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

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Speaker 2: Hello and welcome to another episode of The Odd Laws podcast.

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Speaker 2: I'm Joe Wisenthal.

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Speaker 3: And I'm Tracy Alloway.

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Speaker 2: In this ongoing trade war, I don't know. I guess

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Speaker 2: it's a trade war, all the trade headlines. I have

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Speaker 2: to say. One of the things I always think about

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Speaker 2: is and I write about it, and we reference it.

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Speaker 2: The two of us reference it all the time. The

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Speaker 2: complexity and the importance of sort of building complex things

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Speaker 2: as a marker of a sort of country's capacity for wealth,

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Speaker 2: and the sort of complex international trade webs that undergird

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Speaker 2: the production of complex things.

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Speaker 3: Joe, I know what you think about. It's monkeys and do.

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Speaker 2: You think about that?

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Speaker 4: Yeah?

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Speaker 3: I do think about that.

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Speaker 1: Okay.

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Speaker 3: The reason I think about monkeys and trees is because

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Speaker 3: couple of years ago we had Ricardo Houseman on the

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Speaker 3: podcast and he used this metaphor to describe why some

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Speaker 3: countries are richer, more economically developed than others. And the

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Speaker 3: metaphor was that certain products or industries are like trees

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Speaker 3: in a forest, and the firms are like monkeys, and

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Speaker 3: so businesses kind of jump from tree to tree, and

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Speaker 3: so what you find is if a country gets good

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Speaker 3: at one particular product, then the business the monkey will

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Speaker 3: jump to the next tree, the next adjacent product, and

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Speaker 3: use that experience to build out their offerings. And so

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Speaker 3: you tend to see, you know, the more complex economies,

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Speaker 3: the bigger forests, the more monkeys swinging from trees are

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Speaker 3: indicative of greater advancement and more wealth.

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Speaker 2: Right, And this is how you can have a you know,

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Speaker 2: a country that at one point specialized in rubber becoming

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Speaker 2: a major player in cell phones, or a economy that

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Speaker 2: one point made t shirts, which requires some level of

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Speaker 2: coordination of supply chains from the thread and the electricity

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Speaker 2: to power the looms suddenly become much more advanced any

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Speaker 2: number of things. Anyway, I think there's a very powerful idea.

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Speaker 2: But when I think about, you know, the idea that Okay,

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Speaker 2: now there's this trade barrier between the US and Canada,

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Speaker 2: for example, and we have these complex webs of supply

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Speaker 2: chains in which goods cross the border multiple times. Do

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Speaker 2: we constrain our capacity to do complex things?

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Speaker 3: Are the monkeys going to slam headfirst into a trade wad?

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Speaker 2: Yeah, it's literally right, Like they're swinging around and they're

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Speaker 2: making these webs and densifying and then suddenly they slam

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Speaker 2: into a wall in a very real way. What does

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Speaker 2: it mean for American wealth if America is sort of

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Speaker 2: like constrained.

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Speaker 3: Yeah, this ecology of trade, I think it's a very

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Speaker 3: valid question.

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Speaker 2: Well, I'm very excited back on the podcast that we're

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Speaker 2: going to be speaking with Ricardo Housman, professor at the

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Speaker 2: Harvard Kennedy School and the founding director of the Harvard

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Speaker 2: Growth Lab. So, Professor Housman, thank you so much for

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Speaker 2: coming back on Outlaws.

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Speaker 4: Thank you for having me. I'm really happy to be back.

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Speaker 2: It does not seem like if we're thinking from the

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Speaker 2: complexity framework, right, if we're gonna start like putting up nets,

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Speaker 2: maybe it's nets, we're gonna start putting up nets in

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Speaker 2: the forest between the trees from place it does seem

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Speaker 2: harder for the monkeys to swing.

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Speaker 4: Well, the way I think about the problem is that

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Speaker 4: the complexity that you were talking about in the introduction

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Speaker 4: is really the amount of knowledge that you have to

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Speaker 4: put together in order to be able to do things.

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Speaker 4: And the question is a little bit you know, how

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Speaker 4: mobile is that knowledge, how easy it is for you

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Speaker 4: to get to that knowledge? And that knowledge takes if

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Speaker 4: you want three forms, it takes the form of embodied

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Speaker 4: knowledge and tools and materials. So when you buy a cookbook,

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Speaker 4: it says if you want to make an omelet, it says,

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Speaker 4: you know, take eggs, take milk, take this, take that.

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Speaker 4: It doesn't tell you how to make eggs. It doesn't

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Speaker 4: tell you how to make milk. You just you just

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Speaker 4: buy the eggs, and you don't you disregard all the

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Speaker 4: technologies that go into making chickens and to making eggs,

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Speaker 4: and to feeding the chickens, and you disregard all of that.

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Speaker 4: You just buy the eggs, right, and all the knowledge

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Speaker 4: that was embedded in it, it's just in the egg.

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Speaker 4: So embodied knowledge is one form of knowledge, and trade

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Speaker 4: is one way to get it right. Codified knowledge is

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Speaker 4: the knowledge that exists in recipes, formulas, algorithms, do files.

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Speaker 4: You know, you just need to have the code and

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Speaker 4: follow the instructions if you are and then the third

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Speaker 4: form of knowledge is nohow in brains. And the problem

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Speaker 4: with knowledge is that there's very little knowledge that fits

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Speaker 4: in a brain. So if you want to run a company,

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Speaker 4: you need a lot of knowledge. You need knowledge about accounting,

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Speaker 4: about finance, about human resource management, about procurement, about production,

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Speaker 4: about branding, about marketing, you know about taxes, about contracts.

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Speaker 4: So you need a lot of knowledge. And to bring

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Speaker 4: that knowledge together, you need a team of people that

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Speaker 4: you need to put together. And complexity comes from, you know,

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Speaker 4: the breadth of the team that you have to put together. Now,

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Speaker 4: the more you can kind of modify stuff, then you

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Speaker 4: don't need to put the brains together because it's all

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Speaker 4: in the code. That's one of the things that we

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Speaker 4: may talk about artificial intelligence. It makes things in some

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Speaker 4: sense simpler because the knowledge is in the machine. It's

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Speaker 4: no longer you no longer need a brain to do it. Now,

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Speaker 4: what these trade barriers are doing is that they are

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Speaker 4: preventing you from, say, buying the eggs right so that

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Speaker 4: now you need to know how to do the eggs yourself.

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Speaker 4: So in some sense it's making things harder to do.

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Speaker 4: As Larry Summers has pointed out, there are about sixty

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Speaker 4: times more jobs using steel than job making steel. So

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Speaker 4: you know, you protect steel, you're making it easier for

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Speaker 4: all those guys that were going to make omelets by

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Speaker 4: making now the eggs harder to get. And that's going

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Speaker 4: to come at a detriment. You're going to get maybe

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Speaker 4: more jobs and steel making in the US, and you're

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Speaker 4: going to make all the people who use steel have

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Speaker 4: more trouble competing in the domestic market with their products

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Speaker 4: and more trouble selling their products abroad because now they're

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Speaker 4: buying more expensive eggs, more expensive steel. In this metaphor,

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Speaker 4: so in some sense, yes, what you're saying is that

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Speaker 4: bread barriers are going to make the ability to put

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Speaker 4: things together harder in the US. It's going to incentivize

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Speaker 4: some of the things that are being protected, but it's

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Speaker 4: going to create difficulties for everybody who you uses those

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Speaker 4: things to make other things.

