
Speaker 1: covid Um, where of course there have been periods of
Speaker 1: more demand and less demandents on, but prices were surprisingly stable, right,
Speaker 1: and everybody was a kind of surprising. Why are price
Speaker 1: is so stable? Well because in a very concentrated sectors,
Speaker 1: firms tend to UM to compete over market share, UM,
Speaker 1: compete over conquering new segments of markets, UM, compete over
Speaker 1: cutting costs, and so on, less than UM than using
Speaker 1: any kind of small increase in demand by immediately raising prices. Right,
Speaker 1: Because if you raise prices in your competitor doesn't raise
Speaker 1: prices because both of you are price makers and not
Speaker 1: price takers, then UM, that can actually harm you. So
Speaker 1: therefore UM in in in the kind of institution setting
Speaker 1: that we find ourselves in, UM, I don't think it's
Speaker 1: clear that UM, if people spent less on gas, then
Speaker 1: immediately the prices of everything else that they are UM
Speaker 1: assuming are going up. And I also don't think that
Speaker 1: this is something that we see empirically, that the price
Speaker 1: of gas andoy going down, the inflation in other parts
Speaker 1: of the economy suddenly like going up by any large margins. Isabella,
Speaker 1: We're going to have to leave it there, but thank
Speaker 1: you so much for coming on. Odd lots You're definitely
Speaker 1: one of our favorites. And I'm not just saying that
Speaker 1: because you've translated the past two years into actual academic research. UM.
Speaker 1: Fascinated discussion. Thank you, Thanks Isabella. That conversation was great, UM,
Speaker 1: and the paper is definitely worth a read, although I
Speaker 1: know Isabella said she didn't think anyone was actually going
Speaker 1: to read it. One thing I was thinking is it
Speaker 1: does kind of go back to remember some of the
Speaker 1: conversations we had with Stephanie Kelton on modern monetary theory,
Speaker 1: and you know, her solution was, well, we need instead
Speaker 1: of reducing spending, like maybe we identify where the bottlenecks
Speaker 1: are happening and we increased capacity or try to increase capacity.
Speaker 1: And my criticism of that was it's difficult to do
Speaker 1: it in real time. But I think studies like this
Speaker 1: maybe go some way towards identifying where to look, right.
Speaker 1: I think this use of input output tables and Isabella
Speaker 1: said it is actually a very old thing that you
Speaker 1: never hear mainstream economists talk about. I don't you know,
Speaker 1: it could be is like very useful idea and like, okay,
Speaker 1: it's like difficult. Sure, it's a lot more difficult to
Speaker 1: identify critical sectors, and it is to just raise rates
Speaker 1: when CPI comes in higher than expected. But it's doable.
Speaker 1: And I did read the paper. But when I say
Speaker 1: I read the paper, what I mean is I read
Speaker 1: the first four pages, skipped over the forty pages of equations.
Speaker 1: You have to see the intro and then the conclusions.
Speaker 1: So I read the I read the intro, I skipped
Speaker 1: over like all the equations and Greek symbols or whatever,
Speaker 1: and then the conclusion, and I thought it was really interesting.
Speaker 1: And I think, like I suspect and maybe as a
Speaker 1: result of all this, the pandemic and everything, there might
Speaker 1: be renewed interest in this sort of like pretty vigorous
Speaker 1: approach to identifying critical sectors and how they distribute prices
Speaker 1: across the ecomptment exactly this. I would be really disappointed
Speaker 1: if we came out of the past two or three
Speaker 1: years without a sort of like new way of thinking
Speaker 1: about inflation, or at least maybe an additional dimension. Yeah,
Speaker 1: all right, shall we leave it there. Let's leave it there.
Speaker 1: This has been another episode of the ad Thoughts podcast.
Speaker 1: I'm Tracy Alloway. You can follow me on Twitter at
Speaker 1: Tracy Alloway and I'm Joe, why isn't Though? You can
Speaker 1: follow me on Twitter at the Stalwart. Follow our guest
Speaker 1: Isabella Vaber. She's at Isabella and Vaber, and check out
Speaker 1: her paper, Inflation in times of overlapping emergencies systemically significant
Speaker 1: prices from an input output perspective. Follow our producers Carmen
Speaker 1: Rodriguez at Carmen Armand and Dash Bennett at Dashbot. And
Speaker 1: check out all of our podcasts as Bloomberg under the
Speaker 1: handle at podcasts and for more odd Lots content, go
Speaker 1: to Bloomberg dot com slash odd Lots, where we post transcripts.
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Speaker 1: Thanks for listening.