Tracy: (21:20) So once you've identified these systemically important industries, you know, these ubiquitous industries for inflation, things like basic necessities, housing, farms, food and utilities and energy, how does that inform the policy response?
Isabella: (21:39) Yeah, so the idea here is that because these sectors are so important that if there are large price movements in these sectors that this has implications way beyond these specific sectors. We should be paying more attention to what is happening in these sectors. So the first implication is to say we need more monitoring capacity.
Why do we need more monitoring capacity? Because we are living in some sort of an age of overlapping emergencies, right? Where we have of course, a pandemic that is not over -- looking for example at what's happening in China and how this impacts global production networks -- but also looking at climate change and your great episode on the Mississippi River and how this is kind of just making a whole sector -- in this case, of course, grain and other commodities -- grind to a halt. But we also have these massive geopolitical tensions that can have huge implications for the ways in which production is organized globally.
So, in other words, it seems very likely from my perspective that more shocks will be in the pipeline. Of course, no one wants these shocks, and everybody is hoping that things will be calm and stable. But from the perspective of the dynamics of overlapping emergencies, even if inflation is now easing it seems like in the next couple of years, these kind of shocks are likely to keep coming. So if that is the case, you kind of want to have capacity on the side of the state to be able to monitor these sectors that are so important, in ways that allow you to react to these shocks before they kind of create these huge cascading effects throughout the whole economy and
you then actually get some sort of potentially more generalized kind of inflation.
Beyond monitoring capacity, of course it's not enough to watch. You want to be able to kind of step in and stabilize, right? And here then, I think the big shift in, in policy thinking that emerges from this paper is that once we go on the sectoral level, we kind of leave the world of more or less homogeneous aggregates where we can talk about interest rates up by 1% or down by 1% or 0.5 or 0.75 or whatever. But it's pretty one dimensional, right? And pretty clear that there's one dimension that we can measure in very clear ways, quantitatively in percentage points, very straightforward. If we now think about the prices of chemicals or the stability of the flow of goods and wholesale trade, and therefore the prices attached to wholesale trade or the prices of commodities, we enter the word of qualitative differences, right?
We enter the world of the last two years of Odd Lots episodes, right? Where you have been unpacking this incredible amount of detail on the qualitative differences that have huge quantitative implications for pricing but that require quite an extraordinary extent of understanding of the specifics of these sectors. So to be able to react to shocks in these sectors, I think one would really need quite a bit of capacity that is quite tailored to these sectors. So there's no kind of one solution that does it all. If you think about housing versus oil refineries, you would obviously need a very different kind of policy approach, right? So this then means that kind of these, and I mean, there is a lot of capacity out there, but it needs to be connected back to the question of macroeconomic and monetary stability.
Systemically significant forms of inflation, or industries that could have a broad impact on a variety of prices, have been identified by Economics Professor Isabella Weber in a new paper
Systemically significant forms of inflation, or industries that could have a broad impact on a variety of prices, have been identified by Economics Professor Isabella Weber in a new paper
Isabella Weber On a New Way to Think About Inflation
In economics, there tends to be two dominant ways of thinking about inflation. Either you agree with Milton Friedman, who described inflation as always and everywhere a monetary phenomenon (the result of too much money printing). Or you're more of a New Keynesian who thinks that higher prices are all about the relationship between demand and capacity. In a new paper inspired by Odd Lots and the series of disruptions that have rocked the economy since the global pandemic, UMass Amherst Economics Professor Isabella Weber describes a potential third way of thinking about inflation. She identifies systemically significant sources of inflation, or industries that could end up having a broader impact on a wide variety of prices. The hope is that by identifying these important sources of inflation early, policymakers can put in place measures to make sure price increases don't get out of hand.
You then actually get some sort of potentially more generalized kind of inflation Beyond monitoring capacity, of course not enough to watch you want to be able to kind of step in and stabilize right? And here then I think the the big shift in policy think that emergence from this paper is that once we go on the sector or lab be kind of leave the word of more or less homogeneous Aggregates where we can talk about interest rates up and one percent or down by one percent or point five or point seven five or whatever, but it's like pretty one dimension right clear that there's like one dimension that we can measure very clear ways quantitatively in percentage points, very straightforward if we now think about The price is of chemicals or the stability of the flow of goods and wholesale trade and therefore the the prices attached to Jose trade or the prices of Commodities.
We enter the word of qualitative differences, right the end of the word of the the last two years of odd Lots episodes right where you have been unpacking this incredible amount of detail of the qualitative differences that have huge quantitative implications for pricing but that require quite an extraordinary extend of understanding of the specific specifics of the sectors. So to be able to react to shocks in these sectors, I think one would really need quite a bit of capacity that is quite tailored to these sectors. So there's no like kind of one solution. That's it all if you think about housing versus oil refineries, you would obviously need a very different kind of policy approach. Right? So this then means that kind of these and I mean there is a lot of capacity out there, but it needs to be connected back to the question of macroeconomic and monetary stability.
The decommissioned Greifswald nuclear power station in Lubmin, Germany, on Friday, Jan. 13, 2023. TotalEnergies SA and Swiss energy trader MET Group booked capacity at a new LNG terminal in Lubmin, helping boost supplies to Europe's biggest economy as it looks to replace Russian gas.Photographer: Krisztian Bocsi/BloombergIn economics, there tends to be two dominant ways of thinking about inflation. Either you agree with Milton Friedman, who described inflation as always and everywhere a monetary phenomenon (the result of too much money printing). Or you're more of a New Keynesian who thinks that higher prices are all about the relationship between demand and capacity. In a new paper inspired by Odd Lots and the series of disruptions that have rocked the economy since the global pandemic, UMass Amherst Economics Professor Isabella Weber describes a potential third way of thinking about inflation. She identifies systemically significant sources of inflation, or industries that could end up having a broader impact on a wide variety of prices. The hope is that by identifying these important sources of inflation early, policymakers can put in place measures to make sure price increases don't get out of hand. This transcript has been lightly edited for clarity.