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Speaker 3: Is there a way to design tariffs or other protectionist

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Speaker 3: trade measures in such a way that you would preserve

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Speaker 3: knowledge and I guess preserve access to some of the

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Speaker 3: components you need to build out more complex industries.

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Speaker 4: I mean, an interesting question is what is the case

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Speaker 4: for intervening in the market. Why would you need a policy?

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Speaker 4: And then the second question is would trade would tariffs

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Speaker 4: be your instrument? Okay, so I would say that economic

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Speaker 4: theory gives you at least three good reasons to intervene

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Speaker 4: in the market. That might justify something you might want

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Speaker 4: to call industrial policy. And then the question is is

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Speaker 4: tariff's the right industrial policy because now they're putting tariffs

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Speaker 4: on steel and aluminum. They want more still and aluminum

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Speaker 4: being made in the US. If you wanted more still

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Speaker 4: and aluminum made in the US, what instruments could you

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Speaker 4: have used? And its tariffs the right way? Okay, So

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Speaker 4: first there is the argument that in order to make something,

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Speaker 4: you have to know how to make it. You know,

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Speaker 4: it's hard to make things you don't know how to

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Speaker 4: make it, and typically when you start something you don't

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Speaker 4: you're not particularly good at it, but maybe over time

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Speaker 4: you become better at it. There are some learning curves,

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Speaker 4: and you want to get into those learning curves. And

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Speaker 4: that's a compelling reason maybe to intervene in a relatively

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Speaker 4: new industry where you know you haven't yet to figure

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Speaker 4: things out, saying maybe like solar panels or batteries, or

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Speaker 4: you know something that's relatively new that you still have

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Speaker 4: yet to figure out. You wouldn't do it for a

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Speaker 4: mature industry like say like electric gas turbines, because you

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Speaker 4: know they've optimized that to death and you know there's

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Speaker 4: there's no significant breakthroughs for decades now, so still would

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Speaker 4: not be the obvious thing that would come to mind. Right,

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Speaker 4: it's a nineteenth century chnology, it's an industry that has

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Speaker 4: that's quite mature, etc. But you might have a national

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Speaker 4: security reasons to protect it or something, but definitely not

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Speaker 4: learning curves. By the way, those learning curves, if they

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Speaker 4: are like inside the company, if it's something that the

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Speaker 4: company is learning and the company owns, markets have been

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Speaker 4: super happy to fund that. I mean, markets have funded

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Speaker 4: Amazon for decades while the company was losing money because

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Speaker 4: they're saying no, no, the company is figuring out how

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Speaker 4: to sell stuff on the internet. Eventually, when they do

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Speaker 4: figure it out, they will have access to a humongous

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Speaker 4: market and that's going to be super valuable. So markets

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Speaker 4: supported negative cash flows in Amazon for a very long time.

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Speaker 4: So you have to argue that these learning curves somehow

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Speaker 4: spill over into the value chain, spill over into more

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Speaker 4: complicated things to coordinate, and that's why you need some

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Speaker 4: kind of action. Sometimes the reason why industries get into

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Speaker 4: trouble is that you have chicken and egg problems that

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Speaker 4: you know the supplier is not there because you are

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Speaker 4: not there and you're not there because the supplier is

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Speaker 4: not there. So there's a good equilibrium in which both

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Speaker 4: you and your suppliers are there, and there's a bad

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Speaker 4: equilibrium in which neither of you is there. So how

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Speaker 4: do you go from the val equilibrium where none is

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Speaker 4: there to the good equilibrium where both are there. And

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Speaker 4: that's a problem that we know how to solve. In

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Speaker 4: each one of these cases, caras may not be the

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Speaker 4: right instrument. So for example, you know, if you wanted

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Speaker 4: the supplier and you to be there, well, maybe the

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Speaker 4: garment comes and says, you know, I'm going to give

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Speaker 4: a supplier the guarantee that you're going to buy from them,

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Speaker 4: and I'm going to give you a guarantee that the

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Speaker 4: supplier is going to be there to sell you. So

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Speaker 4: you install your plant, he installs this plant, and the

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Speaker 4: guarantee expires worthless. So the government can coordinate on the

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Speaker 4: good equilibrium. Essentially no money and taxing nobody. A set

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Speaker 4: of guarantees would do the trick. If you want the

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Speaker 4: firm to learn, I mean, one thing is to have

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Speaker 4: these temporary what they call infant protection and the term

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Speaker 4: in the literature is infant industry protection. So you take

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Speaker 4: an industry at its infancy, and you give it some

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Speaker 4: protection until it finds its way, and then you open

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Speaker 4: up an alternative to that is you subsidize their capital investment,

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Speaker 4: or you guarantee their demand maybe government procurement or something else,

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Speaker 4: or you give it a special tax treatment, so you

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Speaker 4: have other ways to intervene. The moment you intervene with tariffs,

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Speaker 4: you're essentially dumping the cost on the consumers of that industry,

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Speaker 4: and the consumers of that industry are going to become

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Speaker 4: less competitive, and their size will shrink, and they may

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Speaker 4: become vulnerable to other attacks. So it's not the ideal instrument.

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Speaker 4: There's an additional reason why it may not be the

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Speaker 4: right thing to do. The US is and politically, part

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Speaker 4: of all these policy is based on the fact that

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Speaker 4: the Midwest did very poorly. The russ Belt did very poorly.

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Speaker 4: They lost a lot of manufacturing jobs, and you would

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Speaker 4: like jobs to go back to the Midwest. Pittsburgh loss

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Speaker 4: it's steal industry. Garandianna lots it's steal industry. Youngstown, Ohio, Cleveland, Detroit,

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Speaker 4: et cetera. These cities lost jobs in some industries. Now

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Speaker 4: you put the barriers you put tariffs at the national level.

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Speaker 4: It doesn't mean that the industries are going to go

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Speaker 4: to the Midwest. They may go to write to work

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Speaker 4: states in the South. They may go to the Southwest.

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Speaker 4: So it's not not your solution to the places at

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Speaker 4: your t I have to help those might be better

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Speaker 4: dealt with using place based instruments.

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Speaker 2: You know, I really like this idea of physical products

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Speaker 2: as embedded knowledge, so that if I'm making some recipe

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Speaker 2: that calls for eggs, that the eggs that I buy

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Speaker 2: are the end result of all the knowledge of the farmers.

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Speaker 2: I don't have to have that knowledge myself. It makes

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Speaker 2: it simpler process. I was reading a speech recently Ellen Young.

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Speaker 2: This speech was given I think in nineteen twenty eight.

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Speaker 2: Here's the former president of the London School of Economics,

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Speaker 2: and he said, it is generally agreed that Adam Smith,

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Speaker 2: when you suggested the division of labor leads to inventions

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Speaker 2: because workmen engaged in specialized routine operations come to see

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Speaker 2: better ways of accomplishing the same results miss the main point.

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Speaker 2: The important thing, of course, is that with the division

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Speaker 2: of labor, a group of complex processes is transformed into

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Speaker 2: a succession of simpler process. So therefore making something with

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Speaker 2: eggs is simpler because someone else doing the simple job

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Speaker 2: of making of growing eggs, I'm making the simple job

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Speaker 2: of maybe making an omelet or something. Something becomes a

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Speaker 2: succession of simpler jobs. But the question I have is,

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Speaker 2: does that mean that sort of like sheer market size

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Speaker 2: as measured by even by things like population, et cetera,

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Speaker 2: become important in these questions because if we're going to

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Speaker 2: make complex things, doesn't that on some level require either

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Speaker 2: through our population or our friends population, a decent number

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Speaker 2: of people who can then do all of these individually

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Speaker 2: simple tasks.

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Speaker 4: Well, I mean, if that's the reason why value chains

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Speaker 4: have become longer, where you just slice it into more modules,

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Speaker 4: and then you bring those modules together, and then some OEM,

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Speaker 4: some original equipment manufacturer that is putting fifty thousand pieces together,

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Speaker 4: and then each one of the fifty thousand pieces, it

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Speaker 4: becomes a more manageable task. But some industries require a

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Speaker 4: lot of a lot of talent that has to come together.

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Speaker 4: And for example, when you go to the do you

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Speaker 4: see a film? In the movies, sometimes they put at

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Speaker 4: the end of a movie it says the end, but

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Speaker 4: it's a misnomer because after they put the end, they

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Speaker 4: start showing you the credits, and the credits go on

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Speaker 4: for minutes and minutes. You know, there's there's the casting,

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Speaker 4: there's the sound effects, there's the visual effects, there's editing,

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Speaker 4: director of photography. So you need a whole massive team

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Speaker 4: of people that are involved in that in that movie

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Speaker 4: making industry. Well, an industry that requires this deep pool

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Speaker 4: of differentiated talent tends to locate only in very large cities,

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Speaker 4: say like Los Angeles or New York. That's the only

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Speaker 4: place where you would you could put together all that

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Speaker 4: necessary talent that is required. So industries that require a

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Speaker 4: more diverse pool of talent tend to locate themselves in

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Speaker 4: bigger cities, and the ones that are kind of simpler,

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Speaker 4: lower complexity, they can afford to locate in a smaller

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Speaker 4: city because in that smaller city they could probably find

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Speaker 4: the more limited diversity of skills that they need. Now,

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Speaker 4: one of the things that is a feature of the

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Speaker 4: American economy over the last twenty years is that the

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Speaker 4: industries that tend to locate in large cities have done

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Speaker 4: dramatically better than the industries that tend to locate in

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Speaker 4: smaller cities. The industries that tend to locate in smaller cities,

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Speaker 4: they tend to demand more land and not that diverse

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Speaker 4: labor force. So they're not willing to pay the high

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Speaker 4: prices of land of big cities so they can buy

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Speaker 4: more land and they don't rely so much on this

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Speaker 4: diverse labor force. But the industries that require a deep,

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Speaker 4: diverse pool of talent, they are willing to pay the

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Speaker 4: higher price of land in larger cities because they don't

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Speaker 4: use that much land. So what I would put it

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Speaker 4: to you is that part of the drama of the

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Speaker 4: US is the fact that there's been this shift in

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Speaker 4: demand in favor of the things that happened to be

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Speaker 4: done in bigger cities. And by the way, let me

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Speaker 4: make a very important point. We just saw the elections

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Speaker 4: in Poland, and the elections in Poland meant that, you know,

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Speaker 4: the president that won that election is a more called it,

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Speaker 4: a more trump like figure, and in fact, his party

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Speaker 4: pis he got elected more or less ten years or

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Speaker 4: eleven years before Trump, so there was already kind of

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Speaker 4: like a Trumpian motivation behind the election of that party.

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Speaker 4: They were upset about Trey and globalization, and Europe and

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Speaker 4: so on. Now, the interesting thing about Poland is that

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Speaker 4: Poland is at the exact opposite experience of the US.

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Speaker 4: In terms of trade. Poland has seen rising market share

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Speaker 4: across the board in all industries, in agriculture and manufacturing,

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Speaker 4: in cars, in machinery, in textiles, they have made out

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Speaker 4: like Bandits. Trade has exploded positively in Poland. But the

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Speaker 4: thing that has exploded in Poland has benefited these larger

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Speaker 4: urban areas and has has heard the smaller, less metropolitan

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Speaker 4: parts of the country, and that has generated a political backlafe.

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Speaker 3: So even even if the gains have been absolute for

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Speaker 3: Poland overall, I guess the relative differences within the country

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Speaker 3: are are have become a grievance.

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Speaker 4: Yes, let me say one point that we often they

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Speaker 4: do not emphasize. No, we often think of countries as

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Speaker 4: small open economies. They are small in the sense that

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Speaker 4: what they do is not going to change the global economy.

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Speaker 4: The US is relatively bigger, but many countries think a

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Speaker 4: smaller open economy. When you think of a city, a

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Speaker 4: city tends to be an even smaller and even more

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Speaker 4: open economy. It's smaller, right, much smaller than the country

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Speaker 4: it's in right, and it's more open because it trades

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Speaker 4: with not only the rest of the world, but the

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Speaker 4: rest of the country, and the labor force can either

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Speaker 4: come from the rest of the country or leave to

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Speaker 4: the rest of the country. Right, So what tends to

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Speaker 4: characterize a city. And you know, for a country, its

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Speaker 4: export base is super important. For a city, its export

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Speaker 4: base is even more important because a city is less

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Speaker 4: self sufficient than a country. A city needs to consume

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Speaker 4: a lot of things that it doesn't make. Most cities

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Speaker 4: don't make cars, don't make antibiotics, most cities don't make

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Speaker 4: X ray machines, they don't make, you know, eggs. So

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Speaker 4: all of these things have to be brought in and

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Speaker 4: to pay for these things that they want to consume

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Speaker 4: in the city, they need to earn money from outside

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Speaker 4: the city. They need to export in order to be

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Speaker 4: able to import. So the set of export activities in

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Speaker 4: a city determines very much the life of the city.

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Speaker 4: If those export activities in the city get into trouble,

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Speaker 4: then it's not just that those jobs in those exports,

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Speaker 4: in thus trees getting, you know, are lost, but those

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Speaker 4: workers used to you know, go to the barber, go

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Speaker 4: to a grocer go to the dentist. So all those

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Speaker 4: jobs in all of these local services also get lost,

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Speaker 4: and you get this multiplier local effect and people start

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Speaker 4: leaving the city. The moment people start leaving the city,

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Speaker 4: their housing prices go down. There's less money to pay

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Speaker 4: for education, so the quality of education, the theories, and

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Speaker 4: you get all of these negative local effects in the city. Okay,

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Speaker 4: that's associated with the export industry of your city getting

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Speaker 4: into trouble. So what I'm saying is that the shift

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Speaker 4: in demand has it hurt cities. The kinds of industries

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Speaker 4: that tend to locate in smaller cities, the kind of

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Speaker 4: industries that need less of a deep pool of talent

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Speaker 4: and more land. And the current industry is a good example.

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Speaker 4: The whole still you skill is a dirty, complicated, large thing.

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Speaker 4: So it may hire a lot of workers, but it

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Speaker 4: doesn't want to have too many people around them. They

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Speaker 4: need a lot of land, so they're not going to

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Speaker 4: go to Los Angeles. They're going to go to a

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Speaker 4: place where they can acquire a lot of land to

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Speaker 4: put their big plant. And it's the fact that the

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Speaker 4: export sector of cities in the Midwest, say, got into trouble.