.…
要登録
以下は非公式
youtube自動読み取り
ーーー
Music] [Applause]
hello and welcome to another episode of the odd Lots podcast I'm Tracy Alloway and I'm Joe weisenthal Joe I I feel like
I'm gonna Jinx things by saying this but it feels like inflation is maybe
starting to come down a little bit at least it's not accelerating yeah let's put it that way well here's how uh
here's what I've been thinking about which is that for the last year or the last year and a half we've done all of
these episodes on like Supply chains and disruptions for this or that reason and
all of the various times we've um used the term perfect storm to describe
certain things in certain industries Perfect Storm of perfect storms my guess right now you know in January 2023 is
that 2023's episodes will be a little less dominated by these topics that would be my guess I'm guessing that this
year we do a few fewer Perfect Storm episodes I think that's right but I think you know we we spoke a lot about
what it was that people didn't see coming when it comes to inflation why did a lot of economists get it wrong why
was the inflation That was supposed to be transitory you know maybe it was transitory in the sense that it was narrow you know not a big sort of like
macro Unleashed inflation but it definitely stuck around longer than a lot of people expected and so every time
we have these big questions like why aren't we better at forecasting inflation it provides an opportunity to
maybe learn something and start thinking about it in a slightly different way well yeah absolutely and I would say
there's really two things that I feel are unanswered by all of the conversations that we've had uh in the
last year so one is still like is inflation like a macro or a micro thing
did it happen because a few categories uh really had some disruptions and then
spill elsewhere and therefore it's not really about fiscal or monetary policy specifically and B okay we do have very
high inflation right now even if there's evidence coming down what tool like if
it is the case that a lot of it is related to disruptions and Chip shortages and freezes in Texas Etc what
are the tools that are best to address that because it is important to get inflation down but on the other hand
there's a pretty good argument that if the issue is some sort of disruption at the ports or whatever that sort of like
strict blunt instruments like raising rates raising rates aren't necessarily the best uh approach to dealing with
that kind of or raising rates won't grow more trees to turn into Lumber or more
births at the ports or anything like that so I'm so glad you said that because today we are going to be speaking with one of our Odd Lots
favorites and she has just written a new paper uh which she says is inspired by
some of the conversations that we've had on odd Lots but it's also just really interesting because it presents a new
sort of third wage potentially of thinking about inflation not transitory
not persistent a new more interesting third option and that maybe could help
us think about ways of accepting yes inflation is real it is a problem but
that some of these blunt instruments that just treat inflation as a function of there's too much money in the economy
we need there to be less maybe there are better approaches than just this sort of like blunt monetary approaches to
addressing them absolutely so without further Ado we are going to be speaking today to Isabella Weber she is of course
a economics professor over at the University of Massachusetts Amherst and you might remember her from from some
previous episodes so Isabella thank you so much for coming back on odd lots
thank you so much for having me it's a pleasure thank you so the paper is called inflation in times of overlapping
emergencies systemically significant prices from an input output perspective but I just want to get you to say on
camera that this is inspired by Autobots it is I mean a happy list
and as you were just saying obviously you have been tracing all these price shocks that have been Rippling for the
economy so um this paper is trying to come up with a framework to trace these shocks and
ripple effects um in a somewhat more Aggregate and possibly less fine print
but maybe a little bit more like formal kind of fashion I love that the most
self-serving first question that we've ever asked on an interview what is you
know what it what is an input output approach mean because my understanding is that this is actually like a very old
idea in economics but that is some kind of it's actually been forgotten is my
understanding and that this sort of like various versions of monitorist thinking which sort of treat if prices are high
if one understand prices we'll just look at how much money or how much credit is in the economy rein that in and you've
seen this paper seems to be like going back to like an older tradition in economics can you talk a little bit
about what this is yeah so as you said we tend to think about inflation as a micro firm right where it's basically just
aggregate measures whereas what we are trying to do here is to think of prices
as um kind of an interconnected Network where um since one sector's output is
another sector's input and therefore one sector's output prices are the cost of
another sector you can kind of Trace um the price movements across the whole
production Network which input output tables allow you to do so these tables
basically like register the relationships of input and outputs um across the whole economy historically
input output tables really had a breakthrough during the war time where
the question was um how can we hit the enemies economy in ways that we kind of like
with the minimum number of bombs um create the maximum damage to really I
mean undermine um the enemy economy's ability to even fight a war I mean concretely of course
this is mainly about the German economy um and so therefore it really is a
method of identifying points um that are of particular systemic significance for
the economy as a whole back then the idea was to identify these points of vulnerability to um I mean as I said
create destruction the idea of our paper is to say if we can
identify these points of vulnerabilities then we can actually um kind of um know what the potential
sources of um of these rapid effects that can create marker outcomes um could be so if
some prices matter more than others we want to know what these prices are and input output is one method of trying to
identify these systemically significant sectors uh so Tracy my takeaway from
that is that in a war it makes more sense to say bomb an oil refinery than a
candy factory like it right like if you're thinking about well what are these sectors that will have the biggest Ripple effects across the economy then
that would be the implication well maybe we should talk about morale in that context but no okay there's another
there's another analogy um that you use in the paper which is you know if you're trying to identify systemically
important sources of inflation and maybe address them before they start actually
contributing to price increases it's kind of like trying to identify systemically important Banks and then
making sure that they you know hold more regulatory capital or maybe go under preemptive stress tests or things like
that can you talk about maybe you know before we get into policy Solutions can you talk about how that approach maybe
differs to traditional ways of thinking about inflation because you know in my
mind there's really there's the monetarist view it's all about the money supply and then there's a sort of new Keynesian view where it's more about you
know supply side and capacity and demand and things like that can you place this new approach in the context of those two
older ways of thinking about it so as different as like kind of monetarism and
new canes business more keynesianism can be they share the understanding that
inflation is always driven by macroeconomic factors right now what we are doing here I mean in one case it's
um the the distance from from uh aggregate capacity utilization in the other case it's more that like classic
story of too much money chasing to too few goods but still it's like trying to locate the the origins of inflation on
the aggregate level what we are trying to do here is to say well if there are micro origins of inflation if shocks to
specific sectors can matter in ways that they can unleash processes that actually
unsettle the stability of prices overall then we want to understand stand what
these sectors are we want to know where these points of vulnerability are so
that we can react to these shocks before they kind of Ripple throughout the whole
system and as you said interest rates are already being recognized as a
systemically significant kind of price right that's why we have central banks which of course historically at some
point was also not the case so it was a historical Evolution to recognize the systemic significance of interest rates
so in some sense what we are arguing here is to um is to say that there are more prices than the price of boring
money that can acquire systemic significance in ways that can have a
very large implications for monetary stability just a shout out we are drawing here on the workouts of Salo or
moreover who has been working on systemically significant prices for a while someone else we definitely have to
have on the podcast at some point it's so funny because you know of course and
we talked about this the last time you were on uh late last year you took a lot of heat for saying well maybe there's a
time for having some discussion about price controls everyone freaked out about that and yet they're like okay now
let's control the price of money as if that isn't a form of price control and yet of course Central Banking the