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Speaker 4: The fact that the export activities in some parts of

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Speaker 4: Poland got into trouble, that they got into this negative

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Speaker 4: spiral as people you know, left because they have better opportunities,

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Speaker 4: and maybe other parts of the country, in larger cities,

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Speaker 4: they leave behind a deteriorating economic and social situation.

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Speaker 3: I promise not to get to hung up on metaphors

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Speaker 3: and monkeys, but I just want to go back to

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Speaker 3: the egg analogy for one second. So I understand. You know,

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Speaker 3: division of labor expertise can lead to efficiency and app

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Speaker 3: gains economically for everyone. However, you know, I'm thinking back

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Speaker 3: to when egg prices were very high in the US

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Speaker 3: earlier this year, and I joked on this podcast that

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Speaker 3: I was going to get my own chickens so that

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Speaker 3: I could declare egg independence, egg autarchy and have my

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Speaker 3: own supply. Are there not arguments, you know for certain

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Speaker 3: things that you would want to have the capacity to

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Speaker 3: build those components at home in order to enable you

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Speaker 3: to build more complex items.

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Speaker 4: Well, no, you would want to make sure that you

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Speaker 4: have a diversified source of supply, so that there's a

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Speaker 4: problem in Brazil, you can buy from somewhere else. Right,

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Speaker 4: So this whole thing about food security that some countries say,

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Speaker 4: you know, we need to have food security, so we

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Speaker 4: need to produce food in our country at three times

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Speaker 4: the international price. Well, I mean that's not food security.

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Speaker 4: That's exacerbated risk because you know your country can be

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Speaker 4: hit by a drought, by a storm, by et cetera.

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Speaker 4: Many things that could destroy your food production. So you're

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Speaker 4: going to face much less risk if you have a

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Speaker 4: diversified source of materials. And that's one reason why you

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Speaker 4: would want to have a good trading relationships with many

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Speaker 4: countries because that way, you know, if you get in trouble,

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Speaker 4: you can buy from somewhere else. So no, I in general,

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Speaker 4: this idea that the price of wheat worldwide goes up,

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Speaker 4: that's the reason for you to have your own wheat production.

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Speaker 4: That doesn't follow at all. Your wheat production might be

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Speaker 4: it might subject you to even more risks than a

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Speaker 4: diversified source of wheat from across the world. It's a

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Speaker 4: different thing if you're talking militarily, right.

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Speaker 3: Yeah, I was going to say, what about something like

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Speaker 3: I want to build semiconductors domestically because I think they're

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Speaker 3: a very important part of our defense strategy.

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Speaker 4: Well, I can perfectly understand that you have an incredible

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Speaker 4: concentration of semiconductors in Taiwan, and it's very easy to

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Speaker 4: imagine a situation where you no longer have access to

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Speaker 4: those semiconductors. So in that case, I can I can

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Speaker 4: see the case that would justify things like the Chips Act,

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Speaker 4: not necessararily things like tariffs on chips, but because tariffs

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Speaker 4: and chips would make all industries that use chips less competitive,

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Speaker 4: et cetera. But you know, in creating an encouragement for

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Speaker 4: and by the way, convincing TSMC or the Taiwan Semiconductor

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Speaker 4: Manufacturing Company, which is the best a foundry in the world,

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Speaker 4: to come and see if they can figure out how

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Speaker 4: to make it in Arizona. And by the way, it's

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Speaker 4: very interesting and it shows you the importance of knowledge

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Speaker 4: and know how that sometimes it's very very difficult for

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Speaker 4: the same firm that supposedly the firm knows how to

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Speaker 4: do something, say Boying knows how to make airplanes in Seattle. Well,

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Speaker 4: guess what, making airplanes in South Carolina. Making Boying airplanes

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Speaker 4: in South Carolina proved to be much harder than making

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Speaker 4: airplanes in Seattle, and transporting the knowledge was a big headache,

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Speaker 4: and right now TSMC is facing serious challenges and transporting

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Speaker 4: the knowledge to Arizona. So if you put the accent

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Speaker 4: on moving the knowledge, things look a little bit different

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Speaker 4: than just a discussion about tariffs.

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Speaker 2: Yeah, supposedly the yields on the Arizona fabs are quite impressive,

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Speaker 2: and they're starting together momentum. Of course, your point is taken,

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Speaker 2: but actually this does raise some questions. I mean, you've

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Speaker 2: talked about, okay, the importance of diversity of your supply chain.

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Speaker 2: To my mind, actually when I hear that, I think, okay,

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Speaker 2: there's something legitimate about like anxiety about China specifically, because

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Speaker 2: what's happening in manufactured goods is that it's not a

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Speaker 2: globally diverse supply chain. It's becoming in many areas a

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Speaker 2: China only supply chain. That China's lead in this, that

435
00:27:13,960 --> 00:27:17,480
Speaker 2: its network effects, that it's internal whatever is becoming so

436
00:27:17,840 --> 00:27:21,879
Speaker 2: concentrated in one country for such a big range of

437
00:27:22,080 --> 00:27:25,840
Speaker 2: goods that at least from a non China perspective, it

438
00:27:25,840 --> 00:27:29,240
Speaker 2: feels like from a risk management standpoint, et cetera, that

439
00:27:29,280 --> 00:27:33,080
Speaker 2: there probably is a very good imperative to put forth

440
00:27:33,160 --> 00:27:37,320
Speaker 2: effort towards not necessarily having an American production capacity, but

441
00:27:37,440 --> 00:27:39,280
Speaker 2: a non China production capacity.

442
00:27:40,040 --> 00:27:44,440
Speaker 4: Well, we went through a Japan scare in the nineteen eighties, right,

443
00:27:44,760 --> 00:27:47,919
Speaker 4: And what ended up happening in Japan is that Japan

444
00:27:48,080 --> 00:27:51,000
Speaker 4: kept on progressing and becoming good at everything to a

445
00:27:51,119 --> 00:27:54,199
Speaker 4: point that wages in Japan went top a lot, and

446
00:27:54,320 --> 00:27:58,320
Speaker 4: Japan started to move their industries outside, the phenomenon that

447
00:27:58,520 --> 00:28:04,119
Speaker 4: was called the flying Geese, right, and so Toyota started

448
00:28:04,160 --> 00:28:08,600
Speaker 4: to make cars in Thailand and put things in Korea

449
00:28:08,640 --> 00:28:11,400
Speaker 4: and so on and so forth, and then they went

450
00:28:11,480 --> 00:28:15,960
Speaker 4: into poor states like Vietnam or Indonesia. So what you

451
00:28:16,040 --> 00:28:19,960
Speaker 4: have is that the more advanced manufacturing or the more

452
00:28:20,000 --> 00:28:23,440
Speaker 4: advanced parts of the value chain like R and D design,

453
00:28:24,680 --> 00:28:28,399
Speaker 4: et cetera, are retained in headquarters, and you move the

454
00:28:28,440 --> 00:28:33,360
Speaker 4: more labor intensive, the less skill intensive, the less complex parts,

455
00:28:33,800 --> 00:28:37,639
Speaker 4: the more standardized parts. You moved to a locations that

456
00:28:37,720 --> 00:28:41,120
Speaker 4: pay lower wages, and everybody is better off because for

457
00:28:41,200 --> 00:28:44,720
Speaker 4: those locations, it's a step up for you. It's a

458
00:28:44,760 --> 00:28:48,680
Speaker 4: way to save on labor costs that you cannot afford

459
00:28:48,680 --> 00:28:50,920
Speaker 4: in your country because you want to pay your workers

460
00:28:51,040 --> 00:28:53,640
Speaker 4: very very well, and you can afford to do that

461
00:28:53,760 --> 00:28:55,640
Speaker 4: because you have plenty of jobs for them, and the

462
00:28:55,680 --> 00:28:57,800
Speaker 4: more complex part of the value chain you don't need

463
00:28:57,840 --> 00:29:00,240
Speaker 4: to hire them, and the less complex part part of

464
00:29:00,240 --> 00:29:04,040
Speaker 4: the beligian So there is a world in which this

465
00:29:04,200 --> 00:29:06,920
Speaker 4: is a process. China is getting richer. A lot of

466
00:29:06,920 --> 00:29:10,000
Speaker 4: the things that are being done in China, by the way,

467
00:29:10,040 --> 00:29:12,520
Speaker 4: initially they were done in the coast, and so now

468
00:29:12,520 --> 00:29:15,520
Speaker 4: the coast has become too expensive, they're moving to elsewhere

469
00:29:15,520 --> 00:29:18,200
Speaker 4: in the country and to elsewhere in the region. And

470
00:29:18,360 --> 00:29:21,200
Speaker 4: you know, now there's more production in Vietnam, there's more

471
00:29:21,240 --> 00:29:25,120
Speaker 4: production even in Cambodia. There's more production in poor other

472
00:29:25,160 --> 00:29:29,040
Speaker 4: countries simply because the Chinese worker is now too expensive.

473
00:29:29,440 --> 00:29:32,320
Speaker 4: So there's a world in which this is just part

474
00:29:32,360 --> 00:29:36,040
Speaker 4: of just a repetition of what happened in Japan. But

475
00:29:36,160 --> 00:29:40,680
Speaker 4: let me make an important point. When a production is

476
00:29:40,720 --> 00:29:44,480
Speaker 4: happening elsewhere, it might be happening in a country. A

477
00:29:44,520 --> 00:29:49,000
Speaker 4: good question is where does the knowledge that they're using

478
00:29:49,200 --> 00:29:53,480
Speaker 4: come from? Because what is happening in the world today

479
00:29:53,600 --> 00:29:56,480
Speaker 4: is that the rich countries are becoming more and more

480
00:29:56,600 --> 00:30:02,240
Speaker 4: concentrated in producing knowledge. In order to monetize that knowledge,

481
00:30:02,520 --> 00:30:05,600
Speaker 4: they need to put brick and mortar things that they

482
00:30:05,640 --> 00:30:08,280
Speaker 4: prefer to put them in other parts of the world.

483
00:30:08,880 --> 00:30:11,440
Speaker 4: So Japan, for example, has come up with a lot

484
00:30:11,480 --> 00:30:13,440
Speaker 4: of innovations and a lot of R and D and

485
00:30:13,480 --> 00:30:16,240
Speaker 4: a lot of patents. But the way they monetize their

486
00:30:16,240 --> 00:30:19,800
Speaker 4: patents is not by hiring Japanese workers. That you know,

487
00:30:20,320 --> 00:30:25,400
Speaker 4: Japanese labor forces is declining and so on, and they

488
00:30:25,400 --> 00:30:28,960
Speaker 4: are at full employment. Anyway, they monetize their knowledge by

489
00:30:29,000 --> 00:30:33,840
Speaker 4: deploying that knowledge elsewhere with foreign direct investments and so on.

490
00:30:34,200 --> 00:30:38,200
Speaker 4: And that means that a lot of the of accounting

491
00:30:38,400 --> 00:30:41,800
Speaker 4: of how this process happens is not well captured by

492
00:30:41,800 --> 00:30:46,680
Speaker 4: our standard accounting techniques. For example, if Japan does R

493
00:30:46,720 --> 00:30:51,360
Speaker 4: and D and that improves the productivity of their foreign investment,

494
00:30:52,040 --> 00:30:56,400
Speaker 4: it doesn't show up as higher Japanese productivity. It is

495
00:30:56,520 --> 00:30:59,720
Speaker 4: increasing productivity, but not just not in Japan, in the

496
00:30:59,720 --> 00:31:03,400
Speaker 4: place is where Japan has its plans, and the same

497
00:31:03,480 --> 00:31:05,280
Speaker 4: is happening in the US. If you think of the

498
00:31:05,360 --> 00:31:09,600
Speaker 4: Magnificent Seven, the magnificence and for example Google, when Google

499
00:31:09,680 --> 00:31:14,080
Speaker 4: sort of like this places all the small newspapers of

500
00:31:14,120 --> 00:31:19,680
Speaker 4: the world because all advertising revenue is moving to it's

501
00:31:19,800 --> 00:31:23,360
Speaker 4: moving online, and Google is capturing a good chunk of

502
00:31:23,360 --> 00:31:28,520
Speaker 4: that that doesn't count as a US export because it's

503
00:31:28,840 --> 00:31:32,360
Speaker 4: some subsidiary that Google put in I don't know, in

504
00:31:32,440 --> 00:31:36,640
Speaker 4: South Africa or wherever that is collecting that revenue, and

505
00:31:36,680 --> 00:31:40,000
Speaker 4: that revenue you could count it as a US export,

506
00:31:40,560 --> 00:31:42,720
Speaker 4: but it's not being counted as a US export.

507
00:31:43,040 --> 00:31:45,520
Speaker 2: It turns into the US marketcap exactly.

508
00:31:45,560 --> 00:31:50,200
Speaker 4: It turns into the US into US marketcap. But US

509
00:31:50,200 --> 00:31:57,280
Speaker 4: marketcap is very poorly captured by balance of payment statistics. So,

510
00:31:57,560 --> 00:32:01,160
Speaker 4: for example, if you started the year two thousand, From

511
00:32:01,200 --> 00:32:05,480
Speaker 4: two thousand to the present, according to official statistics, the

512
00:32:05,640 --> 00:32:09,600
Speaker 4: US borrowed sixteen trillion dollars from the rest of the world.

513
00:32:09,680 --> 00:32:14,440
Speaker 4: It ran a cumulative current account deficit of sixteen trillion dollars.

514
00:32:15,000 --> 00:32:18,800
Speaker 4: You'd say, gee, you borrow sixteen trillion dollars. Well, how

515
00:32:18,880 --> 00:32:21,320
Speaker 4: much are you paying for those sixteen trillion dollars. Let's

516
00:32:21,360 --> 00:32:27,240
Speaker 4: say four percent? No, so four percent would be six

517
00:32:27,360 --> 00:32:31,640
Speaker 4: hundred and forty billion dollars in interest payments right on

518
00:32:32,160 --> 00:32:34,760
Speaker 4: the deck you borrowed. Now, if you look at the

519
00:32:34,880 --> 00:32:40,320
Speaker 4: US balance of payments primary income, essentially, the US doesn't

520
00:32:40,480 --> 00:32:42,880
Speaker 4: look like a country that has an external debt. They

521
00:32:42,880 --> 00:32:47,000
Speaker 4: are essentially paying zero. They borrowed sixteen trillion dollars, which

522
00:32:47,040 --> 00:32:51,320
Speaker 4: is say, sixty percent of GDP, and they're essentially not

523
00:32:51,400 --> 00:32:53,960
Speaker 4: paying anything for it. So you would say, well, if

524
00:32:53,960 --> 00:32:56,520
Speaker 4: I can borrow sixty percent of GDP for free, I

525
00:32:56,560 --> 00:32:59,760
Speaker 4: would do that. Well, in some sense, that's what do

526
00:32:59,760 --> 00:33:02,280
Speaker 4: you has done. The way I would like to describe

527
00:33:02,320 --> 00:33:06,000
Speaker 4: it is that US didn't just borrow sixteen trillion dollars.