ultimate price control the ultimate price control but you know so I joked but I guess it's not really a joke that
like there are some areas where it's kind of obvious that some sort some functions in the economy are more
crucial to other Industries than others so an oil refinery is going to be more crucial to other Industries than a candy
factory but that's obvious how do you go about systematically identifying beyond the
sort of really crude uh examples what is this this sort of like a rigorous or
empirical approach to actually identifying what parts of the economy are in fact the most likely to have
Ripple effects elsewhere so what we have done in this paper is that we have simulated shocks to every industry in
the input output table and just orientation 71 industry so it's not super disaggregated I mean also not
super aggregate compared to macroeconomic variables but it's still fairly broad right so we run a shock on
each of these sectors and then we simulate how this shock runs through the whole economy reciting in in indirect
impact on um on on the CPI right because if the price of oil goes up the price of
plastic goes up the price of plastic toys goes up so therefore in the CPI you do not only have the direct effect of
people con of people consuming fuel or gas but you also have indirect effects
of plastic and plastic toys and then in all sorts of packaging and so on right so we are tracing this direct and
indirect effect that resides from a price shock in any one individual sector
and we run this um the simulation um for for every separate sector so that
we then get distinct magnitudes that show us whether a shock to
um to one sector matters more in comparison to another sector in other words we can create a ranking of what we
call the total inflation impact from a shock in these sectors now um with the
simulation we basically have three determinants that can render a sector systemically significant the first
determinant is the bait in the CPI and housing is a great example here housing
is not something that is very upstream and that creates a lot of property facts in in other Industries but it has a very
large weight in the CPI right so therefore if there is a price change in housing it has a pretty large impact on
on the CPI um something like um like oil and gas is actually pretty
Upstream but not as Upstream as something like wholesale trade um because of the ways in which the
upstreamness measures are constructed but for oil and gas you have very large
price movements so the magnitude of the shocks that we use are either using average volatilities in the in the two
decades before the pandemic or using the actual price change in the pandemic and
in the context of the Ukraine war so in oil and gas we actually had very large price movements already before the
pandemic and then again during the pandemic um and in in the context of the war so here the drivers would be kind of
all three components the importance um in terms of indirect effects creating a
relatively large total um weight in the CPI the large price
movements and relatively Upstream even though not as Upstream as wholesale trade whereas for wholesale trade it's
really um basically because of the upstreamness of that sector and then in the pandemic
of course we also had Fairly large eyes movements there but before the pandemic the price movements and wholesale trade
would have been much smaller than in in something like oil and gas extraction right so it's it's these three
dimensions that we are capturing in in um in creating this ranking so just on
this point can can I just press you when it comes to identifying the systemically important industries or I think you call
them ubiquitous Industries like how do you just disaggregate their weight in
the inflation indices versus the extent to which they matter for other prices
because I'm sure there will be some people who who listen to this and say like well obviously energy and you know
maybe some consumer goods and things like that have a higher weight in the CPI and so that's why you're getting
these results if you look look at the paper which I'm not expecting anyone
we can't we can't distinguish between a direct and an indirect effect right so
what our direct inflation impact is is just the weight in the CPI right this is just giving you this is what the CPI
shows us um uh is the weight of um of the change in safe petroleum and core products um
for the change in the CPI um but then there's this additionist here which we call the indirect effect
which comes um from tracing the indirect price
um uh movements that reside from this initial shock in say petroleum and core products now of course we have to make
assumptions on how Industries um hand over
a cost increases right and we in the paper we make two distinct assumptions
one is that it's just a pass-through of 100 and so firms just have a cost
increase and just pass this on to their customers the second assumption that we make is to say what if firms actually
don't just pass on the cost but they actually want to protect their profit margins now if their cost goes up go up
and they were to increase prices by just the amount of the increasing costs their
profit margin would go down right so what if um what if they actually protect their their profit margin so therefore
increase prices by more than the increase in costs um so this then gives
us different magnitudes of the total effect but we find that the rankings are relatively stable um independent of of
these different um assumptions that we are making and the CPI that we are using here is a synthetic CPI because of
course we have to break it down to um these 70 um One Industries that we have
um so it's it's it's it's not the CPI that you download from the ba um if you
just look for CPI but it's a CPI that you get from the ba if you look into input output tables
you know something I'm interested in and I don't know if it's something you've specifically looked at but it sort of
reminds me of this like you know we talk a lot about or economists have talked a lot in the last year about Goods versus
Services inflation is if these are like two distinct categories of types of
things that people buy that you can draw a bright line and say okay Goods have gone down but service is still up but it
seems to me that any good that we buy is also implicitly a bundle of services that need to go into the you know if I
buy a refrigerator well there's some sort of service person who helped delivery deliver the furniture
um and there are services for you know the truck driver or whatever it is does
your approach the sort of input output approach sort of um
I I'm trying to think exactly the way to phrase that but in your view does it offer a more useful way of thinking
about categories of goods Beyond just or sort of would seem to me like these arbitrary distinctions between between
the types of things that get bought in the economy good question yeah great question
um uh I mean I would of course say Yes um thank you thank you for saying that
is a great question okay no no sorry keep going um to be sure services are part of the
input output tables and we actually find that they are pretty Upstream because of the fact that you just described right
because there is like some form of even like small administrative service um involved in pretty much everything so
if we talk about it administer sorry if we talk about Upstream sectors we tend to think about the physical stuff like
oil and gas or matches or chemicals and so on right but what we actually see
when we do the analysis that is that some that that some services are very Upstream now the price movements in
services are relatively small on average over time because they're very much
um tied to wages right and wages tend to move much less than let's say commodity
prices right so therefore when we run these shocks the service sectors even
though um they are pretty Upstream end up not being very important for the general
movement of of prices in in this model um because just the the initial shock um
is so small if we model the shock um uh based on on magnitudes of past um price
movements and price movements in the um in the in the in the covid-19 inflation
now um I do think that this kind of does give us a different way of distinguishing
um uh categories of of of of sectors if you want so because the idea here really
is to say okay we don't care if it's services or if it's um Commodities or if
it's processed Goods or if it's manufacturing or whatever it might be but all that we care about is um the
importance of this sector it's if you want so it's centrality in relation to um all other sectors and in relation
into people's consumption patterns right so what we
find then is that the sectors that we identify systemically significant are
basically in three groups so it's a basic necessities stuff like housing food Farms that of course produce a lot
of food utilities and of course also energy and then basic production inputs
stuff like um uh the the fossil fuels that we have already talked about but also chemical products and then kind of
like basic circulation infrastructure so things like wholesale trade right which
is critical for Commerce it's a kind of a basic commercial infrastructure so I do think that this
does give us a different way of kind of um distinguishing um the nature of different sectors so once you've
identified these systemically important industries um you know these ubiquitous Industries
for inflation things like basic necessities housing Farms food and utilities and energy
how does that inform the the policy response so the idea here is that
because these sectors are so important that if there are a large price
movements in these sectors that have this has implications Way Beyond these
specific sectors um we should be paying more attention to what is happening in these sectors so
the first implication is to say we need more monetary and capacity why do we