528
00:33:06,360 --> 00:33:09,960
Speaker 4: It borrowed more like thirty two trillion dollars. It used

529
00:33:09,960 --> 00:33:14,440
Speaker 4: sixteen trillion dollars to cover that official deficit and use

530
00:33:14,480 --> 00:33:17,080
Speaker 4: the other sixteen trillion dollars to mix it with your

531
00:33:17,160 --> 00:33:22,240
Speaker 4: knowledge and invest abroad. And that investment abroad, say Google

532
00:33:22,400 --> 00:33:27,360
Speaker 4: in South Africa, mixed with US knowledge as this huge

533
00:33:27,440 --> 00:33:31,160
Speaker 4: rate of return. So when you borrow thirty two trillion dollars,

534
00:33:31,200 --> 00:33:34,600
Speaker 4: sixteen trillion dollars you borrowed at four percent, but the

535
00:33:34,640 --> 00:33:37,720
Speaker 4: other sixteen trillion dollars you invested at a much higher

536
00:33:37,840 --> 00:33:42,120
Speaker 4: rate of return because it was mobilizing your knowledge. And

537
00:33:42,200 --> 00:33:45,760
Speaker 4: so thirty two trillion, say, you pay four percent over

538
00:33:45,880 --> 00:33:49,120
Speaker 4: thirty two trillion dollars you borrowed, but you make eight

539
00:33:49,200 --> 00:33:53,000
Speaker 4: percent on the sixteen trillion dollars you invest abroad. Well,

540
00:33:53,040 --> 00:33:56,200
Speaker 4: it just turns out that eight percent over sixteen trillion

541
00:33:56,280 --> 00:33:58,840
Speaker 4: dollars is the same as four percent over thirty two

542
00:33:58,920 --> 00:34:03,280
Speaker 4: trillion dollars. You're not really running a deficit. You are

543
00:34:03,400 --> 00:34:09,239
Speaker 4: monetizing your knowledge, but current accounting standards don't capture that.

544
00:34:09,360 --> 00:34:13,160
Speaker 3: Well, this is very This reminds me of the Matrix

545
00:34:13,200 --> 00:34:15,560
Speaker 3: and that scene where they say there is no spoon.

546
00:34:15,680 --> 00:34:18,880
Speaker 3: What if there is no US external deficit? But okay,

547
00:34:19,000 --> 00:34:23,000
Speaker 3: one thing I'm struggling to understand. So you know, you're

548
00:34:23,239 --> 00:34:27,480
Speaker 3: arguing that the US actually has a significant amount of

549
00:34:27,560 --> 00:34:30,719
Speaker 3: knowledge and know how that is mixed up with its

550
00:34:31,040 --> 00:34:34,360
Speaker 3: foreign direct investment, and that doesn't show up in the

551
00:34:34,440 --> 00:34:40,680
Speaker 3: official trade statistics. And I guess one thing I'm kind

552
00:34:40,680 --> 00:34:44,840
Speaker 3: of curious about is and you're arguing that the statistics

553
00:34:44,960 --> 00:34:50,000
Speaker 3: undervalue foreign direct investment. But I would have thought that,

554
00:34:50,120 --> 00:34:55,759
Speaker 3: like foreign direct investment, valuations inherently reflect market expectations. And

555
00:34:55,840 --> 00:34:59,160
Speaker 3: to Joe's point, I'm channeling Joe's love of the efficient

556
00:34:59,200 --> 00:35:03,360
Speaker 3: market's HYPOTHESI here, but they should be captured in market

557
00:35:03,360 --> 00:35:06,520
Speaker 3: cap and things like that. Why do we assume that

558
00:35:06,840 --> 00:35:13,080
Speaker 3: the statistical agencies, the accounting systems systematically mispriced these assets.

559
00:35:13,320 --> 00:35:15,640
Speaker 3: Are they not included anywhere.

560
00:35:15,719 --> 00:35:19,200
Speaker 4: They use book value. When you see the investment abroad,

561
00:35:19,239 --> 00:35:24,080
Speaker 4: they count how many dollars you sent abroad, and then

562
00:35:24,200 --> 00:35:27,920
Speaker 4: they count how much money did you make abroad. And

563
00:35:28,480 --> 00:35:30,799
Speaker 4: when you look at it, the rate of return on

564
00:35:31,000 --> 00:35:34,920
Speaker 4: FBI is double the rate of return on debt in

565
00:35:35,000 --> 00:35:38,200
Speaker 4: the accounts, So they're not counting the firm direct investment

566
00:35:38,800 --> 00:35:42,479
Speaker 4: at the market value. By the way, it's very hard

567
00:35:42,480 --> 00:35:45,400
Speaker 4: to calculate that market value because these are subsidiaries of

568
00:35:45,480 --> 00:35:49,319
Speaker 4: companies that listed the S and P five hundred and say,

569
00:35:49,320 --> 00:35:52,879
Speaker 4: if the price earningserration in the US is twenty six

570
00:35:53,040 --> 00:35:55,800
Speaker 4: or something like that last time I checked, it means

571
00:35:55,800 --> 00:35:58,400
Speaker 4: that they are thinking that all that's money that the

572
00:35:58,440 --> 00:36:02,680
Speaker 4: Magnificent seven are making a broad they multiply by twenty

573
00:36:02,719 --> 00:36:06,560
Speaker 4: six or an even higher number. Right, But that was

574
00:36:06,640 --> 00:36:09,520
Speaker 4: not the accounting was made at book value. So in

575
00:36:09,560 --> 00:36:12,879
Speaker 4: most of these companies there's a huge difference between book

576
00:36:12,960 --> 00:36:15,120
Speaker 4: value and market value.

577
00:36:15,320 --> 00:36:17,880
Speaker 3: Yeah, I was about to say, this is the argument.

578
00:36:17,920 --> 00:36:20,560
Speaker 3: I think We've even done an episode on this about

579
00:36:20,719 --> 00:36:24,200
Speaker 3: stock market valuations and how companies with a large amount

580
00:36:24,239 --> 00:36:28,080
Speaker 3: of intangibles. It's not reflected in book value.

581
00:36:27,800 --> 00:36:30,760
Speaker 4: Right, and that, in my mind is the market's valuation

582
00:36:30,880 --> 00:36:34,600
Speaker 4: of your knowledge exactly. So in a world where knowledge

583
00:36:34,680 --> 00:36:38,760
Speaker 4: is intensive, then book value becomes less of a guide

584
00:36:38,760 --> 00:36:42,040
Speaker 4: on what's actually happening. In a lot of international trade

585
00:36:42,080 --> 00:36:45,080
Speaker 4: statistics is book value because that's what they have to

586
00:36:45,120 --> 00:36:46,120
Speaker 4: make the statistics.