need more monitoring capacity because we are living in some sort of a age of overlapping emergencies right where we
have of course a pandemic that is not over um location for example at what's happening in China and how this impacts
um Global production networks but also looking at climate change and your great episode on the Mississippi River and how
this is a kind of just making a whole sector in this case of
course grain um and other Commodities um grind to a hold but we also have
these massive geopolitical tensions that can have some huge implications for the
ways in which production is organized globally so in other words it seems very likely from my perspective that more
shocks may be in the pipeline of course no one wants these shocks and everybody is hoping that things will be calm and
stable um but um but uh like from the perspective of the Dynamics of
overlapping emergencies even if inflation is now easing and it seems like in the next couple of years these
kind of shocks um are likely to keep um coming so if that is the case you kind
of want to have capacity on the side of the state to be able to monitor these
sectors that are so important in um in in ways that allow you to react to these
shocks um before they kind of create these um huge cascading effects
throughout the whole economy and you then actually get some sort of potentially more generalized
um kind of inflation um Beyond monitoring capacity of course not enough to watch you want to be able
to kind of step in and stabilize right and um here then um I think the the big
shift in in policy thinking that emerges from this paper is that once we go on
the sector or a level we kind of leave the world of um more or less homogeneous Aggregates
where we can talk about interest rates up by one percent or down by one percent or 0.5 or 0.75 or whatever but it's like
pretty one dimensional right and pretty clear that there's like one dimension that we can measure very clear ways
quantitatively in percentage points very straightforward if we now think about
the prices of chemicals or um the stability of the flow of goods
and wholesale trade and therefore um the the prices attached to Jose trade or the prices of Commodities we enter
the world of qualitative differences right we enter the word of the the last
um uh uh two years of odd Lots episodes right where you have been unpacking this
um incredible amount of detail on the qualitative differences um that have
huge quantitative implications for pricing but that require
um quite um an extraordinary extent of um understanding of the specific
specifics of these sectors so to be able to react to shocks in these sectors I
think one would really need quite a bit of capacity that is quite tailored to
these sectors so there's no like kind of um uh one solution that that's it all if
you think about housing versus oil refineries you would obviously need a
very different kind of policy approach right so this then means that kind of these and I mean there is a lot of
capacity out there but it needs to be connected back to the question of
macroeconomic and monetary stability it's always so funny to me that there exists a data point on the terminals
that the FED monitor is called capacity utilization is if there's as if the
concept of industrial capacity could ever be homogenized in a single index of like oh here's refining capacity here's
apartment capacity here's capacity to make cars like it just like sort of blows my mind that that's like a that
that could ever be boiled down to a single number let me ask you a random question is there a sector or a part of
the economy that in your research surprised you as having uh more Ripple effects across other prices than you
might have expected that maybe people I mean oil is obvious right we all know that everything needs energy G or whatever but other sectors that maybe
people don't think of that have outsize effects generally speak resides are not terribly
surprising which might make you say like yeah then why bother modeling it
um to which I would answer well it is nice to kind of be able to capture these aggregate effects and Trace them in a
systematic way throughout the economy one of the sectors that I think is quite interesting is chemical products like
which is just in everything right it's like yes ubiquitous almost as um as as
fossil fuels and is incredibly important and apparently is also important not
only like from a quantity perspective of composition of production but also from uh from a price perspective so this is
one that I personally hadn't hadn't thought about as much I think wholesale trade kind of came very much to
um to the top of our minds in the pandemic but our simulations um for before the pandemic
um also show that Jose trade was already pretty important which again is
something that I think like from the pre-covet mindset would not have been something that I would necessarily have
associated with thinking about um inflation wait sorry what's wholesale
trade mean you said what what specific are you talking about yeah so Jose trait again like this is actually one of the
points where probably the level of aggregation can become a problem I mean generally speaking it's stuff like
Logistics but also wholesale Traders I mean any kind of company that um that
provide that that basically does always say merchandising right um which yeah
um yeah so Isabella can I ask one thing you mentioned in your paper you talk
about the possibility of minimum inventory requirements so if you know that a specific industry or thing is
important from an inflation perspective maybe we should build in additional inventory some resilience into the
system and this is you know inventories the idea of business is moving to just
in time and maybe being a little bit more vulnerable to Big shocks in demand this is almost classic odd Lots
territory and it seems like the difficulty there is how do you encourage companies to build up that extra
capacity in their system when maybe their incentives are more skewed towards you know just making money and profits
and short-term things how do you actually go about doing that how realistic is it yeah absolutely great
question um and I think that um I mean if it is about making money and some of the
companies that have experienced uh bottlenecks actually have the experience
that they have managed to increase their prices and raise that rented them even more profitable than before the pandemic
right so then your incentive of um of increasing your inventory might actually
be pretty low because you think like in normal times um I don't wanna have
inventories because I want to be as efficient as I can be and then if sharks hit if everybody is kind of um running
this same model like all competitors in one in one segment are running the same model so that they all don't have a lot
of inventories then there's this exactly wide um supply chain shock which allows
them to hide prices in ways in which they could not hike prices at normal times because now they kind of have this
Mutual knowledge of um of uh of of shortage um so and then they end up
being actually in a pretty good position and which we have seen in in some of the sectors that have experienced
um extreme um uh uh impacts on on their supply chains during the pandemic right so therefore we somehow need a way to
get out of this and I think because of what I just laid out it's not clear that
companies by themselves would necessarily increase their inventories
um that that sufficiently prevent this um Asian at least not to the extent as
it would be like kind of um socially desirable or desirable from a more like um macroeconomic kind of
standpoint how to do it practically again like I really see this paper as um
providing a framework and kind of starting a conversation and I think to get to the question of how to do it
practically and bond really has to start um talking to people who understand inventory management at companies rather
than me like kind of as the armchair Economist coming up with some some sort of fix all the inventories of U.S
corporations at once type of approach we're almost out of time I have one very short question but you know we did an
episode recently and it was pointed out by one of our guests that the way a lot of economists think is that if the price
of gas goes down for example that doesn't improve inflation because the sort of General equilibrium well that's
more money in people's pockets and they're just going to spend more on haircuts now or they're just going to
spend more on cars why there's a limit to how many haircuts yeah right or maybe
they'll spend more on going out to eat okay so uh and then it doesn't really get us anywhere like what do you say I'm
just curious your response to that that's like okay you target a sector great you target energy great then
everything's cheaper people have more money and they spend elsewhere and you don't get anywhere why should that not
why is that not a fatal flaw of your approach I mean this is the famous I mean one of the famous Friedman written
Friedman quotes also where he's saying exactly what you just said we were back to like monitor the sort of core
monitors thinking yeah yeah I mean this then kind of brings you back to the question of how firms are setting prices
right um and if we are in a situation where we have very highly concentrated
um uh corporate structures which I think is a fairly Fair descriptions of large parts of the American economy then we
can actually see that um uh that the demand response sorry that the price
response to demand is so surprisingly small in many cases that the prices are actually quite surprisingly stable I
mean if you think back to the two decades some decades before covet where
of course there have been periods of of more demand and less demand and so on but prices were surprisingly stable
right and everybody was a kind of surprised like why are prices so stable well um because in a very concentrated
sectors firms tend to um to compete over market share and compete over
um conquering new segments of markets um compete over cutting costs and so on less than um than using any kind of
small increase in demand by immediately raising prices right because if you raise prices in your competitor doesn't
raise prices because both of you are price makers they're not price takers right then that can actually harm you so
therefore um in in in the kind of institutional setting that we find ourselves in
um I don't think it's clear that if people spend less on gas then
immediately the prices of everything else that they are consuming are going up and I also don't think that this is
something that we see empirically that the the price of gas and oil going down the inflation in other parts of the
economy assembly like going up by any large margins Isabella we're going to have to leave it
there but thank you so much for coming on odd Lots uh you're definitely one of our favorites and I'm not just saying that because you've translated the past
two years into actual academic research um fascinating discussion thank you so much Isabella that was great thank you
thanks Isabella foreign
[Music]
that conversation was great and the paper is definitely worth a read although I know Isabella said she didn't
think anyone was actually going to read it one thing I was thinking is it does kind of go back to remember some of the
conversations we had with Stephanie Kelton on Modern monetary Theory and you know her solution was well we need
instead of reducing spending like maybe we identify where the bottlenecks are happening and we increase capacity or
try to increase capacity and my criticism of that was it's difficult to do it in real time but I think studies
like this maybe go some way towards identifying where to look right I think
this use of input output tables and is uh Isabella said is actually a very old
thing that you never hear mainstream economists talk about you know yeah it could be is like very useful idea and
like okay it's like difficult sure it's a lot more difficult to like identify critical sectors than it is to just
raise rates when CPI comes in higher than expected but it's doable and I did
read the paper but when I say I read the paper what I mean is I read the first four pages skipped over the 40 pages of
equations you have to do the intro and then the conclusion yeah so I read the I read the intro I skipped over like all
the equations and Greek symbols or whatever and then the conclusion it and I thought it was really uh interesting
and I think like I suspect and maybe as a result of all this the pandemic and
everything there might be renewed interest in this sort of like pretty rigorous approach to identifying
critical sectors and how they distribute prices across the economy exactly this I would be really disappointed if we came
out of the past two or three years without a sort of like new way of thinking about inflation or at least
maybe an additional Dimension yeah all right should we leave it there let's leave it there this has been another
episode of the odd Lots podcast I'm Tracy Alloway you can follow me on Twitter at Tracy Alloway and I'm Joe
weisenthal you can follow me on Twitter at the stalwart follow Our Guest Isabella Weber she's at Isabella and
Weber and check out her paper inflation in times of overlapping emergencies systemically significant prices from an
input output perspective follow our producers Carmen Rodriguez at Carmen Armin and dash Bennett at dashbot and
check out all of our podcasts at Bloomberg under the handle at podcasts and for more Odd Lots content go to
bloomberg.com Odd Lots where we post transcripts Tracy and I blog and we'll
write a Weekly Newsletter every Friday go there subscribe to it get it in your inboxes thanks for listening
[Music]
thank you [Music]
ー
ーーー
0:00
[Music] [Applause]
0:09
hello and welcome to another episode of the odd Lots podcast I'm Tracy Alloway and I'm Joe weisenthal Joe I I feel like
0:17
I'm gonna Jinx things by saying this but it feels like inflation is maybe
0:23
starting to come down a little bit at least it's not accelerating yeah let's put it that way well here's how uh
0:29
here's what I've been thinking about which is that for the last year or the last year and a half we've done all of
0:35
these episodes on like Supply chains and disruptions for this or that reason and
0:41
all of the various times we've um used the term perfect storm to describe
0:46
certain things in certain industries Perfect Storm of perfect storms my guess right now you know in January 2023 is
0:53
that 2023's episodes will be a little less dominated by these topics that would be my guess I'm guessing that this
1:00
year we do a few fewer Perfect Storm episodes I think that's right but I think you know we we spoke a lot about
1:06
what it was that people didn't see coming when it comes to inflation why did a lot of economists get it wrong why
1:12
was the inflation That was supposed to be transitory you know maybe it was transitory in the sense that it was narrow you know not a big sort of like
1:19
macro Unleashed inflation but it definitely stuck around longer than a lot of people expected and so every time
1:27
we have these big questions like why aren't we better at forecasting inflation it provides an opportunity to
1:34
maybe learn something and start thinking about it in a slightly different way well yeah absolutely and I would say
1:40
there's really two things that I feel are unanswered by all of the conversations that we've had uh in the
1:47
last year so one is still like is inflation like a macro or a micro thing
1:52
did it happen because a few categories uh really had some disruptions and then
1:57
spill elsewhere and therefore it's not really about fiscal or monetary policy specifically and B okay we do have very
2:06
high inflation right now even if there's evidence coming down what tool like if
2:11
it is the case that a lot of it is related to disruptions and Chip shortages and freezes in Texas Etc what
2:19
are the tools that are best to address that because it is important to get inflation down but on the other hand
2:25
there's a pretty good argument that if the issue is some sort of disruption at the ports or whatever that sort of like
2:31
strict blunt instruments like raising rates raising rates aren't necessarily the best uh approach to dealing with
2:37
that kind of or raising rates won't grow more trees to turn into Lumber or more
2:42
births at the ports or anything like that so I'm so glad you said that because today we are going to be speaking with one of our Odd Lots
2:48
favorites and she has just written a new paper uh which she says is inspired by
2:53
some of the conversations that we've had on odd Lots but it's also just really interesting because it presents a new
2:59
sort of third wage potentially of thinking about inflation not transitory
3:05
not persistent a new more interesting third option and that maybe could help
3:10
us think about ways of accepting yes inflation is real it is a problem but
3:16
that some of these blunt instruments that just treat inflation as a function of there's too much money in the economy
3:22
we need there to be less maybe there are better approaches than just this sort of like blunt monetary approaches to
3:28
addressing them absolutely so without further Ado we are going to be speaking today to Isabella Weber she is of course
3:35
a economics professor over at the University of Massachusetts Amherst and you might remember her from from some
3:41
previous episodes so Isabella thank you so much for coming back on odd lots
3:46
thank you so much for having me it's a pleasure thank you so the paper is called inflation in times of overlapping
3:54
emergencies systemically significant prices from an input output perspective but I just want to get you to say on
4:01
camera that this is inspired by Autobots it is I mean a happy list
4:10
and as you were just saying obviously you have been tracing all these price shocks that have been Rippling for the
4:16
economy so um this paper is trying to come up with a framework to trace these shocks and
4:23
ripple effects um in a somewhat more Aggregate and possibly less fine print
4:28
but maybe a little bit more like formal kind of fashion I love that the most
4:35
self-serving first question that we've ever asked on an interview what is you
4:40
know what it what is an input output approach mean because my understanding is that this is actually like a very old
4:48
idea in economics but that is some kind of it's actually been forgotten is my
4:53
understanding and that this sort of like various versions of monitorist thinking which sort of treat if prices are high
5:00
if one understand prices we'll just look at how much money or how much credit is in the economy rein that in and you've
5:06
seen this paper seems to be like going back to like an older tradition in economics can you talk a little bit
5:11
about what this is yeah so as you said we tend to think about inflation as a micro firm right where it's basically just
5:19
aggregate measures whereas what we are trying to do here is to think of prices
5:24
as um kind of an interconnected Network where um since one sector's output is
5:31
another sector's input and therefore one sector's output prices are the cost of
5:37
another sector you can kind of Trace um the price movements across the whole
5:42
production Network which input output tables allow you to do so these tables
5:48
basically like register the relationships of input and outputs um across the whole economy historically
5:56
input output tables really had a breakthrough during the war time where
6:02
the question was um how can we hit the enemies economy in ways that we kind of like