587
00:36:46,480 --> 00:36:48,879
Speaker 2: I think there's a really interesting question. I have one

588
00:36:48,960 --> 00:36:51,040
Speaker 2: last question, and I wasn't expecting to go here, but

589
00:36:51,080 --> 00:36:52,600
Speaker 2: I thought that was so interesting what you were saying

590
00:36:52,600 --> 00:36:56,560
Speaker 2: about Poland and some of the politics not necessarily being

591
00:36:56,560 --> 00:37:00,560
Speaker 2: about the country's overall trading position visa the rest of

592
00:37:00,600 --> 00:37:04,280
Speaker 2: the world, but the internal dynamics of what is happening

593
00:37:04,320 --> 00:37:07,760
Speaker 2: in these countries, where the booms are happening in cities,

594
00:37:07,800 --> 00:37:10,560
Speaker 2: and how that is a function to some extent of experts.

595
00:37:11,120 --> 00:37:13,560
Speaker 2: But I'm curious. One of the things that people bemoan

596
00:37:14,040 --> 00:37:17,080
Speaker 2: about the current environment in the United States and probably

597
00:37:17,120 --> 00:37:20,360
Speaker 2: elsewhere is that cities are no longer a good place

598
00:37:20,360 --> 00:37:23,879
Speaker 2: for upward mobility. That you can't be poor or middle

599
00:37:23,880 --> 00:37:25,600
Speaker 2: class that move to a city and find a job

600
00:37:25,640 --> 00:37:27,839
Speaker 2: and move up the career ladder in the same way

601
00:37:27,880 --> 00:37:32,760
Speaker 2: you could when cities were more centers of hard industrial activity.

602
00:37:32,800 --> 00:37:35,120
Speaker 2: And I'm curious when you talk about the types of

603
00:37:35,120 --> 00:37:38,560
Speaker 2: companies that locate in big cities versus the type of

604
00:37:38,640 --> 00:37:42,719
Speaker 2: companies that locate in smaller cities, et cetera. Are the

605
00:37:42,880 --> 00:37:46,040
Speaker 2: type of companies that locate in big cities not as

606
00:37:46,200 --> 00:37:52,120
Speaker 2: conducive inherently towards upward mobility because there's just so much

607
00:37:52,400 --> 00:37:55,319
Speaker 2: talent required just to get in the door anywhere at

608
00:37:55,320 --> 00:37:55,920
Speaker 2: these firms.

609
00:37:57,080 --> 00:37:59,360
Speaker 4: No, I think that the problem of big cities in

610
00:37:59,400 --> 00:38:03,640
Speaker 4: the US is the fact that they have regulated urban

611
00:38:03,760 --> 00:38:07,959
Speaker 4: space in such a way that housing supply is very inelastic,

612
00:38:08,640 --> 00:38:11,280
Speaker 4: so as people try to move to a city, housing

613
00:38:11,360 --> 00:38:14,720
Speaker 4: prices go up until it's unaffordable to move into a city.

614
00:38:15,160 --> 00:38:18,280
Speaker 4: That if cities had a more elastic supply of housing,

615
00:38:18,320 --> 00:38:22,360
Speaker 4: a more elastic supply of urban space, this dynamic would

616
00:38:22,560 --> 00:38:26,480
Speaker 4: help generate more opportunities in those cities and would help

617
00:38:26,520 --> 00:38:31,240
Speaker 4: maybe raise the price of labor in the cities where

618
00:38:31,320 --> 00:38:35,000
Speaker 4: people are leaving, because now they've become scarcer and people

619
00:38:35,120 --> 00:38:37,879
Speaker 4: would be willing to pay more for them. So that's

620
00:38:37,880 --> 00:38:41,040
Speaker 4: why you're seeing so much growth in cities like Boiseaira

621
00:38:41,280 --> 00:38:45,320
Speaker 4: or or Salt Lake City, or cities in Texas, Visa

622
00:38:45,400 --> 00:38:50,600
Speaker 4: these cities in California and having incredibly inelastic supply of housing.

623
00:38:51,040 --> 00:38:52,920
Speaker 4: So I would put there that, you know, on a

624
00:38:52,960 --> 00:38:57,719
Speaker 4: more inclusive policy involves urban development that allows for that

625
00:38:58,280 --> 00:38:59,360
Speaker 4: inclusion to happen.

626
00:39:00,160 --> 00:39:04,600
Speaker 2: Ricardo Houseman, So great chatting with you. Always extremely thought provocative,

627
00:39:04,880 --> 00:39:07,640
Speaker 2: always takes us down avenues that I don't expect. Really

628
00:39:07,680 --> 00:39:09,320
Speaker 2: appreciate you coming back on outlause.

629
00:39:09,719 --> 00:39:10,439
Speaker 3: Yeah, that was great.

630
00:39:10,440 --> 00:39:12,880
Speaker 4: Thank you, Ricardo, Thank you for having me.

631
00:39:26,680 --> 00:39:29,120
Speaker 2: Really like every time, like I mean every time. We've

632
00:39:29,120 --> 00:39:32,359
Speaker 2: always spoken to Ricardo twice, but I feel like every

633
00:39:32,400 --> 00:39:34,719
Speaker 2: time I talk to him, there's like a bunch of

634
00:39:34,760 --> 00:39:36,759
Speaker 2: ideas that are going to stick in my head for

635
00:39:36,800 --> 00:39:39,120
Speaker 2: a long time I'll be chewing on. In this one,

636
00:39:39,239 --> 00:39:44,080
Speaker 2: it's this idea that like official trade statistics don't capture

637
00:39:44,080 --> 00:39:48,160
Speaker 2: the fact that market value of this trade and which

638
00:39:48,200 --> 00:39:51,000
Speaker 2: you could see in the stock market trading in the

639
00:39:51,120 --> 00:39:54,960
Speaker 2: United States is much higher than what just sort of

640
00:39:55,040 --> 00:39:58,000
Speaker 2: like what is captured in the activity. I'm really intrigued

641
00:39:58,000 --> 00:39:58,600
Speaker 2: by this idea.

642
00:39:58,840 --> 00:40:02,400
Speaker 3: On board with that idea, but I kind of wonder

643
00:40:02,719 --> 00:40:05,759
Speaker 3: how far you can stretch it, and like can you

644
00:40:05,800 --> 00:40:08,840
Speaker 3: stretch it all the way to actually, the US doesn't

645
00:40:08,840 --> 00:40:11,480
Speaker 3: have an external deficit, or could you stretch it all

646
00:40:11,480 --> 00:40:14,320
Speaker 3: the way to the idea that like, okay, well China

647
00:40:14,719 --> 00:40:20,000
Speaker 3: needs to like worry about accruing liabilities from importing US expertise, Like.