6:10
with the minimum number of bombs um create the maximum damage to really I
6:17
mean undermine um the enemy economy's ability to even fight a war I mean concretely of course
6:23
this is mainly about the German economy um and so therefore it really is a
6:29
method of identifying points um that are of particular systemic significance for
6:36
the economy as a whole back then the idea was to identify these points of vulnerability to um I mean as I said
6:43
create destruction the idea of our paper is to say if we can
6:48
identify these points of vulnerabilities then we can actually um kind of um know what the potential
6:56
sources of um of these rapid effects that can create marker outcomes um could be so if
7:03
some prices matter more than others we want to know what these prices are and input output is one method of trying to
7:10
identify these systemically significant sectors uh so Tracy my takeaway from
7:15
that is that in a war it makes more sense to say bomb an oil refinery than a
7:21
candy factory like it right like if you're thinking about well what are these sectors that will have the biggest Ripple effects across the economy then
7:28
that would be the implication well maybe we should talk about morale in that context but no okay there's another
7:34
there's another analogy um that you use in the paper which is you know if you're trying to identify systemically
7:40
important sources of inflation and maybe address them before they start actually
7:47
contributing to price increases it's kind of like trying to identify systemically important Banks and then
7:54
making sure that they you know hold more regulatory capital or maybe go under preemptive stress tests or things like
8:01
that can you talk about maybe you know before we get into policy Solutions can you talk about how that approach maybe
8:08
differs to traditional ways of thinking about inflation because you know in my
8:14
mind there's really there's the monetarist view it's all about the money supply and then there's a sort of new Keynesian view where it's more about you
8:20
know supply side and capacity and demand and things like that can you place this new approach in the context of those two
8:27
older ways of thinking about it so as different as like kind of monetarism and
8:33
new canes business more keynesianism can be they share the understanding that
8:39
inflation is always driven by macroeconomic factors right now what we are doing here I mean in one case it's
8:46
um the the distance from from uh aggregate capacity utilization in the other case it's more that like classic
8:52
story of too much money chasing to too few goods but still it's like trying to locate the the origins of inflation on
8:59
the aggregate level what we are trying to do here is to say well if there are micro origins of inflation if shocks to
9:07
specific sectors can matter in ways that they can unleash processes that actually
9:13
unsettle the stability of prices overall then we want to understand stand what
9:20
these sectors are we want to know where these points of vulnerability are so
9:25
that we can react to these shocks before they kind of Ripple throughout the whole
9:31
system and as you said interest rates are already being recognized as a
9:37
systemically significant kind of price right that's why we have central banks which of course historically at some
9:44
point was also not the case so it was a historical Evolution to recognize the systemic significance of interest rates
9:50
so in some sense what we are arguing here is to um is to say that there are more prices than the price of boring
9:58
money that can acquire systemic significance in ways that can have a
10:03
very large implications for monetary stability just a shout out we are drawing here on the workouts of Salo or
10:09
moreover who has been working on systemically significant prices for a while someone else we definitely have to
10:14
have on the podcast at some point it's so funny because you know of course and
10:19
we talked about this the last time you were on uh late last year you took a lot of heat for saying well maybe there's a
10:26
time for having some discussion about price controls everyone freaked out about that and yet they're like okay now
10:32
let's control the price of money as if that isn't a form of price control and yet of course Central Banking the
10:39
ultimate price control the ultimate price control but you know so I joked but I guess it's not really a joke that
10:45
like there are some areas where it's kind of obvious that some sort some functions in the economy are more
10:51
crucial to other Industries than others so an oil refinery is going to be more crucial to other Industries than a candy
10:58
factory but that's obvious how do you go about systematically identifying beyond the
11:05
sort of really crude uh examples what is this this sort of like a rigorous or
11:10
empirical approach to actually identifying what parts of the economy are in fact the most likely to have
11:16
Ripple effects elsewhere so what we have done in this paper is that we have simulated shocks to every industry in
11:23
the input output table and just orientation 71 industry so it's not super disaggregated I mean also not
11:29
super aggregate compared to macroeconomic variables but it's still fairly broad right so we run a shock on
11:36
each of these sectors and then we simulate how this shock runs through the whole economy reciting in in indirect
11:44
impact on um on on the CPI right because if the price of oil goes up the price of
11:50
plastic goes up the price of plastic toys goes up so therefore in the CPI you do not only have the direct effect of
11:57
people con of people consuming fuel or gas but you also have indirect effects
12:02
of plastic and plastic toys and then in all sorts of packaging and so on right so we are tracing this direct and
12:09
indirect effect that resides from a price shock in any one individual sector
12:15
and we run this um the simulation um for for every separate sector so that
12:21
we then get distinct magnitudes that show us whether a shock to
12:26
um to one sector matters more in comparison to another sector in other words we can create a ranking of what we
12:33
call the total inflation impact from a shock in these sectors now um with the
12:39
simulation we basically have three determinants that can render a sector systemically significant the first
12:46
determinant is the bait in the CPI and housing is a great example here housing
12:53
is not something that is very upstream and that creates a lot of property facts in in other Industries but it has a very
12:59
large weight in the CPI right so therefore if there is a price change in housing it has a pretty large impact on
13:07
on the CPI um something like um like oil and gas is actually pretty
13:14
Upstream but not as Upstream as something like wholesale trade um because of the ways in which the
13:19
upstreamness measures are constructed but for oil and gas you have very large
13:24
price movements so the magnitude of the shocks that we use are either using average volatilities in the in the two
13:33
decades before the pandemic or using the actual price change in the pandemic and
13:38
in the context of the Ukraine war so in oil and gas we actually had very large price movements already before the
13:45
pandemic and then again during the pandemic um and in in the context of the war so here the drivers would be kind of
13:52
all three components the importance um in terms of indirect effects creating a
13:58
relatively large total um weight in the CPI the large price
14:03
movements and relatively Upstream even though not as Upstream as wholesale trade whereas for wholesale trade it's
14:10
really um basically because of the upstreamness of that sector and then in the pandemic
14:17
of course we also had Fairly large eyes movements there but before the pandemic the price movements and wholesale trade
14:23
would have been much smaller than in in something like oil and gas extraction right so it's it's these three
14:29
dimensions that we are capturing in in um in creating this ranking so just on
14:34
this point can can I just press you when it comes to identifying the systemically important industries or I think you call
14:41
them ubiquitous Industries like how do you just disaggregate their weight in
14:47
the inflation indices versus the extent to which they matter for other prices
14:53
because I'm sure there will be some people who who listen to this and say like well obviously energy and you know
15:00
maybe some consumer goods and things like that have a higher weight in the CPI and so that's why you're getting
15:06
these results if you look look at the paper which I'm not expecting anyone
15:11
we can't we can't distinguish between a direct and an indirect effect right so
15:18
what our direct inflation impact is is just the weight in the CPI right this is just giving you this is what the CPI
15:25
shows us um uh is the weight of um of the change in safe petroleum and core products um
15:32
for the change in the CPI um but then there's this additionist here which we call the indirect effect
15:40
which comes um from tracing the indirect price
15:45
um uh movements that reside from this initial shock in say petroleum and core products now of course we have to make
15:52
assumptions on how Industries um hand over
15:57
a cost increases right and we in the paper we make two distinct assumptions
16:02
one is that it's just a pass-through of 100 and so firms just have a cost
16:08
increase and just pass this on to their customers the second assumption that we make is to say what if firms actually
16:16
don't just pass on the cost but they actually want to protect their profit margins now if their cost goes up go up
16:23
and they were to increase prices by just the amount of the increasing costs their
16:28
profit margin would go down right so what if um what if they actually protect their their profit margin so therefore
16:34
increase prices by more than the increase in costs um so this then gives
16:41
us different magnitudes of the total effect but we find that the rankings are relatively stable um independent of of
16:48
these different um assumptions that we are making and the CPI that we are using here is a synthetic CPI because of
16:55
course we have to break it down to um these 70 um One Industries that we have
17:00
um so it's it's it's it's not the CPI that you download from the ba um if you
17:06
just look for CPI but it's a CPI that you get from the ba if you look into input output tables
17:11
you know something I'm interested in and I don't know if it's something you've specifically looked at but it sort of
17:18
reminds me of this like you know we talk a lot about or economists have talked a lot in the last year about Goods versus
17:23
Services inflation is if these are like two distinct categories of types of
17:29
things that people buy that you can draw a bright line and say okay Goods have gone down but service is still up but it
17:34
seems to me that any good that we buy is also implicitly a bundle of services that need to go into the you know if I
17:42
buy a refrigerator well there's some sort of service person who helped delivery deliver the furniture
17:48
um and there are services for you know the truck driver or whatever it is does
17:53
your approach the sort of input output approach sort of um
17:58
I I'm trying to think exactly the way to phrase that but in your view does it offer a more useful way of thinking
18:05
about categories of goods Beyond just or sort of would seem to me like these arbitrary distinctions between between
18:11
the types of things that get bought in the economy good question yeah great question
18:16
um uh I mean I would of course say Yes um thank you thank you for saying that
18:22
is a great question okay no no sorry keep going um to be sure services are part of the
18:28
input output tables and we actually find that they are pretty Upstream because of the fact that you just described right
18:34
because there is like some form of even like small administrative service um involved in pretty much everything so
18:41
if we talk about it administer sorry if we talk about Upstream sectors we tend to think about the physical stuff like
18:48
oil and gas or matches or chemicals and so on right but what we actually see
18:54
when we do the analysis that is that some that that some services are very Upstream now the price movements in
19:01
services are relatively small on average over time because they're very much
19:07
um tied to wages right and wages tend to move much less than let's say commodity
19:13
prices right so therefore when we run these shocks the service sectors even
19:18
though um they are pretty Upstream end up not being very important for the general
19:24
movement of of prices in in this model um because just the the initial shock um
19:32
is so small if we model the shock um uh based on on magnitudes of past um price
19:38
movements and price movements in the um in the in the in the covid-19 inflation
19:43
now um I do think that this kind of does give us a different way of distinguishing
19:50
um uh categories of of of of sectors if you want so because the idea here really
19:55
is to say okay we don't care if it's services or if it's um Commodities or if
20:01
it's processed Goods or if it's manufacturing or whatever it might be but all that we care about is um the
20:07
importance of this sector it's if you want so it's centrality in relation to um all other sectors and in relation
20:14
into people's consumption patterns right so what we
20:21
find then is that the sectors that we identify systemically significant are
20:26
basically in three groups so it's a basic necessities stuff like housing food Farms that of course produce a lot
20:33
of food utilities and of course also energy and then basic production inputs
20:39
stuff like um uh the the fossil fuels that we have already talked about but also chemical products and then kind of
20:46
like basic circulation infrastructure so things like wholesale trade right which
20:51
is critical for Commerce it's a kind of a basic commercial infrastructure so I do think that this
20:58
does give us a different way of kind of um distinguishing um the nature of different sectors so once you've
21:05
identified these systemically important industries um you know these ubiquitous Industries
21:11
for inflation things like basic necessities housing Farms food and utilities and energy
21:18
how does that inform the the policy response so the idea here is that
21:25
because these sectors are so important that if there are a large price
21:32
movements in these sectors that have this has implications Way Beyond these
21:37
specific sectors um we should be paying more attention to what is happening in these sectors so
21:43
the first implication is to say we need more monetary and capacity why do we
21:48
need more monitoring capacity because we are living in some sort of a age of overlapping emergencies right where we
21:56
have of course a pandemic that is not over um location for example at what's happening in China and how this impacts
22:03
um Global production networks but also looking at climate change and your great episode on the Mississippi River and how
22:10
this is a kind of just making a whole sector in this case of
22:16
course grain um and other Commodities um grind to a hold but we also have
22:21
these massive geopolitical tensions that can have some huge implications for the
22:26
ways in which production is organized globally so in other words it seems very likely from my perspective that more
22:33
shocks may be in the pipeline of course no one wants these shocks and everybody is hoping that things will be calm and
22:40
stable um but um but uh like from the perspective of the Dynamics of
22:46
overlapping emergencies even if inflation is now easing and it seems like in the next couple of years these
22:52
kind of shocks um are likely to keep um coming so if that is the case you kind
22:57
of want to have capacity on the side of the state to be able to monitor these
23:03
sectors that are so important in um in in ways that allow you to react to these
23:09
shocks um before they kind of create these um huge cascading effects
23:15
throughout the whole economy and you then actually get some sort of potentially more generalized
23:21
um kind of inflation um Beyond monitoring capacity of course not enough to watch you want to be able
23:27
to kind of step in and stabilize right and um here then um I think the the big
23:34
shift in in policy thinking that emerges from this paper is that once we go on
23:40
the sector or a level we kind of leave the world of um more or less homogeneous Aggregates
23:47
where we can talk about interest rates up by one percent or down by one percent or 0.5 or 0.75 or whatever but it's like
23:54
pretty one dimensional right and pretty clear that there's like one dimension that we can measure very clear ways
24:01
quantitatively in percentage points very straightforward if we now think about
24:07
the prices of chemicals or um the stability of the flow of goods
24:12
and wholesale trade and therefore um the the prices attached to Jose trade or the prices of Commodities we enter
24:19
the world of qualitative differences right we enter the word of the the last
24:26
um uh uh two years of odd Lots episodes right where you have been unpacking this
24:32
um incredible amount of detail on the qualitative differences um that have
24:38
huge quantitative implications for pricing but that require
24:43
um quite um an extraordinary extent of um understanding of the specific
24:49
specifics of these sectors so to be able to react to shocks in these sectors I
24:56
think one would really need quite a bit of capacity that is quite tailored to
25:01
these sectors so there's no like kind of um uh one solution that that's it all if
25:08
you think about housing versus oil refineries you would obviously need a
25:13
very different kind of policy approach right so this then means that kind of these and I mean there is a lot of
25:19
capacity out there but it needs to be connected back to the question of
25:24
macroeconomic and monetary stability it's always so funny to me that there exists a data point on the terminals
25:31
that the FED monitor is called capacity utilization is if there's as if the
25:37
concept of industrial capacity could ever be homogenized in a single index of like oh here's refining capacity here's
25:43
apartment capacity here's capacity to make cars like it just like sort of blows my mind that that's like a that
25:49
that could ever be boiled down to a single number let me ask you a random question is there a sector or a part of
25:55
the economy that in your research surprised you as having uh more Ripple effects across other prices than you
26:02
might have expected that maybe people I mean oil is obvious right we all know that everything needs energy G or whatever but other sectors that maybe
26:09
people don't think of that have outsize effects generally speak resides are not terribly
26:15
surprising which might make you say like yeah then why bother modeling it
26:20
um to which I would answer well it is nice to kind of be able to capture these aggregate effects and Trace them in a
26:27
systematic way throughout the economy one of the sectors that I think is quite interesting is chemical products like
26:33
which is just in everything right it's like yes ubiquitous almost as um as as
26:40
fossil fuels and is incredibly important and apparently is also important not
26:47
only like from a quantity perspective of composition of production but also from uh from a price perspective so this is