648
00:40:20,520 --> 00:40:23,240
Speaker 2: Yeah, I don't know what we need. Is a debate

649
00:40:23,320 --> 00:40:25,920
Speaker 2: between Ricardo and Brad. Sets are ups because one of

650
00:40:25,960 --> 00:40:29,239
Speaker 2: the dimensions. Look, one of the counter arguments to some

651
00:40:29,440 --> 00:40:33,480
Speaker 2: of this stuff would be that there are actual flows,

652
00:40:33,560 --> 00:40:37,080
Speaker 2: because the entity that might be set up in South

653
00:40:37,120 --> 00:40:41,120
Speaker 2: Africa by a US multinational might pay licensing fees back

654
00:40:41,160 --> 00:40:43,520
Speaker 2: so the home country for the right to use the

655
00:40:43,560 --> 00:40:46,440
Speaker 2: Google name and so forth. Obviously, Brad talks a lot

656
00:40:46,440 --> 00:40:48,400
Speaker 2: about this in the context I mean, he talks a

657
00:40:48,400 --> 00:40:51,440
Speaker 2: lot about this actually in the context of software. But

658
00:40:51,520 --> 00:40:53,719
Speaker 2: there is some you know. The fact is is that

659
00:40:53,920 --> 00:40:58,759
Speaker 2: like Microsoft is gigantic and so even, and there's you know,

660
00:40:58,800 --> 00:41:01,080
Speaker 2: these companies that are trillions in trillions of dollars and

661
00:41:01,120 --> 00:41:04,040
Speaker 2: have huge footholds all around the world, and whether they're

662
00:41:04,040 --> 00:41:07,000
Speaker 2: accruing value to America in a way that doesn't show

663
00:41:07,080 --> 00:41:11,319
Speaker 2: up strictly in trade statistics strikes me as an important

664
00:41:11,400 --> 00:41:12,799
Speaker 2: load to continue to mind.

665
00:41:13,040 --> 00:41:15,160
Speaker 3: Well, that's the other thing I was going to say,

666
00:41:15,239 --> 00:41:18,560
Speaker 3: which is, you see this debate in markets quite a lot,

667
00:41:18,640 --> 00:41:24,120
Speaker 3: and the difficulty in analyzing intangibles is it's hard, right,

668
00:41:24,239 --> 00:41:27,319
Speaker 3: Like how do you put a price on things like

669
00:41:27,600 --> 00:41:31,400
Speaker 3: brand value or soft power and stuff like that, And

670
00:41:31,440 --> 00:41:34,080
Speaker 3: so you get these arguments over. Okay, well, book value

671
00:41:34,080 --> 00:41:37,840
Speaker 3: doesn't include intangibles, but you know, maybe it should. But

672
00:41:37,960 --> 00:41:40,400
Speaker 3: if it should, then how do you avoid the problem

673
00:41:40,440 --> 00:41:43,560
Speaker 3: of over inflating because you think that this brand value

674
00:41:43,600 --> 00:41:46,320
Speaker 3: is really good and it's difficult to actually measure.

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00:41:46,840 --> 00:41:50,719
Speaker 2: Also, it doesn't matter what our trade statistics say if

676
00:41:50,760 --> 00:41:53,920
Speaker 2: we can't make things critical for national security, Like to

677
00:41:53,960 --> 00:41:57,000
Speaker 2: your point, whatever you say, oh, we don't really run

678
00:41:57,040 --> 00:41:59,640
Speaker 2: any sort of trade issues, except if you don't actually

679
00:41:59,640 --> 00:42:02,719
Speaker 2: have the physical capacity to make important things that are

680
00:42:02,760 --> 00:42:06,000
Speaker 2: necessary for having a sovereign nation, then it kind of

681
00:42:06,000 --> 00:42:08,560
Speaker 2: doesn't matter, doesn't You could run surplus and it wouldn't matter.

682
00:42:08,760 --> 00:42:10,840
Speaker 3: I reject the idea that I need to have a

683
00:42:10,880 --> 00:42:15,760
Speaker 3: diversified supply chain of eggs. I'm going full on egg autarchy.

684
00:42:15,760 --> 00:42:19,360
Speaker 2: But here's the thing, Tracy, Like, you could do egg autarchy,

685
00:42:19,400 --> 00:42:22,480
Speaker 2: but God forbid, Like some wolves get in there like

686
00:42:22,520 --> 00:42:24,640
Speaker 2: you do still have the option of going to the

687
00:42:24,640 --> 00:42:28,120
Speaker 2: grocery store, right, So like, even if you know it's like.

688
00:42:28,520 --> 00:42:31,280
Speaker 3: See, then I just need a diversified supply of new chickens.

689
00:42:31,560 --> 00:42:35,120
Speaker 2: It's like that pulp song about the Greek girl at

690
00:42:35,120 --> 00:42:37,080
Speaker 2: the thirst for knowledge. It's like you'll never know what

691
00:42:37,160 --> 00:42:39,200
Speaker 2: it's like because you always have the option to go

692
00:42:39,239 --> 00:42:40,040
Speaker 2: to the grocery stores.

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00:42:40,440 --> 00:42:40,680
Speaker 4: You know.

694
00:42:40,800 --> 00:42:44,279
Speaker 2: It's like you can't actually replicate true autarchy knowing in

695
00:42:44,320 --> 00:42:45,760
Speaker 2: your head that you have that backup.

696
00:42:45,920 --> 00:42:46,720
Speaker 4: Yeah, that's true.

697
00:42:46,800 --> 00:42:47,920
Speaker 3: That's a good point.

698
00:42:48,040 --> 00:42:49,560
Speaker 2: Yeah, that was a good one, wasn't it.

699
00:42:49,640 --> 00:42:52,319
Speaker 3: That was very good. Okay, I think all right, shall

700
00:42:52,360 --> 00:42:54,760
Speaker 3: we leave it there? Yeah, this has been another episode

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00:42:54,760 --> 00:42:57,680
Speaker 3: of the Authoughts podcast. I'm Tracy Alloway. You can follow

702
00:42:57,719 --> 00:42:59,919
Speaker 3: me at Tracy Alloway and I'm Jill Wise.

703
00:43:00,160 --> 00:43:02,160
Speaker 2: Oh, you can follow me at the Stalwart. Follow our

704
00:43:02,200 --> 00:43:05,359
Speaker 2: producers Kerman Rodriguez at Kerman armand dash Ol Bennett at

705
00:43:05,400 --> 00:43:08,920
Speaker 2: Dashbot and Kelbrooks at Kelbrooks from our Odd Lots content.

706
00:43:09,000 --> 00:43:11,160
Speaker 2: Go to bloomberg dot com slash od Lots with a

707
00:43:11,239 --> 00:43:13,839
Speaker 2: daily newsletter and all of our episodes, and you can

708
00:43:13,920 --> 00:43:15,920
Speaker 2: chat about all of these topics. Twenty four to seven

709
00:43:15,960 --> 00:43:18,920
Speaker 2: in our discord Discord dot gg slash out.

710
00:43:18,800 --> 00:43:21,680
Speaker 3: Lots and if you enjoy odd Lots, if you like

711
00:43:21,760 --> 00:43:24,759
Speaker 3: it when we talk about monkeys swinging from trees or

712
00:43:24,880 --> 00:43:27,680
Speaker 3: egg autarchy, then please leave us a positive review on

713
00:43:27,719 --> 00:43:30,759
Speaker 3: your favorite podcast platform. And remember, if you are a

714
00:43:30,800 --> 00:43:33,759
Speaker 3: Bloomberg subscriber, you can listen to all of our episodes

715
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716
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Speaker 3: the Bloomberg channel on Apple Podcasts and follow the instructions there.

717
00:43:40,400 --> 00:44:02,400
Speaker 3: Thanks for listening. Eight