26:55
one that I personally hadn't hadn't thought about as much I think wholesale trade kind of came very much to
27:02
um to the top of our minds in the pandemic but our simulations um for before the pandemic
27:09
um also show that Jose trade was already pretty important which again is
27:15
something that I think like from the pre-covet mindset would not have been something that I would necessarily have
27:21
associated with thinking about um inflation wait sorry what's wholesale
27:27
trade mean you said what what specific are you talking about yeah so Jose trait again like this is actually one of the
27:33
points where probably the level of aggregation can become a problem I mean generally speaking it's stuff like
27:39
Logistics but also wholesale Traders I mean any kind of company that um that
27:44
provide that that basically does always say merchandising right um which yeah
27:49
um yeah so Isabella can I ask one thing you mentioned in your paper you talk
27:55
about the possibility of minimum inventory requirements so if you know that a specific industry or thing is
28:02
important from an inflation perspective maybe we should build in additional inventory some resilience into the
28:08
system and this is you know inventories the idea of business is moving to just
28:13
in time and maybe being a little bit more vulnerable to Big shocks in demand this is almost classic odd Lots
28:20
territory and it seems like the difficulty there is how do you encourage companies to build up that extra
28:27
capacity in their system when maybe their incentives are more skewed towards you know just making money and profits
28:35
and short-term things how do you actually go about doing that how realistic is it yeah absolutely great
28:42
question um and I think that um I mean if it is about making money and some of the
28:48
companies that have experienced uh bottlenecks actually have the experience
28:53
that they have managed to increase their prices and raise that rented them even more profitable than before the pandemic
28:59
right so then your incentive of um of increasing your inventory might actually
29:05
be pretty low because you think like in normal times um I don't wanna have
29:10
inventories because I want to be as efficient as I can be and then if sharks hit if everybody is kind of um running
29:17
this same model like all competitors in one in one segment are running the same model so that they all don't have a lot
29:24
of inventories then there's this exactly wide um supply chain shock which allows
29:29
them to hide prices in ways in which they could not hike prices at normal times because now they kind of have this
29:35
Mutual knowledge of um of uh of of shortage um so and then they end up
29:41
being actually in a pretty good position and which we have seen in in some of the sectors that have experienced
29:48
um extreme um uh uh impacts on on their supply chains during the pandemic right so therefore we somehow need a way to
29:55
get out of this and I think because of what I just laid out it's not clear that
30:01
companies by themselves would necessarily increase their inventories
30:07
um that that sufficiently prevent this um Asian at least not to the extent as
30:12
it would be like kind of um socially desirable or desirable from a more like um macroeconomic kind of
30:18
standpoint how to do it practically again like I really see this paper as um
30:24
providing a framework and kind of starting a conversation and I think to get to the question of how to do it
30:30
practically and bond really has to start um talking to people who understand inventory management at companies rather
30:37
than me like kind of as the armchair Economist coming up with some some sort of fix all the inventories of U.S
30:44
corporations at once type of approach we're almost out of time I have one very short question but you know we did an
30:51
episode recently and it was pointed out by one of our guests that the way a lot of economists think is that if the price
30:56
of gas goes down for example that doesn't improve inflation because the sort of General equilibrium well that's
31:02
more money in people's pockets and they're just going to spend more on haircuts now or they're just going to
31:07
spend more on cars why there's a limit to how many haircuts yeah right or maybe
31:13
they'll spend more on going out to eat okay so uh and then it doesn't really get us anywhere like what do you say I'm
31:19
just curious your response to that that's like okay you target a sector great you target energy great then
31:24
everything's cheaper people have more money and they spend elsewhere and you don't get anywhere why should that not
31:30
why is that not a fatal flaw of your approach I mean this is the famous I mean one of the famous Friedman written
31:36
Friedman quotes also where he's saying exactly what you just said we were back to like monitor the sort of core
31:42
monitors thinking yeah yeah I mean this then kind of brings you back to the question of how firms are setting prices
31:48
right um and if we are in a situation where we have very highly concentrated
31:55
um uh corporate structures which I think is a fairly Fair descriptions of large parts of the American economy then we
32:02
can actually see that um uh that the demand response sorry that the price
32:07
response to demand is so surprisingly small in many cases that the prices are actually quite surprisingly stable I
32:14
mean if you think back to the two decades some decades before covet where
32:19
of course there have been periods of of more demand and less demand and so on but prices were surprisingly stable
32:26
right and everybody was a kind of surprised like why are prices so stable well um because in a very concentrated
32:33
sectors firms tend to um to compete over market share and compete over
32:40
um conquering new segments of markets um compete over cutting costs and so on less than um than using any kind of
32:49
small increase in demand by immediately raising prices right because if you raise prices in your competitor doesn't
32:55
raise prices because both of you are price makers they're not price takers right then that can actually harm you so
33:02
therefore um in in in the kind of institutional setting that we find ourselves in
33:08
um I don't think it's clear that if people spend less on gas then
33:14
immediately the prices of everything else that they are consuming are going up and I also don't think that this is
33:20
something that we see empirically that the the price of gas and oil going down the inflation in other parts of the
33:27
economy assembly like going up by any large margins Isabella we're going to have to leave it
33:33
there but thank you so much for coming on odd Lots uh you're definitely one of our favorites and I'm not just saying that because you've translated the past
33:40
two years into actual academic research um fascinating discussion thank you so much Isabella that was great thank you
33:46
thanks Isabella foreign
33:54
[Music]
33:59
that conversation was great and the paper is definitely worth a read although I know Isabella said she didn't
34:04
think anyone was actually going to read it one thing I was thinking is it does kind of go back to remember some of the
34:11
conversations we had with Stephanie Kelton on Modern monetary Theory and you know her solution was well we need
34:18
instead of reducing spending like maybe we identify where the bottlenecks are happening and we increase capacity or
34:25
try to increase capacity and my criticism of that was it's difficult to do it in real time but I think studies
34:32
like this maybe go some way towards identifying where to look right I think
34:38
this use of input output tables and is uh Isabella said is actually a very old
34:43
thing that you never hear mainstream economists talk about you know yeah it could be is like very useful idea and
34:50
like okay it's like difficult sure it's a lot more difficult to like identify critical sectors than it is to just
34:56
raise rates when CPI comes in higher than expected but it's doable and I did
35:01
read the paper but when I say I read the paper what I mean is I read the first four pages skipped over the 40 pages of
35:09
equations you have to do the intro and then the conclusion yeah so I read the I read the intro I skipped over like all
35:15
the equations and Greek symbols or whatever and then the conclusion it and I thought it was really uh interesting
35:21
and I think like I suspect and maybe as a result of all this the pandemic and
35:26
everything there might be renewed interest in this sort of like pretty rigorous approach to identifying
35:32
critical sectors and how they distribute prices across the economy exactly this I would be really disappointed if we came
35:38
out of the past two or three years without a sort of like new way of thinking about inflation or at least
35:44
maybe an additional Dimension yeah all right should we leave it there let's leave it there this has been another
35:50
episode of the odd Lots podcast I'm Tracy Alloway you can follow me on Twitter at Tracy Alloway and I'm Joe
35:56
weisenthal you can follow me on Twitter at the stalwart follow Our Guest Isabella Weber she's at Isabella and
36:02
Weber and check out her paper inflation in times of overlapping emergencies systemically significant prices from an
36:10
input output perspective follow our producers Carmen Rodriguez at Carmen Armin and dash Bennett at dashbot and
36:18
check out all of our podcasts at Bloomberg under the handle at podcasts and for more Odd Lots content go to
36:24
bloomberg.com Odd Lots where we post transcripts Tracy and I blog and we'll
36:30
write a Weekly Newsletter every Friday go there subscribe to it get it in your inboxes thanks for listening
36:36
[Music]
36:47
thank you [Music]
0 件のコメント:
コメントを投稿